Current Medical Imaging - Volume 20, Issue 1, 2024

Abdominal multi-slice helical computed tomography (CT) and contrast-enhanced scanning have been widely recognized clinically.

The impact of the deep learning image reconstruction (DLIR) on the quality of dynamic contrast-enhanced CT imaging of primary liver cancer lesions was evaluated through comparison with the filtered back projection (FBP) and the new generation of adaptive statistical iterative reconstruction-V (ASIR-V).

We evaluated the image noise of the lesion, fine structures inside the lesion, and diagnostic confidence in 48 liver cancer subjects. The CT values of the solid part of the lesion and the adjacent normal liver tissue and the systolic and diastolic blood pressure (SD) values of the right paravertebral muscle were measured. The muscle SD value was considered as the background noise of the image, and the signal noise ratio (SNR) and contrast signal-to-noise ratio (CNR) of the lesion and normal liver parenchyma were calculated.

High consistency in the evaluation of image noise (Kappa = 0.717). The Kappa values for margin/pseudocapsule, fine structure within the lesion, and diagnostic confidence were 0.463, 0.527, and 0.625, respectively. Besides, the differences in SD, SNR and CNR data of reconstructed lesion images among the six groups were statistically significant.

The contrast-enhanced CT image noise of DLIR-H in the portal venous phase is much lower than that of ASIR-V and FBP in primary liver cancer patients. In terms of the lesion structure display, the new reconstruction algorithm DLIR is superior.

To investigate CT, MRI, and PET/CT features with histopathological findings of primary thymic neuroendocrine tumor.

All 9 cases with pathologically proven primary thymic neuroendocrine tumors were reviewed retrospectively. Among them, 7 underwent enhanced CT, 1 with MRI (enhanced) and another with PET/CT scan. Multiple characters were examined, including tumor location, contour, CT attenuation, enhancement pattern, involvement of surrounding structure and lymphadenopathy.

Among 9 patients studied, 7 (77%) masses were located in the anterior superior mediastinum, 1 in the anterior superior-middle mediastinum, and 1 in the anterior and middle mediastinum. The maximum diameter (longitudinal) ranged from 4.2 to 23 cm (mean ± standard deviation, 9.5 cm ± 2.8). Four masses had irregular, 3 had lobulated, and 2 had smooth contours, while 8 masses had clear margins and 1 had an ill-defined margin. Six masses showed heterogeneous attenuation with necrotic/cystic component (n=5), calcification (n=2) and hemorrhage(n=1), and 3 showed homogeneous attenuation on the non-enhanced image. After contrast administration, 8 masses showed heterogeneous attenuation, and 1 showed homogeneous attenuation with tumor vessels visible in 4 masses. Among all, 8 masses showed strong enhancement, and 1 showed moderate enhancement in comparison to muscles in the anterior thoracic wall on enhanced images. Involvement of adjacent mediastinal structures was observed in 5 cases. Immunohistochemical analysis showed that the tumor cells were positive for CgA, Syn, CK, CD56 and EMA.

Primary NETs are large masses located anterior superior mediastinum, irregular in contour, showing heterogeneous attenuation with necrotic/cystic component and strong heterogeneous enhancement with tumor vessels, compressing local mediastinal structures. In addition, immunohis-tochemical examination is required in such a diagnosis.

With the rapid development in computed tomography (CT), the establishment of artificial intelligence (AI) technology and improved awareness of health in folks in the decades, it becomes easier to detect and predict pulmonary nodules with high accuracy. The accurate identification of benign and malignant pulmonary nodules has been challenging for radiologists and clinicians. Therefore, this study applied the unenhanced CT images-based radiomics to identify the benign or malignant pulmonary nodules.

One hundred and four cases of pulmonary nodules confirmed by clinicopathology were analyzed retrospectively, including 79 cases of malignant nodules and 25 cases of benign nodules. They were randomly divided into a training group (n = 74 cases) and test group (n = 30 cases) according to the ratio of 7:3. Using ITK-SNAP software to manually mark the region of interest (ROI), and using AK software (Analysis kit, Version 3.0.0.R, GE Healthcare, America) to extract image radiomics features, a total of 1316 radiomics features were extracted. Then, the minimum–redundancy–maximum–relevance (mRMR) algorithms were used to preliminarily reduce the dimension, and retain the 30 most meaningful features, and then the least absolute shrinkage and selection operator (LASSO) algorithm was used to select the optimal subset of features, so as to establish the final model. The performance of the model was evaluated by using the receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), accuracy, sensitivity and specificity. Calibration refers to the agreement between observed endpoints and predictions, and the clinical benefit of the model to patients was evaluated by decision curve analysis (DCA).

The accuracy, sensitivity, and specificity of the training and testing groups were 81.0%, 77.7%, 82.1% and 76.6%, 85.7%, 73.9%, respectively, and the corresponding AUCs were of 0.83 in both groups.

CT image-based radiomics could differentiate benign from malignant pulmonary nodules, which might provide a new method for clinicians to detect benign and malignant pulmonary nodules.

This study aims to assess the accuracy of computed tomography (CT) in detecting recurrent laryngeal tumors after failed chemoradiation therapy (CRT).

Local recurrence of laryngeal tumors following CRT has been reported in approximately 25%, yet it is often difficult to detect.

Ten patients with laryngeal cancer who failed CRT and subsequently underwent salvage total laryngectomy were included. The laryngeal subsites involved in the tumor were identified based on postoperative pathology. The corresponding preoperative CT scans were selected for review by seven experts (head-and-neck surgeons or radiologists) who scored the extent of tumor spread on each scan on a 5-point scale, from no tumor detected to clearly visible tumor.

The rates of high tumor detectability (scores 4-5) varied according to laryngeal subsite, from 75% in the glottic region, to 45% in the subglottic region, and to 19% in the supraglottic region (P=0.01). The detectability rates were higher on scans performed 2 years or more after CRT.

The CT evaluation of laryngeal cancer after CRT has limited value, particularly in the epiglottis and subglottis.

Immunoglobulin G4-related disease (IgG4-RD) is a relatively rare immune-mediated chronic inflammatory disease with fibrosis newly defined in recent years. It can involve multiple systems and organs with complex clinical manifestations. Due to mass-like lesions, it is easily misdiagnosed as tumors.

Herein, we report a 57-year-old woman treated for submandibular mass and anosmia. The serum IgG4 level was increased. The biopsy of the submandibular gland indicated salivary gland tissue and hyperplasia of fibrous tissue and lymphoid tissue. Immunohistochemical examination showed a large number of IgG4-positive plasma cells. M protein was found in the patient's serum by immunofixation electrophoresis, and plasma cell diseases were excluded by bone marrow puncture. PET/CT examination showed that besides the submandibular glands, the parotid gland, common bile duct, the transitional part of the left renal pelvis and ureter, retroperitoneum in the lower abdomen, and multiple lymph nodes were also involved. The patient was diagnosed with IgG4-RD, and after treatment with glucocorticoid, the enlargement of submandibular glands and decreased olfactory function improved. After 14 weeks of treatment, the serological examinations, PET/CT, and ultrasound re-examination results showed significant improvement. So far, the patient has been followed up for 27 months and is in continuous remission.

This case report aims to raise awareness of IgG4-RD and explore the value of PET/CT in the diagnosis and efficacy monitoring of the disease.

The accurate diagnosis of superficial lymphadenopathy is challenging. We aim to explore a non-invasive and accurate machine-learning method for distinguishing benign lymph nodes, lymphoma, and metastatic lymph nodes.

The clinical data and ultrasound images of 160 patients with superficial lymphadenopathy (58 benign lymph nodes, 62 lymphoma, 40 metastatic lymph nodes) admitted to our hospital from January 2020 to November 2022 were retrospectively studied. Patients were randomly divided into a training set and test set according to the ratio of 6:4. Firstly, the radiomics features of each lymph node were extracted, and then a series of statistical methods were used to avoid over-fitting. Then, the gradient boosting machine(GBM) was used to build the model. The area under receiver(AUC) operating characteristic curve, precision, recall rate and F1 value were calculated to evaluate the effectiveness of the model.

Ten robust features were selected to build the model. The AUC values of benign lymph nodes, lymphoma and metastatic lymph nodes in the training set were 1.00, 0.98 and 0.99, and the AUC values of the test set were 0.96, 0.84 and 0.90, respectively.

It was a reliable and non-invasive method for the differential diagnosis of lymphadenopathy based on the model constructed by machine learning.

Medical image registration plays an important role in several applications. Existing approaches using unsupervised learning encounter issues due to the data imbalance problem, as their target is usually a continuous variable.

In this study, we introduce a novel approach known as Unsupervised Imbalanced Registration, to address the challenge of data imbalance and prevent overconfidence while increasing the accuracy and stability of 4D image registration.

Our approach involves performing unsupervised image mixtures to smooth the input space, followed by unsupervised image registration to learn the continual target. We evaluated our method on 4D-Lung using two widely used unsupervised methods, namely VoxelMorph and ViT-V-Net.

Our findings demonstrate that our proposed method significantly enhances the mean accuracy of registration by 3%-10% on a small dataset while also reducing the accuracy variance by 10%.

Unsupervised Imbalanced Registration is a promising approach that is compatible with current unsupervised image registration methods applied to 4D images.

Glaucoma is a significant cause of irreversible blindness worldwide, with symptoms often going undetected until the patient's visual field starts shrinking.

To develop an AI-based glaucoma detection method to reduce glaucoma-related blindness and offer more precise diagnosis.

Discusses various methods and technologies, including Heidelberg Retinal Tomography (HRT), Optical Coherence Tomography (OCT), and Fundus Photography, for obtaining relevant information about the presence of glaucoma in a patient. Additionally, it mentions the use of Support Vector Machines (SVMs) and Convolutional Neural Networks (CNNs) for glaucoma detection. There are many limitations for existing methods as; Asymptomatic Progression, reliance on subjective feedback, multiple tests required, late detection, limited availability of preventive tests, influence of external factors.

Findings reveal promising outcomes in terms of glaucoma detection accuracy, particularly in the analysis of the RIM-ONE-r3 dataset. By scrutinizing 20 images from the Healthy, Glaucoma, and Suspects categories through fundus image recognition, our developed AI model consistently achieved high diagnostic accuracy rates.

Our study suggests that further enhancements in glaucoma detection accuracy are attainable by augmenting the dataset with additional labeled images. We emphasize the significance of considering various application parameters when discussing the integration of computer-aided decision/management systems into healthcare frameworks.

Artificial intelligence (AI) is rapidly evolving in healthcare, with transformative potential. AI revolutionizes medical imaging by enabling online self-diagnosis for patients and improving diagnostic accuracy for healthcare professionals. While valuable datasets aid machine learning in disease detection, challenges persist in diagnosing similar lung conditions from chest X-rays. Integrating AI into healthcare holds promise for enhanced outcomes and efficiency.

In this article, we aim to present a new AI model that solves this challenge by allowing the differentiation, diagnosis and classification of three distinct diseases, whose symptoms are very similar. The fundamental contribution is to reduce the number of parameters used while maintaining the same level of precision for use in embedded systems.

Our proposed model combines the power of the neural network using the SqueezeNet architecture with a set of machine learning algorithms as classifiers, including logistic regression, support vector machine (SVM), k-nearest neighbors (KNN), decision tree, and naive Bayes. The chest X-ray dataset used in the proposed model consists of CXR images that are classified into four categories: pneumonia, tuberculosis, COVID-19, and normal cases.

Our proposed model demonstrated remarkable accuracy (97,32%), precision (97,33), F1 score (97,31%), recall (97,30%), and AUC (99,40), which is close to the best model. Whereas, the number of parameters used by our model (4,6 M) is very small compared to the best model in the literature (47M).

The model demonstrated good classification accuracy. In addition, the proposed model has the ability to use fewer parameters, which means it requires less internal memory and computing resources.

Colon cancer with liver metastasis is a common occurrence in clinical practice. The presence of liver metastasis has a significant impact on the treatment strategy of patients, so the first step is to diagnose whether it is liver metastasis. Imaging is one of the auxiliary methods for diagnosing liver metastases, but due to the presence of different diseases with the same shadow, we need to be cautious when using imaging methods for the diagnosis of liver metastases.

We report a 53-year-old female patient with sigmoid colon cancer and perforation who underwent a surgical operation. Three years after the operation, reexamination of the liver through computed tomography and magnetic resonance imagery scanning revealed multiple progressive liver lesions. However, the liver biopsy did not show malignant changes. Repeated analysis of the patient's liver magnetic resonance imaging revealed that multiple liver nodules were significantly enhanced in the arterial phase and that the portal vein density/signal ratio was higher than that of the liver parenchyma. The coincidence of doughnut-shaped nodules and high signal in the hepatobiliary phase, combined with the results of pathological liver puncture examination, led to nodular regenerative hyperplasia being considered as a possible diagnosis.

A review of the relevant literature showed that following oxaliplatin chemotherapy for colorectal cancer, it is not uncommon for doughnut-shaped nodules with obvious enhancement in the middle hepatic artery phase and high signal intensity in the hepatobiliary phase to develop. Such changes should be paid sufficient attention by radiologists.

Extrahepatic cholangiocarcinoma (EHCC), an exceedingly malignant neoplasm, often eludes early detection, culminating in a dire prognosis. Accurate cancer staging systems and pathological differentiation are designed to guide adjuvant interventions and predict postoperative prognoses.

This study sought to investigate the predictive capacity of DW-MRI in discerning T stages, lymph node metastasis, and pathological differentiation grades in patients with EHCC.

Eighty-five patients were pathologically diagnosed with EHCC and underwent abdominal MRI within two weeks before surgery at our hospital from Aug 2011 to Aug 2021. Tumor axial maximum area (AMA) and apparent diffusion coefficient (ADC) values for diverse T stages, N stages, and differentiation grades were retrospectively analyzed.

The Mann-Whitney U test displayed significantly higher lesion AMA values (P =0.006) and lower tumor ADC values (P = 0.001) in the node-positive group (median ADC and AMA value: 1.220×10^-3 mm²/s, 82.231 mm²) than in the node-negative group (median ADC and AMA value: 1.316×10^-3 mm²/s, 51.174 mm²). A tumor ADC value<1.249×10^-3 mm²/s from the receiver operating characteristic curve (AUC=0.725, P=0.001) exhibited the capability to predict node-positive EHCC with a sensitivity of 64.29%, and specificity of 73.68%. Furthermore, a progressive decrease in the degree of EHCC differentiation was associated with a reduction in the tumor ADC value (P=0.000).

The N stage and differentiation of EHCC can be evaluated non-invasively using diffusion-weighted MRI.

Artificial intelligence (AI) in medical imaging rapidly expands regarding image processing and interpretation. Therefore, the aim was to explore radiographers’ and radiologists’ perceptions and attitudes towards AI use in medical imaging technologies in Saudi Arabia.

The survey was distributed online, and responses were collected from 173 participants nationwide. Data analysis was performed using SPSS Statistics (version 27).

The participants scored an average of 1.7, 1.6, and 1.8 on a scale of 1–3 for attitudinal perspectives on clinical application and the positive and negative impact of integrating AI technology in diagnostic radiology. Lack of knowledge (43.9%) and perceived cyber threats (37.7%) were the most cited factors hindering AI implementation in Saudi Arabia.

The radiographers and radiologists in this study had a favorable attitude toward AI integration in diagnostic radiology; nonetheless, concerns were raised about data protection, cyber security, AI-related errors, and decision-making challenges.

The classification of Congenital Uterine Malformations (CONUTA) relies on coronal imaging of the uterus using 3D TVUS and MRI. In everyday practice, radiologists and gynaecologists often struggle to confidently categorize CONUTA due to varying classification systems and the lack of worldwide consensus.

The aim of this study was to evaluate the diagnostic concordance and discrepancies between two imaging techniques within the context of the ASRM, ESHRE/ESGE, and CUME systems.

Ninety-four patients suspected of having CONUTA underwent evaluation: 67 underwent 3D TVUS, 53 had MRI scans, and 34 were examined using both imaging techniques.

An initial cross-listing table of ASRM, ESHRE/ESGE, and CUME was created, and a flowchart schema was used to define the type of congenital uterine anomaly for each system

The prevalence of anomalies in each system was calculated, and Fleiss’ Kappa was used to assess and determine the level of agreement.

Class VI arcuate uterus was the most common form in ASRM 2016 and 2021, while the partially septate uterus predominated in the CUME 2018 and ESHRE/ESGE 2016 classification systems.

There is no discordance between classification systems for all fusion defects and complete septate type of absorption defects. In the ESHRE/ESGE system, nearly half of the abnormal uteruses were categorized as partially septate. However, the CUME system proved less effective in distinguishing between normal and arcuate uteruses.

Type 2 diabetes mellitus (T2DM) and hypertension (HT) are the two most common underlying diseases worldwide, and they often coexist. The long-term existence of both may lead to left ventricular dysfunction. Therefore, evaluating the cardiac function of T2DM patients with HT is vital to guide treatment and improve prognosis. Left ventricular pressure strain loops (LVPSL) combine left ventricular strain and afterload, which can quantify left ventricular energy expenditure and detect left ventricular subclinical systolic dysfunction. Many studies have focused on myocardial work (MW) in uncomplicated T2DM patients or simple HT patients, but a few have focused on T2DM patients with HT.

The study aimed to evaluate the MW changes in T2DM patients with HT using LVPSL and to find independent related factors of MW parameters.

40 T2DM patients, 35 HT patients, 40 T2DM patients with HT (T2DM+HT group), and 35 controls were enrolled. The differences between clinical data, conventional ultrasound parameters, and MW parameters were analyzed among the four groups.

The global longitudinal strain (GLS) of the T2DM group, HT group, and T2DM+HT group was lower than the control group (P<0.05). The global work index (GWI) and global constructive work (GCW) in the T2DM group were lower than other groups (P<0.05). The GWI of the HT group was higher than other groups (P<0.05), while GCW was only higher than the T2DM group and T2DM+HT group (P<0.05). The GWI and GCW of the T2DM+HT group were higher than the T2DM group and were lower than the HT group(P<0.05), while there was no significant difference with the control group. HT group and T2DM+HT group had higher global work waste (GWW) (P<0.05). The global work efficiency (GWE) of the T2DM+HT group was lower than other groups (P<0.05). Systolic blood pressure (SBP) and glycosylated hemoglobin (HbA1c) were independent factors of each MW parameter.

LVPSL can recognize left ventricular subclinical systolic dysfunction early in patients with T2DM and HT. Compared to simple T2DM or HT, the combination of T2DM and HT had greater damage to left ventricular systolic function. SBP and HbA1c are two factors that have a considerable impact on MW parameters. The impact of afterload on MW parameters should be paid more attention to.

The most difficult aspect of diagnosing lung cancer is early diagnosis. According to the American Cancer Society, each year, there are around 11 million newly diagnosed instances of cancer worldwide. Radiologists often turn to Computed Tomography (CT) scans to diagnose respiratory conditions, which can reveal if lung tissue remains normal or abnormal. However, there is an increased chance of inaccuracy and delay; therefore, radiologists are concerned with the physical segmentation of nodules.

The objective of the research is to implement an advanced modified threshold segmentation and classification model for early and accurate detection of lung cancer from CT images.

Using the Support Vector Machines (SVM) classifier as well as the Artificial Neural Network (ANN) classifier, the authors propose using Modified adaptive threshold segmentation as a segmentation approach for cancer detection. Here, Lung Image Database Consortium (LIDC) datasets, a collection of CT scans, are used as the video frames in an investigation to authorize the recitation of the suggested technique.

Both quantitative as well as qualitative analyses are used to analyze the segmentation function of the anticipated algorithm. Both the ANN and SVM classifiers used in the suggested technique for lung cancer diagnosis achieve world-record levels of accuracy, with the former achieving a 96.3% detection rate and the latter a 97% rate of accuracy.

This innovation may have a major impact on the worldwide rate of lung cancer rate due to its ability to detect lung tumors in their earliest stages when they are most amenable to being avoided and treated. This method is useful because it provides more information and facilitates quick, precise decision-making for doctors diagnosing lung cancer in their patients.

Lymphaticovenous anastomosis (LVA) surgery is an effective treatment for lymphedema. Accurate evaluation and localization of the superficial lymphatic vessels before the operation is crucial for the success of the operation. Contrast-enhanced ultrasound (CEUS) is a new ultrasound technology, and its clinical application value in LVA surgery has not been established.

This study aimed to assess the efficacy of CEUS in LVA surgery and provide a novel approach for the clinical assessment and localization of superficial lymphatic vessels.

Retrospective analysis of imaging and surgical data was performed on 20 LVA patients. Among them, 10 cases underwent evaluation and localization using indocyanine green (ICG) lymphatic imaging (Group A), while 10 cases were evaluated and localized using CEUS (Group B). The differences in surgical data between the two groups were compared and analyzed.

All 20 patients were female (mean age, 57.7 years ± 6.3 [SD]). CEUS demonstrated superior visualization and localization of superficial lymphatic vessels. The average diameter of lymphatic vessels identified in the CEUS group was significantly greater than that in the ICG group (0.78±0.06 vs. 0.52±0.05mm; P<0.001). The duration of operation in group B was significantly shorter than that in group A (4.47±0.37 vs. 6.70±0.45mm; P<0.001). The number of anastomosed lymphatic vessels in group B was less than that in group A [5.0(4.0, 6.0) vs. 9.5 (9.0, 11.3); P<0.001].

CEUS can serve as a viable alternative to ICG lymphatic imaging, facilitating improved lymphatic venous anastomosis surgery.

Recurrence of uterine cervical cancer is common and often shows a dismal prognosis. Local recurrence usually manifests as solid soft tissue lesions and has rarely been reported to have cystic lesions.

Herein, we report a case of recurrent uterine cervical cancer with initial manifestation as a hemorrhagic cyst, assessed using strain sonoelastography, CT, and MRI.

Although cystic recurrence is uncommon, newly detected simple or complex cystic lesions should be closely monitored.

To explore the development of a mind map-based predictive nursing protocol and assess its impact on the quality of images in patients undergoing high-concentration contrast three-dimensional computed tomography (CT) imaging of liver blood vessels.

A total of 600 patients who were admitted to Beijing You an Hospital were chosen for this prospective study and underwent high-concentration contrast three-dimensional CT imaging of liver blood vessels between April 2021 and December 2021. The patients were divided into two groups using the digital table method, with 300 cases. The control group received conventional nursing intervention, while the research group was provided with a mind map-based predictive nursing protocol. We recorded the image quality of three-dimensional CT imaging of liver blood vessels, satisfaction scores regarding nurse examination guidance, and the Self-Rating Anxiety Scale (SAS) and Self-Rating Depression Scale (SDS) in both groups.

The research group achieved a perfect rate of 100.00% for the high-quality three-dimensional CT imaging of liver blood vessels, which was noticeably higher compared to the rate of the control group of 98.67%. Patients in the research group expressed higher satisfaction levels regarding the guidance provided by nurses, including their attitude, timeliness, accuracy, and overall satisfaction, compared to the control group. Initially, the two groups had no notable differences in the SAS and SDS scores. However, after the intervention, both groups experienced a significant decrease in SAS and SDS scores, with the research group showing an even more substantial decline.

Through the creation of a mind map-based predictive nursing protocol and its implementation on patients undergoing high-concentration contrast three-dimensional CT imaging of liver blood vessels, it is possible to significantly enhance the quality of CT scans, alleviate feelings of anxiety and depression, increase patient satisfaction with examination guidance by nurses, and effectively decrease the occurrences of contrast agent leakage and allergic reactions to iodine.

Chest wall tuberculosis may develop if tuberculous (TB) lesions spread through the chest wall and invade the thoracic cavity. The presence of a mass on the patient's chest wall may be the first indication of TB, and a chest CT scan can help diagnose external penetrating chest wall TB, the incursion of tuberculosis from the lungs into the chest wall.

This study examines the safety and efficacy of thoracoscopic-assisted surgery for the treatment of penetrating chest wall tuberculosis as a means of exploring novel concepts of minimally invasive surgery.

Our hospital conducted a retrospective study of 25 patients with penetrating chest wall TB who underwent thoracoscopic surgery between January 2020 and June 2021. General demographics, CT scan data linked to surgery, and postoperative patient outcomes were compared between the two groups. The data was also evaluated to determine the range of operation time and the volume of bleeding from different foci in the thoracic cavity.

All procedures went well after patients took conventional antituberculosis medication for at least two weeks prior to surgery. CT scans showed that thoracoscopic surgery needed a smaller incision than traditional chest wall TB surgery, with no discernible increase in surgical time. Postoperative tube use, length of hospital stay, and blood loss were all significantly lower than they would have been with conventional surgery. In addition, thoracoscopy was associated with a significantly reduced rate of subsequent treatment. Fibrous plate development and calcification caused the longest operation times in the thoracoscopic surgery group, whereas multiple pleural tuberculomas generated the most hemorrhage. Thoracoscopic surgery usually reveals tuberculous foci hiding in the thoracic cavity.

Thethoracic surgery can eliminate the TB focus in the chest wall and intrathoracic while treating penetrating chest wall tuberculosis. The CT scan is a crucial part of the diagnostic process for these patients. Minor surgical trauma, low complication and recurrence rates, and good results. There is a greater distinction between the two surgical approaches for patients with penetrating chest wall TB as opposed to those with basic chest wall tuberculosis.

This study aims to investigate the value of gemstone spectral imaging (GSI) combined with an 80 mm wide-body detector in head-neck CTA.

Ninety patients with head-neck CTA were prospectively selected and randomly divided into a control group and a test group, with 45 patients in each group. The control group was scanned conventionally. With a tube voltage of 100 kVp and detector width of 40 mm, a 70 ml contrast agent was injected at a flow rate of 5.0 ml/s. The test group used GSI. With a tube current fixed of 445 mAs and a detector width of 80 mm, the contrast agent was injected at a flow rate of 3.5 ml/s and 0.6 ml/kg body weight, and the 55 keV virtual monoenergetic images (VMIs) were automatically reconstructed. Finally, the target vessel CT values, background noise (BN), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), subjective scores, contrast agent dose, CT dose index volume (CTDIvol), and dose length product (DLP) were recorded. The DLP was converted to the effective dose (ED).

The target vessel CT values, BN, SNR, CNR, and subjective scores of the two groups were not statistically significant (all P > 0.05), and the image quality of both groups was the same and met the diagnostic requirements. The contrast agent dose and effective dose (ED) in the test group were approximately 44% and 26% lower than that of the control group, respectively (all P < 0.05).

In head-neck CTA examination, the Revolution CT GSI combined with an 80 mm wide-body detector can reduce the contrast agent dose and radiation dose while ensuring image quality.

Hip dysplasia is one of the most prevalent disorders in children and one of the three primary congenital orthopedic deformities. Although there are numerous existing methods (e.g., CT, MRI and arthrography) for early identification of hip dysplasia, their diagnostic criteria differ widely. It is critical to establish a safe, accurate, and reliable way for early diagnosis and treatment of hip dysplasia.

This study aimed to analyze the diagnostic efficacy of high-frequency ultrasound (HFU) for congenital developmental hip dysplasia and hip dislocation and to provide a reference for the early diagnosis of congenital hip dysplasia in the future.

A total of 104 infants and children suspected of having congenital hip dislocation or developmental hip dysplasia admitted to our hospital from April 2019 to August 2022 were enrolled as study subjects. All the infants and children were subjected to HFU and X-ray examination in our hospital. The diagnostic efficacy of HFU for congenital hip dysplasia was observed using X-ray as the gold standard.

HFU confirmed 79 cases of congenital hip dysplasia, while X-ray confirmed 71 cases. The sensitivity and specificity of HFU were 77.42% and 83.33%, respectively, in the diagnosis of congenital developmental hip dysplasia, 76.47% and 96.55% in the diagnosis of congenital hip dislocation, and 77.22% and 60% in the diagnosis of congenital hip abnormality, which is very close to the gold standard. According to statistics on infants and children, the majority of patients were girls, and the left joint was more likely to be affected.

HFU has excellent diagnostic efficiency for congenital developmental hip dysplasia and hip dislocation, which can be considered an early assessment method for congenital hip dysplasia in the future.

Non-invasive imaging methods are still lacking for the evaluation of muscle changes in diabetes.

To investigate the feasibility of muscle CT radiomics in evaluating muscle changes in diabetes.

60 diabetics and 60 health controls (HC) were assessed with the method of muscle CT radiomics. 93 CT images of radiomics features of the pectoralis major muscle (PMM) were obtained by using the software 3D Slicer and were then compared between diabetics and HC cases. The least absolute shrinkage and selection operator (LASSO) regression method was used to establish a prediction model. The receiver operating characteristic (ROC) curve was used to determine the performance of the model.

Diabetics and HC cases differed in 19 radiomics features (P<0.05). By using the LASSO method, 6 features were finally selected. The AUC of the model in the discrimination of diabetics and HC were 0.92 and 0.90, respectively, for the training cohort and validation cohort.

Muscle CT radiomics is feasible in evaluating muscle changes in diabetes.

The degree of cervical foraminal stenosis on MRI scans may be measured and categorised using the Kim or modified Kim methods. These grading scales have not previously been validated in a cohort of patients awaiting surgery.

To establish the normal foraminal and root diameters as well as the consistency of inter and intra-rater grading using the Kim and modified Kim grading systems in pre-operative surgical patients.

Asymptomatic cervical nerve roots and foramina demonstrated on the pre-operative MRI scans of adult surgical patients with cervical radiculopathy were measured and categorised by six raters using the Kim and modified Kim grading methods. Repeat “second pass” measurements were made by the same assessors on the same images a minimum of one month later.

Foraminal diameters (mm) in asymptomatic foramina were C2/C3 (mean ± SD): 4.18 ± 1.44, C3/C4 2.96 ± 1.23, C4/C5 3.02 ± 1.19, C5/C6 3.15 ± 1.33, C6/C7 3.53 ± 1.36, C7/T1 3.93 ± 1.34. Nerve root diameters were C3 3.11 ± 0.87, C4 2.95 ± 0.77, C5 2.56 ± 0.73, C6 2.26 ± 0.76, C7 2.56 ± 0.82, C8 3.83 ± 0.86.

Inter-rater consistency was kappa [95% CI]: Kim 0.01 [0.00, 0.03], modified Kim 0.08 [0.05, 0.10]. Intra-rater consistency was kappa [95% CI]: Kim 0.81 [0.77, 0.86], modified Kim 0.69 [0.62, 0.76].

There was poor inter-rater consistency but good intra-rater consistency when assessing the severity of foraminal stenosis on axial T2 MRI scans. Foraminal diameter was narrowest at C3/C4 and C4/C5, whereas the smallest root diameter was C5/C6. Volumetric or oblique MR may improve consistency.

Generalized cystic lymphangiomatosis (GCL) is a rare disease characterized by the widespread proliferation of lymphatic vessels, often seen in the pediatric patient group. Imaging techniques are instrumental in revealing the extent and morphological features of the disease.

The objective of this study is to interpret the radiological findings of GCL and address the differential diagnosis between GCL and other lymphatic malformations in light of the relevant literature data.

The sample of this retrospective study consisted of six pediatric patients, four males and two females, diagnosed with GCL based on clinical, radiological, and histopathological findings between 2015 and 2022. The age of the patients at the time of diagnosis and their symptoms at admission were obtained from the hospital database. Radiological imaging findings were evaluated in detail based on the involved systems (thorax, abdomen, and musculoskeletal).

The median age of the sample, 4/6 were male, was 9 years at admission (min. 3, max. 12). The most common symptom at admission was dyspnea, often accompanied by pleural effusion. Bone involvement was the most common extrathoracic finding. Abdominal involvement was primarily asymptomatic, and the spleen was the most frequently involved organ in the abdomen.

The diagnosis of GCL is challenging because of its rarity and overlapping diseases. Whole-body magnetic resonance imaging is a valuable tool as it reveals the typical radiological features of GCL and how far it has spread throughout the body.

Real-time shear wave elastography (SWE) has emerged as a useful imaging modality for detecting the lesion location of various diseases, including cervical diseases.

In this paper, the SWE was used to quantitatively determine the tissue hardness of the internal and external orifice of the cervix (IOC & EOC) and to relatively objectively analyze the impact of different production methods on the hardness of the cervical tissue.

A total of 48 patients were selected, and they were divided into three groups according to different production methods: control group (16 cases), cesarean section group (16 cases), and spontaneous delivery group (16 cases). Artificial intelligence has also been incorporated into this work. A deep flexible neural tree model and a new set of FNT models were proposed to assist in classifying cervical physical data in different states. The physical data was extracted as the features, and the different states were considered as category labels.

There was no statistically significant difference in the elasticity of the IOC and the EOC between the groups. However, the difference in the elasticity of the IOC and the EOC within each group was statistically significant. The classification results corresponded with the results of the statistical analysis. The hardness of the EOC is generally lower than that of the IOC, and there was no significant difference in hardness between the IOC and the EOC in the three groups.

There is no significant difference in the cervical elasticity hardness between different delivery modes.

Cesarean scar pregnancy (CSP) refers to the phenomenon in which a fertilized egg implants and develops in the scar of the uterus in a woman with a history of cesarean section.

The study aimed to explore the differential diagnostic value of two-dimensional ultrasound (2D US) combined with three-dimensional ultrasound (3D US) for CSP.

Clinical data of 89 patients with CSP admitted to our hospital from January 2022 to January 2023 were retrospectively analyzed. Of them, 65 patients met the inclusion criteria. Patients underwent 2D US, 3D US, and combined 2D and 3D US imaging. Using the clinical pathological diagnosis as the “gold standard”, the differential diagnostic value of 2D US, 3D US, and 2D US combined with 3D US for CSP was compared.

The detection rate of CSP using a combined 2D US and 3D US was 98.46%, which was higher than 84.62% and 89.23% achieved with 2D US and 3D US alone, respectively (P<0.05). The pathological results showed that among 65 patients, CSP type I accounted for 24.62%, type II accounted for 55.38%, and type III accounted for 20.00%. The coincidence rate of 2D US combined with 3D US was 98.46%, which was higher than that of 2D US (83.08%) and 3D US 89.23%) alone (P<0.05). The accuracy, specificity, and sensitivity of 2D US combined with 3D US in diagnosing CSP were higher compared to the two methods alone (P<0.05).

The combination of 2D US and 3D US can accurately detect and classify CSP, further improving diagnostic efficiency.

Fetal small bowel obstruction (SBO) is a serious condition with high morbidity and mortality rates. Prenatal ultrasound is an important tool for detecting SBO, but the optimal cutoff value for intestinal diameter remains undefined.

This study aimed to investigate the ultrasonic characteristics of fetal SBO and determine the optimal cutoff value for intestinal diameter to enhance prenatal ultrasound diagnosis.

We retrospectively analyzed the ultrasonic characteristics and postpartum data of 76 cases diagnosed with SBO. Receiver operating characteristic (ROC) curve analysis was performed to identify the optimal cutoff value for dilated intestinal diameter.

Among the 76 cases, 31 displayed the “double bubble sign” on ultrasound, with 20 cases identified as annular pancreas, 6 as duodenal atresia, and 5 as duodenal membranous stenosis. In 45 cases, the lesions were located in the jejunal or ileal segment and exhibited intestinal dilatation above the lesion site, including 27 cases of small bowel atresia, 7 cases of membranous jejunal stenosis, and 11 cases of small bowel volvulus. Out of the 76 cases, 9 showed no abnormalities after birth. ROC curve analysis determined optimal cutoff values of 17.5mm and 10.5mm for predicting “double bubble sign” lesions in the gastric and duodenal widths. For predicting small intestinal dilatation, the optimal cutoff values for dilated width and length of the intestinal tube were 11.5mm and 21.5mm, respectively, with high sensitivity and specificity.

Ultrasonic imaging and changes in intestinal diameter provide valuable information for prenatal diagnosis and management of SBO. Establishing these cutoff values can improve the accuracy of prenatal ultrasound diagnosis for SBO.

Preoperative T-staging is essential for planning optimal treatment and care for colorectal cancer (CRC).

To evaluate the accuracy of Dual-energy CT (DECT) in preoperative T-staging of CRC.

The clinical data and DECT images of 37 patients with 39 CRC lesions were retrospectively analyzed. The performance of the DECT quantitative parameters in CRC T-staging was evaluated. Postoperative pathologic results were used as a gold standard. Receiver operating characteristic curves were used to assess the diagnostic efficacy of DECT parameters. P < 0.05 was deemed significant.

The overall accuracy of T-staging by DECT was 76.9%. The DECT parameters were significantly different between the T3 pericolic fat stranding, T4a pericolic fat stranding, and normal pericolic fat stranding. Arterial phase λHU had the best diagnostic performance with a cut-off value of ≥0.967, resulting in a 70.6% sensitivity and a 100% specificity in differentiating between T3 and T4a stages of CRC.

DECT has high accuracy in the T-staging of CRC. Arterial phase λHU has the best diagnostic performance in differentiating between T3 and T4a stages of CRC.

Molybdenum cofactor deficiency (MoCD-A) is an extremely rare autosomal recessive disease that presents with intractable seizures. The diagnosis poses challenges due to the limited number of cases reported worldwide. Magnetic resonance imaging (MRI) is a useful diagnostic tool that can detect brain injury associated with the disorder. The prognosis of MoCD-A is poor partly because most cases are initially misdiagnosed as HIE (hypoxic ischemic encephalopathy), emphasizing the need for an early and accurate diagnosis to improve quality of life and provide adequate genetic counseling to avoid new cases in the future.

This report presents a case of molybdenum cofactor deficiency type A (MoCD-A) caused by MOCS1 gene mutations. A male newborn was admitted on the 10th day of birth due to uncontrolled seizures and feeding difficulties. Brain MRI showed severe cerebral damage with multiple foci that did not enhance upon contrast administration. The diagnosis was confirmed by genetic analysis and the patient received rehabilitation. His parents also received genetic counseling. To the best of our knowledge, this is the first reported MoCD-A case that had enhanced MR imaging with Gd-DTPA (0.1 mmol/kg). In addition, we reviewed the clinical and neuroimaging features of 25 newborns diagnosed with MoCD-A, as documented in the existing literature.

MRI is crucial in the diagnosis of MoCD-A. A correct diagnosis can provide the family with timely genetic counseling to prevent future cases.

Dissection of the lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLNs) in papillary thyroid cancer (PTC) remains controversial.

This study aimed to determine the capability of ultrasonography (US)-based radiomics for presurgical prediction of metastasis in LN-prRLNs in PTC.

Patients were retrospectively enrolled and pathologically confirmed as LN-prRLN metastasis with PTC after surgery. Radiomic analysis based on preoperative US images with manual segmentation of targets was used to develop a radiomics model. US features described in ACR TI-RADS were collected to construct a clinical model. The Radiomics model, a combined model integrating radiomics and clinical model, were also developed for the presurgical prediction of metastasis in LN-prRLNs.

A total of 570 patients, including 488 patients with non-LN-prRLN metastasis and 82 with LN-prRLN metastasis, were assessed. The 15 top-performing features finally remained significant for constructing the radiomics model. The combined model showed that US measured tumor size (OR: 1.036, P = 0.044), US suspected lateral lymph node metastasis (OR: 2.247, P = 0.009), multifocality (OR: 1.920, P = 0.021), Delphian lymph node metastasis (DLNM) (OR: 2.300, P = 0.039), VIa compartment metastasis (OR: 5.357, P = 0.000), the radiomics score (OR: 1.003, P = 0.001) were significant risk factors for predicting LN-prRLN metastasis. The combined model achieved a higher AUC of 0.849 than that of the clinical model (AUC: 0.826) and radiomics model (AUC: 0.759).

The US-based radiomics combined model can more effectively predict LN-prRLN metastasis in PTCs patients preoperatively. This approach had the potential to assist surgeons in decision-making regarding LN-prRLN dissection.

Only a small number of the investigations that were carried out in the Middle East attempted to characterize patients with NCFB. In order to characterize patients with NCFB, as well as their etiologies, microbiological profiles, and outcomes, we therefore carried out this investigation.

This retrospective cohort study was carried out at the Jordan University Hospital (JUH), a tertiary facility located in Amman, Jordan. Non-cystic Fibrosis Bronchiectasis (NCFB) was defined as an HRCT scan typical for bronchiectasis along with a negative sweat chloride test to rule out cystic fibrosis. Patients’ data were collected by the use of Electronic Medical Records (EMR) at our institution. Frequent exacerbation was defined as more than 2 exacerbations in 1 year of the onset of the diagnosis.

A total of 79 patients were included, and 54.4% of them were female. The mean and standard deviation of the patient's age was 48.61 ± 19.62. The etiologies of bronchiectasis were evident in 79.7% of the sample. Asthma, Chronic Obstructive Pulmonary Diseases (COPD), and Kartagener syndrome were the most prevalent etiologies, accounting for related illnesses in 21.8%, 21.5%, and 13.9% of the patients, respectively. The most frequent bacteria cultured in our cohort were Pseudomonas and Candida Species. Moreover, 43 patients of the study cohort were frequent exacerbators, and 5 patients died.

Our study supports the need to identify several bronchiectasis phenotypes linked to various causes. These findings provide information to clinicians for the early detection and treatment of bronchiectasis in Jordan.

Acquired immune deficiency syndrome (AIDS) associated with eosinophilic gastroenteritis is rare. We report a case of duodenal “stone” inducing acute pancreatitis with eosinophilic gastroduodenitis in an AIDS patient.

A 73-year-old female AIDS patient came to the hospital with recurrent abdominal pain for 20 days. Computed tomography (CT) showed pancreatitis with exudation and a high-density shadow under the gastric antrum. Gastroscopy showed that the descending part of the duodenum was blocked by a “stone”. The mucosa of the duodenum was rough, and a red polyp was found on the gastric body. The pathology result was chronic inflammation with eosinophilic granulocytes in the duodenal mucosa and gastric body polyp.

When AIDS patients suffer acute pancreatitis, the possibility of eosinophilic gastroenteritis needs to be considered to enable the patient to accept timely treatment.

Artificial intelligence-based aided diagnostic systems for pulmonary nodules can be divided into subtasks such as nodule detection, segmentation, and benign and malignant differentiation. Most current studies are limited to single-target tasks. However, aided diagnosis aims to distinguish benign from malignant pulmonary nodules, which requires the fusion of multiple-scale features and comprehensive discrimination based on the results of multiple learning tasks.

This study focuses on the aspects of model design, network structure, and constraints and proposes a novel model that integrates the learning tasks of pulmonary nodule detection, segmentation, and classification under weakly supervised conditions.

The main innovations include the following three aspects: (1) a two-dimensional sequence detection model based on a ConvLSTM (Convolutional Long Short-Term Memory) network and U-shaped structure network is proposed to obtain the context space features of image slices fully; (2) a differential diagnosis of benign and malignant pulmonary nodules based on multitask learning is proposed, which uses the annotated data of different types of tasks to mine the potential common features among tasks; and (3) an optimization strategy incorporating prior knowledge of computed tomography images and dynamic weight adjustment of multiple tasks is proposed to ensure that each task can efficiently complete training and learning.

Experiments on the LIDC-IDRI and LUNA16 datasets showed that our proposed method achieved a final competition performance metric score of 87.80% for nodule detection and a Dice similarity coefficient score of 83.95% for pulmonary nodule segmentation.

The cross-validation results of the LIDC-IDRI and LUNA16 datasets show that our model achieved 87.80% of the final competition performance metric score for nodule detection and 83.95% of the DSC score for pulmonary nodule segmentation, representing the optimal result for that dataset.

This study aimed to determine the utility of a radiomic nomogram combined with clinical imaging and radiomic features based on MRI for the diagnosis of triple-negative breast cancer.

Multi-parametric MRI images of 136 breast cancer patients were retrospectively analyzed, 95 cases were stratified into the training cohort, and 41 cases were selected for the test group. According to the pathological molecular typing, the patients were divided into 23 cases of triple-negative breast cancer and 113 cases of non-triple-negative breast cancer. ITK software was used to manually delineate the lesion volume region of interest (VOI), and the Pyradiomics package was used to extract radiomic features for screening and model building. The platform was then used to analyze the clinical and imaging risk factors of breast cancer to build a characteristic model separately. Finally, a radiomic nomogram was constructed by integrating the radiomic and independent clinical image features. The diagnostic performance of the model was assessed using ROC curves.

Univariate and multivariate analyses showed that the menstrual cycle, glandular density, and skin thickening were risk factors for clinical imaging characteristics of triple-negative breast cancer. The Area Under the Curve (AUC) was 0.839 and 0.826 for univariate and multivariate analysis, respectively. After screening, 11 radiomic features participated in the calculation of the radiomic score, and its AUC in the test set was 0.803. Combining it further with clinical models, the AUC improved to 0.899.

The radiomic nomogram developed in this study has great value in the diagnosis of triple-negative breast cancer.

Osteonecrosis of the femoral head (ONFH) is an incapacitating disease that frequently results in the collapse of the femoral head and secondary osteoarthritis. The diagnosis and staging of this pathology, which usually rely on imaging studies, are challenging. Currently, conventional radiography is the basis of the initial diagnostic assessment. In recent decades, however, radiographs have been considered insensitive to early changes in ONFH and thus, a suboptimal diagnostic tool. Paradoxically, the imaging features of radiographs are often profuse, substantial, and characteristic. This study aimed to elucidate the real limitations of this radiologic tool by assessing the diagnostic reliability of the key radiologic features and staging.

This was a retrospective study in which radiographs from 28 idiopathic ONFH confirmed cases who underwent hip arthroplasty were analyzed by eight observers who were asked to identify the presence or absence of ONFH universally reported imaging features in AP hip radiographs.

Concordance analysis revealed a poor agreement between observers for most of the assessed imaging features. Only the identification of femoral head flattening and osteoarthritis signs exhibited moderate agreement with statistical significance. In contrast, the detection of radiological osteoporosis and the loss of trabeculation showed the lowest reliability, with negative kappa coefficients.

There is a lack of agreement between qualified observers, even for the identification of the most characteristic ONFH radiographic features. The reliability of plain radiography for the detection of basic radiological elements is even weaker in the early stages of the disease.

Vitrectomy combined with internal limiting membrane (ILM) peeling or ILM inverted flap greatly improves hole closure and vision prognosis for idiopathic macular holes (IMH). The application of indocyanine green (ICG) in MH surgery increases the visibility of ILM and the safety of surgery. However, the area of ILM peeling and the state of the flap and a closed hole has not been well observed.

Fundus autofluorescence at 7935nm can show the range of ILM peeling and the state of the hole site and ILM flap by monitoring residual ICG postoperatively. However, the characteristics of fundus autofluorescence especially the site of the closed hole, and its relationship with vision prognosis have not been explored. The aim of this project was to find the autofluorescence features of the closed hole and their relation with vision.

To investigate the characteristics of fundus autofluorescence imaging after ICG-assisted vitrectomy for IMH and to evaluate the correlations of fluorescence patterns at the MH site with visual acuity and macular anatomic outcomes.

We retrospectively evaluated 33 IMH patients (33 eyes) who underwent a 25G pars plana vitrectomy (follow-up, 6-14.5 months). ICG staining (2.5 mg/mL) was either used to remove the internal limiting membrane (ILM) or the inverted ILM flap was overlaid on the hole. After surgery, fluorescence imaging of the fundus was obtained using a scanning laser ophthalmoscope at 795 nm.

On fluorescence imaging, the area of ILM peeling in all eyes showed hypofluorescence with no changes over time. The inverted ILM flap (performed in 18 eyes) was positioned on the inferior retina and exhibited early mild hyperfluorescence with blurred edges. This was gradually enhanced up to 3-6 months postoperatively and was then attenuated. MHs showed two distinct patterns on optical coherence tomography: granular (21 eyes) and patchy hyperfluorescence (12 eyes). Best-corrected visual acuity improved postoperatively in all cases (p<0.001, Z=-4.744). VA was worse in the patchy (vs. granular) hyperfluorescence cases (p=0.011, Z=-2.548).

The status of the ILM peeling area, ILM flap, and closed MH can be clearly observed using autofluorescence imaging at 795 nm. Fluorescence may be due to ICG staining of the ILM and accumulation in retinal pigment epithelium cells during ICG-assisted surgery. Granular hyperfluorescence at the MH site may indicate good anatomic and visual prognoses.

A number of studies have evaluated the effect of colour Doppler ultrasound in patients with cervical cancer.

Objective: This study aims to evaluate the efficacy of colour Doppler ultrasound and two-dimensional ultrasound of monitoring patients with cervical cancer.

Colour Doppler ultrasound (Experimental group) and two-dimensional ultrasound (Control group) are used to monitor cervical cancer and assess the treatment effects. PFS, CI, HR, DCR, ORR, PR, SD, PD, ROD, sensitivity, and specificity, accuracy between the two groups were collected and analyzed.

A total of 50 patients are included in this study, and the results show that PFS (Experimental group (EG) 5.8±2.2 versus Control group (CG) 6.1±2.6), CI (EG 20% versus CG 16%), HR (EG0.31±0.18 versus CG 0.36±0.21), DCR (EG 80% versus CG 84%), ORR(EG 28% versus CG 36%), PR (EG 16% versus CG 20%), SD (EG 48% versus CG 56%), PD (EG 12% versus CG 16%) (EG 12% versus CG 16%), ROD(EG 44% versus CG 52%) between the two groups are >0.05, and the values of sensitivity (EG 75.6% versus CG 40.2%), specificity (EG 78.4% versus CG 43.3%), and accuracy(EG 80.5% versus CG 41.4%) between the two groups are<0.05.

Both Colour Doppler ultrasound and two-dimensional ultrasound are effective methods to evaluate the efficacy of concurrent chemo-radiotherapy in patients with cervical cancer.

Wire localisation techniques are used widely for precision surgery in many specialities. This convenient technique has not yet become mainstream in the field of head and neck surgery. With limited space and many vital structures coursing through the head and neck region, pathological nodes that are difficult to palpate can be a challenge for clinicians.

A patient with a history of papillary thyroid cancer treated with surgery and radioactive iodine had a single pathological node detected on ultrasound surveillance. An isolated recurrence of papillary thyroid carcinoma was confirmed. An excisional biopsy was performed using ultrasound wire guidance to successfully remove the diseased node with minimal morbidity.

Wire-guided lymph node excision biopsy is a safe and effective method that can be applied to multiple pathologies. As of yet, it is not routine practice to employ this technique. Larger studies would increase the generalisability and safety profile of this technique in the head and neck region.

The current article presents a clinical case of ultrasound controlled transthoracic tru-cut needle biopsy of a small metastatic lesion in the left lung, performed with contrast-enhanced ultrasonography (CEUS). The following case demonstrates a real-time interventional manipulation of a very small lesion, which was done under local anesthesia, with a minimal invasion to the patient.

A 72-year-old woman is presented, hospitalized for a left-sided pleural effusion with bilateral, multiple nodulеs of different sizes in the lungs. Thoracentesis revealed data for atypical cells in the pleural fluid. The CT scan suspected a probable neoplastic process, but the subsequently performed fiberbronchoscopy couldn’t prove the existence of the same. The final diagnosis was established after ultrasound controlled transthoracic tru-cut needle biopsy of a pulmonary lesion with the application of a contrast medium.

The CEUS allows precise detection of the metastatic area because of its unique perfusion characteristics and ability to remain hypocontrasted after the application of the contrast medium sulfur hexafluoride. The persistence of a concomitant left-sided pleural effusion is used as an ultrasound window during the performance of the manipulation, with the successful verification of the pathology as primary pulmonary adenocarcinoma. By the application of this minimally invasive manipulation, an accurate final histological result was obtained.

Chronic liver disease (CLD) will affect the enhancement of hepatic parenchyma and portal vein on abdominal-enhanced MRI.

To investigate the difference in liver parenchyma and portal vein enhancement in patients with CLD of different liver function grades between Gd-EOB-DTPA and Gd-DPTA in the portal venous phase (PVP).

This retrospective study included 218 patients with CLD who had undergone abdominal enhanced MRI from January 2019 to June 2020. Patients with various degrees of liver dysfunction were identified with Child-Turcotte-Pugh and albumin-bilirubin grade. Two readers measured the precontrast and PVP signal intensities of liver parenchyma, portal vein, spleen, and psoas muscle. Relative liver enhancement, liver-to-spleen contrast index, portal vein image contrast, and portal vein-to-liver contrast were calculated.

The relative enhancement of liver parenchyma was significantly lower for the Gd-EOB-DTPA group in any degree of liver function than the Gd-DTPA group in the PVP. The Gd-EOB-DTPA group showed significantly lower portal vein-to-liver contrast in the overall study population, CTP class B, and ALBI grade 2 patients compared to the group of Gd-DTPA at PVP. No significant difference was noted in the portal vein image contrast between the two contrast agents, regardless of CTP and ALBI grading.

In CLD patients, Gd-EOB-DTPA yielded lower liver parenchymal enhancement and similar portal vein image contrast compared to Gd-DTPA in the PVP. Portal vein-to-liver contrast in the Gd-EOB-DTPA group was lower in the CTP class B and ALBI grade 2 subgroups compared to the Gd-DTPA group.

Lung cancer is a pervasive and persistent issue worldwide, with the highest morbidity and mortality among all cancers for many years. In the medical field, computer tomography (CT) images of the lungs are currently recognized as the best way to help doctors detect lung nodules and thus diagnose lung cancer. U-Net is a deep learning network with an encoder-decoder structure, which is extensively employed for medical image segmentation and has derived many improved versions. However, these advancements do not utilize various feature information from all scales, and there is still room for future enhancement.

In this study, we proposed a new model called Blend U-Net, which incorporates nested structures, redesigned long and short skip connections, and deep supervisions. The nested structures and the long and short skip connections combined characteristic information of different levels from feature maps in all scales, while the deep supervision learning hierarchical representations from all-scale concatenated feature maps. Additionally, we employed a mixed loss function to obtain more accurate results.

We evaluated the performance of the Blend U-Net against other architectures on the publicly available Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) dataset. Moreover, the accuracy of the segmentation was verified by using the dice coefficient. Blend U-Net with a boost of 0.83 points produced the best outcome in a number of baselines.

Based on the results, our method achieves superior performance in terms of dice coefficient compared to other methods and demonstrates greater proficiency in segmenting lung nodules of varying sizes.

Portal vein size and hemodynamics can be altered in patients with portal hypertension. Elastography for liver stiffness has been proposed as a potential predictor of portal hypertension. However, the relationship between liver stiffness measured using point shear wave elastography (pSWE) and portal vein diameter and Doppler parameters remains unclear. Therefore, this observational study aimed to investigate the correlation between liver ultrasound pSWE and portal vein hemodynamics in healthy participants.

Twenty-five healthy men with no underlying medical conditions and who were not on regular medications were enrolled in the study. Liver stiffness, portal vein diameter, and Doppler parameters were measured using ultrasound EPIQ Elite with a curved-array transducer (C5-1 MHz) equipped with pSWE and Doppler imaging. Real-time pSWE measurements were taken from the liver. Portal vein diameter and Doppler parameters were measured in a longitudinal view of the extra-hepatic segment. Spearman correlation was used to assess the association between liver pSWE and portal vein diameter as well as Doppler parameters, with a significance level set at < 0.05.

There was no significant correlation between liver stiffness and portal vein diameter (p = 0.67) or Doppler parameters, including peak systolic velocity (p = 0.89), end-diastolic velocity (p = 0.65), and resistive index (p = 0.86).

Our findings suggest no direct correlation between liver stiffness measured using pSWE and portal vein hemodynamics in healthy adults. Further studies are warranted to investigate the relationship between liver pSWE and the hemodynamics of portal veins in patients with liver diseases.

Generalized distal radius die-punch fractures (GDP) can involve three columns. However, there is no three-column classification for GDP. The aim of this study was to introduce a three-column classification for GDP, and to investigate the application effect of the classification.

613 patients with GDP accrued from January 2013 to December 2021 were classified by column and fracture type based on imaging findings. First, the GDP was categorized into single-, double-, or three-column fractures. Second, the intermediate column fractures were divided into volar, dorsal, split, collapse, or mixed types; the radial column fractures were divided into metaphyseal, articular or mixed types; and the ulnar column fractures were divided into apical or basal types of the styloid process. The intra- and inter-observer consistency between the two assessors was analyzed with kappa statistics. 227 patients with less fracture displacement were treated conservatively, whereas 386 patients with increased fracture displacement were treated surgically, and the selection of surgical approaches and fracture reduction-fixation methods was guided by the classification. The differences in incidence, gender, age, treatment methods, and functional recovery were compared among the three categories, and the characteristics of different types were observed. The wrist joint function was evaluated according to the Sarmiento-modified Gartland-Werley method.

The intra- and the inter-observer kappa coefficients were obtained as ≥ 0.810. There were significant differences in the incidence (12.7%, 68.5%, and 18.8%, respectively) and age (39.8, 46.6, and 47.1 years, respectively) for single-, double- and three-column fractures (P<0.05). However, there was no significant difference in terms of gender among the three (P>0.05). The mixed, collapse, split, dorsal, and volar types accounted for 28.7%, 27.7%, 21.9%, 15.5%, and 4.5%, respectively. The metaphyseal, articular surface, and mixed types accounted for 35.9%, 33.1%, and 31.0%, respectively. The apical and base types were 81.7% and 18.3%, respectively. Among the cases of volar and dorsal types, the missed diagnosis rate of X-ray alone was 28.5%, but it was confirmed by subsequent CT. In the last follow-up of 12.2 months (range, 6 to 24 months), the excellent plus good rate was 82.7% and 82.6%, respectively, in total and among patients undergoing surgical treatment; the excellent plus good rate of the single column fractures was 96.2%, significantly higher than that of double- and three-column fractures (80.0% and 83.5%, respectively) (P<0.05). All patients with fair or poor wrist function had collapse or mixed-type intermediate column fractures.

Different categories/types of GDP have significant differences in terms of incidence, age, efficacy, and prognosis. Imaging classification by column and type of GDP better reflects the features and injury mechanism of the fractures with good consistency. Therefore, it has important reference value for the surgical modality and prognosis evaluation.

Currently, three-dimensional cephalometry measurements are mainly based on cone beam computed tomography (CBCT), which has limitations of ionizing radiation, lack of soft tissue information, and lack of standardization of median sagittal plane establishment.

This study investigated magnetic resonance imaging (MRI)-only based 3D cephalometry measurement based on the integrated and modular characteristics of the human head.

Double U-Net CycleGAN was used for CT image synthesis from MRI. This method enabled the synthesis of a CT-like image from MRI and measurements were made using 3D slicer registration and fusion.

A protocol for generating and optimizing MRI-based synthetic CT was described and found to meet the precision requirements of 3D head measurement using MRI midline positioning methods reported in neuroscience to establish the median sagittal plane. An MRI-only reference frame and coordinate system were established enabling an MRI-only cephalometric analysis protocol that combined the dual advantages of soft and hard tissue display. The protocol was devised using data from a single volunteer and validation data from a larger sample remains to be collected.

The reported method provided a new protocol for MRI-only cephalometric analysis of craniofacial growth and development, malformation occurrence, treatment planning, and outcomes.

Breast cancer, one of the most prevalent malignant tumors in females, usually occurs in the breast epithelial tissues.

The study aimed to explore the diagnostic value of contrast-enhanced ultrasound (CEUS) combined with shear wave elastography (SWE) in the diagnosis of benign and malignant breast masses in BI-RADS (Breast Imaging Reporting and Data System) 4.

Examination outcomes and clinical information of 83 patients with BI-RADS 4 breast masses were analyzed retrospectively. These included patients who received CEUS, SWE, and pathological examinations. The difference of CEUS in determining the classification of BI-RADS 4 breast masses was evaluated using histopathological outcomes of breast masses as a reference standard. The diagnostic value of CEUS, SWE, and CEUS combined with SWE in the diagnosis of benign and malignant breast masses in BI-RADS 4 was also explored.

Pathological biopsy results revealed 63 malignant masses and 20 benign masses among 83 BI-RADS 4 breast masses, with a 75.9% incidence of malignant masses. After the diagnosis of BI-RADS 4 breast masses with CEUS, SWE, and CEUS+SWE, the incidence of malignancy was 56.6%, 78.3%, and 73.5%, respectively. CEUS+SWE showed higher sensitivity (93.7% vs. 81% and 68.3%), specificity (90% vs. 30% and 80%), positive predictive value (96.7% vs. 78.5% and 91.5%), negative predictive value (81.8% vs. 33.3% and 44.4%), and diagnostic coincidence rate (92.8% vs. 68.7% and 71.1%) than SWE and CEUS alone in diagnosing pathological type of breast masses. Moreover, CEUS combined with SWE exhibited a larger area under the receiver operating characteristic (ROC) curve (0.918) than SWE (0.741, p = 0.028) and CEUS (0.555, p 0.001) alone in the diagnosis of BI-RADS 4 breast masses.

Overall, the diagnostic value of CEUS+SWE for the pathological type of BI-RADS is preferred over CEUS and SWE alone. CEUS+SWE showed higher values than CEUS and SWE alone in diagnosing BI-RADS 4 breast masses. Specifically, CEUS+SWE can correctly identify benign and malignant masses, reduce unnecessary trauma, and avoid misdiagnosis. In summary, CEUS combined with SWE can serve as an effective diagnostic method and avoid delaying the best treatment opportunity for some malignant lesions.

This paper presents a novel approach for detecting abnormality in coronary arteries using MRI data in RGB images. The study evaluates the test accuracy of the weak classifiers and the test accuracy and F1 score of the strong classifier.

The method involves separating the image into information planes, including R, G, and B color space, or bit-planes, and training a VGG-like convolutional neural network model on each plane separately, referred to as a “weak classifier.” The classification results of these planes are aggregated using a proposed soft voting method, forming a “strong classifier,” with the weights for the aggregation determined by the model's performance on the training set.

The results indicate that the strong classifier achieves a test accuracy and F1 score of around 68% to 74% on our private coronary artery dataset. Moreover, by aggregating the top three highest bit-plane levels in a grayscale image, the accuracy is slightly lower than that of the three color spaces but requires a significantly smaller CNN model of nearly 4M parameters.

The potential of bit-planes in reducing model storage costs is suggested. This approach holds promise for improving the detection of abnormalities in coronary arteries using MRI data.

To investigate the radiological characteristics of the PHNENs on CT and MRI and improve the understanding of the image manifestations and preoperative diagnosis of the disease.

Primary hepatic neuroendocrine neoplasms (PHNENs) are rare diseases, and most of the relevant studies are case reports. Characterized by no specific clinical symptoms, PHNENs not only have a low preoperative diagnosis rate with great difficulty in early diagnosis but are frequently misdiagnosed as primary hepatic cancer.

15 PHNEN patients were enrolled, with 10 cases in the G2 stage and 5 cases in the G3 stage.

The imaging and clinicopathological information of 15 patients pathologically diagnosed with PHNENs was retrospectively reviewed.

The average age of the patients enrolled was 46.14±18.24 years, and the average tumor size was 91.00±61.17 mm. 13 cases showed nodules or masses, 8 cases were located in the periphery of the liver, showing capsule depression and subcapsular effusion signs. CT enhanced scan showed heterogeneous and obvious enhancement in 9 arterial-phase cases, 2 cases in arterial and portal venous phases both saw mild enhancement; the enhancement degree of lesions in the G2 stage in the arterial phase was significantly higher than in the G3 stage. Gd-EOB-DTPA dynamic enhanced MRI was conducted on 3 cases, and scattered lesions with heterogeneous and slight hyperintensity were observed in the hepatobiliary-specific lesions. Image manifestations showed diffuse lesions in 2 cases, with heterogeneous enhancement in the arterial phase and decreased enhancement in the portal venous phase by the dynamic enhanced scan.

PHNENs were the imaging characteristics of PHNENs. The CT-enhanced scanning during the arterial phase may provide a certain reference for pathological grading (G2 and G3 grades). Gd-EOB-DTPA-enhanced MRI is helpful for PHNEN diagnosis.

This study aimed to characterize and assess the diagnostic value of prenatal magnetic resonance (MR) imaging in detecting fetal cerebellar hypoplasia/dysplasia and developmental malformations.

Reports of suspected intracranial abnormalities were retrospectively collected on ultrasound screening (US), and MR images of fetuses were reviewed at our institution over a 5-year period on picture archiving and communication system (PACS) servers. Two experienced radiologists recorded major abnormalities and coexisting abnormalities at the reading of the census. The results of the MRI were compared against the US in each case.

For prenatal MR imaging, we enlisted a total of 121 patients (mean gestational week, 24.5 ± 4.7 weeks). This included 28 cases with normal findings of MR imaging, 62 cases with findings of cerebellar hypoplasia or dysplasia, and the remaining 31 cases with other abnormities findings. Cerebral malformations cases included agenesis of the corpus callosum, cerebral hemorrhage, hydrocephalus, holoprosencephaly, ventriculomegaly, and brainstem/gyri malformation. Cerebellar abnormalities included vermis absence, cerebellar tonsil hernia, Dandy-Walker malformation, Blake’s pouch cysts, arachnoid cysts, and intracranial hemorrhage. Other systemic malformation cases included tethered cord syndromes (9 cases), cleft lip and palate (1 case), club foot (1 case), and cardiac malformation (1 case). In 12 cases (24.5%), compared to the US, MR imaging proved the value of confirming the diagnosis and/or even yielded more findings on abnormalities.

Prenatal MR imaging can better visualize systemic malformations coexisting with cerebellar abnormalities. MR imaging, a complementary means to the US, can aid in prenatal counseling and treatment selection for term delivery.

The aneurysmal bone cyst is a benign neoplasm that tends to form the appearance of a mass with a bony septum that forms cavities with blood inside. It is estimated to represent 1% of bone tumours and has an incidence of 0.14 per 100,000 people worldwide. Current publications have not shown a multidisciplinary approach that can benefit patients, mainly in the functionality and quality of the management approach.

Describe the multidisciplinary approach and the benefits of quality of life and functionality in this diagnosis.

A paediatric patient was diagnosed with an aneurysmal bone cyst located in the cervical spine, which initially manifested with muscle pain, enlargement of the posterior cervical region, and difficulty in performing arcs of movement. He was treated with multidisciplinary management with surgery, embolisation, radiation, and bisphosphonate support.

The purpose of approaching multidisciplinary management helped to improve the accompanying symptoms that prevented our patient from having an active and quality life. However, more successful cases have not been reported to establish the best therapeutic protocol.

MRI of patients with locally advanced rectal cancer (LARC) can predict the pathological complete response (pCR) to preoperative chemoradiation therapy (CRT). Our purpose was to use MRI results to evaluate the diagnostic value of combined changes in signal intensity (SI) and volume (V) of patients with LARC for predicting pCR to CRT.

This retrospective study on 100 patients with LARC analyzed clinical and imaging data that were collected from March, 2018, to March, 2020. Before and after CRT, T2-weighted (T2W), apparent diffusion coefficient (ADC), and contrast-enhanced T1-weighted (ceT1W) data were analyzed. Percent changes of V (%∆V) and relative SI ratio (%∆SIR) on different sequences were calculated. After CRT, patients had pathological confirmation as pCR or non-pCR. Data were analyzed using nonparametric tests and receiver operating characteristic (ROC) analysis.

There were 34 pCR and 66 non-pCR patients. Except for ADC-%∆SIR, the combined parameters and single parameters had a greater decrease in the pCR group. The combination of ADC-%∆V and T2W-%∆SIR had the greatest diagnostic value (AUC=0.85,cutoff=0.23%) and the combination of ADC-%∆V% and ∆SIR had the best accuracy (89%, cutoff=44.11%). Except for T2W-%∆V and T2W-%∆SIR, the different sequences had moderate differences in diagnostic performance. The diagnostic performance of combined parameters or single parameters on ADC and T2W was significantly better than those on ceT1W (p<0.01).

All sequences except ADC-%∆SIR provided reliable predictions of pCR, although ceT1W data had limited usefulness.

Modern medical imaging modalities used by clinicians have many applications in the diagnosis of complicated diseases. These imaging technologies reveal the internal anatomy and physiology of the body. The fundamental idea behind medical image fusion is to increase the image's global and local contrast, enhance the visual impact, and change its format so that it is better suited for computer processing or human viewing while preventing noise magnification and accomplishing excellent real-time performance.

The top goal is to combine data from various modal images (CT/MRI and MR-T1/MR-T2) into a solitary image that, to the greatest degree possible, retains the key characteristics (prominent features) of the source images.

The clinical accuracy of medical issues is compromised because innumerable classical fusion methods struggle to conserve all the prominent features of the original images. Furthermore, complex implementation, high computation time, and more memory requirements are key problems of transform domain methods. With the purpose of solving these problems, this research suggests a fusion framework for multimodal medical images that makes use of a multi-scale edge-preserving filter and visual saliency detection. The source images are decomposed using a two-scale edge-preserving filter into base and detail layers. Base layers are combined using the addition fusion rule, while detail layers are fused using weight maps constructed using the maximum symmetric surround saliency detection algorithm.

The resultant image constructed by the presumed method has improved objective evaluation metrics than other classical methods, as well as unhindered edge contour, more global contrast, and no ringing effect or artifacts.

The methodology offers a dominant and symbiotic arsenal of clinical symptomatic, therapeutic, and biomedical research competencies that have the prospective to considerably strengthen medical practice and biological understanding.

Castleman's disease is an extremely rare disease in the abdomen region characterized by benign lymphoepithelial proliferation.

We report a case of a 63-year-old female who presented with abdominal pain. Abdominal CT Angio and dynamic contrast-enhanced abdominal MRI revealed a mass lesion showing markedly contrast enhancement, no vascular invasion sign, and diffusion restriction lesion in the truncus coelicus bifurcation region. The mass was surgically resected completely. Pathological evaluation showed a hyaline-vascular type of Castleman’s disease.

Castleman's disease should be kept in mind in the differential diagnosis of an isolated intra-abdominal mass.

Hepatic artery aneurysms (HAAs) exhibit a notable risk of rupture, with both true aneurysms and pseudoaneurysms being exceptionally uncommon (incidence rate approximately 2 per 100,000). Symptoms include epigastric and right upper quadrant pain, jaundice, and potentially life-threatening bleeding upon rupture. This bleeding can extend into the portal vein, hepatic vein, biliary system, or abdominal cavity. While existing literature lacks reports of delayed post-therapeutic complications, this case report discusses a 27-year-old female who developed a pseudoaneurysm six months after bilateral biliary drain insertion, underscoring the potential for delayed complications.

The patient underwent gastric endoscopy revealing an extensive lower esophageal varix protruding into the proximal stomach, subsequently treated with banding. The stomach and duodenum were found to contain fresh blood and blood clots indicating acute bleeding.

An urgent CT scan identified active bleeding (extravasation) at segment V and blood accumulation at the confluence of the right and left biliary drains. This was followed by celiac and selective hepatic digital subtraction angiography (DSA).

This case study outlines the occurrence of a hepatic artery pseudoaneurysm six months after percutaneous insertion of bilateral biliary drains. The pseudoaneurysm manifested precisely at the confluence of the right and left drains. The reported delayed complication may have resulted from friction between the drains at the confluence or erosion of the adjacent artery by the drains. The insights gained from this case shed light on the causes and preventive measures for potential delayed complications associated with percutaneous biliary drain placement.

Ovarian cancer is a common gynecological malignant tumor in women. Most patients have reached the advanced stage when they visit the hospital. In order to diagnose ovarian cancer at an early stage, treat it at an early stage, and improve the survival rate of patients, this study has used the imaging computed tomography (CT) method to diagnose stage IA ovarian cancer.

The purpose of this work was to study CT features of stage IA ovarian cancer, and compare the borderline tumor and stage IC ovarian cancer at the same time so as to improve the CT diagnosis of early ovarian cancer.

We retrospectively collected clinical and CT data of patients with stage I ovarian cancer and borderline ovarian tumor admitted to Nantong Tumor Hospital from 2013 to 2021. Altogether, 23 cases of patients (borderline ovarian tumor, 9 cases; stage IA ovarian cancer, 5 cases; stage IC ovarian cancer, 9 cases) were involved. CT characteristics of these patients were analyzed in terms of the tumor diameter, cystic solid structure, solid component, septation, enhancement, peritoneal thickening, ascites, and abdominal lymph nodes.

CT features of stage IA ovarian cancer included large tumor size (average diameter: 15 cm), cystic solid structure (4/5; 80%), septation (4/5; 80%), and enhanced cystic wall, septum, or solid components of the tumor on contrast-enhanced CT (5/5; 100%), no peritoneal thickening (0/5; 0%), no ascites (0/5; 0%), and no abdominal lymph node enlargement (0/5; 0%). The tumor structure did not differ significantly between stage IA and IC ovarian cancers (p > 0.05), while intraperitoneal ascites did (χ² = 0.031; p < 0.05). Stage IA and borderline ovarian tumors did not differ significantly in ovarian tumor structure (p > 0.05).

CT features of stage IA ovarian cancer included large tumor size, cystic solid structure, septation, and enhanced cystic wall and solid parts in the tumors. No pelvic or abdominal metastasis was observed.

Lung ultrasound (LUS) is gaining recognition as an indispensable diagnostic tool in critical care.

The study aimed to characterize the global research landscape and trend of LUS with quantification and visualization approaches.

Documents related to LUS published between 2007 and 2023 were selected from the Web of Science Core Collection and identified. Visualization and statistical analysis were conducted with the VOSviewer 1.6.18, CiteSpace 5.7.R5, and Bibliometrix 4.1.0 Package, including analysis of the trend of global publications, prominent countries, active institutions, and funding agencies, key authors and journals, co-cited references, and keywords.

A total of 3010 publications, including 2434 articles and 576 reviews, were retrieved. The output of LUS-related research has increased steadily over the years, especially after 2018. Italy (n=756; 25.12%) has shown the highest output, being the country with the highest total citations (23423 times). The most influential author was Gargani Luna with 52 documents, who worked at the Consiglio Nazionale delle Ricerche. Chest and Intensive Care Medicine with high citations and impact factor scores were the most influential journals. Besides “lung ultrasonography”, the keywords developed included “coronavirus disease 2019 (COVID-19)”, “acute respiratory distress syndrome”, and “acute heart failure”.

Research output on LUS has increased steadily, especially after 2018. Italy and the United States are staying ahead in this field. Research collaboration still needs to be strengthened. This comprehensive analysis has presented the global research landscape and trends of LUS-related research, providing valuable information for researchers to pursue further exploration.

The fat attenuation index (FAI) of pericoronary adipose tissue is associated with coronary inflammatory reactions.

This study aimed to analyze the difference in the FAI ratio between pericoronary adipose tissue volume and aortic root epicardial adipose tissue volume (AO-EATV) using computed tomography (CT) in various plaques.

In total, 645 coronary artery CT angiogram images from 215 patients were collected. The types and number of coronary plaques were recorded, and the plaque volume and pericoronary FAI of each branch were compared between the groups. The ratio of the FAI in branches with or without plaques to the AO-EATV was determined and statistically analyzed between the groups.

No significant difference in the plaque volume among the left anterior descending (LAD), left circumflex (LCX), and right coronary artery (RCA) (P > 0.05) as well as in the FAI was observed among various plaque groups (P > 0.05). FAI[LAD]/AO-EATV was in the following order: noncalcified plaques (0.70 ± 0.06) < mixed plaques (0.72 ± 0.06) < calcified plaques (0.73 ± 0.08) < no plaques (0.74 ± 0.07); FAI[LCX]/AO-EATV was in the following order: noncalcified plaques (0.71 ± 0.06) < mixed plaques (0.72 ± 0.08) < calcified plaques (0.73 ± 0.09) < no plaques (0.74 ± 0.06); and FAI[RCA]/AO-EATV was in the following order: noncalcified plaques (0.71 ± 0.06) < mixed plaques (0.73 ± 0.07) < calcified plaques (0.74 ± 0.07) < no plaques (0.75 ± 0.09); the differences were statistically significant in each group (P = 0.041, 0.043, and 0.028, respectively).

Compared to simply comparing FAI, FAI/AO-EATV varied in the coronary arteries in various plaque groups. FAI/AO-EATV was lower in noncalcified or mixed plaques and was associated with coronary inflammatory reactions.

Klippel-Trenaunay syndrome (KTS) is a rare congenital disease that mainly involves blood vessels and is characterized by the presence of capillary malformations (port wine stains), varicose veins, soft tissue and/or bone hypertrophy.

We report a 28-year-old man who was diagnosed 20 years ago with Klippel-Trenaunay syndrome. Approximately 3 years ago, he found enlarged masses on both upper extremities and a new dark red mass that was pathologically diagnosed as cavernous haemangioma appeared on the right index finger.

KTS is a rare and potentially multisystem disease requiring multidisciplinary management for which imaging examination is an important auxiliary diagnostic method. Various complications may occur during its development, so regular follow-up is required to prevent serious accidents.

Meniscal tears are among the most common indications for knee arthroscopy. Artificial polyurethane scaffolds have demonstrated efficacy in reducing pain and promoting the growth of normal meniscal tissue, with high absorption rates facilitating full tissue regeneration.

This study aimed to evaluate the remodeling of polyurethane meniscal implants post-reconstruction using ultrasonography. This imaging technique not only assesses changes in implant properties, such as echogenicity, but also the shape changes during functional examination.

The assessment of meniscal extrusion, comparing size at rest and under weight-bearing, is an indirect parameter that provides insight into the physical properties of the remodeling implant, with greater extrusion indicating reduced stiffness and inferior physical properties of the meniscus. Ultrasonography has the valuable advantage of allowing for assessment of the blood supply to the meniscus through Power Doppler imaging.

The presence of vessels within the meniscal implants serves as evidence of ongoing remodeling. The study included 35 patients (13 female, 22 male; mean age 41.6 years, range 18-66) who underwent arthroscopic meniscal reconstruction with polyurethane implants, with an average time from surgery of 2.8 years (range 0.3-4.5 years). Results showed complete (29.7%), significant (45.9%), or moderate (16.2%) remodeling into natural meniscal tissue in 91.8% of the implants.

The mean values of extrusion in the supine position and during 90-degree flexion were significantly greater in the operated limb (2.603) compared to the contralateral limb (1.978; t(35) = 2.442; P < 0.05). No significant differences in extrusion were found between the limbs in a standing position, indicating favorable physical properties of the polyurethane meniscal implants. Further ultrasonography studies of meniscal scaffolds are deemed relevant.

It has been reported in the literature that Vitamin D can inhibit the growth of uterine fibroids, but the evaluation index is only the size of the uterine fibroids. The purpose of this study was to evaluate the effect of vitamin D on the size, hardness, and blood flow of uterine fibroids in pre-menopausal women by multimodal ultrasound.

A total of 64 pre-menopausal women with uterine fibroids complicated vitamin D deficiency were enrolled in this study and randomly divided into two groups: the vitamin D group (n=32) which received oral vitamin D (1600 IU/ day) and the control group (n=32) without vitamin D supplementation. After three months of intervention, the mean diameter of uterine fibroids, elastic strain ratio, and blood flow grade were evaluated by multimodal ultrasound, and the clinical symptoms of the two groups were evaluated by questionnaire.

The vitamin D group reported a significant increment in the serum 25-hydroxyvitamin D (P < 0.001). In addition, there were significant reductions in the mean diameter, and elastic strain ratio of uterine fibroids (P =.043 and P =.038, respectively), but no significant difference in the blood flow grade of uterine fibroids was observed (P =.272). Compared with the control group, the vitamin D group achieved significant relief in dysmenorrhea and frequent urination, as well as improvement in heavy menstrual bleeding.

The application of multimodal ultrasound provides a more comprehensive theoretical basis for vitamin on uterine fibroids. Vitamin D can effectively reduce the size of uterine fibroids in pre-menopausal women and relieve their symptoms. It is highly likely to be a promising, safe, effective, and inexpensive drug for uterine fibroids, which has good application value and promotion prospects.

Osteoarthritis is a condition that poses a risk to the knee joint, resulting in pain and impaired function. However, traditional knee X-ray evaluations using the Kellgren-Lawrence grading system have proven to be inefficient. These evaluations are subjective, time-consuming, and labor-intensive, particularly in busy hospital settings.

The objective of this research was to present a deep learning-based approach that can detect knee joint regions in medical images. By addressing the limitations of traditional methods, the aim was to develop a more efficient and automated approach for knee joint analysis.

The proposed method utilizes the Faster R-CNN model, which consists of a region proposal network (RPN) and Fast R-CNN. The RPN generates region proposals that potentially contain knee joint regions, while the Fast R-CNN network categorizes and extracts features from these proposals. To train the model, a dataset of knee joint images was employed. The performance of the model was evaluated using metrics, such as accuracy, precision, recall, F1-score, and mean IoU (Intersection Over Union).

The results demonstrated the high accuracy of the proposed method in detecting knee joint regions. The model achieved a mean IoU of 94.5, indicating a strong overlap between the predicted and ground truth regions. These findings highlight the potential of deep learning-based approaches in automating medical image analysis, specifically in the diagnosis and management of knee joint disorders.

This study emphasizes the significance of leveraging advanced technologies, such as deep learning, in medical imaging. By developing more efficient and accurate methods for identifying knee joint regions in medical images, it becomes feasible to enhance patient outcomes and healthcare delivery. The proposed deep learning-based approach showcases promising results, paving the way for further advancements in the field of medical image analysis and contributing to improved diagnostic capabilities for knee joint disorders.

The aim of this study was to explore the criteria that can predict bladder cancer among the lesions that could not be differentiated from intravesical prostate protrusion (IPP) and to create a scoring system using these criteria.

A retrospective analysis was made of patients with an ultrasound report indicating lesions in the bladder neck, for which differentiation between bladder cancer and IPP could not be determined. A total of 174 patients diagnosed with bladder cancer (n=102) or benign prostate lesion (n=72) according to the biopsy results were enrolled in the study. Hemoglobin, prostate-specific antigen (PSA), prostate volume (PV), bladder wall thickness (BWT), lesion height (LH), and the ratio of lesion width to base (LW/B) were compared between the two groups.

ROC analysis revealed an AUC value >0.7 for all factors, and the best cut-off value was identified for each factor. In the multivariate analysis, by determining a score for each factor according to the ORs, the BCa-IPP scoring system was developed to provide a total score in the range of minimum 0 and maximum 15. In the ROC analysis, the AUC value was 0.954 (95% CI: 0.923–0.986) for the BCa-IPP score. The best cut-off value was found to be 10, with sensitivity of 0.93 and specificity of 0.85.

Using simple laboratory and ultrasound findings, the BCa-IPP scoring system was created, which was seen to have high predictive value and can be easily applied in the clinic. The BCa-IPP scoring system is a non-invasive test that can be successfully applied for the differentiation of bladder cancer from benign lesions.

Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS) is usually used for the semi-quantitative evaluation of joint changes in Rheumatoid Arthritis (RA). However, this method cannot evaluate early changes in bone marrow edema (BME).

To determine whether T1 mapping of wrist BME predicts early treatment response in RA.

This study prospectively enrolled 48 RA patients administered oral anti-rheumatic drugs. MRI of the most severely affected wrist was performed before and after 4 (48 patients) and 8 weeks of treatment (38 patients). Mean T1 values of BME in the lunate, triangular, and capitate bones; RAMRIS for each wrist; Erythrocyte-Sedimentation Rate (ESR); and 28-joint Disease Activity Score (DAS28)-ESR score were analyzed. Patients were divided into responders (4 weeks, 30 patients; 8 weeks, 32 patients) and non-responders (4 weeks, 18 patients; 8 weeks, 6 patients), according to EULAR response criteria. Receiver operating characteristic (ROC) curves were used to evaluate the efficacy of T1 values.

ESR and DAS28-ESR were not correlated with T1 value and RAMRIS at each examination (P > 0.05). Changes in T1 value and DAS28-ESR relative to the baseline were moderately positively correlated with each other at 4 and 8 weeks (r = 0.555 and 0.527, respectively; P < 0.05). At 4 weeks, the change and rate of change in T1 value significantly differed between responders and non-responders (-85.63 vs. -19.92 ms; -12.89% vs. -2.81%; P < 0.05). The optimal threshold of the rate of change in T1 value at 4 weeks for predicting treatment response was -5.32% (area under the ROC curve, 0.833; sensitivity, 0.900; specificity, 0.667).

T1 mapping provides a new imaging method for monitoring RA lesions; changes in wrist BME T1 values reflect early treatment response.

This study sought to analyze the ¹⁸F-FDG PET/CT and contrast-enhanced computed tomography (CT) images of synchronous colorectal cancer (CRC) and renal clear cell carcinoma (ccRCC) and identify the shared genes between these two types of cancer through bioinformatic analysis.

A retrospective analysis was conducted on a patient with synchronous CRC and ccRCC who underwent ¹⁸F-FDG PET/CT and contrast-enhanced CT before treatment. Databases were analyzed to identify differentially expressed genes between CRC and ccRCC, and co-expression genes were extracted for RCC and CRC.

¹⁸F-FDG PET/CT revealed intense metabolic activity in the primary colorectal lesion (SUVmax 13.2), while a left renal mass (diameter = 35 mm) was observed with no significant uptake. Contrast-enhanced CT during the arterial phase showed heterogeneous intense enhancement of the renal lesion, and the lesion washed out earlier than in the renal cortex in the nephrographic and excretory phases, indicating ccRCC. The histopathological results confirmed synchronous double primary malignant tumors. Our bioinformatic analysis results showed that synchronous occurrence of CRC and ccRCC may correlate with simultaneous expression of Carbonic Anhydrase 9 (CA9), integrin-binding sialoprotein (IBSP), and Fibrinogen γ chain (FGG).

¹⁸F-FDG PET/CT combined with contrast-enhanced CT is an effective diagnostic tool in evaluating synchronous CRC and RCC. By analyzing this clinical case and conducting bioinformatic analysis, we improved our current understanding of the mechanisms underlying synchronous tumors.

The aim of this study is to evaluate (i) the reasons for requesting ultrasonography (USG) in a dentistry faculty and (ii) the scanning regions, the type of probe used, and the use of Doppler USG.

USG request forms of patients who applied to our radiology clinic for USG were analyzed retrospectively. According to the clinical information of the patients in the request forms, the reasons for requesting USG were divided into four groups: soft tissue swelling, soft tissue calcification, lymph node, and other examinations. Data were statistically compared between sex (female and male) and age groups (≤40−years−old and ˃40−years−old).

The USG request forms of 50 patients were obtained. The mean patient age was 45.06±14.50 years. Twenty-six patients were female (52%), while twenty-four patients were male (48%). Soft tissue swelling, soft tissue calcification, lymph node, and other examinations were noted as the reasons for requesting USG in 42%, 26%, 18%, and 14% of the patients, respectively. The most scanned regions were the submandibular (56%), parotid (16%), and cheek (10%) regions. Extraoral probe was used more frequently than intraoral probe (78% vs. 22%). Doppler USG was used in most patients (98%). A statistically significant difference was found between age groups and calcification examination (p<0.05).

The reasons for requesting USG were mostly soft tissue swelling, soft tissue calcification, and lymph node examinations. The most commonly scanned region and used type of probe were the submandibular region and extraoral probe, respectively. Doppler USG was used in most patients.

High-altitude pulmonary edema (HAPE) is a serious life-threatening disease that occurs after rapid ascent to high altitude; its main early-stage presentations include fatigue, headache, low-grade fever, dyspnea, and cough. X-ray and computed tomography (CT) images show pulmonary shadows and patches, which may be localized (initial right lung field predomination) or generalized to the bilateral lung base.

In this report, we present a case of a 25-year-old man diagnosed with HAPE combined with spontaneous pneumomediastinum. After a quick descent and effective medical treatment, this patient made a full recovery. The case may provide helpful information for the prevention and treatment of this disease since an increased number of people, especially young men, currently travel and work at high altitudes.

After accurate clinical diagnosis with the help of CT or X-ray, immediate descent and appropriate oxygen supplementation are the most effective treatments for HAPE at high altitude.

Non-neoplastic liver lesions show low signal intensity in the hepatobiliary phase (HBP) of gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) after biliary stenting and require differentiation from liver metastases.

The study aimed to evaluate the imaging findings and clinical association of non-neoplastic liver lesions showing hypointensity in the HBP of EOB-MRI after biliary stenting, and assess their differentiation from liver metastases.

This study included 30 patients who underwent EOB-MRI after biliary stenting for pancreaticobiliary malignancies. Among these, 7 patients had pathologically diagnosed non-neoplastic liver lesions, which appeared hypointense in the HBP, and were categorized into the non-neoplastic group. The remaining 23 patients without non-neoplastic liver lesions were included in the control group. Additionally, 29 patients with liver metastasis were included in the liver metastasis group. Clinical associations and imaging features were compared between the groups.

A history of cholangitis and two or more biliary interventional procedures were significantly more frequently observed in the non-neoplastic group (p=0.002 and p=0.01, respectively) than in the control groups. Regarding the imaging findings, the liver-to-lesion signal intensity ratio in the HBP in the liver metastasis group was significantly higher than that in the non-neoplastic group (2.13 vs. 1.53, p=0.002). Additionally, liver metastases were visualized significantly more clearly on diffusion-weighted images (p=0.033) and HBP images (p<0.001) in comparison to non-neoplastic lesions.

Non-neoplastic liver lesions due to biliary inflammation may be observed in the HBP of EOB-MRI in patients after biliary stenting. These lesions may be associated with a history of cholangitis and repeated biliary intervention procedure, and need to be differentiated from liver metastases.

Generative adversarial networks (GANs) have demonstrated superior data generation capabilities compared to other methods, making them popular for use in medical image applications. These features have intrigued researchers in the medical imaging field, resulting in a swift implementation of these techniques in various conventional and novel applications such as image reconstruction, segmentation, detection, classification, and cross-modality synthesis. A comprehensive review of recent medical imaging breakthroughs will benefit researchers interested in this field. In this review, we aimed to introduce the origin, principle, and extended forms of GANs and summarize the state-of-the-art progress of GAN-based medical image processing methods.

We searched the literature for studies on Google Scholar and PubMed using the keywords “Segmentation,” “Classification,” “medical image,” and “generative adversarial network.” Specifically, the initial search revealed 5423 publications after the removal of duplicated and non-accessible full-text publications. Then, after the title and abstract screening, 680 underwent full-text screening. Finally, 121 studies were included in our final analysis after full-text screening.

The date range of the studies covered in this review is from January 1, 2017, to the present. After a thorough screening and qualification assessment, 121 studies involving GAN-based applications in seven areas of medical images were included in the final methodological review. These areas included synthesis, classification, segmentation, conversion, reconstruction, denoising, and lesion detection. We further classified and summarized these papers into clinical applications, classification methods, and imaging modalities.

We thoroughly examined the latest research progress of GAN-based medical image augmentation. These techniques effectively alleviate the challenge of limited training samples for medical image diagnosis and treatment models. Furthermore, several critical issues associated with GANs, such as pattern collapse, instability, and lack of interpretability, require attention in future research.

The objective of this study was to analyze the relationship between quantitative parameters of spectral CT and the Ki67 expression index of tumor cells in hepatocellular carcinoma (HCC).

A total of 19 patients who underwent preoperative spectral CT dual-phase enhancement and who were diagnosed with HCC by postoperative pathology were prospectively selected. Patients with ≥10% Ki67-positive tumor cells formed a high-Ki67 group, and those with <10% Ki67-positive cells formed a low-Ki67 group. The iodine concentrations (ICs) of the lesion and the descending aorta were measured during the arterial and venous phases. Relative iodine concentration (RIC) was calculated thus: RIC=IClesion/ICdescending aorta. CT values of the lesions at 40 and 70 keV were measured during the enhanced arterial and venous phases. The slope of the spectral curve (λ) was calculated thus: λ = (40 keV-70 keV) /(70-30). To compare the differences in quantitative parameters between the high- and low-Ki67 groups, either an independent samples t-test (normal distribution) or a Mann–Whitney U test (non-normal distribution) was used. Receiver operating characteristic curves were used to evaluate the effectiveness of spectral CT parameters in distinguishing between high-Ki67 and low-Ki67 groups. Pearson correlation analysis was used to evaluate the correlation between spectral CT quantitative parameters and Ki67 expression.

IC, RIC and λ values for the high-Ki67 group in arterial and venous phases were higher than those for the low-Ki67 group, P < 0.05. IC, RIC, and λ values in the arterial phase were 0.83, 0.89, and 0.75, respectively; in the venous phase, the values of these three parameters were 0.76, 0.77, and 0.69, respectively. IC, RIC, and λ were positively correlated with Ki67 expression in both arterial and venous phases, with a highest correlation of 0.82 for arterial-phase RIC.

The quantitative parameters of spectral CT in HCC were correlated with Ki67 expression. This finding may make it easier for clinicians to determine whether a tumor is high or low in Ki67 before surgery.

The use of breast MRI for screening has increased over the past decade, mostly in women with a high risk of breast cancer. Abbreviated breast MRI (AB-MR) is introduced to make MRI a more accessible screening modality. AB-MR decreases scanning and reporting time and the overall cost of MRI.

This study aims to evaluate the diagnostic efficacy of abbreviated MRI protocol in detecting breast cancer in screening and diagnostic populations, using histopathology as the reference standard.

This is a single-centre retrospective cross-sectional study of 134 patients with 198 histologically proven breast lesions who underwent full diagnostic protocol contrast-enhanced breast MRI (FDP-MR) at the University Malaya Medical Centre (UMMC) from 1st January 2018 to 31st December 2019. AB-MR was pre-determined and evaluated with regard to the potential to detect and exclude malignancy from 3 readers of varying radiological experiences. The sensitivity of both AB-MR and FDP-MR were compared using the McNemar test, where both protocols' diagnostic performances were assessed via the receiver operating characteristic (ROC) curve. Inter-observer agreement was analysed using Fleiss Kappa.

There were 134 patients with 198 lesions. The average age was 50.9 years old (range 27 – 80). A total of 121 (90%) MRIs were performed for diagnostic purposes. Screening accounted for 9.4% of the cases, 55.6% (n=110) lesions were benign, and 44.4% (n=88) were malignant. The commonest benign and malignant lesions were fibrocystic change (27.3%) and invasive ductal carcinoma (78.4%). The mean sensitivity, specificity, positive predictive value, and negative predictive value for AB-MR were 0.96, 0.57, 0.68 and 0.94, respectively. Both AB-MR and FDP-MR showed excellent diagnostic performance with AUC of 0.88 and 0.96, respectively. The general inter-observer agreement of all three readers for AB-MR was substantial (k=0.69), with fair agreement demonstrated between AB-MR and FDP-MR (k=0.36).

The study shows no evidence that the diagnostic efficacy of AB-MR is inferior to FDP-MR. AB-MR, with high sensitivity, has proven its capability in cancer detection and exclusion, especially for biologically aggressive cancers.

The diagnosis and quantification of early-stage alcoholic liver fibrosis (ALF) are vital and the objective is to establish a noninvasive PET technique to quantify the collagenogenesis of hepatic stellate cells (HSC) in an ALF mouse model.

To establish the ALF animal model, a liquid alcohol diet (8 weeks), and CCl4 were injected intraperitoneally at 5-8 weeks. A liquid scintillation counter was used to measure [³H]proline uptake by rats HSC in vitro experiment. Collagen type 1 production was tested by ELISA in a culture medium. The expression of type 1 collagen and proline transporters in ex vivo experiments was compared between ALF rats and mice. Different doses of unlabeled proline and benztropine were ex vivo quantified [³H]proline in liver tissues. Tracer uptake in different organs including the liver in ALF and control mice in vivo was quantified using [¹⁸F]fluoro-proline microPET/CT.

The optimal dose and time of [³H]proline uptake by HSC was 19-37MBq/L and 30-90min after culture. Higher [³H]proline uptake and type 1 collagen production in HSC were found in ALF and control rats. There was a high correlation between [³H]proline uptake and type 1 collagen in ALF rats. To cut the costs of tracer usage and imaging in vivo, the mouse-to-rat model was compared. Type 1 collagen levels of ALF mice liver tissue in ex vivo were similar to ALF rats, as was proline transporter protein. Unlabeled proline of type 1 collagen and [³H]proline uptake of ALF mice was blocked by benztropine. in vivo [¹⁸F]fluoro-proline PET/CT imaging, SUVmax in the liver, normalized liver/brain and liver/thigh ratio were significantly different between ALF mice and controls and there was a strong positive correlation among these three indexes in ALF mice.

[¹⁸F]fluoro-proline microPET/CT is feasible to quantify collagenogenesis in HSC in early-stage ALF animal models, which may be used as a promising and reliable noninvasive diagnostic technique.

Breast cancer is one of the leading causes of mortality among women. In addition, 1 in 8 women and 1 in 833 men will be diagnosed with breast cancer in 2022. The detection of breast cancer can not only lower treatment costs but also increase survival rates. Due to increased cancer awareness, more women are undergoing breast cancer screening, leading to more cases being diagnosed worldwide, but doctors' ability to analyze these images is limited. As a result, they get overloaded leading to misinterpretations. The advent of computer-aided diagnosis (CAD) minimized man’s involvement and achieved good results. CAD helps medical doctors automatically detect and analyze abnormalities found in the breast. Such abnormalities may be benign or malignant tumors.

The goal of this study is to evaluate the effectiveness of using seven layers to classify breast cancer as either benign or malignant using mammograms.

The open-source MIAS dataset of 322 images was used for our study, of which 207 were normal images and 115 were abnormal images. The proposed CNN model convolves an image into seven layers that extract features from the input images, and these features are used to classify breast cancer as malignant or benign.

The proposed CNN used a limited data set and achieved the best result compared to previous work. The method achieved results with a 0.39% loss, 99.89% accuracy, 99.85% precision, 99.89% recall, 99.87% F1-score, and an area under the curve noted to be 100.0%.

CNN uses a small amount of data to determine abnormalities; the method will assist a medical doctor in determining whether or not a specific patient has cancer.

Ultrasound is extensively used for soft tissue pathology. Scanning bone superficial structures may reveal clear pathologic features to aid diagnosis.

We present the case of a stress fracture in the second metatarsal, with the clinical aspect of a gouty attack. Ultrasound examination showed cortical thickening and disruption, hypoechoic periosteal swelling, hyperemia, soft tissue edema, and displacement of the extensor tendon. The diagnosis was confirmed by X-ray and MRI. The value of different diagnostic tools is discussed, and the importance of gray-scale and color Doppler ultrasound as a first-hand modality is underlined.

Sonography clearly identifies cortical and periosteal abnormalities, differentiates surrounding soft tissue pathologies, and offers dynamic evaluation, and follow-up possibility with low cost, high accessibility, and no risks. Periosteal and cortical irregularities are important diagnostic issues when performing ultrasound examinations for soft tissue pathology.

Liposarcoma (LPS) is a malignant mesenchymal tumor that mostly occurs in the extremities and retroperitoneum and rarely in the scrotum.

In this case report, we introduced a patient who was diagnosed with LPS in the scrotum. In his right scrotum, we found a large soft tissue mass, including fat and calcification.

We reviewed the clinical, pathological and computed tomography (CT) features of patients diagnosed with LPS of the scrotum to help improve the understanding of the disease and the accuracy of diagnosis.

This work aimed to evaluate the level set segmentation algorithm on ocular surface thermograms. In addition, the vascularity functioning between the contralateral portions of two eyes (right and left) was identified using statistical analysis methods.

A total of 25 healthy participants with an average age of 35 years (20 men and 5 women) were selected in April 2022. Thermogram images were captured using a FLIR T series thermal camera. Conventional image processing techniques, such as filtering and edge detection, were used to preprocess thermograms. Next, the level set approach was used with the edge-detected pattern as an input to an automated segmented region of interest (ROI).

Five metrics, namely Dice Coefficient, Tanimoto Index, Jaccard Index, Volume Similarity, and Structural Similarity, were used to assess the performance of the segmentation technique compared to ground truth, which showed 97.5%, 92.5%, 94.5%, 96.5%, and 96.5% correlation, respectively, between the segmented and the ground truth images with average values for both the eyes. Statistical analysis demonstrated that the contralateral portions of the ocular thermograms were significantly different in terms of vascular distribution between the left and right eyes (p < 0.005).

The level set method efficiently segmented the ROI in ocular thermograms with maximum correlation. According to the segmentation’s results, the model showed the dissimilarity between the contralateral parts of the left and right eyes in healthy cases.

This study aims to investigate the efficiency of a radiomics model in identifying high-frequency microsatellite instability (MSI-H) and microsatellite stability (MSS) of colorectal liver metastasis (CRLM) according to machine learning radiomics features of enhanced CT liver images.

A total of 12 patients with MSI-H CRLM and 96 patients with MSS CRLM were randomly divided into the training group and internal validation group according to the ratio of 7: 3 (training: 75 cases, validation: 33 cases). From the enhanced CT (portal phase) image data of patients, 788 radiomics features were extracted, and a random forest model was established with the optimal features selected. The receiver operating characteristics (ROC) curve analysis was performed to assess the model’s diagnostic efficacy.

The training group comprised 8 patients with MSI-H CRLM and 67 patients with MSS CRLM, and the internal validation group included 4 patients with MSI-H CRLM and 29 patients with MSS CRLM. After feature selection, 7 radiomics features good for distinguishing MSI-H CRLM and MSS CRLM were screened out. The ROC curve analysis demonstrated that the random forest model had the AUC (area under the ROC curve) value 0.88, accuracy 0.85, sensitivity 0.85, specificity 0.92, and F1 score 0.88 in the training group. The model had an AUC value of 0.75, accuracy of 0.74, sensitivity of 0.81, specificity of 0.85, and F1_score of 0.78 in the internal validation group in identifying the MSI-H from the MSS CRLM. In order to evaluate the robustness of the overall model, the 788 features obtained were all applied to the 5-fold cross-validation, with the model being built on the random forest and analyzed with the ROC curve analysis. The AUC value of the model was 0.86 (P<0.05), accuracy value 0.91, sensitivity 0.60, and specificity 0.95.

The random forest prediction model built on the radiometric features extracted from enhanced CT images can be used to identify the MSI-H from the MSS CRLM and may provide effective guidance for clinical immunotherapy of CRLM patients with unknown MSI status.

Betel nut chewing is very common in Southeast Asia and other tropical countries. Much clinical evidence suggests that chewing betel nut has pro-inflammatory and carcinogenic effects, but there are few clinical reports of acute toxicity caused by it, especially involving esophageal damage.

We presented a case of a 72-year-old female who was admitted to our hospital for chest pain and hematemesis within several minutes after chewing betel nut. Gastroscopy showed two longitudinal ridge-like mucosal eminences in the esophagus located 20 cm from the incisors down to the gastric cardia, which was similar to varices. At last, a CT scan showed concentric-circle thickening of the esophagus wall, suggesting hematomas. Our treatment included fasting, inhibiting gastric acid and maintaining blood volume. After one week of medical treatment, rechecked gastroscopy showed that esophageal hematomas were gradually absorbed, with the formation of multiple shallow ulcers.

The acute toxicity of chewing betel nut can be easily overlooked. Patients who experience chest pain or hematemesis after chewing betel nut products,especially those who take aspirin at the same time, need to be alert to esophageal hematoma.

Primary anorectal malignant melanoma (ARMM) is a rare tumor. It is often misdiagnosed as hemorrhoids, polyps or colorectal cancer due to the lack of specificity of their clinical symptoms and imaging manifestations.

In this study, we reported an 83-year-old female patient with ARMM. Computed tomography (CT) and Magnetic Resonance Imaging (MRI) showed uneven thickening of the intestinal wall about 7.0 cm from the anal margin, and no typical T1 high signal was seen on MRI. Dual-energy spectral CT showed that the effective atomic number (Zeff) of the tumor and the iodine concentration in the arterial phase (AP) and venous phase (VP) were different from other rectal malignancies reported in the previous literature. Sigmoidoscopy showed a large polypoid mass approximately 7.0 cm from the anal verge. Immunohistochemical staining showed that about 60% of Melan A and HMB-45 were positive, S-100 protein and Ki-67 were positive, and the pathological diagnosis was ARMM.

This was the first dual-energy spectral CT imaging report of ARMM. The Zeff and iodine concentration in the arterial phase and venous phase could help distinguish between ARMM and other rectal malignancies.

Millions of people have been infected with COVID-19, which has spread quickly worldwide since the start of 2020, resulting in numerous fatalities. Identification of infected individuals is essential to control the spread of the virus.

In this study, we propose a hybrid architecture that combines Convolutional Neural Networks (CNNs) with Recurrent Neural Networks (RNNs) and leverages transfer learning to enhance the accuracy of COVID-19 detection from X-ray images.

The proposed work utilizes 4 pre-trained CNN architectures, namely, InceptionnetV3, Densenet121, Inception-ResNet V2, and VGG19, to extract high-level features from the input X-ray images. These features are then fed into the second component, an RNN-based network, which captures the temporal dependencies within the extracted features. To evaluate the performance of the proposed architecture, a comprehensive dataset consisting of X-ray images from COVID-19 positive cases, non-COVID-19 pneumonia cases, and healthy individuals is used. Gradient class activation map (Grad-CAM) analysis has been applied to the obtained results to provide heat-map pictures specific to each class and coloured visualizations of the COVID-19-infected areas in CXR images.

: Experimental results demonstrate that the proposed hybrid CNN-RNN architecture achieves promising results in COVID-19 detection from X-ray images. The model exhibits high accuracy, precision, recall, area under the receiver operating characteristics (ROC) curve (AUC), and F1-score, outperforming other state-of-the-art methods.

The combination of CNNs and RNNs enables the model to effectively capture spatial and temporal information, leading to improved performance in COVID-19 detection. The proposed hybrid architecture with transfer learning from X-ray images provides a robust and efficient solution for COVID-19 detection. The model can potentially assist healthcare professionals in making accurate and timely diagnoses, thereby contributing to the global efforts to combat the COVID-19 pandemic. In the present work, VGG19-RNN architecture outperformed all other networks in terms of accuracy. The most effective training and validation accuracy for the VGG19-RNN architecture is 99% & 97.70%, respectively, and the loss was 0.02 & 0.09 at epoch 100.

Liesegang rings (LR) are concentric acellular lamellar structures, usually found in cystic and inflammatory tissues but can also be seen in neoplastic conditions. They have been mistakenly interpreted as various structures like psammomatous calcification, parasites, and algae. This study has aimed to systematically review and summarize the existence of LRs in both non-neoplastic and neoplastic conditions of the kidney. The systematic search in PUBMED, PUBMED CENTRAL, and EMBASE along with Google Scholar was performed by using Kidney, Liesegang Rings, or Liesegang structure or pseudo parasitic structure in combination with the Boolean operators ‘’and” as searching terms. Data was collected for demographic characteristics and histopathology diagnosis. The search function was limited to human subjects. Two reviewers independently performed the eligibility assessment and data extraction. Eligibility inclusion criteria were all publications in the English literature worldwide related to Liesegang rings in association with kidney’s non-neoplastic and neoplastic conditions, regardless of the years of publication. Also included were those cases whose full articles were unavailable, but the abstract was well-described, fulfilling our inclusive criteria. Eligibility exclusion criteria included LRs found elsewhere in the body organs apart from the kidney and availability of full text in a different language, non-human, and duplicate article/case.

After the exclusion of the articles as per the exclusion criteria, the total articles that fulfilled the inclusive criteria were reviewed. In addition, all the articles were further cross-referenced for additional articles. All published papers retrieved from this search were considered for this review. A total of 22 records (26 cases) were found with a diagnosis of LRs in the kidney to date. Some articles were published as case series. Accordingly, 26 patients were reported to have Liesegang rings associated with kidney neoplastic and non-neoplastic conditions, 12 were male and 14 were female. For one case the gender was not mentioned. LRs presented a higher frequency in individuals between 4^th and 5^th decades of life. No single case was reported in infants and younger children. Regarding predisposing factors for LRs, cystic fluid contents were the most common underlying condition.

In our practice, we encountered an unusual case of a 55-year-old female with a complaint of pain in the left upper quadrant of the abdomen. The ultrasound revealed nephrolithiasis and chronic kidney disease for which a nephrectomy was performed. On the histopathological examination, there was an incidental finding of Liesegang rings and a papillary adenoma along with features of chronic pyelonephritis. Our review will provide insight about LRs in different spectrums of kidney diseases.

This study represents the first available systematic review of the literature demonstrating LRs in the kidney. Although Liesegang rings have no great clinical significance, these, presence in both tissue and cytological specimens should be kept in mind while dealing with different lesions of the kidney as these are good mimickers of many organic and inorganic substances, parasites, and malignancies.

In some hospitals in remote areas, due to the lack of MRI scanners with high magnetic field intensity, only low-resolution MRI images can be obtained, hindering doctors from making correct diagnoses. In our study, high-resolution images can be obtained through low-resolution MRI images. Moreover, as our algorithm is a lightweight algorithm with a small number of parameters, it can be carried out in remote areas under the condition of the lack of computing resources. Moreover, our algorithm is of great clinical significance in providing references for doctors' diagnoses and treatment in remote areas.

We compared different super-resolution algorithms to obtain high-resolution MRI images, including SRGAN, SPSR, and LESRCNN. A global skip connection was applied to the original network of LESRCNN to use global semantic information to get better performance.

Experiments reported that our network improved SSMI by 0.8% and also achieved an obvious increase in PSNR, PI, and LPIPS compared to LESRCNN in our dataset. Similar to LESRCNN, our network has a very short running time, the small number of parameters, low time complexity, and low space complexity while ensuring high performance compared to SRGAN and SPSR. Five MRI doctors were invited for a subjective evaluation of our algorithm. All agreed on significant improvements and that our algorithm could be used clinically in remote areas and has great value.

The experimental results demonstrated the performance of our algorithm in super-resolution MRI image reconstruction. It allows us to obtain high-resolution images in the absence of high-field intensity MRI scanners, which has great clinical significance. The short running time, a small number of parameters, low time complexity, and low space complexity ensure that our network can be used in grassroots hospitals in remote areas that lack computing resources. We can reconstruct high-resolution MRI images in a short time, thus saving time for patients. Our algorithm is biased towards clinical and practical applications, and doctors have affirmed the clinical value of our algorithm.

The lack of knowledge of the relation of the maxillary sinus with the apexes of maxillary posterior teeth can lead to important complications during common dental procedures. This can be avoided using different imaging techniques, such as orthopantomography (OPG) and cone beam computed tomography (CBCT). The present study aims to compare the performance of OPG with CBCT in measuring the vertical distance of the apexes of posterior-superior teeth to the maxillary sinus.

This study corresponded to a cross-sectional study. OPGs and CBCT scans were obtained from the same individuals, and the qualitative and quantitative vertical distance of the apexes in relation to the maxillary sinus was categorized and measured in mm.

A total of 28 pairs of OPGs and CBCT scans from the same patients were obtained. About 381 roots were analysed, which included 89 upper first premolars, 51 upper second premolars, 115 upper first molars, and 126 upper second molars. Projection/protrusion was observed with more frequency in molars, specially 1º molars in both OPG (n= 75, 65.2%) and CBCT (n= 31, 27%); however, 106 more cases (27.9%) were classified as projected in the OPG compared to CBCT (p < 0.05). When comparing the performance of the OPG and CBTC for analysing all roots qualitatively, there was a 57.8% agreement between both techniques. This difference was statistically significant (p <0.0001). Statistically significant differences were also observed when comparing the millimetric differences.

This study showed that OPG is not an accurate technique to observe the relationship between the maxillary sinus and the apexes of the upper posterior teeth. In those cases where precision is required when performing dental procedures in this area, CBCT should be used. When not available, the clinicians should be aware of the limitations of the OPG and add other complementary techniques.

Gastric teratoma (GT) occurs as a rule in infancy and is an extremely unusual gastric tumor in adult patients.

In this paper, we present the clinical and imaging findings of a 56-year-old female patient with a GT. The patient's main symptoms were increasing abdominal discomfort and pain. After the physical examination, she underwent ultrasound (US) and computed tomography (CT), which showed a large mass at the posterior wall of the stomach, and a teratoma was initially considered. After surgery, pathology confirmed the diagnosis of GT. The patient recovered after surgery and was discharged in good health. To the best of our knowledge, this study is the first reported case of gastric teratoma in an adult woman in the literature.

Gastric teratoma of the adult period is a rare benign neoplasm that may have several complications; therefore, imaging is crucial for diagnosis and accurate treatment management. The aim of this study is to emphasize the value of US and CT in the diagnosis and treatment monitoring of mature gastric teratomas.

Brain tumors are predicted from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scan images. In recent years, image processing-based automated tools are developed to predict tumor areas with less human interference. However, such automated tools are suffering from computational complexity and reduced accuracy in certain critical images. In the proposed work, an Ideal Shallow Neural Network (ISNN) is utilized to improve the prediction accuracy, and the computational complexity is reduced by implementing an Artificial Jellyfish Optimization (AJO) algorithm for minimizing the feature dimensionality.

The proposed method utilizes MRI images for the verification process as they are more informative than the CT scan image. The BRATS and the Kaggle datasets are used in this work and a Gabor filtering technique is used for noise reduction and a histogram equalization is used for enhancing the tumor boundary regions. The classification results observed from the AJO-ISNN are further forwarded towards the segmentation process and which uses the Centroid Weighted Segmentation (WCS) along with a Grasshopper Optimization Algorithm (GOA) for improving the segmentation over the boundary regions of the brain tumor.

The experimental result indicates a classification accuracy of 95.14% on the proposed AJO-ISNN model and AJO-ISNN is comparatively better than the Convolutional Neural Network (CNN) model accuracy of 85.41% and VGG 19 model accuracy of 93.75% while implemented with the AJO optimization model. Similarly, the Dice Similarity Coefficient of the proposed CWS-GOA also reaches 93.15% when performed with both BRATS and Kaggle datasets.

Apart from the accuracy attainments the proposed work classifies and segments the tumor region in around 65 seconds on average of 200 image verifications and that is comparatively better than the previous multi-cascaded CNN and the InceptionV3 models.

Hepatocellular carcinoma (HCC) is the leading type of liver cancer in adults, often resulting in fatal outcomes for those with cirrhosis. Dysplastic nodule (DN) is a liver nodule that is substantial in size, ranging from 1-2 cm. However, accurately distinguishing between DN and HCC on imaging has posed a challenge.

The aim of this study is to assess the usefulness of Gd-EOB-DTPA-enhanced MRI T1 mapping in distinguishing between DN and HCC.

This study analyzed 66 patients with confirmed HCC or DN who underwent Gd-EOB-DTPA-enhanced MRI T1 mapping before surgery or puncture at the Army Medical Center in China. The T1 values of each lesion were measured before and after Gd-EOB-DTPA administration, and various calculations were made, including absolute and percentage reduction in T1 value and coefficient of variation. The t-test was used to compare these values between the two groups, and the efficacy of T1 mapping values for differential diagnosis of HCC and DN was evaluated using the receiver operating characteristic curve (ROC).

The study found that T1pre, T1hp, ΔT1, ΔT1%, and CV in the HCC group were significantly higher than in the DN group (p < 0.01). The accuracy of T1hp, ΔT1, and CVT1-hp in identifying HCC from DN was high, with AUCs of 0.955, 0.910, and 0.932, respectively. ΔT1% also had some accuracy, with an AUC of 0.818.

Our results provide preliminary evidence that Gd-EOB-DTPA-enhanced MRI T1 mapping, can be a valuable tool in diagnosing and differentiating between HCC and DN.

Spectral-Domain Optical Coherence Tomography (SD-OCT) provides non-invasive, high-speed, high-resolution, three-dimensional cross-section imaging of the macula.

This study aimed to investigate the diagnostic value of the multimodal imaging technique of three-dimension (3D) optical coherence tomography (OCT) (3D-OCT) for the diagnosis and characterization of acute central serous chorioretinopathy (CSC).

In this prospective clinical study 3D-OCT examinations of 82 cases with acute CSC were performed on the macular area, and the image characteristics were analyzed. Our study included a total of 87 eyes from 82 cases of CSC patients, 67 males and 15 females (mean age ± standard deviation (SD): 42.89 ±7.80 years old; age range: 27 to 56 years old. The 3D-OCT images were evaluated for the presence of subretinal fluid, subretinal space, fluctuation of the internal limiting membrane (ILM), folds of retinal pigment epithelial (RPE), retinal pigment epithelium detachment (PED), and flat irregular PED. The foveal thickness was measured using the manual caliper of OCT software.

The OCT B-scan images showed 87 (100%) eyes had exudative retinal detachment (ERD), 38 (44%) had flat irregular PED, 36 (41%) had PED, 8 (9%) had subretinal turbidity structure, 2 (2%) had subretinal dot-like precipitates, 1 (1%) had focal choroidal excavation (FCE), and 1 (1%) eye had fluctuation of internal limiting membrane (FI). In the ILM-RPE thickness map, all eyes had a round or round like regular uniform domes. Fifty-seven (66%) domes were limited in the examination area and 30 (44%) domes were beyond the scope of this examination and only a partial section of the dome could be observed. In the en-face image, all eyes had a round or round-like black figure that corresponded with domes in the ILM-RPE thickness map. In RPE surface, 76 (87%) eyes had a shallow plate depression, 71(82%) had small focal uplift, and 1 (1%) eye had a focal concave feature.

In the OCT ILM-RPE thickness, en-face image, and RPE surface maps, acute CSC exhibited specific imaging characteristics that can be helpful for reliable diagnosis and differential diagnosis of CSC.

The characteristic imaging findings of breast cancer in young women are not yet fully understood. It causes a delay in diagnosis by mixing with benign findings.

To evaluate the relationship between the imaging and histopathological features of breast cancer in women aged under 40 years.

In our center, 537 suspicious lesions were detected in a total of 15,223 adult female patients under 40 years who were evaluated by breast ultrasonography (US). As a result of the mammographic, histopathological, and immunohistochemical analysis, 101 lesions meeting the study criteria were included in the sample.

The luminal subtypes of breast cancer mostly visualized as irregularly shaped spiculated lesions with calcification and architectural distortion mammography and presented as masses that were sometimes accompanied by increased echogenicity in the surrounding tissue on US. The human epidermal growth factor receptor 2 (HER2) enriched subtypes mostly had microlobulated or indistinct margins with heterogeneous echoes accompanied by high calcification on mammography. The triple-negative (TN) subtypes generally appeared as microlobulated lesions with angular or indistinct margins, hypo echogenicity, posterior enhancement or shadowing, and vascularization.

Some radiological features of breast cancer in young women were found to be associated with molecular subtypes similar to other age groups in the literature. However, unlike other age groups, the incidences of the HER2-enriched subtype presenting with only calcification, TN subtypes presenting with circumscribed masses, and calcification were found to be low among the young women in our study.

A large jejunal diverticulum has been reported as a possible cause of volvulus and acute mesenteric ischemia (AMI) in adults. A large diverticulum of the small bowel complicated with volvulus has been reported before in literature. However, imaging findings of a large diverticulum of the small bowel complicated with both volvulus and AMI on MDCT are rarely described and reported. In this study, we reported a case with a large diverticulum, volvulus, and AMI concurrently; these three imaging findings were reviewed and described on MDCT, and the relevant literature was briefly introduced.

We reported the case of a 69-year-old man who presented to our hospital with acute abdominal pain and vomiting. An emergent abdominal enhanced MDCT imaging was performed and demonstrated the volvulus secondary to a large diverticulum of the jejunum complicated with AMI. Here, a case was presented that highlighted unique imaging findings on MDCT, as well as a literature review.

A review of the literature revealed that a single jejunal diverticulum causing both volvulus and AMI is rare in adults. To our knowledge, a systemic description of their signs on MDCT in a case has not been reported yet.

Agenesis of the corpus callosum (ACC) is a rare hereditary nervous system defect present at birth. ACC is an uncommon condition that is unrepresentative in the general population because some cases do not present with any identifiable symptoms in the early stage.

We present a case of ACC in a two-month-old male patient who was diagnosed after birth. Although the initial brain ultrasound (US) showed dilation of the lateral ventricles and the absence of the corpus callosum, these findings were not fully confirmed. Therefore, magnetic resonance imaging (MRI) of the brain was conducted to confirm the complex diagnosis, and the examination revealed complete ACC. Diagnosing ACC in a neonate demonstrates the complexity of diagnosis through the clinical presentation, especially at an early age.

The clinical utility of neonatal US and MRI highlights the importance of an early diagnosis of ACC. MRI is more effective than the US in detecting this condition, and these imaging modalities provide the patient with an early diagnosis, which helps in treatment management.

We aimed to examine all-cause mortality risk in relation to the extent of non-obstructive coronary artery disease (CAD) by coronary computed tomography angiography (CTA) in Chinese middle-aged and older patients in a multicenter study with nine-year follow-up.

This was a retrospective, observational, multicentre study. The study population consisted of 3,240 consecutive middle-aged and older patients (age ≥ 40 years) with suspected CAD who underwent coronary CTA between June 2011 and December 2013 at three hospitals in Wuhan, China. Patients were grouped according to CAD extent for the final analysis: no CAD, 1-vessel non-obstructive CAD, 2-vessels non-obstructive CAD, and 3-vessels non-obstructive CAD. The primary endpoint was all-cause mortality. Kaplan-Meier method and Cox proportional hazards regression models were used for analysis.

A total of 2,522 patients were included in the present analysis. Of these, 188 (7.5%) deaths occurred during the median 9.0 years (interquartile range 8.6–9.4) of study follow-up. The annualized all-cause mortality rate was 0.54 (95% CI: 0.44–0.68), 0.91 (95% CI: 0.68–1.21), 1.44 (95% CI: 1.01–1.93), and 2.00 (95% CI: 1.46–2.69) for the no CAD, 1-vessel non-obstructive CAD, 2-vessels non-obstructive CAD, and 3-vessels non-obstructive CAD group, respectively. Kaplan–Meier survival curves showed a significant increase in the cumulative events associated with the extent of non-obstructive CAD (P < 0.001). In multivariate Cox regression, after adjustment for age and sex, the presence of 3-vessels non-obstructive CAD was a significant predictor of all-cause mortality (HR 1.60, 95% CI: 1.04–2.45, P = 0.032).

In this cohort of Chinese middle-aged and older patients undergoing coronary CTA, the presence and extent of non-obstructive CAD, compared to no CAD, were associated with a significantly greater nine-year risk of all-cause mortality. The present findings suggest the clinical importance of the stage of non-obstructive CAD and warrant investigation of the optimal risk stratification to improve outcomes among these patients.

The aims were to assess different branching patterns of segmental bronchi in the right superior lobe (RSL), as well as to investigate the anatomical diversity and sex-related variations of these branches in a large sample of the research population.

10,000 participants (5428 males, and 4,572 females, mean age 50+/-13.5 years [SD] years; age range: 3-91 years) who underwent multi-slice CT (MSCT) scans from September 2019 to December 2021 were retrospectively included. The data were applied to generate three-dimensional (3D) and virtual bronchoscopy (VB) simulations of a bronchial tree using the syngo.via post-processing workstation. Following that, the reconstructed images were interpreted to identify and categorize various bronchial patterns in the RSL. Cross-tabulation analysis and the Pearson chi-square test (χ2) were used to calculate the component ratios of bronchial branch types and determine their relevance between male and female groups.

Our results revealed mainly six types for the RSL bronchial tree, i.e., (B1, B2, B3, 60.70%); (B1+2, B3, 18.72%); (B2+3, B1, 6.68%); (B1+3, B2, 7.57%); (B1, B2, B3, B*, 3.19%); (B1a+B3, B1b+B2, 3.14%). There were significant sex-related differences in the proportion of bronchial branches in the RSL (P< 0.05).

The current study has validated the presence of segmental bronchial variations in the RSL. These findings may have significant implications for diagnosing symptomatic patients and performing particular procedures, including bronchoscopy, endotracheal intubation, and lung resection.

This study aimed to investigate the diagnosis of the external jugular venous aneurysm on color Doppler ultrasound and its relationship with pathological characteristics.

A retrospective analysis of 17 patients with external jugular venous aneurysm admitted to the Provincial Hospital Affiliated with Shandong First Medical University from May, 2010, to June, 2020, was performed. The color Doppler ultrasound characteristics of 17 patients with external jugular vein aneurysms were analyzed and summarized, which were then compared with postoperative pathological outcomes.

All 17 patients with external jugular venous aneurysms were presented with cystic structures adjacent to and communicated with the external jugular vein. Color Doppler flow imaging showed a bidirectional venous flow signal in the communication between the cystic structure and the external jugular vein. Among the 17 patients, ultrasound diagnosis showed true venous aneurysm due to degenerative changes in the venous wall in 8 cases, venous pseudoaneurysm in 4 cases, and external jugular venous aneurysm in 5 cases, and postoperative pathology indicated degenerative changes in the venous wall in all 17 patients.

Bidirectional blood flow at the communication between the cystic lesion and the external jugular vein on color Doppler ultrasound should not be the criterion for the diagnosis of external jugular venous pseudoaneurysm, which requires pathological support.