Current Medical Imaging - Current Issue

Accurate determination of tumor boundaries is crucial for staging and treating central lung cancer (CLC).

This retrospective study aimed to evaluate the feasibility of contrast-free CT radiomics in discriminating CLC tumors from atelectasis.

A total of 58 patients with CLC and associated lung atelectasis, corresponding to 58 tumors and 58 atelectasis regions, were included. Radiomics features were extracted from tumor and atelectasis areas using contrast-free CT images. The least absolute shrinkage and selection operator (LASSO) identified the most differential radiomics features. A logistic regression model (LR) was established and evaluated using 5-fold cross-validation. Discrimination performance was assessed using the area under the ROC curve (AUC) and decision curve analysis (DCA). Additionally, the potential of visualizing and distinguishing tumors and atelectasis based on contrast-free CT was explored by comparing pixel-level radiomics features with contrast CT.

A total of 1561 radiomics features were extracted, with 356 showing significant statistical differences between tumor and atelectasis. LASSO identified the 10 most differential radiomics features. The LR model trained with these features achieved an AUC of 0.94 (95% CI: 0.89-0.99), sensitivity of 0.88, and specificity of 0.89 in the training group, and an AUC of 0.81 (95% CI: 0.67–0.95), sensitivity of 0.78, and specificity of 0.65 in the validation group. DCA confirmed the clinical utility, and the radiomics feature square_firstorder_10Percentile showed good performance in distinguishing tumors from atelectasis, with consistency to contrast CT.

Contrast-free CT radiomics can effectively discriminate CLC tumors from atelectasis.

This study aimed to characterize the magnetic resonance imaging (MRI) findings of juvenile suprasellar pilocytic astrocytoma (PA) in a sample of 11 children and help neuroradiologists preoperatively differentiate PAs from other suprasellar tumors.

Eleven consecutive children with pathologically confirmed suprasellar PAs in our hospital from May 2015 to November 2021 were enrolled in this study. The clinical data and preoperative MR images were retrospectively reviewed. MRI included T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), fluid-attenuated inversion recovery (FLAIR), and postcontrast T1WI. Six patients underwent diffusion-weighted imaging (DWI). The location, signal features, enhancement pattern, and apparent diffusion coefficient (ADC) of the lesions on MRI were evaluated. The clinical status of the patients 3 years after surgery was noted.

The 11 suprasellar PAs were mainly located around the optic chiasma and hypothalamus and invaded adjacent structures. The lesions showed hyperintensity or slight hyperintensity on T2WI and hypointensity on T1WI. Among the 11 patients, 5 had solid tumors with homogeneous enhancement, one had a solid tumor with heterogeneous enhancement, and five had cystic and solid tumors with heterogeneous enhancement. Cerebrospinal fluid (CSF) dissemination foci were observed in 4 patients. The solid components of the lesions were hypointense or isointense on DWI, with high ADC values at a mean of 1.77±0.36 ×10^-3 mm²/s. Gross total resection was achieved in only one patient (9.1%), and 10 (90.9%) were subtotally resected. Five patients died during the follow-up period, and the 3-year survival rate was 54.5%.

Juvenile suprasellar PAs are characterized by a solid and intermixed cystic and solid appearance, hyperintensity on T2W images, obvious enhancement of the solid component, and relatively high ADC values.

Various methods have been employed to evaluate secondary limb lymphedema, each with its own set of limitations.

To delve into a novel approach to lymphatic grading, specifically utilizing enhanced ultrasound for assessing lymphatic function, to compensate for the shortcomings of other methods to some extent.

The clinical and ultrasound data of 51 patients with secondary limb lymphedema from June 2022 to September 2023 were retrospectively analyzed. The characteristic ultrasound manifestations of all visualized lymphatic vessels were studied. A contrast-enhanced ultrasound grading of lymphatic vessels (Ceus-Clv) was formulated and applied to grade the 51 patients. The study also correlated Ceus-Clv with Campisi clinical stage, postoperative duration, and duration of edema.

Out of 51 patients, there were 19 cases of Ceus-Clv I, 10 cases of Ceus-Clv II, 19 cases of Ceus-Clv III, and 3 cases of Ceus-Clv IV. The correlation coefficient (rs) between Ceus-Clv and Campisi clinical stages was 0.958 (P < 0.001). Similarly, the correlation coefficient between Ceus-Clv and postoperative duration was 0.824 (P < 0.001), and between Ceus-Clv and duration of edema was 0.763 (P < 0.001).

Ceus-Clv grading is a safe, convenient, and effective method for assessing lymphatic vessel function in secondary limb edema. This method can accurately reflect the patient's lymphatic vessel function and the severity of edema, providing valuable guidance for the treatment of secondary limb edema.

Determination of LVSI is the recommended criterion for performing lymphatic drainage and is important for the preoperative clinical decision-making process; however, Intraoperative Frozen Section (IFS) has limitations for the analysis of LVSI, and there is an urgent need for other indirect methods to predict the presence of LVSI.

This study aimed to investigate the value of Magnetic Resonance Imaging (MRI) features in predicting Lymphovascular Space Invasion (LVSI) in endometrial cancer (EC).

The objective of this study was to analyze MRI features that may be associated with LVSI and to explore their association.

In this study, 179 patients who received treatment for EC confirmed by surgical pathology at two medical institutions from January 2017 to May 2024 were reviewed and grouped according to the presence or absence of vascular cancer embolism in the pathology. The MRI imaging features of the two groups were compared, including the maximum transverse diameter in the sagittal position, myometrial invasion, disruption of the uterine Junctional Zone (JZ), serosal surface, uterine appendages, cervical stromal invasion, lymph node enlargement, and its T2 value, and Diffusion-Weighted Imaging (DWI). The risk factors of the LVSI-positive group were determined by performing logistic regression analysis to analyze the correlation between Apparent Diffusion Coefficient (ADC) values and LVSI in EC.

There were 34 cases in the LVSI-positive group and 145 cases in the negative group. The maximum transverse diameter in sagittal position, myometrial invasion, interruption of the uterine JZ, serous surface, uterine appendages, cervical stromal invasion, lymph node enlargement, and their DWI and ADC values were statistically significant between the two groups (P < 0.05). In multivariate logistic regression analysis, lymph node enlargement (P = 0.001) and ADC value (P = 0.041) were identified as independent risk factors for positive LVSI.

Lymph node enlargement and reduced ADC values (<0.767*10-3mm²/s) in MR imaging are of high value in predicting the occurrence of LVSI in patients with EC and can be used as an important reference for preoperative clinical diagnostic and therapeutic decisions for patients.

Cryptococcosis is a severe but rare opportunistic fungal infection predominantly affecting immunocompromised individuals, such as post-transplant patients. The diagnosis is frequently delayed due to non-specific symptoms and lower incidence than other fungal infections.

A case of a 50-year-old male renal transplant recipient who developed disseminated cryptococcosis complicated by multi-organ failure is presented. Despite adherence to international treatment guidelines, the patient's condition rapidly deteriorated due to the extensive immunosuppression required for transplant rejection management. The patient developed pneumonia and was diagnosed with disseminated cryptococcosis on the 10th day of hospitalization, with Cryptococcus gattii identified in the pulmonary system and pleura. The patient underwent multiple interventions, including bronchoscopy, lobectomy, and pneumonectomy. Despite aggressive treatment, the infection progressed, leading to severe complications, such as neurological decline, gastrointestinal bleeding, and ultimately, multi-organ failure. The patient passed away after 53 days of hospitalization.

This report highlights the importance of early diagnosis and multidisciplinary management in post-transplant patients with suspected opportunistic infections. The high mortality associated with disseminated cryptococcosis, particularly in severely immunosuppressed patients, underscores the need for vigilance and prompt intervention to improve patient outcomes.

To examine the integration of artificial intelligence (AI) into Picture Archiving and Communication Systems (PACS) and assess its impact on medical imaging, diagnostic workflows, and patient outcomes. This review explores the technological evolution, key advancements, and challenges associated with AI-enhanced PACS in healthcare settings.

A comprehensive literature search was conducted in PubMed, Scopus, and Web of Science databases, covering articles from January 2000 to October 2024. Search terms included “artificial intelligence,” “machine learning,” “deep learning,” and “PACS,” combined with keywords related to diagnostic accuracy and workflow optimization. Articles were selected based on predefined inclusion and exclusion criteria, focusing on peer-reviewed studies that discussed AI applications in PACS, innovations in medical imaging, and workflow improvements. A total of 183 studies met the inclusion criteria, comprising original research, systematic reviews, and meta-analyses.

AI integration in PACS has significantly enhanced diagnostic accuracy, achieving improvements of up to 93.2% in some imaging modalities, such as early tumor detection and anomaly identification. Workflow efficiency has been transformed, with diagnostic times reduced by up to 90% for critical conditions like intracranial hemorrhages. Convolutional neural networks (CNNs) have demonstrated exceptional performance in image segmentation, achieving up to 94% accuracy, and in motion artifact correction, further enhancing diagnostic precision. Natural language processing (NLP) tools have expedited radiology workflows, reducing reporting times by 30–50% and improving consistency in report generation. Cloud-based solutions have also improved accessibility, enabling real-time collaboration and remote diagnostics. However, challenges in data privacy, regulatory compliance, and interoperability persist, emphasizing the need for standardized frameworks and robust security protocols.

The integration of AI into PACS represents a pivotal transformation in medical imaging, offering improved diagnostic workflows and potential for personalized patient care. Addressing existing challenges and enhancing interoperability will be essential for maximizing the benefits of AI-powered PACS in healthcare.

This study aimed to investigate the computed tomography (CT) and magnetic resonance imaging (MRI) characteristics of bone remodeling in chronic maxillary sinusitis and assess their clinical significance.

This retrospective study included patients with unilateral chronic maxillary sinusitis and bone remodeling who were admitted to our hospital from January, 2020 to December, 2022. A total of 31 patients were ultimately included. Imaging and clinical data analyses were conducted on the enrolled patients, including multislice spiral computed tomography (MSCT) examination and measurements, as well as plain and enhanced MRI scans. A comparative analysis was performed between the affected and healthy samples. The CT images were evaluated using the “LIAT” systematic assessment method, with a focus on lesion location, extrasinus wall invasion, density, and thickness. Furthermore, a comparative analysis between CT and MRI was carried out for various types of bone remodeling, emphasizing the imaging features of the surrounding soft tissues, including the mucosa and periosteum.

Among the 31 patients with chronic sinusitis, CT revealed 26 cases of cortical-like bone remodeling and 5 cases of cancellous-like bone remodeling. For cortical-like bone remodeling, the thickest part of the posterolateral wall of the maxillary sinus was used to differentiate between mild and moderate-to-severe cases using a 3 mm threshold. Specifically, 15 mild cases exhibited sinus mucosa thickening and a normal blood supply outside the sinus wall on MRI, whereas 11 moderate-to-severe cases exhibited sinus mucosa separation, submucosal edema, and significant vessel proliferation outside the sinus wall on MRI. In cases of cancellous-like bone remodeling, MRI revealed uneven sinus mucosa thickening and mild vessel proliferation outside the sinus wall. Specifically, 21 patients exhibited cross-suture signs, 13 patients exhibited vascular tunnel signs, and 6 patients exhibited nerve canal perineural infiltration.

Chronic maxillary sinusitis bone remodeling appeared in two forms on CT images: cortical-like bone remodeling and cancellous-like bone remodeling. MRI can detect morphological and signal alterations in the soft tissues around the remodeling site. Analyzing the imaging features of bone remodeling in chronic maxillary sinusitis patients can increase the understanding of disease progression and diagnostic accuracy.

This preliminary investigation aimed to assess the value of two elastography techniques, sound touch elastography (STE) and sound touch quantification (STQ), in measuring liver stiffness in children with non-fatty versus fatty livers.

This study used a case-control design. The STE and STQ were used to measure and compare liver stiffness in 121 children with fatty livers and 251 children with non-fatty livers, respectively.

In this study, we found that, compared to children with non-fatty liver disease, children with fatty liver disease had lower Young's modulus values in STE and STQ in the left lobe of the liver, and the difference was statistically significant (P < 0.05). However, after multifactorial analysis, no association was found between liver Young's modulus values measured by STE and STQ and the presence of fatty liver in children.

In the present study, significantly higher Young's modulus values were observed in the left lobe compared to the right lobe of the liver in children with non-fatty liver (P < 0.05). In contrast, no significant difference was found between the left and right lobes in children with fatty liver (P > 0.05). The optimal diagnostic threshold for detecting steatohepatitis in the left lobe was 5.890 kPa using STE and 8.050 kPa using STQ.

STE and STQ, as the latest ultrasound diagnostic techniques based on shear wave elastography, can quantitatively assess fatty liver in children. In this study, some liver elasticity measurements in the fatty liver group differed from those in the non-fatty liver group.

Phlebosclerotic colitis is a rare type of chronic ischemic colitis, with most documented cases occurring in Asians. Plain-film and computed tomography findings of pericolonic vascular calcifications are diagnostic. However, Magnetic Resonance Enterography (MRE) findings of phlebosclerotic colitis have not yet been reported, and its diagnosis might be overlooked without awareness of this disease.

A 70-year-old female patient without prior systemic disease presented with a 3-month history of nausea, vomiting, abdominal pain, and diarrhea. Personal history was unremarkable except for long-term use of herbal medicine. She was initially investigated at a regional hospital with a colonoscopy and biopsy. Due to the presence of stenosis at the transverse colon and biopsy results suggestive of Inflammatory Bowel Disease (IBD), she was referred to our hospital for further investigation and treatment. MRE was performed as part of the IBD workup, which showed a thickened ascending and transverse colonic wall that was fibrotic, non-edematous, and with triangular projections on the mesenteric aspect. Owing to findings that were inconsistent with IBD, subsequent abdominal plain-film radiography confirmed characteristic linear dendritic serpiginous radiopaque opacities alongside the ascending and transverse colon. Re-biopsy of the affected colon confirmed the diagnosis of phlebosclerotic colitis. The patient’s symptoms improved after conservative treatment.

MRE of phlebosclerotic colitis appears as symmetrical non-edematous bowel wall thickening with triangular signal voids indicative of venous calcifications.

Eagle’s Syndrome is a unilateral or bilateral elongation of the styloid process or calcified stylohyoid ligament, along with other symptoms, such as dysphagia, facial pain, globus sensation, and headache. Stylocarotid artery syndrome is a specific type of Eagle’s syndrome that causes various clinical symptoms due to pressure on adjacent anatomical structures.

This study presents a case of a 57-year-old female patient with a complaint of facial pain, head and neck discomfort, globus sensation, difficulty swallowing, and dizziness during head rotation. The patient was diagnosed with a bilateral elongated styloid process through panoramic radiography and cone beam computed tomography. Due to suspicion of stylocarotid artery syndrome, further evaluation was conducted using ultrasound imaging.

Bilateral elongated styloid processes can contribute to Stylocarotid Artery Syndrome (SAS). Ultrasound imaging, specifically B-mode and pulsed wave Doppler, proved to be valuable in detecting real-time vascular flow dynamics in extracranial vessels, highlighting its auxiliary role in the assessment of stylocarotid artery syndrome.

This research aims to develop and evaluate a novel health classification and severity detection system based on Vision Transformers (ViTs) for fetal ultrasound imagery. This contributes to improved precision in fetal health status detection and abnormalities with more accurate results than other traditional models.

Amidst the other imperatives of resource-deficient developing nations, mitigating neonatal mortality rates is a challenge that demands precision-based solutions in the era of artificial intelligence. Though the advent of machine learning models has added an optimal dimension to deal with emerging complexity in fetal ultrasound imagery, there is a call to address the huge gap in the demanded precision for prediction than the existing interpretation.

This research strives to formulate and access a novel health classification and severity detection system based on the implementation of the Vision Transformers frameworks. This pioneering investigation represents an unparalleled exploration into the efficacy of ViTs for discerning intricate patterns within fetal ultrasonographic imagery, facilitating precise categorization of fetal well-being and prognosticating the magnitude of potential anomalies.

A private and confidential dataset of 500 fetal ultrasound images has been collected from diverse hospitals. Each image has been annotated by radiologists according to two main labels: the health status of the fetus, which includes healthy, mild, moderate, or severe, and the severity of abnormalities as a continuous measure. At different levels, the dataset underwent pre-processing via distinct techniques. Then, the composite loss function Cross-Entropy has been deployed to train the optimized VIT model using the Adam algorithm.

The classification accuracy of the proposed model is 90% for detecting the severity with an F1-score of 0.87 and MAE of 0.30. The research ascertained that the model ViT evinced a superlative efficacy for the capturing of fine-grained spatial relations in ultrasound images to produce revolutionary predictions.

These results emphasize that ViTs have the potential to revolutionize fetal health monitoring and will contribute significantly to reducing neonatal mortality by supplying clinicians with accurate and reliable predictions for early interventions. This work stands as a yardstick for further diagnostic applications using AI in fetal health care.

Multiple spectral images can be extrapolated from Spectral Detector CT (SDCT), ED, and OED images. ED and OED images are highly sensitive to moisture-rich tissues. Moreover, they have the potential to detect pulmonary artery thrombi in non-enhanced chest CT images.

The objective of this study was to assess the sensitivity, specificity, and accuracy of ED and OED images obtained using SDCT for the detection of pulmonary embolism on non-enhanced images.

This study aimed to evaluate the utility of unenhanced spectral imaging, Electron Density (ED), and Overlay Electron Density (OED) images for assessing pulmonary embolisms in patients with suspected or confirmed Acute Pulmonary Embolism (APE).

Seventy-nine patients who underwent unenhanced and Computed Tomography Pulmonary Angiography (CTPA) using dual-layer spectral detector CT to evaluate APE between November, 2021 and April, 2022 were enrolled in this retrospective study. Based on unenhanced spectral and CTPA images, two radiologists identified areas of high density in the main, lobar, and segmental pulmonary arteries on ED and OED images and detected Pulmonary Embolism (PE) on enhanced images using a consultative approach. CTPA results were considered the gold standard. The diagnostic performance of ED and OED in detecting PE was analyzed.

PE was detected in 40 patients (40/79), and 17, 69, and 20 PEs were detected in the main, lobar, and segmental arteries, respectively. The PE detection sensitivity on ED images was 69.7–94.7%, and the specificity was 58.5–98.2% for the individual, main, lobe, and segmental pulmonary arteries. The sensitivity and specificity for OED images were 94.1–95.2% and 80.0–98.1%, respectively. The positive predictive value (PPV) and negative predictive value (NPV) were 53.6–87.7% and 69.7–95.9% for ED images and 48.5–88.9% and 94.1–98.9% for OED images, respectively. The accuracy was 76.0–98.9% and 87.3–96.2% when using ED and OED images, respectively. The research identified that whether it was main, lobar, or segmental pulmonary arteries with blood clots, EDW values ranged from 108.1–108.8%EDW, which were 3.9–4.2%EDW higher than those of arteries without emboli. Pulmonary arteries with emboli standardised ED values were 103.6-104.3%EDW.

ED and OED images using spectral CT without contrast media demonstrated high diagnostic performance and could improve the visualization of PE.

With the rapid development of computer technology, the application of digital technology to the display and processing of medical images has become a common concern. In recent years, oral digital imaging technology has received more and more attention.

This paper mainly aims at the ODIS-1 oral digital imaging system to analyze and study the image quality and image aims at the ODIS-1 oral digital imaging system to analyze and study the image quality and processing technology, of which X-ray imaging is indispensable.

In this paper, the ODIS-1 digital scanning technology is used to detect different types of dental tissues, and its application in diagnosing oral diseases is evaluated. This paper takes 320 inpatients as the research object and uses Kodak dental film to compare the image quality of different positions.

It is found that there is no significant difference in image quality between the maxillary anterior teeth and mandibular anterior teeth and the maxillary posterior teeth and mandibular posterior teeth (P>0.05); the image quality of maxillary anterior teeth, mandibular anterior teeth, and maxillary posterior teeth and mandibular teeth are significantly different (P<0.05); among the various positions of the ODIS-1 oral digital imaging system, the image quality of the anterior teeth area is the best, while the image quality of the maxillary posterior teeth area is the worst.

However, the system has a variety of image post-processing functions, which can adjust the brightness and contrast of the image arbitrarily, select the area of interest in the image according to the detection requirements, and perform local amplification, edge enhancement, and other technologies to make the image achieve the best effect. In the case of poor image quality, the clarity of the image can be further improved through image post-processing and analysis.