Current Medical Imaging - Volume 20, Issue 1, 2024

This study aimed to explore the similarities and differences in clinical presentations, multidetector computed tomographic (MDCT) features, and treatment of three types of adult intussusceptions based on location.

We retrospectively reviewed 184 adult patients with 192 intussusceptions. Depending on the location, intussusceptions were classified as enteric, ileocolic, and colonic types. The similarities and differences of clinical presentations, MDCT features, and treatment of three types of adult intussusception were compared. Meanwhile, the three types of intussusceptions were further divided into surgical and conservative groups based on the treatment. Uni- and multivariate logistic analyses were used to identify risk factors for intussusception requiring surgery.

Enteric and ileocolic intussusceptions were mainly presented with abdominal pain (78.46% and 85.71%). Hematochezia/melena (64.29%) was the main symptom of colonic intussusception. On MDCT, ileocolic intussusceptions were longer in length and had more signs of intestinal necrosis (hypodense layer, fluid collection and no/poor bowel wall enhancement) than enteric and colonic intussusceptions. Moreover, it was found that 93.88% (46/49) of ileocolic intussusception and 98.59% (70/71) of colonic intussusception belonged to the surgical group, whereas only 43.06% (31/72) of enteric intussusception belonged to the surgical group. Intussusception length (OR=1.171, P=0.028) and discernible lead point on MDCT (OR=21.003, P<0.001) were reliable indicators of enteric intussusception requiring surgery.

Ileocolic intussusception may be more prone to intestinal necrosis than enteric and colonic intussusceptions, requiring more attention from clinicians. Surgery remains the treatment of choice for most ileocolic and colonic intussusceptions. Less than half of enteric intussusceptions require surgery, and MDCT features are effective in identifying them.

We have aimed to investigate the role of ultrasonographic muscle parameters (UMP) in predicting osteosarcopenia in bedridden patients in a palliative care center.

The role of ultrasound has not been evaluated in predicting osteosarcopenia.

Reduced muscle thickness (MT) and cross-sectional area (CSA) have often been observed in individuals with sarcopenia, reflecting muscle loss and atrophy. Meanwhile, the potential role of muscle ultrasound has not been evaluated in predicting osteosarcopenia.

We have conducted a prospective, observational study between January 2021 and 2022. We have recorded the demographics, comorbidities, and nutritional status by using the mini nutritional assessment-short form. We measured handgrip strength with a hand dynamometer and the muscle mass with dual X-ray absorptiometry. Sarcopenia was defined by the European Working Group on Sarcopenia in Older People 2 criteria. Osteoporosis was diagnosed according to the World Health Organization criteria. We have categorized the body phenotypes into four groups: “non-sarcopenic non-osteoporotic,” “sarcopenic alone,” “osteoporotic alone,” and “sarcopenic osteoporotic.” We have measured the subcutaneous fat thickness (SFT), MT, and CSA of the rectus femoris (RF) and biceps brachii (BB) via ultrasonography. A multivariate regression analysis was performed and area under curve (AUC) values were used to evaluate the accuracy of UMPs.

We included 31 patients (mean age: 74.6±12.1 years, 54.8%: male). The prevalences of sarcopenia, osteoporosis, and sarcopenic osteoporosis were 71%, 48.4%, and 41.9%, respectively. Only the “sarcopenic osteoporotic” phenotype was negatively correlated with all UMPs. In the regression analysis, only the “sarcopenic osteoporotic” phenotype was independently associated with RFCSA (ß=-0.456, p= 0.024). The AUC for all patients was >0.700.

RFCSA measurement might be useful in the screening for osteosarcopenia. This has been the first study investigating the relationship between UMPs and body phenotypes. Multi-center and large-scale studies are, however, needed.

This study aimed to investigate whether there is a correlation between quantitative parameters of dual-energy computed tomography (DECT) and the relative expression of HIF-1α in patients with non-small cell lung cancer (NSCLC) to preliminarily explore the value of DECT in evaluating the hypoxia of tumor microenvironment and tumor biological behavior and provide more information for the treatment of NSCLC.

This retrospective research included 36 patients with pathologically confirmed NSCLC who underwent dual-energy enhanced CT scans. The quantitative parameters of DECT were analyzed, including iodine concentration, water concentration, the CT values corresponding to 40keV, 70keV, 100keV, and 130keV in arterial and venous phases, and the normalized iodine concentration and the slope of the energy spectrum curve were calculated. Postoperative specimens underwent HIF immunohistochemical staining by two pathologists. Spearman correlation analysis was adopted as the statistical methodology. The data were analyzed by SPSS26.0 statistical software.

Water concentration (r=0.659, P<0.001 and r= 0.632, P<0.001, the CT values corresponding to 100keV (r=0.645, P<0.001 and r= 0.566, P<0.001) and 130keV (r=0.687, P<0.001 and r= 0.682, P<0.001) in arterial and venous phases, and CT value of 70keV in arterial phase (r=0.457, P=0.005) were positively correlated with HIF-1α expression level. There was no correlation among iodine concentration, standardized iodine concentration, CT value of 40keV, λHU, and HIF-1α expression in arterial and venous levels (P >0.05).

The quantitative parameters of DECT have a certain correlation with HIF-1α expression in NSCLC. Moreover, it has been demonstrated that DECT can be used to predict hypoxia in tumor tissues and the prognosis of lung cancer patients.

Unilateral absence of the pulmonary artery (UAPA) is a very rare congenital anomaly.

To analyze the diagnostic strategy applied to seven patients with UAPA who were examined and subsequently treated at the National Lung Hospital, Hanoi, Vietnam.

All seven patients, including three pediatric cases (1, 2, and 14 years old) and four adult cases (21, 26, 44, and 53 years old), had a history of recurrent pneumonia, and the clinical symptoms on admission included cough, progressive dyspnea, chest pain, and fatigue. The patients were initially examined clinically, followed by hematological testing, blood biochemistry testing, and chest X-ray radiology. The results suggested UAPA, so echocardiography and contrast-enhanced chest computed tomography (CT) were performed as soon as practical.

The echocardiographic and CT imaging findings confirmed the suspected diagnosis of UAPA in all seven patients, which was accompanied by congenital heart disease in three patients. Three of the seven patients had mild and medium pulmonary hypertension. All seven patients were treated with drugs, which led to improvement in symptoms.

Frontal chest X-ray provided the initial signs suggesting a diagnosis of UAPA. Subsequent echocardiography and contrast-enhanced chest CT were effective diagnostic tools for fast and accurate confirmation of UAPA.

To explore the application value of a combined model based on multi-parameter MRI radiomics and clinical features in preoperative prediction of lymphatic vascular space invasion (LVSI) in endometrial carcinoma (EC).

This retrospective study collected the clinicopathological and imaging data of 218 patients with EC in Yuncheng Central Hospital from March 2018 to May 2022. The patients were randomly divided into training group (n=152) and validation group (n= 66) according to the ratio of 7: 3. Based on the ADC, CE-sag, CE-tra, DWI, T2WI-sag-fs, T2WI-tra sequence images of each patient, the region of interest was manually segmented and the features were extracted. The four-step dimensionality reduction method based on max-relevance and min-redundancy (MRMR) and least absolute shrinkage and selection operator (LASSO) regression was used for feature selection and radiomics model construction. Independent predictors of clinicopathological features were screened by multivariate logistic regression analysis. The imaging model based on ADC, CE-sag, CE-tra, DWI, T2WI-sag-fs, T2WI-tra single sequence and combined sequence and the fusion model with clinicopathological features were constructed, and the nomogram was made. ROC curve, correction curve and decision analysis curve were used to evaluate the efficacy and clinical benefits of the nomogram.

There was no significant difference in general clinical data between the training and validation groups (P > 0.05). After screening the extracted features, 16 radiomics features were obtained, which were all related to LVSI in EC patients (P < 0.05). The area under the ROC curve (AUC) of the six independent sequence radiomics models in the training group was 0.807, 0.794, 0.826, 0.794, 0.828, 0.824, respectively. The AUC corresponding to the radiomics model constructed by the combined sequence was 0.884, and the diagnostic efficiency was the best, which was verified in the validation group. The AUC of the nomogram constructed by the combined radiomics model and age、maximum tumor diameter(MTD), lymph node enlargement (LNE) in the training group and the validation group were 0.914 and 0.912, respectively. The correction curve shows that the nomogram has good correction performance. The decision curve suggests that taking radiomics nomogram to predict LVSI net benefit when the risk threshold is > 10% is better than considering all patients as LVSI+ or LVSI-.

The combined model based on multi-parametric MRI radiomics features and clinical features has good predictive value for LVSI status in EC patients.

Nowadays, people attach increasing importance to accurate and timely disease diagnosis and personalized treatment. Because of the uncertainty and latency of the pathogenesis, it is difficult to detect breast tumour early. With higher resolution, magnetic resonance imaging (MRI) has become an important method for early detection of cancer in recent years. At present, DL technology can automatically study imaging features of different depths.

This work aimed to use DL to study medical image-assisted diagnosis.

The image data were collected from the patients. ROI (region of interest) containing the complete tumor area in the medical image was generated. The ROI image was extracted, and the extracted feature data were expanded. By constructing a three-dimensional (3D) CNN model, the evaluation indicators of breast tumour diagnosis results have been proposed. In the experiment part, 3D CNN model and other models have been used to diagnose the medical image of breast tumour.

The 3D CNN model exhibited good ROI region extraction effect and breast tumor image diagnosis effect, and the average diagnostic accuracy of breast tumor image diagnosis was 0.736, which has been found to be much higher than other models and could be applied to breast tumor medical image-aided diagnosis.

The 3D CNN model has been trained by combining the two-dimensional CNN training mode, and the evaluation index of diagnostic results has been established. The experimental part verified the medical image diagnosis effect of the 3D CNN model. The model had exhibited a high ROI region extraction effect and breast tumor image diagnosis effect.

In the last few years, coronavirus disease 2019 (COVID-19) has changed human lifestyle, behavior, and perception of life. This disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-COV-2). In the literature, there are limited studies about the late renal effects of COVID-19 that reflect the systemic involvement of this disease.

In the present study, we aimed to compare sonoelastographic changes in both kidneys between patients who had totally recovered from COVID-19 and healthy individuals using strain wave elastography (SWE).

This study was conducted between June 2021 and May 2022 in Kahramanmaraş City Hospital Department of Radiology. File and archive records were retrospectively evaluated. Basic demographic, laboratory, and renal ultrasonography (USG) and sonoelastographic findings were screened and noted. Two groups were defined to compare sonoelastographic findings. Post-/long-COVID-19 group had 92 post-long COVID-19 patients, and the comparator group comprised healthy individuals”. Both groups’ demographic, laboratory, and ultrasound-elastographic findings were assessed.

The post-long COVID-19 group had a higher renal elastographic value than the comparator group (1.52 [0.77–2.3] vs. 0.96 [0.54–1.54], p<0.001). There were no statistically significant differences between the two groups in terms of age (p=0.063), gender (p=0.654), or body mass index (BMI) (p=0.725), however, there was a significant difference observed between the two groups in the renal strain ratio (RSR). According to an receiver operating characteristic curve (ROC) analysis, an RSR cutoff of >1.66 predicted post-long COVID-19 with 44.9% sensitivity and 81.9% specificity. (AUC=0.655, p<0.001). A separate ROC analysis was performed to predict post-long COVID-19 with a BMI cutoff of <33.52, kg/m² sensitivity of 92.4% and specificity of 17% (AUC=0.655, p<0.001).

We demonstrated that renal parenchymal stiffness increases with SWE in post-long COVID-19 patients.

In this work, we have used histopathology as the gold standard for the diagnosis, calculated the sensitivity and positive predictive value (PPV) of computed tomography (CT), and analyzed the CT and clinical characteristics of pathologically proven elastofibromas.

A systematic retrospective analysis was performed on all patients with infrascapular lesions who were treated in the hospital from 2006 to 2018. CT and histopathological examinations were performed for all cases, and the CT sensitivity and PPV for the diagnosis of elastofibroma were calculated. 12 of 53 cases (20 lesions) underwent enhanced CT scan after CT plain scan, and the related clinical and CT features of elastofibromas have been discussed.

Of the 54 patients treated during the study, CT diagnosis was consistent with histopathology in 53 cases. One was a false-positive patient. The PPV and sensitivity of the CT in the diagnosis of elastofibroma were 93.3% (95% CI 68.0%-99.8%) and 100%, respectively. The CT values of 12 patients with 20 lesions on plain and enhanced scans were statistically significant (P=0.001). The prevalence of elastofibromas in males and females was statistically significant (P=.000). There was no statistically significant difference in the incidence of left and right elastofibromas (P=0.752). There was no significant difference in the volume of left and right lesions (P=0.209) and the volume of elastofibromas between males and females (P=.474).

CT is the most practical tool for the evaluation of elastofibromas in the infrascapular region.

In late December 2019, Wuhan, the capital of Hubei Province, China, became the center of an outbreak of pneumonia caused by severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2).

The radiological changes in the lungs of critical people with coronavirus disease 2019 (COVID-19) pneumonia at different times have not been fully characterized. We aim to describe the computed tomography findings of patients with critical COVID-19 pneumonia at different disease stages.

Clinical and laboratory features of critical patients were assessed. CT scans were assigned to groups 1, 2, 3, or 4 based on the interval from symptom onset (within 2 weeks; ≥ 2-4 weeks; ≥ 4-6 weeks; or ≥ 6 weeks, respectively). Imaging features were analyzed and compared across the four groups. Total CT scores, corresponding periods of laboratory findings, and glucocorticoid dosages during the imaging intervals were longitudinally observed in five patients with complete data.

All 11 critical patients (median age: 60 years [42-69]) underwent a total of 40 CT examinations, and the acquisition times ranged from 1-59 days after symptom onset. Median total CT scores were 18 (9-25.25); 445 (42.88-47.62); 4375 (38.62-49.38); and 42 (32.25-53.25) in groups 1, 2, 3, and 4, respectively. The observed lesions were mainly bilateral (37 [92.5%]). The median values of involved lung segments were 10.5 (4.5-13.5); 17 (16-18.5); 18 (18-19.5); and 18 (18-19) in groups 1-4, respectively. The predominant patterns of observed abnormalities were ground-glass opacities (GGO) (9 [90%]); GGO with reticulation and mixed patterns (3 [37.5%] for both); GGO with consolidation (3 [30%]); and GGO with reticulation (8 [66.7%]) in groups 1-4, respectively. Patients developed fibrotic manifestations at later stages.

Critical patients with COVID-19 infection generally presented with temporally changing abnormal CT features from focal unilateral to diffuse bilateral GGO and consolidation that progressed to or coexisted with reticulation in the long term after symptom onset. Low-dose glucocorticoids may be effective in patients with interstitial changes on CT findings.

Neurolymphomatosis (NL) is a rare disease. Ultrasound (US) plays a crucial role in diagnosing and following up the NL.

A 59-year-old man was hospitalized with acute pain in the left upper extremity. Ultrasound revealed segmental swelling of multiple nerves around his left elbow with abundant blood flow signals. Contrast-Enhanced Ultrasound (CEUS) showed a rapid, complete and homogenous enhancement in the nerve lesions in the early arterial phase. The NL was confirmed by imaging and flow cytometry, and he accepted chemotherapy. The post-therapeutic ultrasound showed that the nerves in the left upper limb were basically normal. Unfortunately, the patient died of cerebral metastasis in 5 months.

The nerve US and CEUS can show specific manifestations and provide more diagnostic information about NL.

Lung cancer patients with post-chemotherapy may have disconnected or weakened function connections within brain networks.

This study aimed to explore the abnormality of brain functional networks in lung cancer patients with post-chemotherapy by modular edge analysis.

Resting-state functional magnetic resonance imaging (rs-fMRI) scans were performed on 40 patients after chemotherapy, 40 patients before chemotherapy and 40 normal controls. Patients in all three groups were age and sex well-matched. Then, modular edge analysis was applied to assess brain functional network alterations.

Post-chemotherapy patients had the worst MoCA scores among the three groups (p < 0.001). In intra-modular connections, compared with normal controls, the patients after chemotherapy had decreased connection strengths in the occipital lobe module (p < 0.05). Compared with the non-chemotherapy group, the patients after chemotherapy had decreased connection strengths in the subcortical module (p < 0.05). In inter-modular connections, compared with normal controls, the patients after chemotherapy had decreased connection strength in the frontal-temporal lobe modules (p < 0.05). Compared with the non-chemotherapy group, the patients after chemotherapy had decreased connection strength in the subcortical-temporal lobe modules (p < 0.05).

The results reveal that chemotherapy can disrupt connections in brain functional networks. As far as we know, the use of modular edge analysis to report changes in brain functional brain networks associated with chemotherapy was rarely reported. Modular edge analysis may play a crucial part in predicting the clinical outcome for the patients after chemotherapy.

While pulmonary vein filling defects on CT are typically considered diagnostic for thrombus, under certain circumstances, they can be artifactual as a result of flow phenomena.

We report a case of a 53-year-old female with chest pain who was found to have filling defects in pulmonary vein branches on CCTA that were initially treated as thromboses. However, follow-up cardiac MRI was negative for thrombi, and pseudo-thrombosis was therefore diagnosed.

Pulmonary vein pseudo-thrombosis should be considered in the differential diagnosis of pulmonary vein filling defects.

Diffuse-type tenosynovial giant cell tumor (D-TGCT) originates from synovial cells in tendon sheaths and bursae and rarely presents as a calcaneal mass.

A 44-year-old female presented with left heel pain that had persisted for over a year and had worsened over the past six months. A mass was found on the Lateral radiograph of the calcaneus, which was diagnosed as an aneurysmal bone cyst. Non-contrast computed tomography (CT) and magnetic resonance imaging (MRI)diagnosed a benign tumor. Based on light microscopy, special stains, and immunohistochemistry, a final diagnosis of diffuse tenosynovial giant cell tumor (D-TGCT) was rendered.

D-TGCT is a slow-growing, infiltrative tumor that can form single or multiple masses outside the joint, and can also involve adjacent jointsmainly affects weight-bearing joints such as the knee, hip, and ankle. However, D-TGCT presents as a calcaneal mass, which poses a diagnostic challenge for all radiologists.

A calcaneal mass exhibiting well-defined borders, focal cortical destruction, a sclerotic rim, and T2WI hypointensity, the possibility of D-TGCT should be considered.

It is essential to determine whether bone marrow signal changes on magnetic resonance imaging (MRI) represent a physiological response or pathology; at present, the clinical significance of these signal changes is unclear. It is unknown whether a bone marrow biopsy is required when bone marrow signal changes are detected incidentally in individuals without suspected malignancy.

The primary purpose of this study was to determine whether incidentally detected bone marrow signal changes on MRI performed for various reasons (at the time of admission or during follow-up) are clinically significant.

We retrospectively evaluated the bone marrow biopsy clinical and laboratory findings of 42 patients with incidental bone marrow signal changes on MRI between September 2016 and January 2020. We also determined whether the patients were diagnosed with malignancy during admission or follow-up.

Of the 42 patients, three (7%) were diagnosed with hematological malignancies during admission, while two were diagnosed with multiple myeloma and one with B-cell acute lymphoblastic leukemia. Of the 42 patients, 35 had a mean follow-up of 40.6 ± 5.3 months. One patient was diagnosed with monoclonal gammopathy of undetermined significance four months after their first admission.

In addition to MRI, detailed clinical and laboratory evaluations should be performed to inform the decision for bone marrow biopsy and exclude hematological malignancy. If there is any doubt, a bone marrow biopsy should be performed. Moreover, since bone marrow signal changes may be a preliminary finding, follow-up of these patients is essential.

Pyogenic liver abscess (PLA) is a purulent disease caused by microbial contamination of liver parenchyma and includes amoebic liver abscess, fungal liver abscess, and the most common bacterial liver abscess.

Explore the efficacy of contrast-enhanced ultrasound (CEUS) via vessels and surgical drain guidance percutaneous catheter drainage (PCD) in the treatment of pyogenic liver abscesses (PLA).

A total of 86 PLA patients who underwent PCD treatment in our hospital from May 2018 to February 2023 were retrospectively selected. Of them, 41 patients were treated under intravenous CEUS guidance (Control group), and 45 patients were treated under CEUS via vessels and surgical drain guidance (study group). Perioperative characteristics, treatment effectiveness, and incidence of complications were analyzed and compared between groups.

The duration of surgery, drainage, white blood cell recovery, body temperature recovery, and hospitalization in the study group were longer than those in the control group (P<0.05). The total effective rate of the study group (95.56%) was higher than that of the control group (80.49%) (P<0.05). The incidence of complications in the study group (4.44%) was lower than that in the control group (19.51%) (P<0.05).

Compared with intravenous CEUS alone, treatment under CEUS via vessels and surgical drains-guided PCD was associated with shorter surgical time, faster recovery, better treatment effect, lower risk of complications, and ensured treatment safety in PLA patients.

Mesothelioma is an insidious neoplasm that develops from mesothelial cells. About 80% of mesotheliomas originate in the pleural cavity. Other sites where it has been reported are the peritoneal cavity, tunica vaginalis, and the pericardium.

A 45-year-old female complained of abdominal distention and pain for three months. There was a significant weight loss of approximately 15 kg in the past three months, and there was no family history of any malignancy, tuberculosis, substance abuse, or asbestosis exposure. Physical examination revealed signs of muscle wasting, loss of subcutaneous fat, and hollowing of the eye sockets. There was pitting edema in the bilateral lower limbs; per abdomen examination revealed abdominal distension with umbilicus in the midline. No visible peristalsis or dilated veins were seen all over the abdomen. Hernial sites were normal. Gross ascites were present, and no organomegaly, definitive mass, or lump was palpable. The dull note was heard all over the abdomen, and fluid thrill was noted on percussion. Bowel sounds were normal on auscultation. The ascitic fluid examination revealed the presence of atypical cells. An omentectomy was done and it was sent for histopathological examination.

The specimen of omentectomy was in multiple fragments and measured 17x16x3cm; a few of the fragments were nodular, soft to firm on palpation. The cut section of mass was gray and white with areas of necrosis. Microscopic examination showed sheets of malignant cells. These tumor cells were immunoreactive to EMA, cytokeratin, vimentin, calretinin, WT-1, and D2-40 and immune negative to desmin (highlighting only the entrapped reactive mesothelial cells), inhibin, BerEP4, TTF-1, CD 68, napsin, ER, CEA, CDX2, PR, PAX-8, and SALL4. Ki67 labelling index was 15%. The features were of epithelioid mesothelioma.

Image enhancement is a very significant topic in image processing that improves the quality of the images. The methods of image enhancement are classified into 3 categories. They include histogram method, fuzzy logic method and optimal method. Studies on image enhancement are often based on rules: if it's bright then it's brighter, if it's dark then it's darker and using the global approach. So, it's hard to enhance objects in all dark and light areas, as in the medical images.

Input data is downloaded from the link: http://www.med.harvard.edu/AANLIB.

This paper introduces a new algorithm for enhancing medical images that is called the medical image enhancement based on cluster enhancement (MIECE). Firstly, the input image is clustered by the algorithm of fuzzy clustering. Then, the upper bound, and lower bound are calculated according to cluster. Next, the sub-algorithm is implemented for clustering enhancement using an enhancement operator. For each pixel, the gray levels for each channel (R, G, B) are transformed with this sub-algorithm to generate new corresponding gray levels. Because after clustering, each pixel belongs to each cluster with the corresponding membership value. Therefore, the output gray level value will be aggregated from the enhanced gray levels by the sub-algorithm with the weight of the corresponding cluster membership value.

This paper experiences the method MIECE with input data downloaded from the link: http://www.med.harvard.edu/AANLIB. The experimental results are compared with some recent methods that include: SGHIE (2017), Ying (2017) and KinD++ (2021).

This paper introduces the new algorithm which is based on cluster enhancement (MIECE) to enhance the medical image contrast. The experimental results show that the output images of the proposed algorithm are better than some other recent methods for enhancing dark objects.

Epicardial Adipose Tissue (EAT) accumulation is closely associated with the presence and severity of coronary artery disease (CAD), myocardial ischemia, plaque vulnerability, and major adverse cardiovascular events.

The aim of this study was to investigate the correlation between myocardial ischemia defined by computed tomography-derived fractional flow reserve (CT-FFR) and region-specific EAT in patients with type 2 diabetes mellitus (T2DM).

Between January 2022 and May 2023, 200 T2DM patients were randomly selected from the Department of Endocrinology in The Central Hospital of Wuhan. These patients were divided into two groups based on myocardial ischemia defined by CT-FFR: myocardial ischemia group (152 cases) and control group (48 cases). Both groups of patients used a post-treatment workstation to measure the thickness of region-specific EAT. Receiver operating characteristic (ROC) curve analysis and binary logistic regression were used to evaluate the correlation between various parameters and myocardial ischemia.

Patients in the myocardial ischemia group had significantly higher values of age, male gender, systolic blood pressure, total cholesterol, triglycerides, LDL, HDL, fasting blood glucose, fasting insulin, HOMA-IR, EAT thickness in right ventricular wall, left atrioventricular groove, and superior and inferior interventricular groove. ROC curve analysis results showed that EAT thickness in the left atrioventricular groove had the largest area under the ROC curve for diagnosing myocardial ischemia (0.837 [95% CI 0.766-0.865]; P < 0.001). Binary logistic regression analysis showed that EAT thickness in the left atrioventricular groove was an independent risk factor for myocardial ischemia in patients with T2DM (P < 0.05).

The EAT thickness in the left atrioventricular groove is an independent risk factor for myocardial ischemia in patients with T2DM. Adipose tissue in the left atrioventricular groove region plays a major role in EAT-mediated CAD.

Some patients with suspected brain metastases (BM) could not tolerate longer scanning examinations according to the standardized MRI protocol.

The purpose of this study was to evaluate the clinical value of contrast-enhanced fast fluid-attenuated inversion recovery (CE FLAIR) imaging in combination with contrast-enhanced T1 weighted imaging (CE T1WI) in detecting BM of lung cancer and explore a quick and effective MRI protocol.

In 201 patients with lung cancers and suspected BM, T1WI and FLAIR were performed before and after administration of gadopentetate dimeglumine. Two radiologists reviewed pre- and post-contrast images to determine the presence of abnormal contrast enhancement or signal intensity and decided whether it was metastatic or not on CE T1WI (Group 1) and CE FLAIR (Group 2). The number, locations and features of abnormal findings in two groups were recorded. Receiver Operating Characteristic (ROC) analyses were conducted in three groups: Group 1, 2 and 3(combination of CE FLAIR and CE T1WI).

A total of 714 abnormal findings were revealed, of which 672 were considered as BM and 42 nonmetastatic. Superficial and small metastases(≤10mm) in parenchyma and ependyma, leptomeningeal and non-expansive skull metastases were typically better seen on CE FLAIR. The areas under ROC in the three groups were 0.720,0.887 and 0.973, respectively. Group 3 was significantly better in diagnostic efficiency of BMs than Group 1 (p<0.0001) or Group 2 (p=0.0006).

The combination of CE T1WI and CE FLAIR promotes diagnostic performance and results in better observation and characterization of BM in patients with lung cancers. It provides a quick and efficient way of detecting BM.

Breast Cancer (BC) is a significant threat affecting women globally. An accurate and reliable disease classification method is required to get an early diagnosis. However, existing approaches lack accurate and robust classification.

This study aims to design a model to classify BC Histopathology images accurately by leveraging segmentation techniques.

This work proposes a combined segmentation and classification approach for classifying BC using histopathology images to address these issues. Chan-Vese algorithm is used for segmentation to accurately delineate regions of interest within the histopathology images, followed by the proposed SegEIR-Net (Segmentation using EfficientNet, InceptionNet, and ResNet) for classification. Bilateral Filtering is also employed for noise reduction. The proposed model uses three significant networks, ResNet, InceptionNet, and EfficientNet, concatenates the outputs from each block followed by Dense and Dropout layers. The model is trained on the breakHis dataset for four different magnifications and tested on BACH (BreAst Cancer Histology) and UCSB (University of California, Santa Barbara) datasets.

SegEIR-Net performs better than the existing State-of-the-Art (SOTA) methods in terms of accuracy on all three datasets, proving the robustness of the proposed model. The accuracy achieved on breakHis dataset are 98.66%, 98.39%, 97.52%, 95.22% on different magnifications, and 93.33% and 96.55% on BACH and UCSB datasets.

These performance results indicate the robustness of the proposed SegEIR-Net framework in accurately classifying BC from histopathology images.