Total kidney volume in autosomal dominant polycystic kidney disease: intraobserver and interobserver agreement of two methods with MRI.

Background/aim: Total kidney volume (TKV) is a parameter used in both treatment decision and follow-up in autosomal dominant polycystic kidney disease (ADPKD) patients. The objective of this study was to evaluate intra- and interobserver agreement of the ellipsoid formula (EF) and manual boundary tracing method (MBTM) used in TKV measurement of ADPKD patients across different levels of experience radiologists. Additionally, the study aimed to evaluate the correlation between the EF and MBTM, which is considered the gold standard for TKV. Materials and methods: A retrospective evaluation was conducted on magnetic resonance imaging (MRI) data from 55 ADPKD patients who underwent abdominal MRI between January 2017 and November 2021 to evaluate TKV. TKV measurements were performed by three independent observers (observer 1, an abdominal imaging radiologist with 5 years of experience; observer 2, a fourth-year radiology resident; observer 3, a second-year radiology resident).To assess intraobserver variability, all observers repeated the measurements at two-week intervals. The ICC was used to assess both intraobserver and interobserver variability. A comparison of the two methods was performed by linear regression for all three observers. Results: The ICC (95% CI) indicated excellent agreement between the observers for both methods (among all observers, p < 0.001). Furthermore, excellent intraobserver agreement was found between all observer measurements either EF or MBTM based on ICC (95% CI) (p < 0.001). The results of the linear regression analysis demonstrated high correlations between the two methods in all three observers (r = 0.992, p < 0.001 for the first observer; r = 0.975, p < 0.001 for the second observer; r = 0.989, p < 0.001 for the third observer). Conclusion: Both the EF and MBTM methods used for the measurement of TKV provided excellent intra- and interobserver reproducibility. The EF is as accurate and precise as the MBTM. It may therefore be preferred in radiology departments with heavy workload, as it is a reliable method for rapid and easy assessment, independent of experience.

[Segmentation of acute pulmonary embolism in computed tomography pulmonary angiography using the deep learning method]. / Derin ögrenme yöntemiyle akut pulmoner embolinin bilgisayarli tomografik pulmoner anjiografide segmentasyonu.

Introduction: Pulmonary embolism is a type of thromboembolism seen in the main pulmonary artery and its branches. This study aimed to diagnose acute pulmonary embolism using the deep learning method in computed tomographic pulmonary angiography (CTPA) and perform the segmentation of pulmonary embolism data. Materials and Methods: The CTPA images of patients diagnosed with pulmonary embolism who underwent scheduled imaging were retrospectively evaluated. After data collection, the areas that were diagnosed as embolisms in the axial section images were segmented. The dataset was divided into three parts: training, validation, and testing. The results were calculated by selecting 50% as the cut-off value for the intersection over the union. Result: Images were obtained from 1.550 patients. The mean age of the patients was 64.23 ± 15.45 years. A total of 2.339 axial computed tomography images obtained from the 1.550 patients were used. The PyTorch U-Net was used to train 400 epochs, and the best model, epoch 178, was recorded. In the testing group, the number of true positives was determined as 471, the number of false positives as 35, and 27 cases were not detected. The sensitivity of CTPA segmentation was 0.95, the precision value was 0.93, and the F1 score value was 0.94. The area under the curve value obtained in the receiver operating characteristic analysis was calculated as 0.88. Conclusions: In this study, the deep learning method was successfully employed for the segmentation of acute pulmonary embolism in CTPA, yielding positive outcomes.

A Case of Intestinal Perforation Associated with Mesenteric Thrombosis Due to Post-COVID-19 Syndrome.

PURPOSE: We aimed to present a case who developed intestinal ischemia and associated perforation and abscess due to Superior Mesenteric Vein (SMV) thrombosis caused by post-COVID-19 syndrome and discuss the preoperative Computed Tomography (CT) imaging findings used in diagnosis. CASE PRESENTATION: A 58-year-old patient presented to our clinic with a complaint of acute abdominal pain. His CT examination revealed thrombosis in SMV, congestion in the mesenteric venous structures, contamination in the mesentery, and thickening and dilatation of the jejunal loops due to ischemia. The patient had a history of acute COVID-19 infection. He had typical COVID-19 pneumonia findings (peripheral ground-glass opacities in both lung parenchyma predominantly in the lower lobe) on the thorax CT at that time. He was followed up with anticoagulant therapy. During his follow-up, a thoracic and abdominal CT was performed due to recurrent acute abdominal findings. On thorax CT, there was a web-like filling defect consistent with pulmonary embolism, traction bronchiectasis consistent with late findings of COVID-19 pneumonia, and poorly circumscribed subpleural ground glass opacities. On abdominal CT, in addition to mesenteric ischemia findings, loss of wall integrity was observed in the jejunal loops due to perforation and collection areas containing air consistent with an abscess. He was treated with small bowel resection and abscess drainage. CONCLUSION: Patients with acute COVID-19 infection should be followed up for the early diagnosis of serious symptoms that may develop due to post-COVID-19 syndrome, and contrast-enhanced CT should be the imaging method of choice to detect possible mesenteric vascular thrombosis in patients with acute abdominal symptoms.

Correlation of Indeterminate Lesions of COVID-19 Pneumonia Detected on Computed Tomography with RT-PCR Results.

BACKGROUND: The typical findings of COVID-19 pneumonia include multilobar groundglass opacities and consolidation areas observed predominantly in the basal and peripheral parts of both lungs in computed tomography. OBJECTIVE: The current study aimed to correlate indeterminate lesions of COVID-19 pneumonia detected on computed tomography with the results of the reverse transcription-polymerase chain reaction (RT-PCR) test. METHODS: Patients with high-resolution computed tomography images that were reported to contain indeterminate lesions in terms of COVID-19 pneumonia were included retrospectively in the study. The lesions were categorized and the patterns were classified. The RT-PCR-positive and the RTPCR- negative patients were compared. P<0.05 was accepted as the statistical significance limit. RESULTS: The RT-PCR-positive patients exhibited a higher rate of peripheral lesions. Limited consolidation areas were not detected in the RT-PCR-positive patients. In the RT-PCR-negative patients, the rates of acinar nodules and the tree-in-bud pattern were significantly higher. The RTPCR- negative patients had higher nodular contour features and lesion coalescence. In the subgroup consisting of lesions with ground-glass opacities and/or ground-glass opacity around the nodule, the rate of nodular contour positivity was significantly higher in the RT-PCR- positive patients. CONCLUSION: COVID-19 pneumonia should be suspected when peripheral indeterminate lesions are detected. When indeterminate lesions, such as tree-in-bud pattern, acinar nodules and limited consolidation area are detected, alternative diagnoses should be considered first, even if there are ground glass opacities accompanying these lesions.