Background: Conventional ultrasonography is a method preferred for the investigation of chronic liver diseases in pediatric groups, as it is non-invasive, cheap, feasible and available. The purpose of this study is to present the role of Share-wave Elastography (SWE) in terms of diagnostic value in children diagnosed with “chronic liver disease.”Methods: We studied patients who had been diagnosed with chronic liver disease between March 2012-September 2015, and who had undergone liver biopsy and had their pathology results, compared with 26 healthy subjects. Statistical analysis was performed with IBM SPSS Statistics for Windows, Version 20.0. “Pearson Correlation Analysis” was performed in order to measure the relationship between elastography values and Brunt level.Results: This study had 107 subjects in total, consisting of 81 patients between 0-204 months of age Pearson correlation coefficient level was determined as r = 0.644. Since the correlation coefficient is positive, there is a same-directional relationship between Elastography level and Brunt degree. This means that while one of the variables is increasing, the other one will also increase.Conclusion: Since it is known that development of hepatic fibrosis is a dynamic process, and that many hepatic fibrosis etiologies are known to continue throughout the course of life, the application of Real time SWE method instead of repeated liver biopsies on patients is a much simpler and smart method. Increasing the clinical use of Real Time SWE method with future studies might provide an opportunity for preventing unnecessary liver biopsies since the patients are evaluated in a shorter time and in a cost-effective manner.Keywords: Shear-Wave Elastography, Brunt degree, chronic liver disease, liver biopsy.

Splanchnic venous thrombosis is a rare type of venous thromboembolism, and its actual incidence is still unknown. Splenic infarction develops due to splenic vein (SV) thrombosis. Patients with COVID-19 had a risk of thrombotic events, and the system affected at the highest level by coagulopathy is the respiratory system. The case presented here is splenic infarction that developed because of SV thrombosis, which is a rare form of venous thromboembolism.

Background/Aim: Tomography imaging is a valuable alternative to colonoscopy for diagnosing colorectal cancer cases especially when colonoscopy is not applicable. Therefore, processing tomography images by computer-aided diagnosis support systems is essential for helping clinicians. The aim of this study is to investigate the applicability of convolutional neural networks (CNN) for diagnosis of colorectal cancer from tomography images. This study uses CNN models to classify abdominal tomography im Methods: ages automatically. The image classication is performed using four benchmark CNN models, namely, MobileNETv2, ResNet101V2, InceptionResnetV2, EfcientNetB2, and a shallower sequential CNN model. The benchmark models are experimented with using transfer learning for two separate cases: with and without data augmentation. According to the results, the proposed sequential CNN model achieve Results: d the highest classication scores with mean accuracy, precision, recall and F1-score of 0.9803, 0.9813, 0.9793, and 0.9803, respectively. It is Conclusion: possible to achieve a better detection performance when a shallower CNN model with lower number of parameters is used. Making prediction with such a model means performing less computation to achieve the result. All in all, computer aided diagnosis of colorectal cancer is possible to help the clinicians during their daily practices

Background: The clinical significance of gastrointestinal wall thickening (GWT) on abdominal computed tomography (CT) is not certain, yet. Despite the need for clinical guidelines describing the importance and evaluation of GWT on a CT scan, there have been few studies evaluating these incidental imaging abnormalities. The aim of this study is to endoscopically evaluate certain etiologies that cause incidental GWT found on CT. Methods: This retrospective cohort study was carried out with patients who had incidentally detected GWT on a CT scan at the Kanuni Sultan Süleyman Training and Research Hospital between February 2016 and December 2018. Results: A total of 129 patients (62 males and 67 females; mean age 57.5 years, range: 26-87 years) were included in the study. Abnormalities observed during endoscopy at the exact site of the GWT noted on a CT image were found in 114 patients (99%): upper endoscopy revealed malignancy in 33 (29%), gastritis in 63 (52%), hiatal hernia in 19 (16%), a gastric ulcer in 7 (6%), and alkaline gastritis in 3 (2%). Colonoscopy revealed malignancy in 4 (33%), benign polyps in 5 (35%), colonic ulcer in 2 (16%), and 2 patients (16%) had normal findings. Malignancy was detected more frequently in the cardioesophageal region compared with the antrum (P = 0.020). Conclusion:In this study, detection of GWT on CT often indicated pathologies which were subsequently confirmed endoscopically. Pathological findings were detected in 83% of these patients, with approximately 30% determined to be malignant. Endoscopic evaluation is recommended when GWT is reported on a CT scan.