Aim: The prognostic value of the De Ritis ratio (AST/ALT) in localized prostate cancer remains uncertain. This study evaluated its predictive role in International Society of Urological Pathology (ISUP) grade upgrading and adverse pathological features following radical prostatectomy.Material and Methods: This retrospective study included 152 patients who underwent radical prostatectomy for prostate adenocarcinoma between 2012 and 2022. The De Ritis ratio was calculated using preoperative AST and ALT levels. Patients were grouped according to ISUP grade upgrading between biopsy and final pathology. Receiver operating characteristic (ROC) analysis and multivariate logistic regression were performed.Results: ISUP upgrading occurred in 46.3% of patients. Mean De Ritis ratios did not differ significantly between groups (p = 0.38). However, a ratio ≤1.22 was associated with higher upgrading rates (51.5% vs. 34.7%, p = 0.05). ROC analysis demonstrated limited discriminatory ability (AUC = 0.552; sensitivity 75%, specificity 39%). Multivariate analysis identified age (p = 0.02), prostate volume (p = 0.048), and biopsy ISUP grade (p = 0.001) as independent predictors, whereas the De Ritis ratio was not independently associated with upgrading.Conclusions: The De Ritis ratio was not an independent predictor of ISUP upgrading, although associations with adverse pathological features were observed. Its limited discriminatory performance suggests that it should not be used as a standalone predictor. Further prospective studies are warranted to clarify its potential supplementary clinical value.
Gastric schwannomas are rare benign peripheral nerve sheath tumors of the gastrointestinal tract and may closely mimic gastrointestinal stromal tumors (GIST) clinically, endoscopically, and radiologically. We present a 67-year-old man who was evaluated for microcytic anemia and found to have a large submucosal gastric mass initially suspected to be a GIST. Contrast-enhanced computed tomography demonstrated a 53 × 46 × 71 mm mural lesion extending into both the gastric lumen and the extragastric space. Laparoscopic wedge resection was performed. Histopathological and immunohistochemical examination established the diagnosis of gastric schwannoma, with tumor cells showing positivity for S100 and SOX10 and negativity for CD117, DOG1, and CD34.This case highlights the diagnostic difficulty in distinguishing gastric schwannoma from GIST preoperatively. Gastric schwannoma should therefore be considered in the differential diagnosis of gastric submucosal masses with imaging and endoscopic features suggestive of GIST. Histopathological examination combined with immunohistochemical evaluation plays a central role in establishing the definitive diagnosis.
Aim: This study aimed to comprehensively compare the performance of different deep learning architectures for automatic segmentation of carotid artery ultrasound images and classification of breast ultrasound images, and to develop clinical decision support systems.Material and Methods: Nine segmentation algorithms (U-Net, SegNet, DeepLab v3+, Mask R-CNN, Attention U-Net, U-Net++, TransUNet, Swin-UNet, Vision Mamba UNet) and ten classification algorithms were evaluated on a single held-out partition of the Common Carotid Artery (CCA; 1100 images from 11 subjects) and Breast Ultrasound Images (BUSI; 780 images) datasets; the segmentation models were trained with the configurations recommended in their original publications and the classification models with a shared SGD configuration. Performance was measured using the Dice similarity coefficient (DSC), intersection over union (IoU), precision, sensitivity and F1 score.Results: Vision Mamba UNet achieved the highest segmentation performance for carotid artery (DSC=0.943, IoU=0.896). For the BUSI dataset, Vision Mamba UNet obtained the highest segmentation DSC (0.834) and Vision Transformer the highest classification F1 (0.887). The three highest-ranked segmentation models differed by at most 0.005 DSC on CCA and 0.029 on BUSI.Conclusion: In this single-run evaluation, state space model-based and transformer-based segmentation architectures obtained higher scores than conventional CNN approaches; the ranking was not tested statistically. The web-based applications are prototypes that have not been evaluated in a clinical setting.
Aim: Interventional Radiology (IR) is a rapidly expanding field providing minimally invasive, image-guided diagnostic and therapeutic procedures; however, awareness of IR among future physicians may remain limited. This study aimed to assess the knowledge and awareness of IR among final-year medical students and to examine factors associated with knowledge levels.Material and Methods: This cross-sectional analytical study was conducted among final-year medical students at a university medical faculty during the 2022–2023 academic year. Of 182 eligible students, 165 participated between July 1 and September 30, 2023. A researcher-developed 28-item questionnaire was administered face-to-face. Eight items (five closed-ended, three open-ended) were used to calculate an IR knowledge score ranging from 0 to 8, expressed as a proportion. Data were analyzed using IBM SPSS Statistics version 25.0.Results: Of the 165 participants, 72.7% (n = 120) reported witnessing an IR procedure during their radiology internship. Most participants (55.8%, n = 92) rated their IR knowledge as poor, and 81.8% (n = 135) reported being unable to provide adequate information about IR. The same proportion (81.8%, n = 135) believed that primary care physicians should have knowledge of IR. The mean IR knowledge score was 0.58 ± 0.20.Conclusion: Final-year medical students demonstrated moderate knowledge of IR, while their self-perceived knowledge and confidence were limited. Gaps were particularly evident regarding the professional scope and training pathway of interventional radiologists. Structured undergraduate education and increased exposure to IR may help address these gaps.
Aim: Persistent symptoms following COVID-19 may adversely affect nutritional status and health-related quality of life. This study evaluated these outcomes and their associations with pulmonary function and clinical characteristics.Material and Methods: This cross-sectional retrospective study included 200 ICU-hospitalized COVID-19 patients (June 2020–December 2022) who later attended outpatient follow-up. Hospitalization and post-discharge data were obtained from institutional electronic systems and HSYS. Statistical analyses were conducted using SPSS 27.0, with p<0.05 considered significant.Results: Participants were predominantly male (65.0%), with a mean age of 51.5 ± 12.1 years; 67.5% were obese and 57.5% had chronic diseases, predominantly hypertension and diabetes. Persistent symptoms were reported by 81.0% of patients, most commonly dyspnea, fatigue, forgetfulness, and cough. Persistent symptoms were more frequent among women and individuals with chronic diseases. Among the 182 patients with available pulmonary function test (PFT) data, 72.0% had a normal pattern, 7.1% an obstructive pattern, and 20.9% a restrictive pattern. The mean EQ-5D-3L total score was 88.9±10.3, and the mean EQ-VAS score was 83.2±10.8. Problems in specific EQ-5D-3L dimensions were more frequent among patients aged >60 years and those with chronic diseases. Overall, 89.0% of participants had normal nutritional status, 10.0% were at risk of malnutrition, and 1.0% were classified as malnourished. Participants with normal nutritional status had significantly higher EQ-VAS scores than those who were at risk of malnutrition or malnourished (p=0.020).Conclusion: Post-COVID-19 individuals exhibited reductions in both nutritional status and quality of life, underscoring the importance of long-term monitoring and targeted follow-up, particularly among high-risk groups.
