To evaluate the frequency of abdominal computed tomography (CT) findings in patients with coronavirus disease-2019 (COVID-19) and interrogate the relationship between abdominal CT findings and patient demographic features, clinical findings, and laboratory test results as well as the CT atherosclerosis score in the abdominal aorta. This study was designed as a multicenter retrospective study. The abdominal CT findings of 1.181 patients with positive abdominal symptoms from 26 tertiary medical centers with a positive polymerase chain-reaction test for severe acute respiratory syndrome coronavirus 2 were reviewed. The frequency of ischemic and non-ischemic CT findings as well as the association between CT findings, clinical features, and abdominal aortic calcific atherosclerosis score (AA-CAS) were recorded. Ischemic and non-ischemic abdominal CT findings were detected in 240 (20.3%) and 328 (27.7%) patients, respectively. In 147 patients (12.4%), intra-abdominal malignancy was present. The most frequent ischemic abdominal CT findings were bowel wall thickening (n = 120; 10.2%) and perivascular infiltration (n = 40; 3.4%). As for non-ischemic findings, colitis (n = 91; 7.7%) and small bowel inflammation (n = 73; 6.2%) constituted the most frequent disease processes. The duration of hospital stay was found to be higher in patients with abdominal CT findings than in patients without any positive findings (13.8 ± 13 vs. 10.4 ± 12.8 days, P < 0.001). The frequency of abdominal CT findings was significantly higher in patients who did not survive the infection than in patients who were discharged after recovery (41.7% vs. 27.4%, P < 0.001). Increased AA-CAS was found to be associated with a higher risk of ischemic conditions in abdominal CT examinations. Abdominal symptoms in patients with COVID-19 are usually associated with positive CT findings. The presence of ischemic findings on CT correlates with poor COVID-19 outcomes. A high AA-CAS is associated with abdominal ischemic findings in patients with COVID-19.

Background/Objectives: The purpose of this study was to compare the prevalence of sarcopenia and frailty in patients with acromegaly and hypopituitarism to healthy controls. Methods: This descriptive, comparative study included 32 patients with acromegaly, 24 patients with hypopituitarism, and 28 healthy volunteers who had undergone abdominal computed tomography (CT) within a month of their presentation at the endocrinology outpatient clinic between October 2023 and October 2024. The Tilburg Frailty Indicator was used to measure frailty. Sarcopenia was assessed using a dynamometer to measure handgrip strength and a CT-derived skeletal muscle index (SMI) at the L3 spinal level to measure muscle mass. Results: Both the hypopituitarism (7.5 ± 2.8) and acromegaly (7 ± 2.7) groups had substantially greater frailty ratings than the controls (4.8 ± 2.9) (p = 0.015). Frailty prevalence was 43% in the control group, 75% in acromegaly, and 83% in hypopituitarism (p = 0.019). The hypopituitarism group’s muscle strength (20.8 ± 7.4 kg) was substantially lower than that of the acromegaly (37.5 ± 14.3 kg) and control groups (36.4 ± 9.6 kg) (p < 0.001). Patients with hypopituitarism had substantially lower SMI values (45.1 ± 11.3 cm²/m²) than those with acromegaly (53 ± 8.9 cm²/m²) (p = 0.04). A total of 50% of the control group, 9% of those with acromegaly, and 54% of those with hypopituitarism had probable or confirmed sarcopenia (p < 0.001). Conclusions: This study shows that frailty is more prevalent in patients with acromegaly and hypopituitarism than in healthy controls, with sarcopenia being especially noticeable in hypopituitarism. After adjusting for age and sex, the association with frailty remained significant for hypopituitarism (OR = 5.24, p = 0.021) while acromegaly showed a borderline trend (OR = 3.00, p = 0.076). These results imply that pituitary hormones might contribute to maintaining the functional ability and integrity of the musculoskeletal system. Further research in prospective studies using population-based controls is necessary to examine screening for frailty and sarcopenia in patients with pituitary diseases.

Aims: To conduct a bibliometric and thematic analysis of the 100 most-cited articles published over the last decade concerning the intersection of non-small cell lung cancer (NSCLC) and radiology, highlighting paradigm shifts and current research trends.Methods: The Web of Science Core Collection was queried for literature on NSCLC and radiology/imaging published between 2016 and 2026. The top 100 most-cited original articles and reviews were extracted. Data were categorized thematically and mapped bibliometrically using VOSviewer to analyze keyword co-occurrence and chronological evolution.Results: The thematic analysis revealed that “Artificial Intelligence (AI) & Deep Learning” (25 articles, 9711 citations) and “treatment response & Prognosis” (26 articles, 6271 citations) dominated the high-impact literature. Timeline mapping demonstrated a notable shift from traditional anatomical staging toward predictive radiomics, deep learning models, and immunotherapy evaluation. The Lancet Oncology and Harvard University emerged as the leading journal and institution, respectively. Despite high citation rates, a lack of methodological standardization in image processing remains a significant barrier to clinical translation.Conclusion: NSCLC radiology has evolved from a qualitative morphological evaluation into a quantitative, AI-driven discipline capable of predicting genetic mutations and treatment outcomes. Overcoming standardization bottlenecks and developing multimodal systems are crucial for integrating these robust models into clinical workflows.

Aims: To determine whether active smokers with preserved post-bronchodilator spirometry (FEV₁/FVC ≥ lower limit of normal [LLN]) and normal thoracic computed tomography (CT) show lower FEF₂₅₋₇₅ values and a higher prevalence of isolated small airway dysfunction than never-smokers, and to assess PEF-FEV₁ agreement for Global Initiative for Chronic Obstructive Lung Disease (GOLD) severity staging.Methods: We analysed spirometry data from 286 consecutive adults (≥40 years) at a single pulmonary function laboratory. Two chest radiologists independently reviewed all thoracic CT scans (ICC=0.95). Logistic regression included FVC z-score as a prespecified covariate to account for the volume-dependence of FEF₂₅-₇₅; model stability was confirmed by penalised regression and bootstrap validation.Results: Among 244 participants with preserved FEV₁/FVC (136 smokers, 108 never-smokers), FEF₂₅₋₇₅ was lower in smokers (76.2±26.1% vs 93.5±21.9%; p

Background/Objectives: This study aimed to evaluate the diagnostic accuracy of Apparent Diffusion Coefficient (ADC) values, derived from Diffusion-Weighted Imaging (DWI), in differentiating benign and malignant ascites. Methods: This retrospective study included 150 patients (85 benign, 65 malignant) who underwent abdominal MRI. All patients were scanned on a DWI sequence (b-values: 0, 500, and 1000 s/mm²). Two experienced radiologists, blinded to clinical and cytological outcomes, measured the mean ADC (ADCmean) from three distinct ROIs and the minimum ADC (ADCmin) from the area of lowest signal intensity on the ADC map. The diagnostic performance of ADC parameters and the Serum-Ascites Albumin Gradient (SAAG) was assessed using Receiver Operating Characteristic (ROC) curve analysis. Results: The mean values of ADCmean (3162 ± 204 × 10⁻⁶ mm²/s) and ADCmin (2885 ± 148 × 10⁻⁶ mm²/s) in the malignant group were significantly lower than those in the benign group (3596 ± 239 and 3322 ± 218 × 10⁻⁶ mm²/s; p = 0.006 and p = 0.0016, respectively). Inter-observer agreement was good for both ADCmean (ICC = 0.844) and ADCmin (ICC = 0.879). In the ROC analysis, ADCmin demonstrated the highest diagnostic performance (AUC: 0.930). An optimal cut-off value for ADCmin of ≤ 2983 × 10⁻⁶ mm²/s yielded 81.5% sensitivity and 85.8% specificity. The diagnostic performance of ADCmin was found to be superior to that of ADCmean (AUC: 0.877) and SAAG (AUC: 0.919). Conclusions: ADC values derived from DWI, particularly ADCmin, represent a highly accurate, non-invasive, and reproducible biomarker for differentiating benign from malignant ascites. The identified ADCmin threshold provides quantitative parameter that can aid in patient triage, especially when cytology is inconclusive, potential surrogate for fluid characterization.