Objectives To investigate the utility of shear wave elastography (SWE) in detecting morphologic abnormalities of the median nerve and posterior tibial nerve in transverse and longitudinal axes in adolescents with type 1 diabetes mellitus (DM) without diabetic peripheral neuropathy (DPN). Methods The median nerves and posterior tibial nerves of 25 adolescents with diagnosis and follow‐up of type 1 DM without DPN and 32 healthy volunteers were evaluated with SWE by 2 observers on the transverse and longitudinal axes. The cross‐sectional area and thickness of the nerves and disease duration were noted, and probable associations of these parameters with SWE features were analyzed. Interobserver and intraobserver correlations were also examined. The statistical significance level was set at P < .05. Results Both the median nerve and posterior tibial nerve were smaller, thinner, and stiffer in the patient group for both observers on both axes. The disease duration weakly correlated with median nerve SWE features (r = 0.245–0391). The thickness and cross‐sectional area had no correlations with SWE features. Conclusions The median nerve and posterior tibial nerve in adolescents with type 1 DM without DPN have morphologic abnormalities that can be displayed by SWE regardless of the imaging axis. Shear wave elastography may have a potential role in subclinical DPN, but the reliability of the findings is not as high as desirable.

Background Gastrointestinal vascular malformations are rare benign vascular neoplasms of the gastrointestinal tract, with the rectosigmoid region being the most frequently involved site. Patients often manifest with recurrent, intermittent rectal bleeding, which might occasionally be life-threatening. Case presentation A 39-year-old man with a history of hemorrhoid operations twice was presented to our gastroenterology department with blood in the stool and abdominal pain. After the colonoscopy, multiparametric MRI, and CT examinations, robotic low anterior resection was performed with the diagnosis of rectosigmoid venous malformation. The histopathological examination confirmed the diagnosis. Conclusion Colonoscopy is the preferred method in diagnosing rectosigmoid vascular malformation, but wrong and delayed diagnoses are common. Thus, imaging modalities might add to colonoscopy in equivocal cases.

Objective To investigate whether commercially available deep learning (DL) software improves the Prostate Imaging-Reporting and Data System (PI-RADS) scoring consistency on bi-parametric MRI among radiologists with various levels of experience; to assess whether the DL software improves the performance of the radiologists in identifying clinically significant prostate cancer (csPCa). Methods We retrospectively enrolled consecutive men who underwent bi-parametric prostate MRI at a 3 T scanner due to suspicion of PCa. Four radiologists with 2, 3, 5, and > 20 years of experience evaluated the bi-parametric prostate MRI scans with and without the DL software. Whole-mount pathology or MRI/ultrasound fusion-guided biopsy was the reference. The area under the receiver operating curve (AUROC) was calculated for each radiologist with and without the DL software and compared using De Long’s test. In addition, the inter-rater agreement was investigated using kappa statistics. Results In all, 153 men with a mean age of 63.59 ± 7.56 years (range 53–80) were enrolled in the study. In the study sample, 45 men (29.80%) had clinically significant PCa. During the reading with the DL software, the radiologists changed their initial scores in 1/153 (0.65%), 2/153 (1.3%), 0/153 (0%), and 3/153 (1.9%) of the patients, yielding no significant increase in the AUROC (p > 0.05). Fleiss’ kappa scores among the radiologists were 0.39 and 0.40 with and without the DL software (p = 0.56). Conclusions The commercially available DL software does not increase the consistency of the bi-parametric PI-RADS scoring or csPCa detection performance of radiologists with varying levels of experience.