Triage is essential for the early diagnosis and reporting of neurologic emergencies. Herein, we report the development of an anomaly detection algorithm (ADA) with a deep generative model trained on brain computed tomography (CT) images of healthy individuals that reprioritizes radiology worklists and provides lesion attention maps for brain CT images with critical findings. In the internal and external validation datasets, the ADA achieved area under the curve values (95% confidence interval) of 0.85 (0.81–0.89) and 0.87 (0.85–0.89), respectively, for detecting emergency cases. In a clinical simulation test of an emergency cohort, the median wait time was significantly shorter post-ADA triage than pre-ADA triage by 294 s (422.5 s [interquartile range, IQR 299] to 70.5 s [IQR 168]), and the median radiology report turnaround time was significantly faster post-ADA triage than pre-ADA triage by 297.5 s (445.0 s [IQR 298] to 88.5 s [IQR 179]) (all p < 0.001).

Background Transcatheter arterial embolization (TAE) is not common for hemorrhagic complications after gynecologic hysterectomy. Purpose To evaluate the effectiveness and safety of TAE for hemorrhage after hysterectomy for gynecologic diseases. Material and Methods This is a retrospective, multicenter study, which investigated 11 patients (median age = 45 years) who underwent TAE for hemorrhage after gynecologic hysterectomy between 2004 and 2020. Results The median interval between surgery and angiography was one day (range = 0–82 days). Hemodynamic instability and massive transfusion were present in 6 (54.5%) and 4 (36.4%) patients, respectively. CT scans (n = 7) showed contrast extravasation (n = 5), pseudoaneurysm (n = 1), or both (n = 1). On angiography, the bleeding arteries were the anterior division branches of the internal iliac artery (IIA) (n = 6), posterior division branch (lateral sacral artery, n = 1), and inferior epigastric artery (n = 1) in eight patients with active bleeding. In the remaining three patients, angiographic staining without active bleeding foci was observed at the vaginal stump, and the feeders for staining were all anterior division branches of the IIA. Technical and clinical success rates were 100% and 90.9% (10/11), respectively. In one patient, active bleeding focus was successfully embolized on angiography, but surgical hemostasis was performed for suspected bleeding on exploratory laparotomy. Postembolization syndrome occurred in one patient. Conclusions TAE is effective and safe for hemorrhage after hysterectomy for gynecologic diseases. Angiographic findings are primarily active bleeding, but angiographic staining is not uncommon. A bleeding focus is possible in any branch of the IIA, as well as the arteries supplying the abdominal wall.

Objective To develop and validate a model using radiomics features from apparent diffusion coefficient (ADC) map to diagnose local tumor recurrence in head and neck squamous cell carcinoma (HNSCC). Materials and Methods This retrospective study included 285 patients (mean age ± standard deviation, 62 ± 12 years; 220 male, 77.2%), including 215 for training (n = 161) and internal validation (n = 54) and 70 others for external validation, with newly developed contrast-enhancing lesions at the primary cancer site on the surveillance MRI following definitive treatment of HNSCC between January 2014 and October 2019. Of the 215 and 70 patients, 127 and 34, respectively, had local tumor recurrence. Radiomics models using radiomics scores were created separately for T2-weighted imaging (T2WI), contrast-enhanced T1-weighted imaging (CE-T1WI), and ADC maps using non-zero coefficients from the least absolute shrinkage and selection operator in the training set. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of each radiomics score and known clinical parameter (age, sex, and clinical stage) in the internal and external validation sets. Results Five radiomics features from T2WI, six from CE-T1WI, and nine from ADC maps were selected and used to develop the respective radiomics models. The area under ROC curve (AUROC) of ADC radiomics score was 0.76 (95% confidence interval [CI], 0.62–0.89) and 0.77 (95% CI, 0.65–0.88) in the internal and external validation sets, respectively. These were significantly higher than the AUROC values of T2WI (0.53 [95% CI, 0.40–0.67], p = 0.006), CE-T1WI (0.53 [95% CI, 0.40–0.67], p = 0.012), and clinical parameters (0.53 [95% CI, 0.39–0.67], p = 0.021) in the external validation set. Conclusion The radiomics model using ADC maps exhibited higher diagnostic performance than those of the radiomics models using T2WI or CE-T1WI and clinical parameters in the diagnosis of local tumor recurrence in HNSCC following definitive treatment.