Bilello, Michel

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps.

Background— The incidence and impact of clinical stroke and silent radiographic cerebral infarction complicating open surgical aortic valve replacement (AVR) are poorly characterized. Methods and Results— We performed a prospective cohort study of subjects ≥65 years of age who were undergoing AVR for calcific aortic stenosis. Subjects were evaluated by neurologists preoperatively and postoperatively and underwent postoperative magnetic resonance imaging. Over a 4-year period, 196 subjects were enrolled at 2 sites (mean age, 75.8±6.2 years; 36% women; 6% nonwhite). Clinical strokes were detected in 17%, transient ischemic attack in 2%, and in-hospital mortality was 5%. The frequency of stroke in the Society for Thoracic Surgery database in this cohort was 7%. Most strokes were mild; the median National Institutes of Health Stroke Scale was 3 (interquartile range, 1–9). Clinical stroke was associated with increased length of stay (median, 12 versus 10 days; P =0.02). Moderate or severe stroke (National Institutes of Health Stroke Scale ≥10) occurred in 8 (4%) and was strongly associated with in-hospital mortality (38% versus 4%; P =0.005). Of the 109 stroke-free subjects with postoperative magnetic resonance imaging, silent infarct was identified in 59 (54%). Silent infarct was not associated with in-hospital mortality or increased length of stay. Conclusions— Clinical stroke after AVR was more common than reported previously, more than double for this same cohort in the Society for Thoracic Surgery database, and silent cerebral infarctions were detected in more than half of the patients undergoing AVR. Clinical stroke complicating AVR is associated with increased length of stay and mortality.