Transient Ischemic Attack in Women: Real-World Hospitalization Incidence, Outcomes, and Risk of Hemorrhage and Stroke.

Background: Sex-specific differences in stroke risk factors, clinical presentation, and outcomes are well documented. However, little is known about real-world differences in transient ischemic attack (TIA) hospitalizations and outcomes between men and women.

Methods: This was a retrospective cohort study of the 2016 to 2021 Nationwide Readmissions Database in the United States.

Improving the Robustness of Deep-Learning Models in Predicting Hematoma Expansion from Admission Head CT.

Background And Purpose: Robustness against input data perturbations is essential for deploying deep-learning models in clinical practice. Adversarial attacks involve subtle, voxel-level manipulations of scans to increase deep-learning models' prediction errors. Testing deep-learning model performance on examples of adversarial images provides a measure of robustness, and including adversarial images in the training set can improve the model's robustness.

A Hybrid Transformer-Convolutional Neural Network for Segmentation of Intracerebral Hemorrhage and Perihematomal Edema on Non-Contrast Head Computed Tomography (CT) with Uncertainty Quantification to Improve Confidence.

Intracerebral hemorrhage (ICH) and perihematomal edema (PHE) are key imaging markers of primary and secondary brain injury in hemorrhagic stroke. Accurate segmentation and quantification of ICH and PHE can help with prognostication and guide treatment planning. In this study, we combined Swin-Unet Transformers with nnU-NETv2 convolutional network for segmentation of ICH and PHE on non-contrast head CTs.

Machine Learning Models for 3-Month Outcome Prediction Using Radiomics of Intracerebral Hemorrhage and Perihematomal Edema from Admission Head Computed Tomography (CT).

: Intracerebral hemorrhages (ICH) and perihematomal edema (PHE) are respective imaging markers of primary and secondary brain injury in hemorrhagic stroke. In this study, we explored the potential added value of PHE radiomic features for prognostication in ICH patients. : Using a multicentric trial cohort of acute supratentorial ICH ( = 852) patients, we extracted radiomic features from ICH and PHE lesions on admission non-contrast head CTs.

Neuroimaging Correlates of the NIH-Toolbox-Driven Cognitive Metrics in Children.

Background: The National Institutes of Health (NIH) Toolbox Cognition Battery is increasingly being used as a standardized test to examine cognitive functioning in multicentric studies. This study examines the associations between the NIH Toolbox Cognition Battery composite scores with neuroimaging metrics using data from the Adolescent Brain Cognitive Development (ABCD) study to elucidate the neurobiological and neuroanatomical correlates of these cognitive scores.

Methods: Neuroimaging data from 5290 children (mean age 9.