Fig. 1: Overview of the study design.
From: Deep learning-based brain age predicts stroke recurrence in acute ischemic cerebrovascular disease
a Training procedure of the Mask-based Brain Age estimation Network (MBA Net). The model was developed to predict consistent brain age values for both masked and unmasked T2 fluid-attenuated inversion recovery (T2-FLAIR) images in heathy individuals. b Inference phase of contextual brain age (CBA) for patients with acute ischemic cerebrovascular disease (AICVD). The infarct lesion segmentation maps were converted into rectangular masks and subsequently applied to T2-FLAIR images to generate the corresponding masked T2-FLAIR images. These images were then processed through the MBA Net to estimate CBA and calculate the brain age gap (BAG). c Clinical application of the BAG in AICVD. For each additional year of BAG, the risks of stroke recurrence increased by 9% at 3 months and by 7% at 5 years.
