Artificial Intelligence-Assisted Evaluation of the Spatial Relationship between Brain Arteriovenous Malformations and the Corticospinal Tract to Predict Postsurgical Motor Defects.

ABSTRACT:

Background and purpose

Preoperative evaluation of brain AVMs is crucial for the selection of surgical candidates. Our goal was to use artificial intelligence to predict postsurgical motor defects in patients with brain AVMs involving motor-related areas.

Materials and methods

Eighty-three patients who underwent microsurgical resection of brain AVMs involving motor-related areas were retrospectively reviewed. Four artificial intelligence-based indicators were calculated with artificial intelligence on TOF-MRA and DTI, including FN_5mm/50mm (the proportion of fiber numbers within 5-50mm from the lesion border), FN_10mm/50mm (the same but within 10-50mm), FP_5mm/50mm (the proportion of fiber voxel points within 5-50mm from the lesion border), and F

SUBMITTER: Jiao Y 

PROVIDER: S-EPMC9835926 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature