Artificial Intelligence-Assisted Detection of Amyloid-Related Imaging Abnormalities: Promise and Pitfalls.

The advent of anti-amyloid therapies (AATs) for Alzheimer disease (AD) has elevated the importance of MRI surveillance for amyloid-related imaging abnormalities (ARIA) such as microhemorrhages and siderosis (ARIA-H) and edema (ARIA-E). We report a literature review and early quality-assurance experience with an FDA-cleared decision support artificial intelligence (AI) tool intended for detection of ARIA in MRI clinical workflows. The AI system improved the sensitivity for detection of subtle ARIA-E and ARIA-H lesions but at the cost of a reduction in specificity. We propose a tiered workflow combining protocol harmonization and expert interpretation with an AI overlay review. AI-assisted ARIA detection is a paradigm shift that offers great promise to enhance patient safety as disease-modifying therapies for AD gain broader clinical use; however, some pitfalls need to be considered.

Duke Scholars

Author Andrew John Liu Neurology, Behavioral Neurology

Author Jeffrey Robert Petrella Radiology, Neuroradiology