Accurate quantification of chronic lesion expansion in MS: Introducing the GRADE algorithm

Motivation: Persistent disability progression despite successful relapse suppression presents a critical challenge in MS management. Chronic expansion of existing lesions is likely a key driver and therefore a potential biomarker of disease progression and target for novel DMTs. Currently, no automated MR pipeline exists that can accurately quantify chronic expansion. Goal(s): To develop and validate an algorithm that accurately differentiates and quantifies chronic expansion from new confluent lesion volume within expanding MS lesions. Approach: Longitudinal FLAIR lesion masks will be analyzed using our GRadient-Adjusted Decay Estimation (GRADE) algorithm, assigning voxel-wise chronic expansion probabilities. Validation against manual ground truth with 100+ patients. Impact: Despite its signification role in MS progression, accurate quantification of chronic lesion expansion has remained elusive. This newly designed GRADE algorithm will be validated for routine clinical quantification of chronic expansion, potentially revolutionizing patient monitoring and development of targeted therapies.