AUTHOR=Thakur Siddhesh P. , Schindler Matthew K. , Bilello Michel , Bakas Spyridon 

TITLE=Clinically Deployed Computational Assessment of Multiple Sclerosis Lesions

JOURNAL=Frontiers in Medicine

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.797586

DOI=10.3389/fmed.2022.797586

ISSN=2296-858X

ABSTRACT=Multiple Sclerosis (MS) is a demyelinating disease of the central nervous system that affects more than 1 million adults in the United States. Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis, treatment planning, and follow-up in MS patients. In particular, follow-up MRI with T2-FLAIR images of the brain, which depict white matter lesions, is the mainstay for monitoring disease activity and making treatment decisions. In this paper, we present a computational approach that has been deployed and integrated into a real-world routine clinical workflow, with a two-fold goal: a) detecting disease progression in MS patients, and b) determining the necessity for injecting Gadolinium Based Contract Agents (GBCAs). The computer-aided detection (CAD) software has been utilized on more than $18,000$ patients over the course of 10 years, while its added function of identifying patients who need GBCA injection, has been operative for the past 3 years, with $>85\%$ sensitivity. The benefits of this approach are summarized in: 1) offering a reproducible and accurate clinical assessment of MS lesion patients, 2) reducing the adverse effects of GBCAs (and the deposition of GBCAs to the patient’s brain) by identifying the patients who may benefit from injection, and 3) reducing healthcare costs, patients' discomfort, and caregivers' workload.