Home > Neurology > AAN 2022 > Multiple Sclerosis > Predicting new T2 lesions using a machine learning algorithm

Predicting new T2 lesions using a machine learning algorithm

Presented By
Mr Bastien Caba, Biogen Digital Health, MA, USA
Conference
AAN 2022
Trial
Phase 3, ADVANCE; ASCEND
Doi
https://doi.org/10.55788/abf790d2
A machine learning algorithm was able to detect abnormalities within normal-appearing white matter (NAWM) before any lesion could be detected. Using cross-sectional T1- and T2-weighted non-contrast brain MRI data from NAWM, this machine learning method could predict new T2 lesions up to 48 weeks prior to actual emergence. Conventional MRI is not sufficiently sensitive to enable early diagnosis, nor is its specificity sufficient to predict disease severity. Machine learning analyses of brain scan data may help to fill this gap. Mr Bastien Caba (Biogen Digital Health, MA, USA) and colleagues analysed brain T1- and T2-weighted MRI scans from the pivotal, phase 3 ADVANCE trial (NCT00906399), which included 1,512 patients with relapsing-remitting multiple sclerosis (RRMS), to validate the algorithm [1]. They then tested this algorithm utilising MRIs of 886 pat...


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