Therapy effect on AI-derived thalamic atrophy using clinical routine MRI protocol: A longitudinal, multi-center, propensity-matched multiple sclerosis study

Background: The effect of disease modifying therapies (DMTs) on brain atrophy in persons with multiple sclerosis (pwMS) is typically investigated in highly stan-dardized clinical trial settings or single-center academic institutions. We aimed at utilizing artificial intelligence (AI)-based volumetric analysis on routine un-standardized T2-FLAIR scans in determining the effect of DMTs on lateral ventricular volume (LVV) and thalamic volume (TV) changes in pwMS.Methods: The DeepGRAI (Deep Gray Rating via Artificial Intelligence) registry is a multi-center, longitudinal, observational, real-word study with a convenience sample of 1002 relapsing-remitting (RR) pwMS from 30 United States sites. Brain MRI exams acquired as part of the routine clinical management were collected at baseline and on average at 2.6-years follow-up. The MRI scans were acquired either on 1.5T or 3T scanners with no prior harmonization. TV was determined using the DeepGRAI tool and lateral ventricular volume LVV was measured using NeuroSTREAM software.Results: After propensity matching based on baseline age, disability and time of follow-up, untreated pwRRMS had significantly greater TV change when compared to treated pwRRMS (-1.2% vs.-0.3%, p = 0.044). PwRRMS treated with high-efficacy DMTs had significant and two-fold lower% LVV change when compared to pwRRMS treated on moderate-efficacy DMTs (3.5% vs. 7.0%, p = 0.001). PwRRMS who stopped DMT during the follow-up had significantly greater annualized% TV change compared to pwRRMS who remained on their DMT (-0.73% vs.-0.14%, p = 0.012) and significantly greater annualized% LVV change (3.4% vs. 1.7%, p = 0.047). These findings were also observed in a propensity analysis that additionally incorporated matching for scanner model at both baseline and follow-up visits.Conclusions: LVV and TV measured on T2-FLAIR scans can detect treatment-induced short-term neurodegenerative changes measured in a real-word unstandardized, multicenter, clinical routine setting.

Automated summary

In this study, artificial intelligence-based volumetric analysis was used to investigate the effect of disease modifying therapies (DMTs) on brain atrophy in multiple sclerosis (MS) patients. The results showed that untreated patients had greater brain atrophy changes compared to treated patients, especially those receiving high-efficacy DMTs. Patients who stopped DMTs during follow-up also showed increased brain atrophy. The study demonstrates the potential of using T2-FLAIR scans to detect treatment-induced neurodegenerative changes in a real-world clinical setting.