Article Text

Download PDFPDF
Original research
Thalamic atrophy measured by artificial intelligence in a multicentre clinical routine real-world study is associated with disability progression


Background The thalamus is a key grey matter structure, and sensitive marker of neurodegeneration in multiple sclerosis (MS). Previous reports indicated that thalamic volumetry using artificial intelligence (AI) on clinical-quality T2-fluid-attenuated inversion recovery (FLAIR) images alone is fast and reliable.

Objective To investigate whether thalamic volume (TV) loss, measured longitudinally by AI, is associated with disability progression (DP) in patients with MS, participating in a large multicentre study.

Methods The DeepGRAI (Deep Grey Rating via Artificial Intelligence) Registry is a multicentre (30 USA sites), longitudinal, observational, retrospective, real-world study of relapsing-remitting (RR) MS patients. Each centre enrolled between 30 and 35 patients. Brain MRI exams acquired at baseline and follow-up on 1.5T or 3T scanners with no prior standardisation were collected. TV measurement was performed on T2-FLAIR using DeepGRAI, and on two dimensional (D)-weighted and 3D T1-weighted images (WI) by using FMRIB’s Integrated Registration and Segmentation Tool software where possible.

Results 1002 RRMS patients were followed for an average of 2.6 years. Longitudinal TV analysis was more readily available on T2-FLAIR (96.1%), compared with 2D-T1-WI (61.8%) or 3D-T1-WI (33.2%). Over the follow-up, DeepGRAI TV loss was significantly higher in patients with DP, compared with those with disability improvement (DI) or disease stability (−1.35% in DP, −0.87% in DI and −0.57% in Stable, p=0.045, Bonferroni-adjusted, age-adjusted and follow-up time-adjusted analysis of covariance). In a regression model including MRI scanner change, age, sex, disease duration and follow-up time, DP was associated with DeepGRAI TV loss (p=0.022).

Conclusions Thalamic atrophy measured by AI in a multicentre clinical routine real-world setting is associated with DP over mid-term follow-up.


Data availability statement

All data relevant to the study are included in the article or uploaded as online supplemental information. N/A.

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.