An automated quantitative report for multiple sclerosis using only 3D T2-fluid-attenuated inversion recovery MRI.
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Mendelsohn Zoe, Prados Ferran, Pontillo Giuseppe, Goodkin Olivia, Jasperse Bas, Rovira Alex, Grech-Sollars Matthew, Colman Jordan, Moggridge James, Hamed Weaam, Ijishakin Ayodeji, Foster Michael A, Mahmoudi Nima, Wattjes Mike P, Brunetti Arturo, Gonzalez-Escamilla Gabriel, Groppa Sergiu, Høgestøl Einar August, Westlye Lars T, Palace Jacqueline, Messina Silvia, Cortese Rosa, De Stefano Nicola, Sastre-Garriga Jaume, Ropele Stefan, Enzinger Christian, Rocca Maria A, Filippi Massimo, Chataway Jeremy, Wade Charles, Toosy Ahmed, Ciccarelli Olga, Pemberton Hugh, Cole James H, Scheel Michael, Nawabi Jawed, Yousry Tarek, Thornton John, Barkhof Frederik
Аннотация
METHODS: 2516 cross-sectional 3D T2-FLAIR scans from people with MS (pwMS) and healthy controls (HC) were retrospectively collected from 14 centres within Magnetic Resonance Imaging in MS (MAGNIMS) and affiliated sites, as well as open-source datasets. Validated T2-FLAIR-based algorithms quantified total and regional lesion count (LC), lesion volume (LV), brain volume (BV), and brain age gap estimation (BrainAGE). Distributions in pwMS and HC were estimated using quantile regression. A QReport was designed to present biomarkers and reference models in graphical formats. Four neuroradiologists assessed agreement between QReport outputs and their visual assessment, and evaluated its usefulness, in 22 cases.
RESULTS: We analysed scans from 1723 HC (age, mean ± SD: 54.5 ± 16.0; range: 18-75; F/M: 949/774) and 793 pwMS (age, mean ± SD: 43.0 ± 11.1; range: 18-75; F/M: 538/255) across 14 centres. The QReport presents single-subject measures contextualised against the 95th, 50th, and 5th percentile distributions in pwMS and HC, and includes BrainAGE. In 94% of evaluations, QReport outputs demonstrated Moderate-to-Complete agreement with visual assessment and were rated as useful in 82%.
CONCLUSION: We developed an MS QReport requiring only 3D T2-FLAIR, integrating validated quantification algorithms and incorporating BrainAGE within a clinically interpretable framework.