An automated quantitative report for multiple sclerosis using only 3D T2-fluid-attenuated inversion recovery MRI

AI Summary

Open-source QReport using only 3D T2-FLAIR integrates validated quantification algorithms and BrainAGE with multi-centre MS and healthy reference models.
Analysed 2516 cross-sectional scans from 14 centres, producing single-subject biomarkers contextualised against 5th, 50th and 95th percentile distributions.
Clinical evaluation: QReport matched visual assessment in 94% of evaluations and was judged useful by neuroradiologists in 82%.

AI Summary

We developed an open-source quantitative report (QReport) that integrates validated 3D T2-FLAIR quantification methods with multi-centre MS and healthy reference models, and presents outputs in a structured graphical report to support contextualised interpretation of clinically relevant biomarkers. 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).

Basic summary

Neuroradiology. 2026 Jun 6. doi: 10.1007/s00234-026-04060-2. Online ahead of print.

ABSTRACT

PURPOSE: Automated tools quantifying multiple sclerosis (MS) imaging biomarkers often require non-routine MRI sequences and lack MS reference data. We developed an open-source quantitative report (QReport) that integrates validated 3D T2-FLAIR quantification methods with multi-centre MS and healthy reference models, and presents outputs in a structured graphical report to support contextualised interpretation of clinically relevant biomarkers.

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.

PMID:42249985 | DOI:10.1007/s00234-026-04060-2

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