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Quantifying chronic lesion expansion in multiple sclerosis: Exploring imaging markers for longitudinal assessment
Samuel Klistorner1, Michael H Barnett2, John Parratt3
1Save Sight Institute, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia.
Multiple Sclerosis and Related Disorders
|June 2, 2024
Summary
Central brain atrophy and mean diffusivity changes in chronic multiple sclerosis (MS) lesions can accurately predict future lesion expansion over four years. These imaging markers offer a reliable method for assessing MS disease progression without requiring longitudinal lesion segmentation.
Area of Science:
- Neuroimaging
- Radiology
- Neurology
Background:
- Chronic lesion expansion in multiple sclerosis (MS) significantly impacts disease progression.
- Quantifying slow lesion volume changes in MS is challenging due to the need for longitudinal segmentation.
Purpose of the Study:
- To estimate chronic lesion expansion in MS using imaging markers that bypass longitudinal segmentation.
- To identify reliable imaging markers for predicting future lesion expansion over a 4-year period.
Main Methods:
- Analysis of pre- and post-gadolinium 3D-T1, 3D FLAIR, and diffusion tensor images from 42 MS patients.
- Evaluation of lesion expansion (PVSI) using central brain atrophy (CBA) and changes in T1 intensity and mean diffusivity (MD) within chronic lesions over 2 years.
Main Results:
- CBA after 2 years accurately estimated 4-year lesion expansion (r=0.82, AUC=0.92).
- Increased MD within chronic lesions over 2 years strongly correlated with future expansion (r=0.77, AUC=0.87).
- Changes in T1 hypointensity were poor predictors of future lesion expansion.
Conclusions:
- Central brain atrophy (CBA) measured over 2 years reliably estimates chronic lesion expansion in MS.
- Mean diffusivity (MD) changes within chronic lesions also serve as a sensitive, albeit lesser, predictor of expansion.
- These markers provide a sensitive and reliable method for assessing chronic lesion expansion without longitudinal segmentation.
