Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis

Name: 7T MRI Seminar: 7T Spinal Cord MRI: current landscape and feedback from the Marseille site
Start: 2025-03-20
End: 2025-03-20
Location: CHUV Radiology, room BH07 147 demo1 and online

AUTHORS: Ravano V., Andelova M., Piredda G.F., Sommer S., Caneschi S., Roccaro L., Krasensky J., Kudrna M., Uher T., Corredor-Jerez R. A., Disselhorst J. A., Maréchal B., Hilbert T., Thiran J.-P., Richiardi J., Horakova D., Vaneckova M., Kober T.

Journal of Neurology, 271(9): 5944-5957, 13 July 2024

ABSTRACT

Background and objectives

In multiple sclerosis (MS), slowly expanding lesions were shown to be associated with worse disability and prognosis. Their timely detection from cross-sectional data at early disease stages could be clinically relevant to inform treatment planning. Here, we propose to use multiparametric, quantitative MRI to allow a better cross-sectional characterization of lesions with different longitudinal phenotypes.

Methods

We analysed T1 and T2 relaxometry maps from a longitudinal cohort of MS patients. Lesions were classified as enlarging, shrinking, new or stable based on their longitudinal volumetric change using a newly developed automated technique. Voxelwise deviations were computed as z-scores by comparing individual patient data to T1, T2 and T2/T1 normative values from healthy subjects. We studied the distribution of microstructural properties inside lesions and within perilesional tissue.

Results and conclusions

Stable lesions exhibited the highest T1 and T2 z-scores in lesion tissue, while the lowest values were observed for new lesions. Shrinking lesions presented the highest T1 z-scores in the first perilesional ring while enlarging lesions showed the highest T2 z-scores in the same region. Finally, a classification model was trained to predict the longitudinal lesion type based on microstructural metrics and feature importance was assessed. Z-scores estimated in lesion and perilesional tissue from T1, T2 and T2/T1 quantitative maps carry discriminative and complementary information to classify longitudinal lesion phenotypes, hence suggesting that multiparametric MRI approaches are essential for a better understanding of the pathophysiological mechanisms underlying disease activity in MS lesions.