Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis.

Area of Science:

• Neuroimaging
• Radiology
• Neurology

Background:

• Slowly expanding lesions in multiple sclerosis (MS) correlate with poorer outcomes.
• Early detection of lesion progression is crucial for effective MS management.
• Quantitative MRI offers potential for detailed lesion characterization.

Purpose of the Study:

• To characterize MS lesions with different longitudinal behaviors using multiparametric quantitative MRI.
• To assess microstructural properties within lesions and perilesional tissue.
• To develop a model for predicting longitudinal lesion phenotypes.

Main Methods:

• Analysis of T1 and T2 relaxometry maps in a longitudinal MS patient cohort.
• Automated classification of lesions into enlarging, shrinking, new, or stable types.
• Calculation of voxelwise z-scores comparing patient data to healthy normative values.
• Investigation of microstructural properties in lesion and perilesional areas.

Main Results:

• Stable lesions showed the highest T1 and T2 z-scores; new lesions had the lowest.
• Shrinking lesions had high T1 z-scores in the perilesional ring; enlarging lesions had high T2 z-scores.
• A classification model successfully predicted longitudinal lesion types using microstructural metrics.

Conclusions:

• Quantitative MRI metrics in lesion and perilesional tissue provide discriminative information for classifying MS lesion phenotypes.
• Multiparametric MRI is vital for understanding MS lesion pathophysiology and disease activity.
• This approach can improve the cross-sectional characterization of MS lesions.