MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies

Area of Science:

• Neuroimaging
• Biomarker Discovery
• Data Science

Background:

• Sharing harmonized data from large cooperative studies is essential for biomarker development.
• Multiple sclerosis (MS) research urgently needs to translate advanced MRI findings into clinical practice.
• Inconsistent MRI acquisition, analysis, and storage across sites introduce bias, hindering multicenter studies.

Purpose of the Study:

• To review the current state, recent advances, and future directions in harmonizing large-scale, multicenter MRI data for MS cohorts.
• To provide recommendations for standardizing MRI data management in MS research.
• To address the challenges and opportunities in managing large imaging datasets for personalized MS patient care.

Main Methods:

• Literature review of harmonization techniques for MRI data in MS.
• Analysis of current technical advancements in MRI acquisition and analysis.
• Discussion of data storage strategies for multicenter imaging studies.

Main Results:

• Significant efforts are underway to create harmonized MRI datasets for MS research.
• Technical advances are improving MRI data consistency across different sites.
• Standardized data management is identified as a key opportunity and challenge for future MS research.

Conclusions:

• Achieving harmonized MRI data requires ongoing research and specialized resources.
• Collective efforts are vital for personalized MS management and resource optimization.
• Standardized multicenter MRI data will accelerate biomarker discovery and clinical translation in MS.