TY - JOUR
T1 - MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies
AU - de Stefano, Nicola
AU - Battaglini, Marco
AU - Pareto, Deborah
AU - Cortese, Rosa
AU - Zhang, Jian
AU - Oesingmann, Niels
AU - Prados, Ferran
AU - Rocca, Maria A.
AU - Valsasina, Paola
AU - Vrenken, Hugo
AU - Gandini Wheeler-Kingshott, Claudia A. M.
AU - Filippi, Massimo
AU - Barkhof, Frederik
AU - Rovira, Àlex
N1 - Publisher Copyright: © 2022 The Author(s)
PY - 2022/1/1
Y1 - 2022/1/1
N2 - There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.
AB - There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resources.
KW - Harmonization
KW - MRI
KW - Multiple sclerosis
UR - http://www.scopus.com/inward/record.url?scp=85125497757&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.nicl.2022.102972
DO - https://doi.org/10.1016/j.nicl.2022.102972
M3 - Article
C2 - 35245791
SN - 2213-1582
VL - 34
JO - NeuroImage. Clinical
JF - NeuroImage. Clinical
M1 - 102972
ER -