Quantitative susceptibility mapping of the cervical spinal cord for MS monitoring

Abstract

International audienceObjectives:Quantitative susceptibility mapping (QSM) [1] is a promising MRI technique that can be used in multiple sclerosis (MS) to characterize lesions and serve as a biomarker of chronic inflammation in white matter lesions. While QSM has been widely used for brain applications, its feasibility in the spinal cord (SC) has not been demonstrated. Yet, SC lesions are seen in up to 80% of people with MS and have a strong prognostic value. Moreover, a histopathologic study [2] found a high prevalence of 41% chronic active SC lesions among lesions of 119 MS patients. Thus, a QSM tool capable of quantifying the inflammatory status of SC lesions could be of great value in better understanding MS and tailoring treatments.Materials and Methods:The presence of fat in the spinal cord prompted us to use a water-fat separation IDEAL technique [3] (implemented in python) to estimate the total field before computing the QSM map using the algorithm MEDI [1] (available in the open-source software Sepia [4]). For initialization of IDEAL, we designed a 2-sequence MRI protocol that provides in-phase (IP) and out-of-phase (OOP) SC QSM data. Images from 8 healthy controls (HC) and 5 MS patients were acquired on a 3T Prisma scanner (clinical trials ID: NCT05622643; NCT05107232) in the axial plane between C3 and C5 with high spatial resolution (0.4x0.4x1mm3, TE1 IP 2.64ms, TE1 OOP 3.69ms, ΔTE=2.46ms, TR 33ms, 12 echoes each).Results:We obtain encouraging SC QSM maps where it is possible to distinguish hyperintense gray matter and QSM signal variations in lesions, as shown below in a HC (fig. 1) and an MS patient (fig2.). The T2* axial patient imagewas used to segment lesions (in green on QSM).Conclusion:We showed that SC QSM with high spatial resolution is feasible and allows to detect QSM signal variations in lesions. Future prospects include increasing the number of patients, classifying SC lesions according to QSM maps, and a reproducibility study.References :[1] Wang Y et al. MRM 2015;[2] Waldman A, et al. Acta Neuropathol 2024;[3] Guo et al. NMR Biomed 2019;[4] Chan et al. Neuroimage, 2021.Acknowledgments:This work is supported by the RHU PRIMUS, FLI RE4 QSM-SPICO and France Sclérose en Plaques