Background In multiple sclerosis (MS), knowledge about how spinal cord abnormalities translate into clinical manifestations is incomplete. Comprehensive, multiparametric MRI studies are useful in this perspective, but studies for the spinal cord are lacking. Purpose To identify MRI features of cervical spinal cord damage that could help predict disability and disease course in MS by using a comprehensive, multiparametric MRI approach. Materials and Methods In this retrospective hypothesis-driven analysis of longitudinally acquired data between June 2017 and April 2019, 120 patients with MS (58 with relapsing-remitting MS [RRMS] and 62 with progressive MS [PMS]) and 30 age- and sex-matched healthy control participants underwent 3.0-T MRI of the brain and cervical spinal cord. Cervical spinal cord MRI was performed with three-dimensional (3D) T1-weighted, T2-weighted, and diffusion-weighted imaging; sagittal two-dimensional (2D) short inversion time inversion-recovery imaging; and axial 2D phase-sensitive inversion-recovery imaging at the C2-C3 level. Brain MRI was performed with 3D T1-weighted, fluid-attenuated inversion-recovery and T2-weighted sequences. Associations between MRI variables and disability were explored with age-, sex- and phenotype-adjusted linear models. Results In patients with MS, multivariable analysis identified phenotype, cervical spinal cord gray matter (GM) cross-sectional area (CSA), lateral funiculi fractional anisotropy (FA), and brain GM volume as independent predictors of Expanded Disability Status Scale (EDSS) score (R2 = 0.86). The independent predictors of EDSS score in RRMS were lateral funiculi FA, normalized brain volume, and cervical spinal cord GM T2 lesion volume (R2 = 0.51). The independent predictors of EDSS score in PMS were cervical spinal cord GM CSA and brain GM volume (R2 = 0.44). Logistic regression analysis identified cervical spinal cord GM CSA and T2 lesion volume as independent predictors of phenotype (area under the receiver operating characteristic curve = 0.95). An optimal cervical spinal cord GM CSA cut-off value of 11.1 mm2 was found to enable accurate differentiation of patients with PMS, having values below the threshold, from those with RRMS (sensitivity = 90% [56 of 62], specificity = 91% [53 of 58]). Conclusion Cervical spinal cord MRI involvement has a central role in explaining disability in multiple sclerosis (MS): Lesion-induced damage in the lateral funiculi and gray matter (GM) in relapsing-remitting MS and GM atrophy in patients with progressive MS are the most relevant variables. Cervical spinal cord GM atrophy is an accurate predictor of progressive phenotype. Cervical spinal cord GM lesions may subsequently cause GM atrophy, which may contribute to evolution to PMS. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Zivadinov and Bergsland in this issue.
Clinical Relevance of Multiparametric MRI Assessment of Cervical Cord Damage in Multiple Sclerosis / Bonacchi, R.; Pagani, E.; Meani, A.; Cacciaguerra, L.; Preziosa, P.; De Meo, E.; Filippi, M.; Rocca, M. A.. - In: RADIOLOGY. - ISSN 1527-1315. - 296:3(2020), pp. 605-615. [10.1148/radiol.2020200430]
Clinical Relevance of Multiparametric MRI Assessment of Cervical Cord Damage in Multiple Sclerosis
Bonacchi R.;Cacciaguerra L.;Preziosa P.;De Meo E.;Filippi M.;Rocca M. A.
2020-01-01
Abstract
Background In multiple sclerosis (MS), knowledge about how spinal cord abnormalities translate into clinical manifestations is incomplete. Comprehensive, multiparametric MRI studies are useful in this perspective, but studies for the spinal cord are lacking. Purpose To identify MRI features of cervical spinal cord damage that could help predict disability and disease course in MS by using a comprehensive, multiparametric MRI approach. Materials and Methods In this retrospective hypothesis-driven analysis of longitudinally acquired data between June 2017 and April 2019, 120 patients with MS (58 with relapsing-remitting MS [RRMS] and 62 with progressive MS [PMS]) and 30 age- and sex-matched healthy control participants underwent 3.0-T MRI of the brain and cervical spinal cord. Cervical spinal cord MRI was performed with three-dimensional (3D) T1-weighted, T2-weighted, and diffusion-weighted imaging; sagittal two-dimensional (2D) short inversion time inversion-recovery imaging; and axial 2D phase-sensitive inversion-recovery imaging at the C2-C3 level. Brain MRI was performed with 3D T1-weighted, fluid-attenuated inversion-recovery and T2-weighted sequences. Associations between MRI variables and disability were explored with age-, sex- and phenotype-adjusted linear models. Results In patients with MS, multivariable analysis identified phenotype, cervical spinal cord gray matter (GM) cross-sectional area (CSA), lateral funiculi fractional anisotropy (FA), and brain GM volume as independent predictors of Expanded Disability Status Scale (EDSS) score (R2 = 0.86). The independent predictors of EDSS score in RRMS were lateral funiculi FA, normalized brain volume, and cervical spinal cord GM T2 lesion volume (R2 = 0.51). The independent predictors of EDSS score in PMS were cervical spinal cord GM CSA and brain GM volume (R2 = 0.44). Logistic regression analysis identified cervical spinal cord GM CSA and T2 lesion volume as independent predictors of phenotype (area under the receiver operating characteristic curve = 0.95). An optimal cervical spinal cord GM CSA cut-off value of 11.1 mm2 was found to enable accurate differentiation of patients with PMS, having values below the threshold, from those with RRMS (sensitivity = 90% [56 of 62], specificity = 91% [53 of 58]). Conclusion Cervical spinal cord MRI involvement has a central role in explaining disability in multiple sclerosis (MS): Lesion-induced damage in the lateral funiculi and gray matter (GM) in relapsing-remitting MS and GM atrophy in patients with progressive MS are the most relevant variables. Cervical spinal cord GM atrophy is an accurate predictor of progressive phenotype. Cervical spinal cord GM lesions may subsequently cause GM atrophy, which may contribute to evolution to PMS. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Zivadinov and Bergsland in this issue.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.