Imaging biomarkers for early multiple system atrophy


      • Cerebellar white matter, brainstem, and pons from MRI can separate early MSA-C from controls.
      • Cerebellum white matter diffusion changes may capture early disease in MSA.
      • Changes in putamen and striatum were not useful for tracking longitudinal disease progression.
      • Brainstem and cerebellar pathways can be potential surrogate markers for future MSA clinical trials.



      To systematically evaluate structural MRI and diffusion MRI features for cross-sectional discrimination and tracking of longitudinal disease progression in early multiple system atrophy (MSA).


      In a prospective, longitudinal study of synucleinopathies with imaging on 14 controls and 29 MSA patients recruited at an early disease stage (15 predominant cerebellar ataxia subtype or MSA-C and 14 predominant parkinsonism subtype or MSA-P), we computed regional morphometric and diffusion MRI features. We identified morphometric features by ranking them based on their ability to distinguish MSA-C from controls and MSA-P from controls and evaluated diffusion changes in these regions. For the top performing regions, we evaluated their utility for tracking longitudinal disease progression using imaging from 12-month follow-up and computed sample size estimates for a hypothetical clinical trial in MSA. We also computed these selected morphometric features in an independent validation dataset.


      We found that morphometric changes in the cerebellar white matter, brainstem, and pons can separate early MSA-C patients from controls both cross-sectionally and longitudinally (p < 0.01). The putamen and striatum, though useful for separating early MSA-P patients from control subjects at baseline, were not useful for tracking MSA disease progression. Cerebellum white matter diffusion changes aided in capturing early disease related degeneration in MSA.


      Regardless of clinically predominant features at the time of MSA assessment, brainstem and cerebellar pathways progressively deteriorate with disease progression. Quantitative measurements of these regions are promising biomarkers for MSA diagnosis in early disease stage and potential surrogate markers for future MSA clinical trials.



      MSA (Multiple System Atrophy), MRI (Magnetic Resonance Imaging)
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        • Gilman S.
        • Wenning G.K.
        • Low P.A.
        • et al.
        Second consensus statement on the diagnosis of multiple system atrophy.
        Neurology. Aug 26 2008; 71: 670-676
        • Low P.A.
        • Reich S.G.
        • Jankovic J.
        • et al.
        Natural history of multiple system atrophy in the USA: a prospective cohort study.
        Lancet Neurol. Jul 2015; 14: 710-719
        • Poewe W.
        • Seppi K.
        • Fitzer-Attas C.J.
        • et al.
        Efficacy of rasagiline in patients with the parkinsonian variant of multiple system atrophy: a randomised, placebo-controlled trial.
        Lancet Neurol. Feb 2015; 14: 145-152
        • Low P.A.
        • Robertson D.
        • Gilman S.
        • et al.
        Efficacy and safety of rifampicin for multiple system atrophy: a randomised, double-blind, placebo-controlled trial.
        Lancet Neurol. Mar 2014; 13: 268-275
        • Singer W.
        • Low P.A.
        Optimizing clinical trial design for multiple system atrophy: lessons from the rifampicin study.
        Clin. Auton. Res. Feb 2015; 25: 47-52
        • Brenneis C.
        • Seppi K.
        • Schocke M.F.
        • et al.
        Voxel-based morphometry detects cortical atrophy in the Parkinson variant of multiple system atrophy.
        Mov. Disord. Oct 2003; 18: 1132-1138
        • Seppi K.
        • Yekhlef F.
        • Diem A.
        • et al.
        Progression of parkinsonism in multiple system atrophy.
        J. Neurol. Jan 2005; 252: 91-96
        • Krismer F.
        • Seppi K.
        • Göbel G.
        • et al.
        Morphometric MRI profiles of multiple system atrophy variants and implications for differential diagnosis.
        Mov. Disord. Jul 2019; 34: 1041-1048
        • Pellecchia M.T.
        • Barone P.
        • Vicidomini C.
        • et al.
        Progression of striatal and extrastriatal degeneration in multiple system atrophy: a longitudinal diffusion-weighted MR study.
        Mov Disord. Jun 2011; 26: 1303-1309
        • Chougar L.
        • Faouzi J.
        • Pyatigorskaya N.
        • et al.
        Automated categorization of parkinsonian syndromes using magnetic resonance imaging in a clinical setting.
        Mov Disord. Feb 2021; 36: 460-470
        • Archer D.B.
        • Bricker J.T.
        • Chu W.T.
        • et al.
        Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study.
        Lancet Digit Health. Sep 2019; 1: e222-e231
        • Singer W.
        • Dietz A.B.
        • Zeller A.D.
        • et al.
        Intrathecal administration of autologous mesenchymal stem cells in multiple system atrophy.
        Neurology. Jul 2 2019; 93: e77-e87
        • Levin J.
        • Maaß S.
        • Schuberth M.
        • et al.
        Safety and efficacy of epigallocatechin gallate in multiple system atrophy (PROMESA): a randomised, double-blind, placebo-controlled trial.
        Lancet Neurol. Aug 2019; 18: 724-735
        • Wenning G.K.
        • Tison F.
        • Seppi K.
        • et al.
        Development and validation of the unified multiple system Atrophy rating scale (UMSARS).
        Mov. Disord. Dec 2004; 19: 1391-1402
        • Low P.A.
        Composite autonomic scoring scale for laboratory quantification of generalized autonomic failure.
        Mayo Clin. Proc. Aug 1993; 68: 748-752
        • Lipp A.
        • Sandroni P.
        • Ahlskog J.E.
        • et al.
        Prospective differentiation of multiple system atrophy from Parkinson disease, with and without autonomic failure.
        Arch Neurol. Jun 2009; 66: 742-750
        • Caruyer E.
        • Lenglet C.
        • Sapiro G.
        • Deriche R.
        Design of multishell sampling schemes with uniform coverage in diffusion MRI.
        Magn. Reson. Med. Jun 2013; 69: 1534-1540
        • Desikan R.S.
        • Segonne F.
        • Fischl B.
        • Quinne B.T.
        • Dickerson B.C.
        • et al.
        A Computer Generated Labeling System for Subdividing the Human Cerebral Cortex on MRI Scans into Gyral Based Regions of Interest.
        31(3). NeuroImage, Jul 2005 (968-980, doi:10.1016/j.neuroimage.2006.01.021)
        • Schwarz C.G.
        • Gunter J.L.
        • Wiste H.J.
        • et al.
        A large-scale comparison of cortical thickness and volume methods for measuring Alzheimer's disease severity.
        Neuroimage: Clinic. 2016; 11: 802-812
        • Reid R.I.
        • Schwarz C.G.
        • et al.
        Diffusion Specific Segmentation: Skull Stripping with Diffusion MRI Data Alone. Computational Diffusion MRI Mathematics and Visualization.
        Springer, Cham2018
        • Veraart J.
        • Novikov D.S.
        • Christiaens D.
        • Ades-Aron B.
        • Sijbers J.
        • Fieremans E.
        Denoising of diffusion MRI using random matrix theory.
        NeuroImage. Nov 15 2016; : 394-406
        • Kellner E.
        • Dhital B.
        • Kiselev V.G.
        • Reisert M.
        Gibbs-ringing artifact removal based on local subvoxel-shifts.
        Magnet. Reson. Med. Nov 2016; 76: 1574-1581
        • Koay C.G.
        • Ozarslan E.
        • Basser P.J.
        A signal transformational framework for breaking the noise floor and its applications in MRI.
        J. Magn. Reson. Apr 2009; 197: 108-119
        • Garyfallidis E.
        • Brett M.
        • Amirbekian B.
        • et al.
        Dipy, a library for the analysis of diffusion MRI data.
        Front. Neuroinf. 2014; 8: 8
        • Avants B.B.
        • Tustison N.J.
        • Song G.
        • Cook P.A.
        • Klein A.
        • Gee J.C.
        A reproducible evaluation of ANTs similarity metric performance in brain image registration.
        NeuroImage. Feb 1 2011; 54: 2033-2044
        • Oishi K.
        • Faria A.
        • Jiang H.
        • et al.
        Atlas-based whole brain white matter analysis using large deformation diffeomorphic metric mapping: application to normal elderly and Alzheimer's disease participants.
        NeuroImage. Jun 2009; 46: 486-499
        • Lin J.
        • Xu X.
        • Hou Y.
        • Yang J.
        • Shang H.
        Voxel-based meta-analysis of gray matter abnormalities in multiple system Atrophy.
        Front. Aging Neurosci. 2020; 12591666
        • Meissner W.G.
        • Fernagut P.O.
        • Dehay B.
        • et al.
        Multiple system Atrophy: recent developments and future perspectives.
        Mov. Disord. Nov 2019; 34: 1629-1642
        • Benarroch E.E.
        Brainstem in multiple system atrophy: clinicopathological correlations.
        Cell. Mol. Neurobiol. 2003/10//2003; 23: 519-526
        • Poewe W.
        • Seppi K.
        • Fitzer-Attas C.J.
        • et al.
        Efficacy of rasagiline in patients with the parkinsonian variant of multiple system atrophy: a randomised, placebo-controlled trial.
        Lancet Neurol. Feb 2015; 14: 145-152
        • Koga S.
        • Aoki N.
        • Uitti R.J.
        • et al.
        When DLB, PD, and PSP masquerade as MSA: an autopsy study of 134 patients.
        Neurology. Aug 4 2015; 85: 404-412
        • Brooks D.J.
        • Seppi K.
        Proposed neuroimaging criteria for the diagnosis of multiple system atrophy.
        Mov. Disord. May 15 2009; 24: 949-964
        • Meijer F.J.
        • Aerts M.B.
        • Abdo W.F.
        • et al.
        Contribution of routine brain MRI to the differential diagnosis of parkinsonism: a 3-year prospective follow-up study.
        J. Neurol. May 2012; 259: 929-935
        • Huppertz H.J.
        • Möller L.
        • Südmeyer M.
        • et al.
        Differentiation of neurodegenerative parkinsonian syndromes by volumetric magnetic resonance imaging analysis and support vector machine classification.
        Mov. Disord. Oct 2016; 31: 1506-1517
        • Krismer F.
        • Seppi K.
        • Wenning G.K.
        • et al.
        Abnormalities on structural MRI associate with faster disease progression in multiple system atrophy.
        Parkinsonism Relat. Disord. Jan 2019; 58: 23-27
        • Planetta P.J.
        • Ofori E.
        • Pasternak O.
        • et al.
        Free-water imaging in Parkinson's disease and atypical parkinsonism.
        Brain J. Neurol. Feb 2016; 139: 495-508
        • Worker A.
        • Blain C.
        • Jarosz J.
        • et al.
        Cortical thickness, surface area and volume measures in Parkinson's disease, multiple system atrophy and progressive supranuclear palsy.
        PLoS One. 2014; 9e114167
        • Worker A.
        • Blain C.
        • Jarosz J.
        • et al.
        Diffusion tensor imaging of Parkinson's disease, multiple system atrophy and progressive supranuclear palsy: a tract-based spatial statistics study.
        PLoS One. 2014; 9e112638
        • Yang H.
        • Wang X.
        • Liao W.
        • Zhou G.
        • Li L.
        • Ouyang L.
        Application of diffusion tensor imaging in multiple system atrophy: the involvement of pontine transverse and longitudinal fibers.
        Int J Neurosci. Jan 2015; 125: 18-24