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Research paper
A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis
  1. Hans-Peter Müller1,
  2. Martin R Turner2,
  3. Julian Grosskreutz3,
  4. Sharon Abrahams4,
  5. Peter Bede5,
  6. Varan Govind6,
  7. Johannes Prudlo7,
  8. Albert C Ludolph1,
  9. Massimo Filippi8,
  10. Jan Kassubek1
  11. for The Neuroimaging Society in ALS (NiSALS) DTI Study Group
    1. 1Department of Neurology, University of Ulm, Ulm, Germany
    2. 2Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
    3. 3Hans-Berger Department of Neurology, Jena University Hospital, Jena, Germany
    4. 4Human Cognitive Neuroscience, Psychology–PPLS & Euan MacDonald Centre for MND Research & Centre for Cognitive Ageing and Epidemiology, University of Edinburgh, Edinburgh, UK
    5. 5Quantitative Neuroimaging Group, Academic Unit of Neurology, Trinity College Dublin, Dublin, Ireland
    6. 6Department of Radiology, University of Miami School of Medicine, Miami, Florida, USA
    7. 7Department of Neurology, University of Rostock and DZNE, Rostock, Germany
    8. 8Division of Neuroscience, Neuroimaging Research Unit, Institute of Experimental Neurology, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
    1. Correspondence to Professor Jan Kassubek, Department of Neurology, University of Ulm, Oberer Eselsberg 45, Ulm 89081, Germany; jan.kassubek{at}uni-ulm.de

    Abstract

    Objective Damage to the cerebral tissue structural connectivity associated with amyotrophic lateral sclerosis (ALS), which extends beyond the motor pathways, can be visualised by diffusion tensor imaging (DTI). The effective translation of DTI metrics as biomarker requires its application across multiple MRI scanners and patient cohorts. A multicentre study was undertaken to assess structural connectivity in ALS within a large sample size.

    Methods 442 DTI data sets from patients with ALS (N=253) and controls (N=189) were collected for this retrospective study, from eight international ALS-specialist clinic sites. Equipment and DTI protocols varied across the centres. Fractional anisotropy (FA) maps of the control participants were used to establish correction matrices to pool data, and correction algorithms were applied to the FA maps of the control and ALS patient groups.

    Results Analysis of data pooled from all centres, using whole-brain-based statistical analysis of FA maps, confirmed the most significant alterations in the corticospinal tracts, and captured additional significant white matter tract changes in the frontal lobe, brainstem and hippocampal regions of the ALS group that coincided with postmortem neuropathological stages. Stratification of the ALS group for disease severity (ALS functional rating scale) confirmed these findings.

    Interpretation This large-scale study overcomes the challenges associated with processing and analysis of multiplatform, multicentre DTI data, and effectively demonstrates the anatomical fingerprint patterns of changes in a DTI metric that reflect distinct ALS disease stages. This success paves the way for the use of DTI-based metrics as read-out in natural history, prognostic stratification and multisite disease-modifying studies in ALS.

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