RT Journal Article
SR Electronic
T1 A large-scale multicentre cerebral diffusion tensor imaging study in amyotrophic lateral sclerosis
JF Journal of Neurology, Neurosurgery & Psychiatry
JO J Neurol Neurosurg Psychiatry
FD BMJ Publishing Group Ltd
SP 570
OP 579
DO 10.1136/jnnp-2015-311952
VO 87
IS 6
A1 Hans-Peter Müller
A1 Martin R Turner
A1 Julian Grosskreutz
A1 Sharon Abrahams
A1 Peter Bede
A1 Varan Govind
A1 Johannes Prudlo
A1 Albert C Ludolph
A1 Massimo Filippi
A1 Jan Kassubek
YR 2016
UL http://jnnp.bmj.com/content/87/6/570.abstract
AB 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.