Open AccessCorticospinal tract degeneration in ALS unmasked in T1‐weighted images using texture analysis
Author(s) -
Ishaque Abdullah,
Mah Dennell,
Seres Peter,
Luk Collin,
Johnston Wendy,
Chenji Sneha,
Beaulieu Christian,
Yang YeeHong,
Kalra Sanjay
Publication year - 2019
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.24437
Subject(s) - corticospinal tract , medicine , diffusion mri , voxel , magnetic resonance imaging , amyotrophic lateral sclerosis , nuclear medicine , internal capsule , upper motor neuron , radiology , pathology , white matter , disease
The purpose of this study was to investigate whether textures computed from T1‐weighted (T1W) images of the corticospinal tract (CST) in amyotrophic lateral sclerosis (ALS) are associated with degenerative changes evaluated by diffusion tensor imaging (DTI). Nineteen patients with ALS and 14 controls were prospectively recruited and underwent T1W and diffusion‐weighted magnetic resonance imaging. Three‐dimensional texture maps were computed from T1W images and correlated with the DTI metrics within the CST. Significantly correlated textures were selected and compared within the CST for group differences between patients and controls using voxel‐wise analysis. Textures were correlated with the patients' clinical upper motor neuron (UMN) signs and their diagnostic accuracy was evaluated. Voxel‐wise analysis of textures and their diagnostic performance were then assessed in an independent cohort with 26 patients and 13 controls. Results showed that textures autocorrelation , energy , and inverse difference normalized significantly correlated with DTI metrics ( p < .05) and these textures were selected for further analyses. The textures demonstrated significant voxel‐wise differences between patients and controls in the centrum semiovale and the posterior limb of the internal capsule bilaterally ( p < .05). Autocorrelation and energy significantly correlated with UMN burden in patients ( p < .05) and classified patients and controls with 97% accuracy (100% sensitivity, 92.9% specificity). In the independent cohort, the selected textures demonstrated similar regional differences between patients and controls and classified participants with 94.9% accuracy. These results provide evidence that T1‐based textures are associated with degenerative changes in the CST.