Direct evidence of intra- and interhemispheric corticomotor network degeneration in amyotrophic lateral sclerosis: an automated MRI structural connectivity study

Neuroimage. 2012 Feb 1;59(3):2661-9. doi: 10.1016/j.neuroimage.2011.08.054. Epub 2011 Aug 26.

Abstract

Although the pathogenesis of amyotrophic lateral sclerosis (ALS) is uncertain, there is mounting neuroimaging evidence to suggest a mechanism involving the degeneration of multiple white matter (WM) motor and extramotor neural networks. This insight has been achieved, in part, by using MRI Diffusion Tensor Imaging (DTI) and the voxelwise analysis of anisotropy indices, along with DTI tractography to determine which specific motor pathways are involved with ALS pathology. Automated MRI structural connectivity analyses, which probe WM connections linking various functionally discrete cortical regions, have the potential to provide novel information about degenerative processes within multiple white matter (WM) pathways. Our hypothesis is that measures of altered intra- and interhemispheric structural connectivity of the primary motor and somatosensory cortex will provide an improved assessment of corticomotor involvement in ALS. To test this hypothesis, we acquired High Angular Resolution Diffusion Imaging (HARDI) scans along with high resolution structural images (sMRI) on 15 patients with clinical evidence of upper and lower motor neuron involvement, and 20 matched control participants. Whole brain probabilistic tractography was applied to define specific WM pathways connecting discrete corticomotor targets generated from anatomical parcellation of sMRI of the brain. The integrity of these connections was interrogated by comparing the mean fractional anisotropy (FA) derived for each WM pathway. To assist in the interpretation of results, we measured the reproducibility of the FA summary measures over time (6months) in control participants. We also incorporated into our analysis pipeline the evaluation and replacement of outlier voxels due to head motion and physiological noise. When assessing corticomotor connectivity, we found a significant reduction in mean FA within a number of intra- and interhemispheric motor pathways in ALS patients. The abnormal intrahemispheric pathways include the corticospinal tracts involving the left and right precentral gyri (lh.preCG, rh.preCG) and brainstem (bs); right postcentral gyrus (rh.postCG) and bs; lh.preCG and left posterior cingulate gyrus (lh.PCG); rh.preCG and right posterior cingulate gyrus (rh.PCG); and the rh.preCG and right paracentral gyrus (rh.paraCG). The abnormal interhemispheric pathways included the lh.preCG and rh.preCG; lh.preCG and rh.paraCG; lh.preCG and right superior frontal gyrus (rh.supFG); lh.preCG and rh.postCG; rh.preCG and left paracentral gyrus (lh.paraCG); rh.preCG and left superior frontal gyrus (lh.supFG); and the rh.preCG and left caudal middle frontal gyrus (lh.caudMF). The reproducibility of the measurement of these pathways was high (variation less than 5%). Maps of the outlier rejection voxels, revealed clusters within the corpus callosum and corticospinal projections. This finding highlights the importance of correcting for motion artefacts and physiological noise when studying clinical populations. Our novel findings, many of which are consistent with known pathology, show extensive involvement and degeneration of multiple corticomotor pathways in patients with upper and lower motor neuron signs and provide support for the use of automated structural connectivity techniques for studying neurodegenerative disease processes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Amyotrophic Lateral Sclerosis / pathology*
  • Artifacts
  • Diffusion Tensor Imaging / methods*
  • Efferent Pathways / pathology
  • Efferent Pathways / physiology
  • Female
  • Functional Laterality / physiology
  • Head Movements / physiology
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging / methods
  • Male
  • Middle Aged
  • Models, Statistical
  • Nerve Degeneration / pathology*
  • Nerve Net / pathology*
  • Reproducibility of Results