Direct evidence of intra- and interhemispheric corticomotor network degeneration in amyotrophic lateral sclerosis: An automated MRI structural connectivity study
Highlights
► MRI reveals loss of intra- and interhemispheric white matter connectivity in ALS. ► MRI structural connectivity measures are highly reproducible. ► Motion artifact and physiological noise may compromise connectivity analyses.
Introduction
Amyotrophic Lateral Sclerosis (ALS) is a progressive disease that is traditionally associated with loss of upper and lower motor neurons (UMN and LMN, respectively). Patients with ALS are defined according to strict criteria that require abnormalities of UMN and LMN (Brooks et al., 2000), although patients who fulfil these criteria may show heterogeneity of clinical features (Kiernan et al., 2011). ALS is uniformly fatal with paralysis and death normally occurring within 3–5 years after onset of symptoms.
Although ALS was first described over 140 years ago, progress regarding our understanding of the aetiology is still limited with many proposed models of pathogenesis (Ilieva et al., 2009, Rothstein, 2009). However, it is recognised that ALS pathology in the brain is widespread and involves motor networks other than those comprising the primary corticospinal tracts (CST) (Eisen and Weber, 2001), as highlighted in recent neuroimaging reviews (Agosta et al., 2010a, Turner and Modo, 2010). Such information supports the concept of motor neuron degeneration being a progressive process that spreads contiguously through multiple corticomotor networks, which potentially explains the wide variation in clinical features for patients who present with mixed UMN and LMN signs (Ravits and La Spada, 2009). Central to these findings has been the use of diffusion tensor imaging (DTI), which enables the assessment of the integrity of white matter (WM) pathways by measuring the preferred direction of water diffusion along WM fibre tracts (Basser et al., 1994, Beaulieu, 2002).
With regard to analysis strategies, numerous studies have taken advantage of the ability to study WM tract degeneration using a voxelwise analysis of DTI-derived fractional anisotropy (FA) measures (Abe et al., 2004, Agosta et al., 2007, Ciccarelli et al., 2009, Filippini et al., 2010, Keller et al., 2011, Metwalli et al., 2010, Sage et al., 2007, Sage et al., 2009, Senda et al., 2011, Stanton et al., 2009). Quantitative FA measures are believed to reflect changes in myelination, fibre density and packing (Concha et al., 2010, Mädler et al., 2008). Alternative approaches have made use of diffusion tensor tractography (DTT) which enables the study of specific WM pathways associated with ALS neuropathology (Aoki et al., 2005, Agosta et al., 2010b, Blain et al., 2011 Hong et al., 2008, Sage et al., 2009, Sato et al., 2010, Senda et al., 2009, van der Graaff et al., 2011). A useful extension to these studies is the use of DTT, employing predefined cortical targets derived from structural MRI (sMRI) to investigate structural connectivity of corticomotor networks in ALS (Ciccarelli et al., 2006, Verstraete et al., 2010). Although these previous studies were limited to connectivity analyses of the primary motor cortex in ALS, the concept of using multiple cortical target regions has significant appeal as connections between various cortical and subcortical regions can be investigated in a completely automated fashion (Hagmann et al., 2008, Johansen-Berg and Rushworth, 2009).
An important issue that is rarely addressed when applying DTI in clinical populations is the effect of image artefacts, induced by head motion and physiological noise, on summary measures of WM integrity, such as FA. Well known sources of image artefact, such as those induced by eddy currents and susceptibility effects, can be reduced with appropriate acquisition and post processing techniques (Jones, 2010). However a recent study has highlighted the deleterious impact of subtle head movement and cardiac pulsatile motion on anisotropy indices (Walker et al., 2011). Voxels containing these artefacts can be identified (RESTORE, Chang et al., 2005), and replaced (Morris et al., 2011) within the processing pipeline. One would expect this problem to be common when scanning patients with neurodegenerative disease using DTI due to lack of head control.
The objective of this study was to investigate the integrity of the corticomotor pathways associated with the primary motor and somatosensory cortex in patients with sporadic ALS presenting with mixed UMN and LMN signs using a fully automated structural connectivity approach. Our specific hypothesis is that an analysis of intra- and interhemispheric structural connectivity, based on a measure of mean FA derived from all streamlines defining the WM connections associated with the precentral and postcentral gyri, will provide new insight into corticomotoneuron involvement in ALS. To achieve this goal, we have employed a strategy combining High Angular Resolution Diffusion Imaging (HARDI) with constrained spherical deconvolution which describes diffusion in complex WM networks using a fibre orientation distribution function (FOD) (Tournier et al., 2007). Whole brain probabilistic tractography was applied to define specific WM pathways connecting discrete corticomotor targets generated from anatomical parcellation of high-resolution sMRI of the brain (Pannek et al., 2010). A schematic diagram outlining our automated pipeline is provided in Fig. 1. Importantly, within this pipeline we have endeavoured to integrate strategies to reduce artefacts generated from head motion and physiological noise. To enable comparison with previous studies, we have also investigated a voxelwise analysis of FA maps using Tract Based Spatial Statistics (TBSS, Smith et al., 2006). Furthermore, to assist in the interpretation of results, the reproducibility of the FA encoded corticomotor connections involving the precentral and postcentral gyri was also evaluated in control participants.
Section snippets
Participants
Fifteen patients with probable or definite ALS as defined by the revised EL Escorial criteria (Brooks et al., 2000) were recruited into the study, see Table 1. These patients were all typical ALS with progressive muscular atrophy and primary lateral sclerosis variants excluded. All patients were referred from the multidisciplinary ALS clinical service at the Royal Brisbane and Women's Hospital and were clinically classified for the stage of disease using the Amyotrophic Lateral Sclerosis
Structural images
Cortical parcellation was performed on structural images with the Freesurfer image analysis suite (http://surfer.nmr.mgh.harvard.edu). Intensity inhomogeneity of the images was corrected (Sled et al., 1998) and non-brain tissue was removed using a hybrid watershed/surface deformation procedure (Fischl et al., 2004). The cerebral cortex was parcellated into 33 units per hemisphere based on gyral and sulcal structure (Desikan et al., 2006, Fischl et al., 2004) along with a mask delineating
Reproducibility of connectivity measures in control participants
The reproducibility over time of mean FA for each corticocortical or corticospinal connection for each of the precentral and postcentral gyri was assessed by evaluating the average absolute relative difference of this measure, as expressed by the following equation.where A is the mean FA for each connection from scans 1 and 2, respectively. We have used a similar approach to measure the reproducibility of quantitative average pathlength maps generated using whole brain
Results
Demographic and clinical summary measures for the 15 ALS patients are presented in Table 1. All patients had clinical signs of upper and lower motor neuron involvement. 3 patients had bulbar onset, 7 had upper limb onset and 5 had lower limb onset. There was no significant difference in mean age between the ALS and control participants (p < 0.14) and all participants were right handed. The gender ratio was similar for both groups. Results obtained for the voxelwise analysis of FA measures using
Discussion
The results of our voxelwise analysis of FA maps corroborates previous findings (Agosta et al., 2010a, Turner and Modo, 2010), showing motor neuron degeneration in multiple corticomotor networks in ALS, which potentially explains the wide variation in clinical features for patients who present with mixed UMN and LMN signs (Ravits and La Spada, 2009). However, a limitation of this approach is the difficulty of identifying which motor networks are primarily involved with ALS pathology. To
Acknowledgments
We wish to acknowledge the Motor Neuron Disease Research Institute of Australia for their funding support and the significant contribution by the late Dr Jonathan Chalk in the important planning stages of this project.
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