Diffusion tensor imaging analysis of sequential spreading of disease in amyotrophic lateral sclerosis confirms patterns of TDP-43 pathology.

Diffusion tensor imaging can identify amyotrophic lateral sclerosis-associated patterns of brain alterations at the group level. Recently, a neuropathological staging system for amyotrophic lateral sclerosis has shown that amyotrophic lateral sclerosis may disseminate in a sequential regional pattern during four disease stages. The objective of the present study was to apply a new methodological diffusion tensor imaging-based approach to automatically analyse in vivo the fibre tracts that are prone to be involved at each neuropathological stage of amyotrophic lateral sclerosis. Two data samples, consisting of 130 diffusion tensor imaging data sets acquired at 1.5 T from 78 patients with amyotrophic lateral sclerosis and 52 control subjects; and 55 diffusion-tensor imaging data sets at 3.0 T from 33 patients with amyotrophic lateral sclerosis and 22 control subjects, were analysed by a tract of interest-based fibre tracking approach to analyse five tracts that become involved during the course of amyotrophic lateral sclerosis: the corticospinal tract (stage 1); the corticorubral and the corticopontine tracts (stage 2); the corticostriatal pathway (stage 3); the proximal portion of the perforant path (stage 4); and two reference pathways. The statistical analyses of tracts of interest showed differences between patients with amyotrophic lateral sclerosis and control subjects for all tracts. The significance level of the comparisons at the group level was lower, the higher the disease stage with corresponding involved fibre tracts. Both the clinical phenotype as assessed by the amyotrophic lateral sclerosis functional rating scale-revised and disease duration correlated significantly with the resulting staging scheme. In summary, the tract of interest-based technique allowed for individual analysis of predefined tract structures, thus making it possible to image in vivo the disease stages in amyotrophic lateral sclerosis. This approach can be used not only for individual clinical work-up purposes, but enlarges the spectrum of potential non-invasive surrogate markers as a neuroimaging-based read-out for amyotrophic lateral sclerosis studies within a clinical context.

[1]  G. Comi,et al.  Defining peripheral nervous system dysfunction in the SOD-1G93A transgenic rat model of amyotrophic lateral sclerosis. , 2014, Journal of neuropathology and experimental neurology.

[2]  John Q. Trojanowski,et al.  Amyotrophic lateral sclerosis—a model of corticofugal axonal spread , 2013, Nature Reviews Neurology.

[3]  A. Al-Chalabi,et al.  The epidemiology of ALS: a conspiracy of genes, environment and time , 2013, Nature Reviews Neurology.

[4]  O. Ciccarelli,et al.  Diagnostic accuracy of diffusion tensor imaging in amyotrophic lateral sclerosis: a systematic review and individual patient data meta-analysis. , 2013, Academic radiology.

[5]  D. Cleveland,et al.  Converging Mechanisms in ALS and FTD: Disrupted RNA and Protein Homeostasis , 2013, Neuron.

[6]  A. Bokde,et al.  Multiparametric MRI study of ALS stratified for the C9orf72 genotype , 2013, Neurology.

[7]  Murray Grossman,et al.  Stages of pTDP‐43 pathology in amyotrophic lateral sclerosis , 2013, Annals of neurology.

[8]  B. Avants,et al.  White matter imaging helps dissociate tau from TDP-43 in frontotemporal lobar degeneration , 2013, Journal of Neurology, Neurosurgery & Psychiatry.

[9]  Hideto Miwa,et al.  Ultrasonography of the diaphragm in amyotrophic lateral sclerosis: Clinical significance in assessment of respiratory functions , 2013, Amyotrophic lateral sclerosis & frontotemporal degeneration.

[10]  R. Dengler,et al.  Longitudinal diffusion tensor imaging in amyotrophic lateral sclerosis , 2012, BMC Neuroscience.

[11]  M. Sabatelli,et al.  Sural nerve pathology in ALS patients: a single-centre experience , 2012, Neurological Sciences.

[12]  M. Pomper,et al.  Diagnostic accuracy using diffusion tensor imaging in the diagnosis of ALS: a meta-analysis. , 2012, Academic radiology.

[13]  S. Pillen,et al.  Muscle ultrasonography: A diagnostic tool for amyotrophic lateral sclerosis , 2012, Clinical Neurophysiology.

[14]  J. Gee,et al.  White matter imaging contributes to the multimodal diagnosis of frontotemporal lobar degeneration , 2012, Neurology.

[15]  H. Huppertz,et al.  Neuroanatomical patterns of cerebral white matter involvement in different motor neuron diseases as studied by diffusion tensor imaging analysis , 2012, Amyotrophic lateral sclerosis : official publication of the World Federation of Neurology Research Group on Motor Neuron Diseases.

[16]  John L. Robinson,et al.  Pattern of ubiquilin pathology in ALS and FTLD indicates presence of C9ORF72 hexanucleotide expansion , 2012, Acta Neuropathologica.

[17]  Jan Kassubek,et al.  Neuroimaging of motor neuron diseases , 2012, Therapeutic advances in neurological disorders.

[18]  J. Trojanowski,et al.  Gains or losses: molecular mechanisms of TDP43-mediated neurodegeneration , 2011, Nature Reviews Neuroscience.

[19]  S. Kuwabara,et al.  Ultrasonographic detection of fasciculations markedly increases diagnostic sensitivity of ALS , 2011, Neurology.

[20]  F. Walker,et al.  Peripheral nerve and muscle ultrasound in amyotrophic lateral sclerosis , 2011, Muscle & nerve.

[21]  M. Filippi,et al.  The Topography of Brain Microstructural Damage in Amyotrophic Lateral Sclerosis Assessed Using Diffusion Tensor MR Imaging , 2011, American Journal of Neuroradiology.

[22]  A. Chiò,et al.  Phenotypic heterogeneity of amyotrophic lateral sclerosis: a population based study , 2011, Journal of Neurology, Neurosurgery & Psychiatry.

[23]  O. Hardiman,et al.  Amyotrophic lateral sclerosis , 2011, The Lancet.

[24]  S. Pillen,et al.  Muscle changes in amyotrophic lateral sclerosis: A longitudinal ultrasonography study , 2011, Clinical Neurophysiology.

[25]  Michel Modo,et al.  Advances in the application of MRI to amyotrophic lateral sclerosis. , 2010, Expert opinion on medical diagnostics.

[26]  N Filippini,et al.  Corpus callosum involvement is a consistent feature of amyotrophic lateral sclerosis , 2010, Neurology.

[27]  A. Peltier,et al.  Muscle ultrasound quantifies the rate of reduction of muscle thickness in amyotrophic lateral sclerosis , 2010, Muscle & nerve.

[28]  M. Filippi,et al.  Assessment of White Matter Tract Damage in Patients with Amyotrophic Lateral Sclerosis: A Diffusion Tensor MR Imaging Tractography Study , 2010, American Journal of Neuroradiology.

[29]  N. Young,et al.  Gadolinium enhancement of the lumbar roots in a case of ALS , 2010, Amyotrophic lateral sclerosis : official publication of the World Federation of Neurology Research Group on Motor Neuron Diseases.

[30]  Jan Kassubek,et al.  Intersubject variability in the analysis of diffusion tensor images at the group level: fractional anisotropy mapping and fiber tracking techniques. , 2009, Magnetic resonance imaging.

[31]  J. Trojanowski,et al.  Evidence of multisystem disorder in whole-brain map of pathological TDP-43 in amyotrophic lateral sclerosis. , 2008, Archives of neurology.

[32]  S. Pillen,et al.  Quantitative muscle ultrasonography in amyotrophic lateral sclerosis. , 2008, Ultrasound in medicine & biology.

[33]  Jan Kassubek,et al.  Diffusion tensor imaging and tractwise fractional anisotropy statistics: quantitative analysis in white matter pathology , 2007, Biomedical engineering online.

[34]  A Unrath,et al.  Preservation of diffusion tensor properties during spatial normalization by use of tensor imaging and fibre tracking on a normal brain database , 2007, Physics in medicine and biology.

[35]  Daniel Rueckert,et al.  Tract-based spatial statistics: Voxelwise analysis of multi-subject diffusion data , 2006, NeuroImage.

[36]  H. Mitsumoto,et al.  The natural history of primary lateral sclerosis , 2006, Neurology.

[37]  Osamu Abe,et al.  The optimal trackability threshold of fractional anisotropy for diffusion tensor tractography of the corticospinal tract. , 2004, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[38]  Shu-Wei Sun,et al.  Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia , 2003, NeuroImage.

[39]  I. Johnsrude,et al.  The problem of functional localization in the human brain , 2002, Nature Reviews Neuroscience.

[40]  H. Moser,et al.  Imaging cortical association tracts in the human brain using diffusion‐tensor‐based axonal tracking , 2002, Magnetic resonance in medicine.

[41]  C. Reimers,et al.  Muskelsonographie bei neuromuskulären Erkrankungen , 2002, Der Orthopäde.

[42]  D. Le Bihan,et al.  Diffusion tensor imaging: Concepts and applications , 2001, Journal of magnetic resonance imaging : JMRI.

[43]  C. Reimers,et al.  Die Rolle bildgebender Verfahren bei neuromuskulären Erkrankungen , 2000 .

[44]  M. Swash,et al.  El Escorial revisited: Revised criteria for the diagnosis of amyotrophic lateral sclerosis , 2000, Amyotrophic lateral sclerosis and other motor neuron disorders : official publication of the World Federation of Neurology, Research Group on Motor Neuron Diseases.

[45]  J. Cedarbaum,et al.  The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function , 1999, Journal of the Neurological Sciences.

[46]  U. Ziemann,et al.  Fasciculations: Clinical, electromyographic, and ultrasonographic assessment , 1996, Journal of Neurology.

[47]  Wolfgang Müller-Felber,et al.  Muscular ultrasound in idiopathic inflammatory myopathies of adults , 1993, Journal of the Neurological Sciences.

[48]  B. Patten,et al.  Amyotrophic lateral sclerosis: Abnormalities of the tongue on magnetic resonance imaging , 1989, Annals of neurology.

[49]  A. Ludolph,et al.  Amyotrophic lateral sclerosis. , 2012, Current opinion in neurology.

[50]  清野 智恵子,et al.  Onset and spreading patterns of lower motor neuron involvements predict survival in sporadic amyotrophic lateral sclerosis , 2012 .