Quantifying changes on susceptibility weighted images in amyotrophic lateral sclerosis using MRI texture analysis

References

• Su X, Clardy S, Stephens H, Simmons Z, Connor J. Serum ferritin is elevated in amyotrophic lateral sclerosis patients. Amyotroph Lateral Scler Frontotemporal Degener. 2015;16:102–7.
   Google Scholar
• Kwan J, Jeong S, Van Gelderen P, Deng H, Quezado M, Danielian L, et al. Iron accumulation in deep cortical layers accounts for MRI signal abnormalities in ALS: correlating 7 tesla MRI and pathology. PLoS One. 2012;7:e35241.
   Google Scholar
• Halon M, Kaczor J, Ziolkowski W, Flis D, Borkowska A, Popowska U, et al. Changes in skeletal muscle iron metabolism outpace amyotrophic lateral sclerosis onset in transgenic rats bearing the G93A hmSOD1 gene mutation. Free Radic Res. 2014;48:1363–70.
   Google Scholar
• Lee JK, Shin JH, Gwag BJ, Choi E-J. Iron accumulation promotes TACE-mediated TNF-α secretion and neurodegeneration in a mouse model of ALS. Neurobiol Dis. 2015;80:63–9.
   Google Scholar
• Haacke EM, Xu Y, Cheng Y-C, Reichenbach JR. Susceptibility weighted imaging (SWI). Magn Reson Med. 2004;52:612–8.
   Google Scholar
• Liu C, Li W, Tong K, Yeom K, Kuzminski S. Susceptibility-weighted imaging and quantitative susceptibility mapping in the brain. J Magn Reson Imaging. 2015;42:23–41.
   Google Scholar
• Prell T, Hartung V, Tietz F, Penzlin S, Ilse B, Schweser F, et al. Susceptibility-weighted imaging provides insight into white matter damage in amyotrophic lateral sclerosis. PLoS One. 2015;10:e0131114.
   Google Scholar
• Adachi Y, Sato N, Saito Y, Kimura Y, Nakata Y, Ito K, et al. Usefulness of SWI for the detection of iron in the motor cortex in amyotrophic lateral sclerosis. J Neuroimaging. 2015;25:443–51.
   Google Scholar
• Endo H, Sekiguchi K, Shimada H, Ueda T, Kowa H, Kanda F, et al. Low signal intensity in motor cortex on susceptibility-weighted MR imaging is correlated with clinical signs of amyotrophic lateral sclerosis: a pilot study. J Neurol. 2018;265:552–61.
   Google Scholar
• Acosta-Cabronero J, Machts J, Schreiber S, Abdulla S, Kollewe K, Petri S, et al. Quantitative susceptibility MRI to detect brain iron in amyotrophic lateral sclerosis. Radiology. 2018;289:195–203.
   Google Scholar
• Weidman EK, Schweitzer AD, Niogi SN, Brady EJ, Starikov A, Askin G, et al. Diffusion tensor imaging and quantitative susceptibility mapping as diagnostic tools for motor neuron disorders. Clin Imaging. 2019;53:6–11.
   Google Scholar
• Kassner A, Thornhill R. Texture analysis: a review of neurologic MR imaging applications. AJNR Am J Neuroradiol. 2010;31:809–16.
   Google Scholar
• Haralick R, Shanmugam K, Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybern. 1973;3:610–21.
   Google Scholar
• Castellano G, Bonilha L, Li L, Cendes F. Texture analysis of medical images. Clin Radiol. 2004;59:1061–9.
   Google Scholar
• Maani R, Yang Y-H, Emery D, Kalra S. Cerebral degeneration in amyotrophic lateral sclerosis revealed by 3-dimensional texture analysis. Front Neurosci. 2016;10:120.
   Google Scholar
• Ishaque A, Mah D, Seres P, Luk C, Johnston W, Chenji S, et al. Corticospinal tract degeneration in ALS unmasked in T1-weighted images using texture analysis. Hum Brain Mapp. 2019; 40:1174–83
   Google Scholar
• Ishaque A, Mah D, Seres P, Luk C, Eurich D, Johnston W, et al. Evaluating the cerebral correlates of survival in amyotrophic lateral sclerosis. Ann Clin Transl Neurol. 2018;5: 1350–61.
   Google Scholar
• Albuquerque M, Anjos L, Andrade H, Oliveira M, Castellano G, Rezende T, et al. MRI texture analysis reveals deep gray nuclei damage in amyotrophic lateral sclerosis. J Neuroimaging. 2015;26:201–6.
   Google Scholar
• Maani R, Yang Y, Kalra S. Voxel-based texture analysis of the brain. PloS One. 2015;10:e0117759.
   Google Scholar
• Luk C, Ishaque A, Khan M, Ta D, Mah D, Yang YH, et al. Alzheimer’s disease: 3-dimensional MRI-texture for prediction of conversion from mild cognitive impairment. Neurology 2018;10:755–63.
   Google Scholar
• Sørensen L, Igel C, Hansen NL, Osler M, Lauritzen M, Rostrup E, et al. Early detection of Alzheimers disease using MRI hippocampal texture. Hum Brain Mapp. 2016;37:1148–61.
   Google Scholar
• Zhang J, Yu C, Jiang G, Liu W, Tong L. 3D texture analysis on MRI images of Alzheimer's disease. Brain Imaging Behav. 2012;6:61–9.
   Google Scholar
• Michoux N, Guillet A, Rommel D, Mazzamuto G, Sindic C, Duprez T. Texture analysis of t2-weighted MR images to assess acute inflammation in brain MS lesions. PLoS One. 2015;10:e0145497.
   Google Scholar
• Sikiö M, Holli-Helenius KK, Harrison LC, Ryymin P, Ruottinen H, Saunamäki T, et al. MR image texture in Parkinson's disease: a longitudinal study. Acta Radiol. 2015;56:97–104.
   Google Scholar
• Brooks B, Miller R, Swash M, Munsat T. El Escorial revisited: revised criteria for the diagnosis of amyotrophic lateral sclerosis. Amyotroph Lateral Scler Other Motor Neuron Disord. 2000;1:293–9.
   Google Scholar
• Kent-Braun JA, Walker CH, Weiner MW, Miller RG. Functional significance of upper and lower motor neuron impairment in amyotrophic lateral sclerosis. Muscle Nerve. 1998;21:762–8.
   Google Scholar
• Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage. 2007;38:95–113.
   Google Scholar
• Bede P, Elamin M, Byrne S, McLaughlin RL, Kenna K, Vajda A, et al. Basal ganglia involvement in amyotrophic lateral sclerosis. Neurology. 2013;81:2107–15.
   Google Scholar
• Schuster C, Kasper E, Dyrba M, Machts J, Bittner D, Kaufmann J, et al. Cortical thinning and its relation to cognition in amyotrophic lateral sclerosis. Neurobiol Aging. 2014;35:240–6.
   Google Scholar
• Mezzapesa D, D’Errico E, Tortelli R, Distaso E, Cortese R, Tursi M, et al. Cortical thinning and clinical heterogeneity in amyotrophic lateral sclerosis. PLoS One. 2013;8:e80748.
   Google Scholar
• Qin Y, Zhang S, Jiang R, Gao F, Tang X, Zhu W. Region-specific atrophy of precentral gyrus in patients with amyotrophic lateral sclerosis. J Magn Reson Imaging. 2018;47:115–22.
   Google Scholar
• Thorns J, Jansma H, Peschel T, Grosskreutz J, Mohammadi B, Dengler R, et al. Extent of cortical involvement in amyotrophic lateral sclerosis—an analysis based on cortical thickness. BMC Neurol. 2013;13:148.
   Google Scholar
• Cosottini M, Pesaresi I, Piazza S, Diciotti S, Cecchi P, Fabbri S, et al. Structural and functional evaluation of cortical motor areas in Amyotrophic Lateral Sclerosis. Exp Neurol. 2012;234:169–80.
   Google Scholar
• Chenji S, Mah D, Johnston W, Camicioli R, Fisher N, Kalra S. Utility of the Addenbrooke’s cognitive examination in amyotrophic lateral sclerosis. Can J Neurol Sci. 2018;45:527–32.
   Google Scholar
• Abrahams S, Newton J, Niven E, Foley J, Bak TH. Screening for cognition and behaviour changes in ALS. Amyotroph Lateral Scler Frontotemporal Degener. 2014;15:9–14.
   Google Scholar
• Wang Y, Li X, Chen W, Wang Z, Xu Y, Luo J, et al. Detecting neuronal dysfunction of hand motor cortex in ALS: a MRSI study. Somatosens Mot Res. 2017;34:15–20.
   Google Scholar
• Li H, Chen Y, Li Y, Yin B, Tang W, Yu X, et al. Altered cortical activation during action observation in amyotrophic lateral sclerosis patients: a parametric functional MRI study. Eur Radiol. 2015;25:2584–92.
   Google Scholar
• Sharma KR, Sheriff S, Maudsley A, Govind V. Diffusion tensor imaging of basal ganglia and thalamus in amyotrophic lateral sclerosis. J Neuroimaging. 2013;23:368–74.
   Google Scholar