Machine learning classificatory as a tool in the diagnosis of amyotrophic lateral sclerosis using diffusion tensor imaging parameters collected with 1.5T MRI scanner: A case study
More details
Hide details
Department of Clinical Radiology, Medical University of Warsaw, Warsaw, POLAND
Department of Psychology, SWPS University of Social Sciences and Humanities, Warsaw, POLAND
Department of Pediatric Radiology, University Clinical Center of the Medical University of Warsaw, Warsaw, POLAND
Department of Neurology, Medical University of Warsaw, Warsaw, POLAND
Online publication date: 2023-08-06
Publication date: 2023-11-01
Electron J Gen Med 2023;20(6):em535
The relevance of the study lies in the need to improve the diagnosis of amyotrophic lateral sclerosis (ALS) by utilizing diffusion tensor imaging (DTI) obtained from conventional 1.5 Tesla MRI scanners. The study aimed to investigate the potential of using different machine learning (ML) classifiers to distinguish between individuals with ALS. In this study, five ML classifiers (“support vector machine (SVM)”, “k-nearest neighbors (K-NN)”, naïve Bayesian classifier, “decision tree”, and “decision forest”) were used, based on two DTI parameters: fractional anisotropy and apparent diffusion coefficient, obtained from two manually selected ROIs at the level of the brain pyramids in 47 ALS patients and 55 healthy subjects. The quality of each classifier was evaluated using the confusion matrix and ROC curves. The highest accuracy in differentiating ALS patients from healthy individuals based on DTI data was demonstrated by the radial kernel support vector method (77% accuracy [p=0.01]), while K-NN and “decision tree” classifiers had slightly lower performance, and “decision forest” classifier was overtrained to the training set (AUC=1). The authors have shown a sufficiently accuracy of ML classifier “SVM” in detecting radiological characteristics of ALS in pyramidal tracts.
Meyer T. Amyotrophic lateral sclerosis (ALS)–diagnosis, course of disease and treatment options. Dtsch Med Wochenschr. 2021;146(24-25):1613-8. https://doi.org/10.1055/a-1562... PMid:34879411.
Brown CA, Lally C, Kupelian V, Flanders WD. Estimated prevalence and incidence of amyotrophic lateral sclerosis and SOD1 and C9orf72 genetic variants. Neuroepidemiol. 2021;55(5):342-53. https://doi.org/10.1159/000516... PMid:34247168.
Corcia P, Beltran S, Bakkouche SE, Couratier P. Therapeutic news in ALS. Rev Neurol. 2021;177(5):544-9. https://doi.org/10.1016/j.neur... PMid:33781562.
Oskarsson B, Gendron TF, Staff NP. Amyotrophic lateral sclerosis: An update for 2018. Mayo Clin Proc. 2018;93(11): 1617-28. https://doi.org/10.1016/j.mayo... PMid:30401437.
Kwan J, Vullaganti M. Amyotrophic lateral sclerosis mimics. Muscle Nerve. 2022;66(3):240-52. https://doi.org/10.1002/mus.27... PMid:35607838.
Ido BJF, Kacem I, Ouedraogo M, et al. Sensitivity of Awaji criteria and revised El Escorial criteria in the diagnosis of amyotrophic lateral sclerosis (ALS) at first visit in a Tunisian cohort. Neurol Res Int. 2021;2021:8841281. https://doi.org/10.1155/2021/8... PMid:33552600 PMCid:PMC7847325.
Turner MR, UK MND Clinical Studies Group. Diagnosing ALS: The Gold Coast criteria and the role of EMG. Pract Neurol. 2022;22(3):176-8. https://doi.org/10.1136/practn... PMid:34992096 PMCid:PMC9120398.
Cosottini M, Donatelli G, Costagli M, et al. High-resolution 7T MR imaging of the motor cortex in amyotrophic lateral sclerosis. Am J Neuroradiol. 2016;37(3):455-61. https://doi.org/10.3174/ajnr.a... PMid:26680464 PMCid:PMC7960124.
Roccatagliata L, Bonzano L, Man-Cardi G, Canepa C, Capon-Netto C. Detection of motor cortex thinning and corticospinal tract involvement by quantitative MRI in amyotrophic lateral sclerosis. Amyotroph Lateral Scler. 2009;10(1):47-52. https://doi.org/10.1080/174829... PMid:18622772.
Mohammadi B, Kollewe K, Samii A, Krampfl K, Dengler R, Münte TF. Changes of resting state brain networks in amyotrophic lateral sclerosis. Exp Neurol. 2009;217(1):147-53. https://doi.org/10.1016/j.expn... PMid:19416664.
Foerster BR, Callaghan BC, Petrou M, Edden RAE, Chenevert TL, Feldman EL. Decreased motor cortex–Aminobutyric acid in amyotrophic lateral sclerosis. Neurology. 2012;78(20):1596-600. https://doi.org/10.1212/wnl.0b... PMid:22517106 PMCid:PMC3348851.
Trojsi F, Di Nardo F, Siciliano M, et al. Frontotemporal degeneration in amyotrophic lateral sclerosis (ALS): A longitudinal MRI one-year study. CNS Spectr. 2021; 26(3):258-67. https://doi.org/10.1017/s10928... PMid:32089134.
Li H, Zhang Q, Duan Q, Jin J, Hu F, Dang J, Zhang M. Brainstem involvement in amyotrophic lateral sclerosis: A combined structural and diffusion tensor MRI analysis. Front Neurosci. 2021;15:675444. https://doi.org/10.3389/fnins.... PMid:34149349 PMCid:PMC8206526.
Kassubek J, Pagani M. Imaging in amyotrophic lateral sclerosis: MRI and PET. Curr Opin Neurol. 2019;32(5):740-6. https://doi.org/10.1097/wco.00... PMid:31335337.
Baek SH, Park J, Kim YH, et al. Usefulness of diffusion tensor imaging findings as biomarkers for amyotrophic lateral sclerosis. Sci Rep. 2020;10:5199. https://doi.org/10.1038/s41598... PMid:32251314 PMCid:PMC7090054.
Li J, Pan P, Song W, Huang R, Chen K, Shan H. A meta-analysis of diffusion tensor imaging studies in amyotrophic lateral sclerosis. Neurobiol Aging. 2012;33(8):1833-8. https://doi.org/10.1016/j.neur... PMid:21621298.
Maj E, Jamroży M, Bielecki M, Bartoszek M, Gołębiowski M, Wojtaszek M, Kuźma-Kozakiewicz M. Role of DTI-MRI parameters in diagnosis of ALS: Useful biomarkers for daily practice? Tertiary centre experience and literature review. Neurol Neurochir Pol. 2022;56(6):490-8. https://doi.org/10.5603/pjnns.... PMid:36426927.
Keil C, Prell T, Peschel T, Hartung V, Dengler R, Grosskreutz J. Longitudinal diffusion tensor imaging in amyotrophic lateral sclerosis. BMC Neurosci. 2012;13:141. https://doi.org/10.1186/1471-2... PMid:23134591 PMCid:PMC3531302.
Alexander AL, Lee JE, Lazar M, Field AS. Diffusion tensor imaging of the brain. Neurotherapeutics. 2007;4(3):316-29. https://doi.org/10.1016%2Fj.nu... PMid:17599699 PMCid:PMC2041910.
R Core Team. R-project. Available at: https://www.R-project.org/ (Accessed: 12 May 2023).
Kosherbayeva L, Medeulova A, Hailey D, Yermukhanova L, Uraz R, Aitmanbetova A. Influence of a health technology assessment on the use of pediatric cochlear implantation in Kazakhstan. Health Policy Technol. 2018;7(3):239-42. https://doi.org/10.1016/j.hlpt....
Serniak YP, Sagalevych AI, Frolov OS, Serniak PY, Kryvopustov MS. Extraperitoneoscopic radical prostatectomy after pelvic sugery procedures. Wiad Lek. 2020;73(6):1093-6. https://doi.org/10.36740/WLek2... PMid:32723932.
Okassova AK, Ilderbayev OZ, Nursafina AZ, et al. Evaluation of lipid peroxidation under immobilization stress in irradiated animals in experiment. Open Access Macedon J Med Sci. 2021;9:119-22. https://doi.org/10.3889/oamjms....
Scott IA. Machine learning and evidence-based medicine. Ann Intern Med. 2018;169(1):44-6. https://doi.org/10.7326/M18-01... PMid:29710098.
Akhmetova KM, Vochshenkova TA, Dalenov ED, Abduldayeva AA, Benberin VV. The interconnection of metabolic disorders and carotid atherosclerosis in the Kazakh population. Syst Rev Pharm. 2020;11(12):2152-9.
Molcan J, Dobrovanov A, Koren R, Kralinsky K, Balaz V. Unilateral scrotal hernia with dual ureter herniation: The first experience of successful surgical correction. Pediatriya Zh. im G.N. Speranskogo. 2021;100(4):171-5. https://doi.org/10.24110/0031-....
Fernandes F, Barbalho I, Barros D, et al. Biomedical signals and machine learning in amyotrophic lateral sclerosis: A systematic review. Biomed Eng OnLine. 2021;20(1):61. https://doi.org/10.1186/s12938... PMid:34130692 PMCid:PMC8207575.
Faghri F, Brunn F, Dadu A, et al. Identifying and predicting amyotrophic lateral sclerosis clinical subgroups: A population-based machine-learning study. Lancet Digit Health. 2022;4(5):359-69. https://doi.org/10.1016/s2589-... PMid:35341712.
Fukushima K, Takamatsu N, Yamamoto Y, et al. Early diagnosis of amyotrophic lateral sclerosis based on fasciculations in muscle ultrasonography: A machine learning approach. Clin Neurophysiol. 2022;140:136-44. https://doi.org/10.1016/j.clin... PMid:35772191.
Tursynova A, Omarov B, Sakhipov A, Tukenova N. Brain stroke lesion segmentation using computed tomography images based on modified U-net model with ResNet blocks. Int J Online Biomed Engin. 2022;18(13):97-112. https://doi.org/10.3991/ijoe.v....
Behler A, Müller HP, Ludolph AC, Kassubek J. Diffusion tensor imaging in amyotrophic lateral sclerosis: Machine learning for biomarker development. Int J Mol Sci. 2023;24(3):1911. https://doi.org/10.3390/ijms24... PMID:36768231 PMCid:PMC9915541.
Kocar TD, Behler A, Ludolph AC, Müller HP, Kassubek J. 2021. Multiparametric microstructural MRI and machine learning classification yields high diagnostic accuracy in amyotrophic lateral sclerosis: Proof of concept. Front Neurol. 2021;12:745475. https://doi.org/10.3389/fneur.... PMid:34867726 PMCid:PMC8637840.
Welsh RC, Jelsone-Swain LM, Foerster BR. The utility of independent component analysis and machine learning in the identification of the amyotrophic lateral sclerosis diseased brain. Front Hum Neurosci. 2023;7:251. https://doi.org/10.3389/fnhum.... PMid:23772210 PMCid:PMC3677153.
Li W, Wei Q, Hou Y, et al. Disruption of the white matter structural network and its correlation with baseline progression rate in patients with sporadic amyotrophic lateral sclerosis. Transl Neurodegener. 2021;10(1):35. https://doi.org/10.1186/s40035... PMid:34511130 PMCid:PMC8436442.
Sarica A, Cerasa A, Valentino P, et al. The corticospinal tract profile in amyotrophic lateral sclerosis. Hum Brain Map. 2017;38(2):727-39. https://doi.org/10.1002/hbm.23... PMid:27659483 PMCid:PMC6867092.
Stadnik SN. Effect of statinotherapy on the cognitive functions of patients with disturbances of cardic rhythm and conduction. Azerb Pharm Pharmacother J. 2021;21(2):61-9.
Atamanyuk IP, Kondratenko YP. Calculation method for a computer’s diagnostics of cardiovascular diseases based on canonical decompositions of random sequences. CEUR Workshop Proceed. 2015;1356:108-20.
Toosy AT, Werring DJ, Orrell RW, et al. Diffusion tensor imaging detects corticospinal tract involvement at multiple levels in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry. 2003;74(9):1250-7. https://doi.org/10.1136/jnnp.7... PMid:12933929 PMCid:PMC1738665.
Cosottini M, Giannelli M, Siciliano G, et al. Diffusion-tensor MR imaging of corticospinal tract in amyotrophic lateral sclerosis and progressive muscular atrophy. Radiology. 2005;237:258-64. https://doi.org/10.1148/radiol... PMid:16183935.
Dobrovanov O, Kralinsky K, Molcan J, Kovalchuk VP. Relevance of ultrasound neonatal screening of the urinary system. Ross Vest Perinat Pediatr. 2019;64(2):68-72. https://doi.org/10.21508/1027-....
Shckorbatov Y, Pasiuga V, Kolchigin N, Batrakov D, Kazansky O, Kalashnikov V. Changes in the human nuclear chromatin induced by ultra wideband pulse irradiation. Cent Eur J Biol. 2009;4(1):97-106. https://doi.org/10.2478/s11535....
Schapovalova O, Gorlova A, de Munter J, et al. Immunomodulatory effects of new phytotherapy on human macrophages and TLR4- and TLR7/8-mediated viral-like inflammation in mice. Front Med. 2022;9:952977. https://doi.org/10.3389/fmed.2... PMid:36091684 PMCid:PMC9450044.
Yendiki A, Panneck P, Srinivasan P, et al. Automated probabilistic reconstruction of white-matter pathways in health and disease using an atlas of the underlying anatomy. Front Neuroinform. 2011;5:23. https://doi.org/10.3389/fninf.... PMid:22016733 PMCid:PMC3193073.
Journals System - logo
Scroll to top