Identification of Amyotrophic Lateral Sclerosis Based on Diffusion Tensor Imaging and Support Vector Machine

Abstract

Objectives: White matter (WM) impairments involving both motor and extra-motor areas have been well-documented in amyotrophic lateral sclerosis (ALS). This study tested the potential of diffusion measurements in WM for identifying ALS based on support vector machine (SVM). Methods: Voxel-wise fractional anisotropy (FA) values of diffusion tensor images (DTI) were extracted from 22 ALS patients and 26 healthy controls and served as discrimination features. The revised ALS Functional Rating Scale (ALSFRS-R) was employed to assess ALS severity. Feature ranking and selection were based on Fisher scores. A linear kernel SVM algorithm was applied to build the classification model, from which the classification performance was evaluated. To promote classifier generalization ability, a leave-one-out cross-validation (LOOCV) method was adopted. Results: By using the 2,400∼3,400 ranked features as optimal features, the highest classification accuracy of 83.33% (sensitivity = 77.27% and specificity = 88.46%, P = 0.0001) was achieved, with an area under receiver operating characteristic curve of 0.862. The predicted function value was positively correlated with patient ALSFRS-R scores (r = 0.493, P = 0.020). In the optimized SVM model, FA values from several regions mostly contributed to classification, primarily involving the corticospinal tract pathway, postcentral gyrus, and frontal and parietal areas. Conclusions: Our results suggest the feasibility of ALS diagnosis based on SVM analysis and diffusion measurements of WM. Additional investigations using a larger cohort is recommended in order to validate the results of this study.

Diffusion magnetic resonance imaging-based surrogate marker in amyotrophic lateral sclerosis

“…FA decrease was also found in the corpus callosum, and this shift extended to main motor cortices [98][99][100][101][102][103][104][105][106]. In addition, a decrease in FA in the left corona radiata was shown to have a positive correlation with the ALS Functional Rating Scale-Revised (ALSFRS-R) score [98,[107][108][109]. The ALSFRS-R is a standard tool for evaluating the quality of life of people with ALS.…”

Aberrant Multimodal Connectivity Pattern Involved in Default Mode Network and Limbic Network in Amyotrophic Lateral Sclerosis

“…This is consistent with previous studies that showed widespread structural (but not functional) damage in ALS patients compared with HCs [36,39]. Incorporating the significant differences in SC-FC coupling as features in the SVM model resulted in classification performance with similar or even higher accuracy (72.09-81.40%), sensitivity (72.00-88.00%), and specificity (61.11-94.44%) for distinguishing ALS patients from HCs compared to that obtained in previous studies using other neu-roimaging features [42][43][44][45]. Our findings show that SC-FC coupling may be a valuable neuroimaging marker for ALS.…”

“…These findings should be replicated in future multicenter longitudinal datasets. Second, other MRI modalities (e.g., DTI) can also help to identify ALS at the early stage [43]; thus, multimodal neuroimaging combinations should be considered in future research. Third, we did not determine the C9orf72 repeat expansion status of ALS patients in this study.…”

Toward diffusion tensor imaging as a biomarker in neurodegenerative diseases: technical considerations to optimize recordings and data processing

“…Discrimination of NDD patients from controls could be performed by the application of an SVM based on ROI-or TOI-based FA values of previously defined NDD-associated brain structures (AD – Zhang et al, 2011 ; Houria et al, 2022 ; PD – Haller et al, 2012 ; Huang et al, 2023 ; ALS – Chen et al, 2020 ; Kocar et al, 2021 ; Münch et al, 2022 ).…”