Amyotrophic lateral sclerosis, a progressive neurodegenerative disease, presents challenges in predicting individual disease trajectories due to its heterogeneous nature. This study explores the application of texture analysis on T1-weighted MRI in patients with amyotrophic lateral sclerosis, stratified by the D50 disease progression model. The D50 model, which offers a more nuanced representation of disease progression than traditional linear metrics, calculates the sigmoidal curve of functional decline and provides independent quantifications of disease aggressiveness and accumulation. In this research, a representative cohort of 116 patients with amyotrophic lateral sclerosis was studied using the D50 model and texture analysis on MRI images. Texture analysis, a technique used for quantifying voxel intensity patterns in MRI images, was employed to discern alterations in brain tissue associated with amyotrophic lateral sclerosis. This study examined alterations of the texture feature autocorrelation across sub-groups of patients based on disease accumulation, aggressiveness and the first site of onset, as well as in direct regressions with accumulation/aggressiveness. The findings revealed distinct patterns of the texture-derived autocorrelation in grey and white matter, increase in bilateral corticospinal tract, right hippocampus and left temporal pole as well as widespread decrease within motor and extra-motor brain regions, of patients stratified based on their disease accumulation. Autocorrelation alterations in grey and white matter, in clusters within the left cingulate gyrus white matter, brainstem, left cerebellar tonsil grey matter and right inferior fronto-occipital fasciculus, were also negatively associated with disease accumulation in regression analysis. Otherwise, disease aggressiveness correlated with only two small clusters, within the right superior temporal gyrus and right posterior division of the cingulate gyrus white matter. The findings suggest that texture analysis could serve as a potential biomarker for disease stage in amyotrophic lateral sclerosis, with potential for quick assessment based on using T1-weighted images.
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