title: Brain white matter shape changes in amyotrophic lateral sclerosis (ALS): a fractal dimension study.
abstract: Amyotrophic lateral sclerosis (ALS) is a fatal progressive neurodegenerative disorder. Current diagnosis time is about 12-months due to lack of objective methods. Previous brain white matter voxel based morphometry (VBM) studies in ALS reported inconsistent results. Fractal dimension (FD) has successfully been used to quantify brain WM shape complexity in various neurological disorders and aging, but not yet studied in ALS. Therefore, we investigated WM morphometric changes using FD analyses in ALS patients with different clinical phenotypes. We hypothesized that FD would better capture clinical features of the WM morphometry in different ALS phenotypes than VBM analysis. High resolution MRI T1-weighted images were acquired in controls (n = 11), and ALS patients (n = 89). ALS patients were assigned into four subgroups based on their clinical phenotypes.VBM analysis was carried out using SPM8. FD values were estimated for brain WM skeleton, surface and general structure in both controls and ALS patients using our previously published algorithm. No significant VBM WM changes were observed between controls and ALS patients and among the ALS subgroups. In contrast, significant (p<0.05) FD reductions in skeleton and general structure were observed between ALS with dementia and other ALS subgroups. No significant differences in any of the FD measures were observed between control and ALS patients. FD correlated significantly with revised ALS functional rating scale (ALSFRS-R) score a clinical measure of function. Results suggest that brain WM shape complexity is more sensitive to ALS disease process when compared to volumetric VBM analysis and FD changes are dependent on the ALS phenotype. Correlation between FD and clinical measures suggests that FD could potentially serve as a biomarker of ALS pathophysiology, especially after confirmation by longitudinal studies.
authors.affiliation: Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States of America ; Human Performance and Engineering Laboratory, Kessler Foundation Research Center, West Orange, New Jersey, United States of America.
authors.forename: Venkateswaran
authors.initials: V
authors.lastname: Rajagopalan
authors.forename: Zao
authors.initials: Z
authors.lastname: Liu
authors.forename: Didier
authors.initials: D
authors.lastname: Allexandre
authors.forename: Luduan
authors.initials: L
authors.lastname: Zhang
authors.forename: Xiao-Feng
authors.initials: XF
authors.lastname: Wang
authors.forename: Erik P
authors.initials: EP
authors.lastname: Pioro
authors.forename: Guang H
authors.initials: GH
authors.lastname: Yue
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D000690:Amyotrophic Lateral Sclerosis / Q000175:diagnosis* / Q000503:physiopathology; D001921:Brain / Q000473:pathology* / Q000503:physiopathology; D005260:Female; D017709:Fractals; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D012680:Sensitivity and Specificity
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