RESUMO
PURPOSE: Diagnostic work-up in motor neuron disease (MND) needs a quantitative biomarker of upper motor neuron (UMN) impairment. We investigated the susceptibility properties of the precentral cortex in a cohort of patients affected by Amyotrophic lateral sclerosis (ALS) to obtain a useful biomarker of UMN impairment in a fully automatic paradigm. MATERIALS AND METHODS: We retrospectively collected imaging and clinical data of 42 ALS patients who had undergone brain 3 T MRI including tridimensional T1-weighted and spoiled gradient-echo multi-echo T2-weighted images. We further acquired images from 23 healthy control (HC) volunteers. The precentral cortex was automatically segmented and the cortical thickness calculated. Histogram metrics (mean, median, standard deviation, skewness, kurtosis) derived from the quantitative susceptibility map (QSM) were extracted from the automatically segmented precentral cortex. Multivariate regression analyses were performed to identify the variables predicting the disease status (ALS vs HC), the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) and the UMN score. RESULTS: A decreased cortical thickness (B = 9.40; Wald's test = 7.43; p = 0.006) and increased susceptibility skewness (B = -3.08; Wald's test = 4.36; p = 0.037) independently predicted ALS in a logistic regression model (χ2(3, N = 65) = 22.07, p < 0.001. No predictors of ALSFRS-R were identified. An increased susceptibility skewness (ß = 0.55; t = 4.23; p < 0.001) and longer disease duration (ß = 0.35; t = 2.67; p = 0.011) independently predicted a higher UMN score in a linear regression model (R2 = 0.32; p < 0.001). CONCLUSION: The susceptibility skewness might be an unbiased quantitative biomarker of UMN impairment in ALS patients.