Toward a marker of upper motor neuron impairment in amyotrophic lateral sclerosis: A fully automatic investigation of the magnetic susceptibility in the precentral cortex. Issue 124 (March 2020)

• Record Type: Journal Article
• Authors: Contarino, Valeria Elisa; Conte, Giorgio; Morelli, Claudia; Trogu, Francesca; Scola, Elisa; Calloni, Sonia Francesca; Sanmiguel Serpa, Luis Carlos; Liu, Chunlei; Silani, Vincenzo; Triulzi, Fabio
• Is Part Of: European journal of radiology. Issue 124(2020)
• Publication Date: 2020-03
• Subjects: ALS amyotrophic lateral sclerosis -- ALSFRS-R Amyotrophic Lateral Sclerosis Functional Rating Scale - Revised -- HC healthy control -- LMN lower motor neuron -- MND motor neuron disease -- QSM quantitative susceptibility mapping -- UMN upper motor neuron; Quantitative susceptibility mapping -- motor neuron disease -- Amyotrophic lateral sclerosis -- motor cortex -- Upper motor neuron impairment; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2020.108815
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: an automatic pipeline was used to assess cortical thickness and iron deposition in ALS. cortical thickness of the precentral cortex is reduced in ALS patients. susceptibility skewness of the precentral cortex is increased in ALS patients. cortical thickness of the precentral cortex predicts upper motor neuron score. susceptibility skewness of the precentral cortex predicts upper motor neuron score. Abstract: 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 (χ 2 (3, N = 65) = 22.07, p < 0.001. No predictors of ALSFRS-R were identified. An increased susceptibility skewness (β = 0.55; t = 4.23; p < 0.001) and longer disease duration (β = 0.35; t = 2.67; p = 0.011) independently predicted a higher UMN score in a linear regression model (R 2 = 0.32; p < 0.001). Conclusion: The susceptibility skewness might be an unbiased quantitative biomarker of UMN impairment in ALS patients.