The corticospinal tract profile in amyotrophic lateral sclerosis
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- 作者：Alessia Sarica ; Antonio Cerasa ; Paola Valentino ; Jason Yeatman ; Maria Trotta ; Stefania Barone ; Alfredo Granata ; Rita Nisticò ; Paolo Perrotta ; Franco Pucci and Aldo Quattrone
- 刊名：Human Brain Mapping
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：38
- 期：2
- 页码：727-739
- 全文大小：847K
- ISSN：1097-0193
文摘
This work evaluates the potential in diagnostic application of a new advanced neuroimaging method, which delineates the profile of tissue properties along the corticospinal tract (CST) in amyotrophic lateral sclerosis (ALS), by means of diffusion tensor imaging (DTI). Twenty-four ALS patients and twenty-four demographically matched healthy subjects were enrolled in this study. The Automated Fiber Quantification (AFQ), a tool for the automatic reconstruction of white matter tract profiles, based on a deterministic tractography algorithm to automatically identify the CST and quantify its diffusion properties, was used. At a group level, the highest non-overlapping DTI-related differences were detected in the cerebral peduncle, posterior limb of the internal capsule, and primary motor cortex. Fractional anisotropy (FA) decrease and mean diffusivity (MD) and radial diffusivity (RD) increases were detected when comparing ALS patients to controls. The machine learning approach used to assess the clinical utility of this DTI tool revealed that, by combining all DTI metrics measured along tract between the cerebral peduncle and the corona radiata, a mean 5-fold cross validation accuracy of 80% was reached in discriminating ALS from controls. Our study provides a useful new neuroimaging tool to characterize ALS-related neurodegenerative processes by means of CST profile. We demonstrated that specific microstructural changes in the upper part of the brainstem might be considered as a valid biomarker. With further validations this method has the potential to be considered a promising step toward the diagnostic utility of DTI measures in ALS. Hum Brain Mapp 38:727–739, 2017.