Diffusion Tensor Imaging of the Substantia Nigra in Parkinson's Disease Revisited

• Type of Material: Article
• Authors: Jason Langley, Georgia Institute of Technology; Daniel Huddleston, Emory University; Michael Merritt, Georgia Institute of Technology; Xiangchuan Chen, Emory University; Rebecca McMurray, Emory University; Michael Silver, Emory University; Stewart Factor, Emory University; Xiaoping Hu, Emory University
• Language: English
• Date: 2016-07-01
• Publisher: Wiley
• Publication Version: Author Accepted Manuscript (After Peer Review)
• Copyright Statement: © 2016 Wiley Periodicals, Inc.
• Final Published Version (URL): http://dx.doi.org/10.1002/hbm.23192
• Title of Journal or Parent Work: Human Brain Mapping
• ISSN: 1065-9471
• Volume: 37
• Issue: 7
• Start Page: 2547
• End Page: 2556
• Grant/Funding Information: This work was partially supported by William N. and Bernice E. Bumpus Foundation Early Career Investigator Innovation Award (BFIA 2011.3), NIH grant R01-CA169937, Udall Center for Excellence in Parkinson's Disease Research Pilot Award (P50-NS071669), the Michael J. Fox Foundation (MJF 10854), and NINDS Parkinson's Disease Biomarkers Program U18 Award (U18 NS082143).
• Keywords: diffusion tensor imaging; Science & Technology; neuromelanin sensitive MRI; PATHOLOGY; Parkinson's disease; ECHO-PLANAR IMAGES; Neuroimaging; TRACTOGRAPHY; Radiology, Nuclear Medicine & Medical Imaging; LOCUS-COERULEUS; BRAIN IMAGES; Neurosciences; OPTIMIZATION; ROBUST; IRON CONTENT; NEUROMELANIN; substantia nigra; REGISTRATION; Life Sciences & Biomedicine; Neurosciences & Neurology
• Research Categories: Health Sciences, Medicine and Surgery; Health Sciences, Radiology

Abstract

Objective: To analyze diffusion tensor imaging (DTI) data in the substantia nigra (SN) using a more consistent region of interest (ROI) defined by neuromelanin-sensitive MRI in order to assess Parkinson's disease (PD) related changes in diffusion characteristics in the SN. Methods: T1-weighted and DTI data were obtained in a cohort of 37 subjects (17 control subjects and 20 subjects with PD). The subjects in the PD group were clinically diagnosed PD patients with an average Unified Parkinsonian Disease Rating Scale (UPDRS)-III score of 23.2 ± 9.3. DTI data were analyzed using SN ROIs defined by neuromelanin-sensitive MRI and, for comparison, with ROIs defined on T2-weighted images (b = 0 images). Results: Compared with control subjects, significantly lower fractional anisotropy was observed in PD in the neuromelanin SN ROI but not in the ROI derived from the T2-weighted image. This decrease was largest in the rostral and lateral portions of the neuromelanin volume, which were found to have more hypointensity in the T2-weighted image and, presumably, higher iron content in the PD group. In addition, a larger decrease in fractional anisotropy was seen in the SN region of interest on the side contralateral to the side exhibiting more severe symptoms. These results indicate that the use of neuromelanin sensitive MRI to define the ROI in the SN for analyzing DTI data leads to more significant results, enhancing the robustness of DTI study and DTI based biomarkers of PD.