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Hum Brain Mapp. 2017 Oct;38(10):5035-5050. doi: 10.1002/hbm.23713. Epub 2017 Jun 28.

Mapping the order and pattern of brain structural MRI changes using change-point analysis in premanifest Huntington's disease.

Author information

1
The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.
2
Center for Imaging Science, Johns Hopkins University, Baltimore, Maryland.
3
Institute for Computational Medicine, Johns Hopkins University, Baltimore, Maryland.
4
Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland.
5
F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland.
6
Department of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa.
7
Departments of Psychiatry, Neurology, Psychology and Neurosciences, University of Iowa, Iowa City, Iowa.
8
Division of Neurobiology, Departments of Psychiatry, Neurology, Neuroscience and Pharmacology, and Program in Cellular and Molecular Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
9
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland.

Abstract

Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder that progressively affects motor, cognitive, and emotional functions. Structural MRI studies have demonstrated brain atrophy beginning many years prior to clinical onset ("premanifest" period), but the order and pattern of brain structural changes have not been fully characterized. In this study, we investigated brain regional volumes and diffusion tensor imaging (DTI) measurements in premanifest HD, and we aim to determine (1) the extent of MRI changes in a large number of structures across the brain by atlas-based analysis, and (2) the initiation points of structural MRI changes in these brain regions. We adopted a novel multivariate linear regression model to detect the inflection points at which the MRI changes begin (namely, "change-points"), with respect to the CAG-age product (CAP, an indicator of extent of exposure to the effects of CAG repeat expansion). We used approximately 300 T1-weighted and DTI data from premanifest HD and control subjects in the PREDICT-HD study, with atlas-based whole brain segmentation and change-point analysis. The results indicated a distinct topology of structural MRI changes: the change-points of the volumetric measurements suggested a central-to-peripheral pattern of atrophy from the striatum to the deep white matter; and the change points of DTI measurements indicated the earliest changes in mean diffusivity in the deep white matter and posterior white matter. While interpretation needs to be cautious given the cross-sectional nature of the data, these findings suggest a spatial and temporal pattern of spread of structural changes within the HD brain. Hum Brain Mapp 38:5035-5050, 2017.

KEYWORDS:

atlas-based segmentation; brain atrophy; change-point analysis; diffusion tensor MRI; premanifest HD; spatiotemporal order

PMID:
28657159
PMCID:
PMC5766002
[Available on 2018-10-01]
DOI:
10.1002/hbm.23713
[Indexed for MEDLINE]

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