Rajan, Surya, Brettschneider, Julia and Collingwood, Joanna F. (2020) Data for Regional segmentation strategy for DTI analysis of human corpus callosum indicates motor function deficit in mild cognitive impairment. [Dataset]

	Other (R code to generate tables in manuscript) tables.R - Published Version Available under License Creative Commons Attribution 4.0. Download (7Kb)
	Other (R code to generate figures in manuscript) figures.R - Published Version Available under License Creative Commons Attribution 4.0. Download (21Kb)
	Microsoft Excel (Data for sub_regions) data_for_corpus_callosum_segmented_by_subregions.csv - Published Version Available under License Creative Commons Attribution 4.0. Download (47Kb)
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	Microsoft Excel (Data for whole ROI) data_with_corpus_callosum_segmented_as_single_ROI.csv - Published Version Available under License Creative Commons Attribution 4.0. Download (6Kb)
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Abstract

Background: The corpus callosum is the largest white matter tract in the human brain, involved in inter-hemispheric transfer and integration of lateralised visual, sensory-motor, language, and cognitive information. Microstructural alterations are implicated in ageing as well as various neurological conditions.

New Method: Cross-sectional diffusion-weighted images of 107 healthy adults were used to create a linear regression model of the ageing corpus callosum and its sub-regions to evaluate the impact of analysis by sub-region, and to test for deviations from healthy ageing parameters in 28 subjects with mild cognitive impairment (MCI). Alterations in diffusion properties including fractional anisotropy, mean, radial and axial diffusivities were investigated as a function of age.

Results: Changes in DTI parameters showed regional differences as a function of ageing, likely arising from axonal diameter variation across cross-sectional regions of interest in the corpus callosum. Patterns suggestive of degeneration with healthy ageing were observed in all regions. Diffusion parameters in sub-regions projecting to pre-motor, primary, and supplementary motor areas of the brain differed for MCI versus healthy controls, and the MCI subjects were more likely than healthy controls to experience a reduction in motor skills.

Comparison with Existing Methods: Statistical analyses of the corpus callosum by five manually-defined sub-regions, instead of a single manually-defined region of interest, revealed region-specific changes in microstructure in healthy ageing and MCI, and accounted for clinically-evaluated differences in motor skills between cohorts.

Conclusion: This method will support future studies of corpus callosum, enabling identification and measurement of white matter changes that are undetectable with the single ROI approach.

Item Type:	Dataset
Alternative Title:	Supplementary materials (data and code)
Subjects:	Q Science > QP Physiology R Medicine > RC Internal medicine
Divisions:	Faculty of Science, Engineering and Medicine > Engineering > Engineering Faculty of Science, Engineering and Medicine > Science > Statistics
Type of Data:	Experimental data
Library of Congress Subject Headings (LCSH):	Corpus callosum, Diffusion tensor imaging, Aging, Mild cognitive impairment, Psychomotor disorders, Corpus callosum -- Cross-sectional imaging
Publisher:	University of Warwick, School of Engineering
Official Date:	14 July 2020
Dates:	Date Event 14 July 2020 Published
Status:	Not Peer Reviewed
Publication Status:	Published
Media of Output (format):	.r .csv
Access rights to Published version:	Open Access (Creative Commons)
Copyright Holders:	University of Warwick
Description:	Data record consists of 2 sets of R code designed to generate the tables in the manuscript and 5 sets of data. The 5 datasets are named according to the data they contain.
Date of first compliant deposit:	15 July 2020
Date of first compliant Open Access:	15 July 2020
RIOXX Funder/Project Grant:	Project/Grant ID RIOXX Funder Name Funder ID UNSPECIFIED University of Warwick http://dx.doi.org/10.13039/501100000741
Related URLs:	Related item in WRAP Other
Contributors:	Contribution Name Contributor ID Depositor Rajan, Surya 86902

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