Tract-specific statistics based on diffusion-weighted probabilistic tractography

Reid, Andrew T.; Camilleri, Julia A.; Hoffstaedter, Felix; Eickhoff, Simon B.

Abstract

Diffusion-weighted neuroimaging approaches provide rich evidence for estimating the structural integrity of white matter in vivo, but typically do not assess white matter integrity for connections between two specific regions of the brain. Here, we present a method for deriving tract-specific diffusion statistics, based upon predefined regions of interest. Our approach derives a population distribution using probabilistic tractography, based on the Nathan Kline Institute (NKI) Enhanced Rockland sample. We determine the most likely geometry of a path between two regions and express this as a spatial distribution. We then estimate the average orientation of streamlines traversing this path, at discrete distances along its trajectory, and the fraction of diffusion directed along this orientation for each participant. The resulting participant-wise metrics (tract-specific anisotropy; TSA) can then be used for statistical analysis on any comparable population. Based on this method, we report both negative and positive associations between age and TSA for two networks derived from published meta-analytic studies (the “default mode” and “what-where” networks), along with more moderate sex differences and age-by-sex interactions. The proposed method can be applied to any arbitrary set of brain regions, to estimate both the spatial trajectory and DWI-based anisotropy specific to those regions.

Citation

Reid, A. T., Camilleri, J. A., Hoffstaedter, F., & Eickhoff, S. B. (2022). Tract-specific statistics based on diffusion-weighted probabilistic tractography. Communications Biology, 5(1), Article 138. https://doi.org/10.1038/s42003-022-03073-w

• Journal Article Type: Article
• Acceptance Date: Jan 24, 2022
• Online Publication Date: Feb 17, 2022
• Publication Date: Feb 17, 2022
• Deposit Date: Nov 3, 2021
• Publicly Available Date: Feb 17, 2022
• Journal: Communications Biology
• Electronic ISSN: 2399-3642
• Publisher: Springer Science and Business Media LLC
• Peer Reviewed: Peer Reviewed
• Volume: 5
• Issue: 1
• Article Number: 138
• DOI: https://doi.org/10.1038/s42003-022-03073-w
• Keywords: General Agricultural and Biological Sciences; General Biochemistry, Genetics and Molecular Biology; Medicine (miscellaneous)
• Public URL: https://nottingham-repository.worktribe.com/output/6609723
• Publisher URL: https://www.nature.com/articles/s42003-022-03073-w