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Optimizing the intrinsic parallel diffusivity in NODDI: An extensive empirical evaluation

Guerrero, JM; Adluru, N; Bendlin, BB; Goldsmith, HH; Schaefer, SM; Davidson, RJ; Kecskemeti, SR; ... Alexander, AL; + view all (2019) Optimizing the intrinsic parallel diffusivity in NODDI: An extensive empirical evaluation. PLoS One , 14 (9) , Article e0217118. 10.1371/journal.pone.0217118. Green open access

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Abstract

Purpose NODDI is widely used in parameterizing microstructural brain properties. The model includes three signal compartments: intracellular, extracellular, and free water. The neurite compartment intrinsic parallel diffusivity (d∥) is set to 1.7 μm2⋅ms−1, though the effects of this assumption have not been extensively explored. This work investigates the optimality of d∥ = 1.7 μm2⋅ms−1 under varying imaging protocol, age groups, sex, and tissue type in comparison to other biologically plausible values of d∥. Methods Model residuals were used as the optimality criterion. The model residuals were evaluated in function of d∥ over the range from 0.5 to 3.0 μm2⋅ms−1. This was done with respect to tissue type (i.e., white matter versus gray matter), sex, age (infancy to late adulthood), and diffusion-weighting protocol (maximum b-value). Variation in the estimated parameters with respect to d∥ was also explored. Results Results show d∥ = 1.7 μm2⋅ms−1 is appropriate for adult brain white matter but it is suboptimal for gray matter with optimal values being significantly lower. d∥ = 1.7 μm2⋅ms−1 was also suboptimal in the infant brain for both white and gray matter with optimal values being significantly lower. Minor optimum d∥ differences were observed versus diffusion protocol. No significant sex effects were observed. Additionally, changes in d∥ resulted in significant changes to the estimated NODDI parameters. Conclusion The default (d∥) of 1.7 μm2⋅ms−1 is suboptimal in gray matter and infant brains.

Type: Article
Title: Optimizing the intrinsic parallel diffusivity in NODDI: An extensive empirical evaluation
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pone.0217118
Publisher version: https://doi.org/10.1371/journal.pone.0217118
Language: English
Additional information: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. https://creativecommons.org/licenses/by/4.0/
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10082715
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