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The effect of gradient nonlinearities on fiber orientation estimates from spherical deconvolution of diffusion MRI data

Guo, Fenghua, De Luca, Alberto, Parker, Greg, Jones, Derek K., Viergever, Max A., Leemans, Alexander and Tax, Chantal M. W. 2021. The effect of gradient nonlinearities on fiber orientation estimates from spherical deconvolution of diffusion MRI data. Human Brain Mapping 42 (2) , pp. 367-383. 10.1002/hbm.25228

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Abstract

Gradient nonlinearities in magnetic resonance imaging (MRI) cause spatially varying mismatches between the imposed and the effective gradients and can cause significant biases in rotationally invariant diffusion MRI measures derived from, for example, diffusion tensor imaging. The estimation of the orientational organization of fibrous tissue, which is nowadays frequently performed with spherical deconvolution techniques ideally using higher diffusion weightings, can likewise be biased by gradient nonlinearities. We explore the sensitivity of two established spherical deconvolution approaches to gradient nonlinearities, namely constrained spherical deconvolution (CSD) and damped Richardson‐Lucy (dRL). Additionally, we propose an extension of dRL to take into account gradient imperfections, without the need of data interpolation. Simulations show that using the effective b‐matrix can improve dRL fiber orientation estimation and reduces angular deviations, while CSD can be more robust to gradient nonlinearity depending on the implementation. Angular errors depend on a complex interplay of many factors, including the direction and magnitude of gradient deviations, underlying microstructure, SNR, anisotropy of the effective response function, and diffusion weighting. Notably, angular deviations can also be observed at lower b‐values in contrast to the perhaps common assumption that only high b‐value data are affected. In in vivo Human Connectome Project data and acquisitions from an ultrastrong gradient (300 mT/m) scanner, angular differences are observed between applying and not applying the effective gradients in dRL estimation. As even small angular differences can lead to error propagation during tractography and as such impact connectivity analyses, incorporating gradient deviations into the estimation of fiber orientations should make such analyses more reliable.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Physics and Astronomy
Psychology
Cardiff University Brain Research Imaging Centre (CUBRIC)
Publisher: Wiley
ISSN: 1065-9471
Funders: Wellcome Trust
Date of First Compliant Deposit: 7 October 2020
Date of Acceptance: 24 September 2020
Last Modified: 06 Jan 2021 14:19
URI: http://orca.cf.ac.uk/id/eprint/135405

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