Biophysical compartment models for single-shell diffusion MRI in the human brain: a model fitting comparison. (7th March 2022)

• Record Type: Journal Article
• Authors: Davis, Andrew D; Hassel, Stefanie; Arnott, Stephen R; Hall, Geoffrey B; Harris, Jacqueline K; Zamyadi, Mojdeh; Downar, Jonathan; Frey, Benicio N; Lam, Raymond W; Kennedy, Sidney H; Strother, Stephen C
• Is Part Of: Physics in medicine & biology. Volume 67:Number 5(2022)
• Publication Date: 2022-03-07
• Subjects: magnetic resonance imaging -- diffusion-weighted imaging -- diffusion tensor imaging -- DTI -- neuroimaging -- compartment model -- biophysical modelling; Biophysics -- Periodicals; Medical physics -- Periodicals; 610.153
• DOI: 10.1088/1361-6560/ac46de
• Languages: English
• ISSNs: 0031-9155

Abstract

Abstract: Clinically oriented studies commonly acquire diffusion MRI (dMRI) data with a single non-zero b -value (i.e. single-shell) and diffusion weighting of b = 1000 s mm −2 . To produce microstructural parameter maps, the tensor model is usually used, despite known limitations. Although compartment models have demonstrated improved fits in multi-shell dMRI data, they are rarely used for single-shell parameter maps, where their effectiveness is unclear from the literature. Here, various compartment models combining isotropic balls and symmetric tensors were fitted to single-shell dMRI data to investigate model fitting optimization and extract the most information possible. Full testing was performed in 5 subjects, and 3 subjects with multi-shell data were included for comparison. The results were tested and confirmed in a further 50 subjects. The Markov chain Monte Carlo (MCMC) model fitting technique outperformed non-linear least squares. Using MCMC, the 2-fibre-orientation mono-exponential ball and stick model ( BS ME 2 ) provided artifact-free, stable results, in little processing time. The analogous ball and zeppelin model ( BZ 2 ) also produced stable, low-noise parameter maps, though it required much greater computing resources (50 000 burn-in steps). In single-shell data, the gamma-distributed diffusivity ball and stick model ( BS GD 2 ) underperformed relative to other models, despite being an often-used software default. It produced artifacts in the diffusivity maps even with extremely long processing times. Neither increased diffusion weighting nor a greater number of gradient orientations improved BS GD 2 fits. In white matter (WM), the tensor produced the best fit as measured by Bayesian information criterion. This result contrasts with studies using multi-shell data. However, in crossing fibre regions the tensor confounded geometric effects with fractional anisotropy (FA): the planar/linear WM FA ratio was 49%, while BZ 2 and BS ME 2 retained 76% and 83% of restricted fraction, respectively. As a result, the BZ 2 and BS ME 2 models are strong candidates to optimize information extraction from single-shell dMRI studies.