Test–retest reliability and long‐term stability of three‐tissue constrained spherical deconvolution methods for analyzing diffusion MRI data

Abstract

Purpose Several recent studies have used a three‐tissue constrained spherical deconvolution pipeline to obtain quantitative metrics of brain tissue microstructure from diffusion‐weighted MRI data. The three tissue compartments, consisting of white matter, gray matter, and CSF‐like (free water) signals, are potentially useful in the evaluation of brain microstructure in a range of pathologies. However, the reliability and long‐term stability of these metrics have not yet been evaluated. Methods This study examined estimates of whole‐brain microstructure for the three tissue compartments, in three separate test–retest cohorts. Each cohort had different lengths of time between baseline and retest, ranging from within the same scanning session in the shortest interval to 3 months in the longest interval. Each cohort was also collected with different acquisition parameters. Results The CSF‐like compartment displayed the greatest reliability across all cohorts, with intraclass correlation coefficient (ICC) values being above 0.95 in each cohort. White matter–like and gray matter–like compartments both demonstrated very high reliability in the immediate cohort (both ICC > 0.90); however, this declined in the 3‐month interval cohort to both compartments having ICC > 0.80. Regional CSF‐like signal fraction was examined in bilateral hippocampus and had an ICC > 0.80 in each cohort. Conclusion The three‐tissue constrained spherical deconvolution techniques provide reliable and stable estimates of tissue‐microstructure composition, up to 3 months longitudinally in a control population. This forms an important basis for further investigations using three‐tissue constrained spherical deconvolution techniques to track changes in microstructure across a variety of brain pathologies.

In vivo microstructural heterogeneity of white matter lesions in healthy elderly and Alzheimer's disease participants using tissue compositional analysis of diffusion MRI data

“…The added advantage of SS3T-CSD is that it can model 3 tissue compartments using single-shell data alone, enabling investigation of existing single-shell data without increasing acquisition requirements ( Aerts et al, 2019 ). While we had high b-value single shell data available in this cohort, SS3T-CSD could also be valuable at lower b-values ( Dimond et al, 2020 , Newman et al, 2020 ).…”

Exercise Training-Related Changes in Cortical Gray Matter Diffusivity and Cognitive Function in Mild Cognitive Impairment and Healthy Older Adults

“…MRtrix3 Tissue is a method that allows 3-tissue constrained spherical deconvolution results from single-shell diffusion data. The three tissue compartments determine the contribution of free water CSFlike, WM-like, and GM-like signal within each voxel and has been shown to exhibit high reliability, particularly for estimating the contribution of free water CSF-like diffusion (intraclass correlation above 0.95; Newman et al, 2020). The three tissue compartment response functions were created and estimated for each diffusion scan, and a study wide response function for each tissue type was created.…”

“…These three tissue compartment images were then normalized to sum to 1 on a voxel-wise basis to provide a three-tissue signal fraction map (providing the percent of GM-like, CSF-like, and WM-like signal in each voxel). As previously suggested (Newman et al, 2020), each subject's CSF mask was then thresholded to only include voxels considered to have 50% or more CSF-like signal. All subjects' CSF masks were then warped into MNI space using the same warp used on the MD images.…”

“…Reductions in hyperperfusion from exercise are hypothesized to result from the normalization of blood flow and oxygen availability due to cerebrovascular growth (Pereira et al, 2007;Alfini et al, 2019), leading to lower inflammation and improve cellular integrity (Wierenga et al, 2014). However, we controlled for the fast free water compartment in our analysis, which absorbs a large portion of perfusion effects and thus, helps limit contamination in the diffusion signal from CSF and the intravoxel incoherent motion of blood due to differences in capillary perfusion (Rydhög et al, 2017;Newman et al, 2020). As an additional check, we also found no association between the subsample of perfusion values and MD values or between change in perfusion and change in MD values extracted from the left insular interaction cluster.…”

Fixel-Based Analysis and Free Water Corrected DTI Evaluation of HIV Associated Neurocognitive Disorders

“…FD or the apparent fiber density (AFD) is calculated from the fiber orientation distribution (FOD) which is estimated using multi tissue constrained spherical deconvolution (MT-CSD) (Jeurissen et al, 2014). By modeling grey matter (GM), WM, and CSF separately, MT-CSD accounts for FW contamination and has been shown to have better test-retest reliability than traditional DTI metrics (Newman et al, 2020). FC reflects the cross-sectional area of a fiber bundle, perpendicular to the length axis, and is derived from the Jacobian of the non-linear transformation from subject space to template space.…”