It has previously been demonstrated that, by using 3-tissue constrained spherical deconvolution, separate compartments encompassing cerebrospinal fluid-like, white matter-like, and grey matter-like, signal fractions can be derived from diffusion MRI data. This study explores the reliability of these compartments in three test-retest cohorts with a variety of timescales and scanning parameters. Whole-brain average signal fractions show excellent reliability across all datasets, particularly in determining the CSF-like signal fraction. This suggests that variations in whole brain signal fraction measurements are likely to be attributable to experimental manipulation or pathology and not variation introduced by performing the analysis.
3-tissue CSD was performed using the open source software MRtrix5, several preprocessing and postprocessing steps also utilized FSL6and ANTs7. Three cohorts of subjects were scanned twice to create baseline and retest dMRI images. The first cohort consisted of individuals participating in a separate study that included multiple scanning sessions. In each session two identical dMRI sequences were performed sequentially without table repositioning to evaluate reliability of the analysis technique. Data was acquired on a Siemens Prisma 3T scanner with isotropic voxels 1.7x1.7x1.7mm3, TE=70ms and TR=2900ms; 10 b=0 images were acquired, and 64 gradient directions at both b=1500s/mm2and b=3000s/mm2.
For the second cohort images were obtained from the publicly available Nathanial Kline Institute for Psychiatric Research enhanced test-retest dataset (eNKI-TRT)8. Baseline and rescan sessions occurred between 7-60 days apart. Images were obtained using a Siemens Trio Tim with voxel size 2x2x2mm3, TE=85ms and TR=2400ms; 9 b=0 images were acquired and 127 directions at b=1500s/mm2.
The third cohort was composed of individuals from a previous experiment9. Scanning sessions were spaced 3 months apart. Data was acquired on the same Siemens 3T scanner as the first cohort using a different sequence with voxel size 2.7x2.7x2.7mm3, TE=100ms; 1 b=0 image was acquired, and 30 gradient directions at both b=1000s/mm2 and b=2000s/mm2.
All data was analyzed using the following pipeline: images were denoised10, corrected for Gibbs ringing11, susceptibility distortions12, motion13, and eddy currents14. All images were upsampled to a voxel size of 1.3x1.3x1.3mm3 and 3-tissue CSD was performed after selecting response functions using an unsupervised method2. Final tissue map intensities were intensity normalized, and each compartment is presented as representing the fraction of total signal observed in each voxel (Fig. 1).
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