Abstract
White matter microstructures have been studied most commonly using diffusion tensor imaging (DTI) that models diffusivity in each voxel of diffusion MRI images as a tensor. Classic DTI parameters (e.g., mean diffusivity or MD, fractional anisotropy or FA) derived from the eigenvalues of tensors have been widely used to describe white matter properties. More recently, novel metrics like neurite orientation dispersion and density imaging (NODDI) have broadened the spectrum over which we can both characterize healthy connectivity and investigate pathology. When looking at specific brain regions, previous works combining DTI and NODDI have focused on regions of interest (ROI) analysis where regional masks were generated by mapping known atlas to standard spaces and applied to skeletonized FA maps from tract-based spatial statistics (TBSS). Recent advancement in probabilistic tractography, e.g., the FSL XTRACT toolbox, provides an alternative method of ROI analysis by estimating tract regions in an individual native diffusion space, but the exact advantages and disadvantages compared to using a standard space have not been well documented. In the present study, we perform ROI analysis on DTI and NODDI parameters from diffusion MRI (dMRI) of 39 healthy adults collected from two time points, using both standard-space method (“TBSS ROI analysis”) and native-space method (“XTRACT ROI analysis”). We compare the test-retest reliability of these two methods by evaluating the coefficient of variation (\(C_{V}\)) at each time point, the Pearson’s correlation (R) between the two time points, and the intra-class correlation coefficient (ICC) between the two time points. With these statistics, we aim to determine the precision of the TBSS ROI analysis and the XTRACT ROI analysis quantitatively in the practice of analyzing a particular dataset. The prospective results will provide a new and general reference for choosing analysis methods in future dMRI studies.
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Cai, L.T., Baida, M., Wren-Jarvis, J., Bourla, I., Mukherjee, P. (2021). Diffusion MRI Automated Region of Interest Analysis in Standard Atlas Space versus the Individual’s Native Space. In: Cetin-Karayumak, S., et al. Computational Diffusion MRI. CDMRI 2021. Lecture Notes in Computer Science(), vol 13006. Springer, Cham. https://doi.org/10.1007/978-3-030-87615-9_10
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