The quantitative analysis of diffusion tensor image (DTI) data has attracted increasing attention in recent decades for studying white matter (WM) integrity and development. Among the current DTI analysis methods, tract-based spatial statistics (TBSS), as a pioneering approach for the voxelwise analysis of DTI data, has gained a lot of popularity due to its user-friendly framework. However, in recent years, the reliability and interpretability of TBSS have been challenged by several works, and several improvements over the original TBSS pipeline have been suggested. In this paper, we propose a new DTI statistical analysis method, named tractography atlas-based spatial statistics (TABSS). It doesn't rely on the accurate alignment of fractional anisotropy (FA) images for population analysis and gets rid of the skeletonization procedures of TBSS, which have been indicated as the major sources of error. Furthermore, TABSS improves the interpretability of results by directly reporting the resulting statistics on WM tracts, waiving the need of a WM atlas in the interpretation of the results. The feasibility of TABSS was evaluated in an example study to show age-related FA alternation pattern of healthy human brain. Through this preliminary study, it is validated that TABSS can provide detailed statistical results in a comprehensive and easy-to-understand way.
Keywords: DTI; FA; Statistical analysis; TBSS; Tractography atlas.
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