DTI data analysis: application of fiber tracking to group averaged data sets

Introduction: Transformation into stereotactic space of diffusion tensor imaging (DTI) data is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The objective of the present study was to demonstrate the feasibility of averaging DTI data sets at the group level.

Methods: Averaging for DTI data sets of 64 healthy subjects was applied in order to perform fractional anisotropy (FA) data analysis and fiber tracking (FT). The FT techniques used were modified deterministic streamline tracking (MDST) and modified probabilistic FT (MPFT). The directional information of single data sets during the FT process was taken into account. All data analyses were performed in one common analysis software environment (TIFT – Tensor Imaging and Fiber Tracking).

Results: Fiber tracking was applied to averaged data sets and showed similar results compared with FT on single subject data. The application of tractwise fractional anisotropy statistics (TFAS) to averaged data showed results that were in accordance with results for TFAS applied to single subject data.

Fig.1: Fiber tracking along the pyramidal tracts (left) and starting in the corpus callosum (right).

Conclusion: The applicability of FT techniques to the analysis of group averaged data sets was demonstrated. By merging directional information of DTI data sets at the group level, averaged data sets could be constructed that carry information relevant for fiber tracking specific for a certain subject group.