Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.

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The frontal aslant tract is a direct pathway connecting Broca's region with the anterior cingulate and pre-supplementary motor area. This tract is left lateralized in right-handed subjects, suggesting a possible role in language. However, there are no previous studies that have reported an involvement of this tract in language disorders. In this study we used diffusion tractography to define the anatomy of the frontal aslant tract in relation to verbal fluency and grammar impairment in primary progressive aphasia. Thirty-five patients with primary progressive aphasia and 29 control subjects were recruited. Tractography was used to obtain indirect indices of microstructural organization of the frontal aslant tract. In addition, tractography analysis of the uncinate fasciculus, a tract associated with semantic processing deficits, was performed. Damage to the frontal aslant tract correlated with performance in verbal fluency as assessed by the Cinderella story test. Conversely, damage to the uncinate fasciculus correlated with deficits in semantic processing as assessed by the Peabody Picture Vocabulary Test. Neither tract correlated with grammatical or repetition deficits. Significant group differences were found in the frontal aslant tract of patients with the non-fluent/agrammatic variant and in the uncinate fasciculus of patients with the semantic variant. These findings indicate that degeneration of the frontal aslant tract underlies verbal fluency deficits in primary progressive aphasia and further confirm the role of the uncinate fasciculus in semantic processing. The lack of correlation between damage to the frontal aslant tract and grammar deficits suggests that verbal fluency and grammar processing rely on distinct anatomical networks.

Diffusion tensor imaging (DTI) methods are widely used to reconstruct white matter trajectories and to quantify tissue changes using the average diffusion properties of each brain voxel. Spherical deconvolution (SD) methods have been developed to overcome the limitations of the diffusion tensor model in resolving crossing fibers and to improve tractography reconstructions. However, the use of SD methods to obtain quantitative indices of white matter integrity has not been extensively explored. In this study, we show that the hindrance modulated orientational anisotropy (HMOA) index, defined as the absolute amplitude of each lobe of the fiber orientation distribution, can be used as a compact measure to characterize the diffusion properties along each fiber orientation in white matter regions with complex organization. We demonstrate that the HMOA is highly sensitive to changes in fiber diffusivity (e.g., myelination processes or axonal loss) and to differences in the microstructural organization of white matter like axonal diameter and fiber dispersion. Using simulations to describe diffusivity changes observed in normal brain development and disorders, we observed that the HMOA is able to identify white matter changes that are not detectable with conventional DTI indices. We also show that the HMOA index can be used as an effective threshold for in vivo data to improve tractography reconstructions and to better map white matter complexity inside the brain. In conclusion, the HMOA represents a true tract-specific and sensitive index and provides a compact characterization of white matter diffusion properties with potential for widespread application in normal and clinical populations.