Knowledge-based Automated Reconstruction of Human Brain White Matter Tracts Using a Path-Finding Approach with Dynamic Programming

I could have used this right after my stroke and I'm sure there are millions each year that need this put into a stroke protocol. But its not going to happen with the current  idiots in charge of the stroke world.
http://www.sciencedirect.com/science/article/pii/S1053811913010239

Highlights

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Dynamic programming (DP) was applied to tractography based on DTI data.

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DP finds the most probable path between two specified brain regions.

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DP delineates large tracts that could not be reconstructed by streamline methods.

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For accurate path generation, knowledge-based ROI sets are built.

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Fifty two tracts were reconstructed in the MNI space for white matter atlases.

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Abstract

It has been shown that the anatomy of major white matter tracts can be delineated using diffusion tensor imaging (DTI) data. Tract reconstruction, however, often suffers from a large number of false-negative results when a simple line propagation algorithm is used. This limits the application of this technique to only the core of prominent white matter tracts. By employing probabilistic path-generation algorithms, connectivity between a larger number of anatomical regions can be studied, but an increase in the number of false-positive results is inevitable. One of the causes of the inaccuracy is the complex axonal anatomy within a voxel; however, high-angular resolution (HAR) methods have been proposed to ameliorate this limitation. However, HAR data are relatively rare due to the long scan times required and the low signal-to-noise ratio. In this study, we tested a probabilistic path-finding method in which two anatomical regions with known connectivity were pre-defined and a path that maximized agreement with the DTI data was searched. To increase the accuracy of the trajectories, knowledge-based anatomical constraints were applied. The reconstruction protocols were tested using DTI data from 19 normal subjects to examine test–retest reproducibility and cross-subject variability. Fifty-two tracts were found to be reliably reconstructed using this approach, which can be viewed on our website.