Automated probabilistic reconstruction of white matter pathways facilitates tractography in large studies. TRACULA TRActs Constrained by UnderLying Anatomy follows a Markov-chain Monte Carlo MCMC approach that is compute-intensive. TRACULA is available on our Neuroscience Gateway NSG, a user-friendly environment for fully automated data processing on grid computing resources. Despite the robustness of TRACULA, our users and others have reported incidents of partially reconstructed tracts. Investigation revealed that in these situations the MCMC algorithm is caught in local minima. We developed a method that detects unsuccessful tract reconstructions and iteratively repeats the sampling procedure while maintaining the anatomical priors to reduce computation time. The anatomical priors are recomputed only after several unsuccessful iterations. Our method detects affected tract reconstructions by analyzing the dependency between samples produced by the MCMC algorithm. We extensively validated the original and the modified methods by performing five repeated reconstructions on a dataset of 74 HIV-positive patients and 47 healthy controls. Our method increased the rate of successful reconstruction in the two most prominently affected tracts forceps major and minor on average from 74% to 99%. In these tracts, no group difference in FA and MD was found, while a significant association with age could be confirmed.
['Jalmar Teeuw', 'Matthan W. A. Caan', 'Sílvia Delgado Olabarriaga']
Robust Automated White Matter Pathway Reconstruction for Large Studies