Automatic Removal of False Connections in Diffusion MRI Tractography Using Topology-Informed Pruning (TIP)

Abstract

Diffusion MRI fiber tracking provides a non-invasive method for mapping the trajectories of human brain connections, but its false connection problem has been a major challenge. This study introduces topology-informed pruning (TIP), a method that automatically identifies singular tracts and eliminates them to improve the tracking accuracy. The accuracy of the tractography with and without TIP was evaluated by a team of 6 neuroanatomists in a blinded setting to examine whether TIP could improve the accuracy. The results showed that TIP improved the tracking accuracy by 11.93% in the single-shell scheme and by 3.47% in the grid scheme. The improvement is significantly different from a random pruning (p value < 0.001). The diagnostic agreement between TIP and neuroanatomists was comparable to the agreement between neuroanatomists. The proposed TIP algorithm can be used to automatically clean-up noisy fibers in deterministic tractography, with a potential to confirm the existence of a fiber connection in basic neuroanatomical studies or clinical neurosurgical planning.

In vivo Restricted-Diffusion Imaging (RDI) is sensitive to differences in axonal density in typical children and adults

“…Unlike most other diffusion metrics, RDI does does not depend on an underlying diffusion model or numerical optimization to estimate model parameters, making it easily applicable to a wider range of databases and clinical scanner protocols. RDI’s sensitivity to cell density has been useful in differentiating tissue in patients with tumors 44, 45 , as well as measuring therapeutic benefits of deep brain stimulation 46 . In a phantom study by Yeh et al, the optimized restricted diffusion showed an almost perfect correlation of 0.998 with cell density 1 .…”

Shape Analysis of the Human Association Pathways

“…All recognized trajectories were then summed up and pruned by topology-informed pruning (Yeh et al, 2019). A total of 20 pruning iterations was conducted.…”

“…This automatic recognition method isolated target pathways and simultaneously excluded irrelevant or false connections that substantially deviated from the known trajectories. After recognition, we further applied topology-informed pruning (Yeh et al, 2019) to eliminate possible false connections. TIP used track density at each voxel to eliminate noisy tracks that failed to form a bundle.…”

A New Era for Surgical Neurotherapeutics

“…Switching gears to adjuvant techniques, Fernandez-Miranda and colleagues [8] provide an overview of high-definition fiber tractography, an advanced imaging technique that they developed, and have pioneered in neurosurgical planning to optimize functional outcomes in tumor surgery. Yeh and colleagues [9] then tackle the false connection problem in tractography imaging, describing topology-informed pruning (TIP), a method that automatically identifies singular tracts and eliminates them to improve fiber tracking accuracy. Continuing a computational theme, in an original research article, Vakharia and colleagues [10] describe machine learning approaches for predicting trajectories that optimize the extent of mesial temporal lobe ablations during laser interstitial thermal therapy of epilepsy.…”