TractEM: Fast Protocols for Whole Brain Deterministic Tractography-Based White Matter Atlas

Abstract

Reproducible identification of white matter tracts across subjects is essential for the study of structural connectivity of the human brain. One of the key challenges is anatomical differences between subjects. Labeling white matter regions of interest presents many challenges due to the need to integrate both local and global information. Clearly communicating the human/manual processes to capture this information is cumbersome, and the state-of-the-art for white matter atlas is the population-averaged Johns Hopkins Eve atlas. A critical bottleneck with the Eve atlas framework is that manual labeling time is extensive and peripheral white matter regions are conservatively labeled. In this work, we developed and tested a protocol for a simpler and flexible approach based on modern tractography definitions. The TractEM protocols for whole brain tractography take less than 6 hours for one subject. We tested the protocols on 61 unique tracts for 20 subjects manually labeled at least twice per subject. We analyzed reproducibility of the fiber bundles using volumetric overlap metrics, Dice correlation coefficient, continuous Dice correlation coefficient; distance metric, root mean squared error; and probabilistic intraclass correlation (ICC). Raters with minimal neuroanatomical expertise attained good and high reproducibility for typical 3T research resolution and high-resolution Human Connectome Project datasets, respectively. While the existing tractography methods tend to cover larger tracts and target only a limited number of tracts, the TractEM manual labeling protocols allow for reconstruction of reproducible region-specific fiber bundles across the brain. The protocols and sample results have been made available in open source.

Tractostorm: The what, why, and how of tractography dissection reproducibility

“…Hence, changing tractography algorithm would require a re‐evaluation of the reproducibility is considered as part of important future work. For example, the project “ TractEm ” (Bayrak et al, ) featured a framework to obtain 61 bundle of interests from deterministic tractography and report some voxel‐wise measures for intra‐rater and inter‐rater reproducibility. However, this protocol is likely optimized for specific datasets (BLSA, HCP).…”

“…Reproducibility “ scores ” cannot be easily generalized and any attempt would be dangerous, as any deviation from a known protocol creates the need for a new assessment. Aiming for standardized and harmonized protocols that are agreed upon within the field should be the main focus on the long term, such as (Bayrak et al, ; Catani & De Schotten, ).…”

“…The set of all streamlines forms an object often called the tractogram (Catani & De Schotten, ; Jeurissen, Descoteaux, Mori, & Leemans, ). When specific hypotheses about known pathways, that is, WM bundles, are investigated, neuroanatomists design “ dissection plans ” that contain anatomical landmarks and instructions to isolate the bundle of interest from this whole brain tractogram (Bayrak et al, ; Catani & De Schotten, ; Catani, Howard, Pajevic, & Jones, ; Chenot et al, ; Hau et al, ). From now on “ dissection plans ” will be referred as segmentation protocols.…”

Reproducibility of MRI-based white matter tract estimation using multi-fiber probabilistic tractography: effect of user-defined parameters and regions

“…More recently, a study looked at optimizing the number of selected streamlines through mathematical models aiming to reduce the reproducibility of probabilistic tractography but did not consider the influence of user-dependent choices [30]. Another recent work looked at whole brain streamline reproducibility between users by comparing binarized streamline volumes, but using deterministic and atlas-driven approaches [31]. Automated pipelines for generation of white matter fibers have been proposed [32,33].…”

An atlas of white matter anatomy, its variability, and reproducibility based on Constrained Spherical Deconvolution of diffusion MRI

“…However, it is widely accepted that DTI suffers limitations that make it suboptimal for many tractography applications, particularly in a clinical setting (Farquharson et al, 2013;Mori and Tournier, 2014;Tournier et al, 2011). This has led to increased interest in more accurate and reliable approaches using high angular resolution imaging (HARDI) data (Bayrak et al, 2020;Bloy et al, 2012;Wasserthal et al, 2018;Yeh et al, 2018). At the same time, technological advances to accelerate data acquisition and reconstruction, such as multiband (Bouyagoub et al, 2020;Duan et al, 2015;Larkman et al, 2001;Moeller et al, 2010) and compressed sensing (Lustig et al, 2007b(Lustig et al, , 2007a in combination with improved computational efficiency, will increase the adoption of advanced reconstruction models in applications traditionally reserved for DTI.…”