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Background: Fiber tracking with diffusion-weighted MRI has become an essential tool for estimating in vivo brain white matter architecture. Fiber tracking results are sensitive to the choice of processing method and tracking criteria., Purpose: To assess the variability for an algorithm in group studies reproducibility is of critical context. However, reproducibility does not assess the validity of the brain connections. Phantom studies provide concrete quantitative comparisons of methods relative to absolute ground truths, yet do no capture variabilities because of in vivo physiological factors. The ISMRM 2017 TraCED challenge was created to fulfill the gap., Study Type: A systematic review of algorithms and tract reproducibility studies., Subjects: Single healthy volunteers., Field Strength/sequence: 3.0T, two different scanners by the same manufacturer. The multishell acquisition included b-values of 1000, 2000, and 3000 s/mm 2 with 20, 45, and 64 diffusion gradient directions per shell, respectively., Assessment: Nine international groups submitted 46 tractography algorithm entries each consisting 16 tracts per scan. The algorithms were assessed using intraclass correlation (ICC) and the Dice similarity measure., Statistical Tests: Containment analysis was performed to assess if the submitted algorithms had containment within tracts of larger volume submissions. This also serves the purpose to detect if spurious submissions had been made., Results: The top five submissions had high ICC and Dice >0.88. Reproducibility was high within the top five submissions when assessed across sessions or across scanners: 0.87-0.97. Containment analysis shows that the top five submissions are contained within larger volume submissions. From the total of 16 tracts as an outcome relatively the number of tracts with high, moderate, and low reproducibility were 8, 4, and 4., Data Conclusion: The different methods clearly result in fundamentally different tract structures at the more conservative specificity choices. Data and challenge infrastructure remain available for continued analysis and provide a platform for comparison., Level of Evidence: 5 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:234-249., (© 2019 International Society for Magnetic Resonance in Medicine.)

Analysis of the structural connectomes can lead to powerful insights about the brain's organization and damage. However, the accuracy and reproducibility of constructing the structural connectome done with different acquisition and reconstruction techniques is not well defined. In this work, we evaluated the reproducibility of the structural connectome techniques by performing test-retest (same day) and longitudinal studies (after 1 month) as well as analyzing graph-based measures on the data acquired from 22 healthy volunteers (6 subjects were used for the longitudinal study). We compared connectivity matrices and tract reconstructions obtained with the most typical acquisition schemes used in clinical application: diffusion tensor imaging (DTI), high angular resolution diffusion imaging (HARDI), and diffusion spectrum imaging (DSI). We observed that all techniques showed high reproducibility in the test-retest analysis (correlation >.9). However, HARDI was the only technique with low variability (2%) in the longitudinal assessment (1-month interval). The intraclass coefficient analysis showed the highest reproducibility for the DTI connectome, however, with more sparse connections than HARDI and DSI. Qualitative (neuroanatomical) assessment of selected tracts confirmed the quantitative results showing that HARDI managed to detect most of the analyzed fiber groups and fanning fibers. In conclusion, we found that HARDI acquisition showed the most balanced trade-off between high reproducibility of the connectome, higher rate of path detection and of fanning fibers, and intermediate acquisition times (10-15 minutes), although at the cost of higher appearance of aberrant fibers., (Copyright © 2015 by the American Society of Neuroimaging.)

Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.

This work investigates the possibilities of applying high-angular-resolution-diffusion-imaging- (HARDI-) based methods in a clinical setting by investigating the performance of non-Gaussian diffusion probability density function (PDF) estimation for a range of b-values and diffusion gradient direction tables. It does so at realistic SNR levels achievable in limited time on a high-performance 3T system for the whole human brain in vivo. We use both computational simulations and in vivo brain scans to quantify the angular resolution of two selected reconstruction methods: Q-ball imaging and the diffusion orientation transform. We propose a new analytical solution to the ODF derived from the DOT. Both techniques are analytical decomposition approaches that require identical acquisition and modest postprocessing times and, given the proposed modifications of the DOT, can be analyzed in a similar fashion. We find that an optimal HARDI protocol given a stringent time constraint (<10 min) combines a moderate b-value (around 2000 s/mm2) with a relatively low number of acquired directions (>48). Our findings generalize to other methods and additional improvements in MR acquisition techniques. [ABSTRACT FROM AUTHOR]