Insights from the IronTract challenge: optimal methods for mapping brain pathways from multi-shell diffusion MRI
Author:
Maffei Chiara, Girard Gabriel, Schilling Kurt G.ORCID, Aydogan Dogu Baran, Adluru NageshORCID, Zhylka Andrey, Wu Ye, Mancini MatteoORCID, Hamamci Andac, Sarica Alessia, Teillac Achille, Baete Steven H., Karimi Davood, Yeh Fang-Cheng, Yildiz Mert E., Gholipour Ali, Bihan-Poudec Yann, Hiba Bassem, Quattrone Andrea, Quattrone Aldo, Boshkovski TommyORCID, Stikov Nikola, Yap Pew-Thian, de Luca AlbertoORCID, Pluim Josien, Leemans Alexander, Prabhakaran Vivek, Bendlin Barbara B., Alexander Andrew L., Landman Bennett A., Canales-Rodríguez Erick J., Barakovic Muhamed, Rafael-Patino Jonathan, Yu Thomas, Rensonnet Gaëtan, Schiavi SimonaORCID, Daducci Alessandro, Pizzolato Marco, Fischi-Gomez Elda, Thiran Jean-Philippe, Dai George, Grisot Giorgia, Lazovski Nikola, Puch Santi, Ramos Marc, Rodrigues Paulo, Prchkovska Vesna, Jones Robert, Lehman Julia, Haber Suzanne N., Yendiki Anastasia
Abstract
AbstractLimitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.
Publisher
Cold Spring Harbor Laboratory
Cited by
2 articles.
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