3 research outputs found
Evaluating the Reliability of Human Brain White Matter Tractometry
Published Nov 17, 2021The validity of research results depends on the reliability of analysis methods. In recent years, there have been concerns about the validity of research that uses diffusion-weighted MRI (dMRI) to understand human brain white matter connections in vivo, in part based on the reliability of analysis methods used in this field. We defined and assessed three dimensions of reliability in dMRI-based tractometry, an analysis technique that assesses the physical properties of white matter pathways: (1) reproducibility, (2) test-retest reliability, and (3) robustness. To facilitate reproducibility, we provide software that automates tractometry (https://yeatmanlab.github.io/pyAFQ). In measurements from the Human Connectome Project, as well as clinical-grade measurements, we find that tractometry has high test-retest reliability that is comparable to most standardized clinical assessment tools. We find that tractometry is also robust: showing high reliability with different choices of analysis algorithms. Taken together, our results suggest that tractometry is a reliable approach to analysis of white matter connections. The overall approach taken here both demonstrates the specific trustworthiness of tractometry analysis and outlines what researchers can do to establish the reliability of computational analysis pipelines in neuroimaging.This work was supported through grant 1RF1MH121868-
01 from the National Institute of Mental Health/the BRAIN
Initiative, through grant 5R01EB027585-02 to Eleftherios
Garyfallidis (Indiana University) from the National Institute
of Biomedical Imaging and Bioengineering, through Azure
Cloud Computing Credits for Research & Teaching provided
through the University of Washingtonâs Research
Computing unit and the University of Washington eScience
Institute, and NICHD R21HD092771 to Jason D. Yeatma
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