@article{kruper_yeatman_richie-halford_bloom_grotheer_caffarra_kiar_karipidis_roy_chandio_et al._2021,
title={Evaluating the Reliability of Human Brain White Matter Tractometry},
volume={2021},
DOI={10.52294/e6198273-b8e3-4b63-babb-6e6b0da10669},
abstractNote={
The 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.
},
number={1},
publisher={Organization for Human Brain Mapping},
author={Kruper, John and Yeatman, Jason D. and Richie-Halford, Adam and Bloom, David and Grotheer, Mareike and Caffarra, Sendy and Kiar, Gregory and Karipidis, Iliana I. and Roy, Ethan and Chandio, Bramsh Q. and et al.},
year={2021},
month={Nov}
}