MASiVar: Multisite, multiscanner, and multisubject acquisitions for studying variability in diffusion weighted MRI
| Autor: | Allen T. Newton, Jeffrey J. Luci, Fang-Cheng Yeh, Vishwesh Nath, Bennett A. Landman, Cailey I. Kerley, Heidi A. Edmonson, Eleftherios Garyfallidis, François Rheault, Leon Y. Cai, Maxime Descoteaux, Colin B. Hansen, Karthik Ramadass, Kurt G. Schilling, Qi Yang, Benjamin N. Conrad, Hakmook Kang, Praitayini Kanakaraj, Gavin R. Price |
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| Rok vydání: | 2021 |
| Předmět: |
Adult
Connectomics Orientation (computer vision) business.industry Brain Pattern recognition White Matter Article Correlation Data set Diffusion Magnetic Resonance Imaging Diffusion Tensor Imaging Fractional anisotropy Connectome Neurites Anisotropy Humans Radiology Nuclear Medicine and imaging Artificial intelligence Index of dispersion business Child Diffusion MRI Mathematics |
| Zdroj: | Magn Reson Med |
| ISSN: | 1522-2594 |
| Popis: | Purpose Diffusion-weighted imaging allows investigators to identify structural, microstructural, and connectivity-based differences between subjects, but variability due to session and scanner biases is a challenge. Methods To investigate DWI variability, we present MASiVar, a multisite data set consisting of 319 diffusion scans acquired at 3 T from b = 1000 to 3000 s/mm2 across 14 healthy adults, 83 healthy children (5 to 8 years), three sites, and four scanners as a publicly available, preprocessed, and de-identified data set. With the adult data, we demonstrate the capacity of MASiVar to simultaneously quantify the intrasession, intersession, interscanner, and intersubject variability of four common DWI processing approaches: (1) a tensor signal representation, (2) a multi-compartment neurite orientation dispersion and density model, (3) white-matter bundle segmentation, and (4) structural connectomics. Respectively, we evaluate region-wise fractional anisotropy, mean diffusivity, and principal eigenvector; region-wise CSF volume fraction, intracellular volume fraction, and orientation dispersion index; bundle-wise shape, volume, fractional anisotropy, and length; and whole connectome correlation and maximized modularity, global efficiency, and characteristic path length. Results We plot the variability in these measures at each level and find that it consistently increases with intrasession to intersession to interscanner to intersubject effects across all processing approaches and that sometimes interscanner variability can approach intersubject variability. Conclusions This study demonstrates the potential of MASiVar to more globally investigate DWI variability across multiple levels and processing approaches simultaneously and suggests harmonization between scanners for multisite analyses should be considered before inference of group differences on subjects. |
| Databáze: | OpenAIRE |
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