4.5 Article

Longitudinal Reproducibility of Neurite Orientation Dispersion and Density Imaging (NODDI) Derived Metrics in the White Matter

Journal

NEUROSCIENCE
Volume 457, Issue -, Pages 165-185

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neuroscience.2021.01.005

Keywords

diffusion-weighted imaging; Neurite Orientation Dispersion and Density Imaging (NODDI); Reproducibility; Reliability; Precision

Categories

Funding

  1. Otto von Guericke University Magdeburg [2039236003]

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The study used NODDI method to acquire multi-shell DWI data from 29 healthy young subjects twice, finding high test-retest reproducibility for the orientation dispersion index (ODI) and slightly worse results for the neurite density index (NDI). The choice of analysis approach was found to have significant consequences for the results, with voxel-based approach and ROI-averaging showing higher reproducibility.
Diffusion-weighted magnetic resonance imaging (DWI) is undergoing constant evolution with the ambitious goal of developing in-vivo histology of the brain. A recent methodological advancement is Neurite Orientation Dispersion and Density Imaging (NODDI), a histologically validated multi-compartment model to yield microstructural features of brain tissue such as geometric complexity and neurite packing density, which are especially useful in imaging the white matter. Since NODDI is increasingly popular in clinical research and fields such as developmental neuroscience and neuroplasticity, it is of vast importance to characterize its reproducibility (or reliability). We acquired multi-shell DWI data in 29 healthy young subjects twice over a rescan interval of 4 weeks to assess the within-subject coefficient of variation (CVws), between-subject coefficient of variation (CVBS) and the intraclass correlation coefficient (ICC), respectively. Using these metrics, we compared regional and voxel-by-voxel reproducibility of the most common image analysis approaches (tract-based spatial statistics [TBSS], voxel-based analysis with different extents of smoothing [VBM-style], ROI-based analysis). We observed high test-retest reproducibility for the orientation dispersion index (ODI) and slightly worse results for the neurite density index (NDI). Our findings also suggest that the choice of analysis approach might have significant consequences for the results of a study. Collectively, the voxel-based approach with Gaussian smoothing kernels of >= 4 mm FWHM and ROI-averaging yielded the highest reproducibility across NDI and ODI maps (CV ws mostly <= 3%, ICC mostly >= 0.8), respectively, whilst smaller kernels and TBSS performed consistently worse. Furthermore, we demonstrate that image quality (signal-to-noise ratio [SNR]) is an important determinant of NODDI metric reproducibility. We discuss the implications of these results for longitudinal and cross-sectional research designs commonly employed in the neuroimaging field. (C) 2021 IBRO. Published by Elsevier Ltd. All rights reserved.

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