2 March 2018 Evaluation of inter-site bias and variance in diffusion-weighted MRI
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Abstract
An understanding of the bias and variance of diffusion weighted magnetic resonance imaging (DW-MRI) acquisitions across scanners, study sites, or over time is essential for the incorporation of multiple data sources into a single clinical study. Studies that combine samples from various sites may be introducing confounding factors due to site-specific artifacts and patterns. Differences in bias and variance across sites may render the scans incomparable, and, without correction, inferences obtained from these data may be misleading. We present an analysis of the bias and variance of scans of the same subjects across different sites and evaluate their impact on statistical analyses. In previous work, we presented a simulation extrapolation (SIMEX) technique for bias estimation as well as a wild bootstrap technique for variance estimation in metrics obtained from a Q-ball imaging (QBI) reconstruction of empirical high angular resolution diffusion imaging (HARDI) data. We now apply those techniques to data acquired from 5 healthy volunteers on 3 independent scanners under closely matched acquisition protocols. The bias and variance of GFA measurements were estimated on a voxel-wise basis for each scan and compared across study sites to identify site-specific differences. Further, we provide model recommendations that can be used to determine the extent of the impact of bias and variance as well as aspects of the analysis to account for these differences. We include a decision tree to help researchers determine if model adjustments are necessary based on the bias and variance results.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Allison E. Hainline, Allison E. Hainline, Vishwesh Nath, Vishwesh Nath, Prasanna Parvathaneni, Prasanna Parvathaneni, Justin Blaber, Justin Blaber, Baxter Rogers, Baxter Rogers, Allen Newton, Allen Newton, Jeffrey Luci, Jeffrey Luci, Heidi Edmonson, Heidi Edmonson, Hakmook Kang, Hakmook Kang, Bennett A. Landman, Bennett A. Landman, } "Evaluation of inter-site bias and variance in diffusion-weighted MRI", Proc. SPIE 10574, Medical Imaging 2018: Image Processing, 1057413 (2 March 2018); doi: 10.1117/12.2293735; https://doi.org/10.1117/12.2293735
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