Multisite concordance of apparent diffusion coefficient measurements across the NCI quantitative imaging network
Magnetic Resonance Imaging
© The Authors. The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. Diffusion weighted MRI has become ubiquitous in many areas of medicine, including cancer diagnosis and treatment response monitoring. Reproducibility of diffusion metrics is essential for their acceptance as quantitative biomarkers in these areas. We examined the variability in the apparent diffusion coefficient (ADC) obtained from both postprocessing software implementations utilized by the NCI Quantitative Imaging Network and online scan time-generated ADC maps. Phantom and in vivo breast studies were evaluated for two (ADC 2 ) and four (ADC 4 ) b-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and in vivo ADC 2 , with relative biases <0.1% (ADC 2 ) and <0.5% (phantom ADC 4 ) but with higher deviations in ADC at the lowest phantom ADC values. In vivo ADC 4 concordance was good, with typical biases of ±2% to 3% but higher for online maps. Multiple b-value ADC implementations were separated into two groups determined by the fitting algorithm. Intergroup mean ADC differences ranged from negligible for phantom data to 2.8% for ADC 4 in vivo data. Some higher deviations were found for individual implementations and online parametric maps. Despite generally good concordance, implementation biases in ADC measures are sometimes significant and may be large enough to be of concern in multisite studies.
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