Multisite Concordance of Apparent Diffusion Coefficient Measurements across the NCI Quantitative Imaging Network


David C Newitt, Dariya Malyarenko, Thomas L Chenevert, Chad C Quarles, Laura Bell, Andriy Fedorov, Fiona Fennessy, Michael A Jacobs, Meiyappan Solaiyappan, Stefanie Hectors, Bachir Taouli, Mark Muzi, Paul E Kinahan, Kathleen M Schmainda, Melissa A Prah, Erin N Taber, Christopher Kroenke, Wei Huang, Lori R Arlinghaus, Thomas E Yankeelov, Yue Cao, Madhava Aryal, Yi-Fen Yen, Jayashree Kalpathy-Cramer, Amita Shukla-Dave, Maggie Fung, Jiachao Liang, Michael Boss, and Nola Hylton. 2018. “Multisite Concordance of Apparent Diffusion Coefficient Measurements across the NCI Quantitative Imaging Network.” J Med Imaging (Bellingham), 5, 1, Pp. 011003. Copy at


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 breast studies were evaluated for two ([Formula: see text]) and four ([Formula: see text]) [Formula: see text]-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and [Formula: see text], with relative biases [Formula: see text] ([Formula: see text]) and [Formula: see text] (phantom [Formula: see text]) but with higher deviations in ADC at the lowest phantom ADC values. [Formula: see text] concordance was good, with typical biases of [Formula: see text] to 3% but higher for online maps. Multiple -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 [Formula: see text] 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.
Last updated on 05/03/2018