Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network

David C. Newitt; Dariya Malyarenko; Thomas L. Chenevert; C. Chad Quarles; Laura C. Bell; Andriy Fedorov; Fiona M. Fennessy M.D.; Michael A. Jacobs; Meiyappan Solaiyappan; Stefanie Hectors; Bachir Taouli M.D.; Mark Muzi; Paul E. Kinahan; Kathleen M. Schmainda; Melissa A. Prah; Erin N. Taber; Christopher D. 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 A. Boss; Nola M. Hylton

doi:10.1117/1.JMI.5.1.011003

10 October 2017 Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network

David C. Newitt, Dariya Malyarenko, Thomas L. Chenevert, C. Chad Quarles, Laura C. Bell, Andriy Fedorov, Fiona M. Fennessy M.D., Michael A. Jacobs, Meiyappan Solaiyappan, Stefanie Hectors, Bachir Taouli M.D., Mark Muzi, Paul E. Kinahan, Kathleen M. Schmainda, Melissa A. Prah, Erin N. Taber, Christopher D. 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 A. Boss, Nola M. Hylton

Author Affiliations +

Journal of Medical Imaging, Vol. 5, Issue 1, 011003 (October 2017). https://doi.org/10.1117/1.JMI.5.1.011003

Abstract

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 (ADC2) and four (ADC4) b-value diffusion metrics. Concordance of the majority of implementations was excellent for both phantom ADC measures and in vivo ADC2, with relative biases <0.1 % (ADC2) and <0.5 % (phantom ADC4) but with higher deviations in ADC at the lowest phantom ADC values. In vivo ADC4 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 ADC4in 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.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Citation Download Citation

David C. Newitt, Dariya Malyarenko, Thomas L. Chenevert, C. Chad Quarles, Laura C. Bell, Andriy Fedorov, Fiona M. Fennessy M.D., Michael A. Jacobs, Meiyappan Solaiyappan, Stefanie Hectors, Bachir Taouli M.D., Mark Muzi, Paul E. Kinahan, Kathleen M. Schmainda, Melissa A. Prah, Erin N. Taber, Christopher D. 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 A. Boss, and Nola M. Hylton "Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network," Journal of Medical Imaging 5(1), 011003 (10 October 2017). https://doi.org/10.1117/1.JMI.5.1.011003

Received: 4 July 2017; Accepted: 13 September 2017; Published: 10 October 2017

ACCESS THE FULL ARTICLE

JOURNAL ARTICLE
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY