Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network Journal Article
| Authors: | Newitt, D. C.; Malyarenko, D.; Chenevert, T. L.; Quarles, C. C.; Bell, L.; Fedorov, A.; Fennessy, F.; Jacobs, M. A.; Solaiyappan, M.; Hectors, S.; Taouli, B.; Muzi, M.; Kinahan, P. E.; Schmainda, K. M.; Prah, M. A.; Taber, E. N.; Kroenke, C.; Huang, W.; Arlinghaus, L. R.; Yankeelov, T. E.; Cao, Y.; Aryal, M.; Yen, Y. F.; Kalpathy-Cramer, J.; Shukla-Dave, A.; Fung, M.; Liang, J.; Boss, M.; Hylton, N. |
| Article Title: | Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network |
| 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 ADC4 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. © 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. |
| Keywords: | controlled study; human tissue; cancer patient; reproducibility; tumor localization; breast; tumor volume; clinical assessment; in vivo study; feasibility study; algorithm; multicenter study; breast tumor; image processing; diffusion weighted imaging; predictive value; online system; diagnostic test accuracy study; radiological parameters; parametric test; apparent diffusion coefficient; human; article; breast mri. |
| Journal Title: | Journal of Medical Imaging |
| Volume: | 5 |
| Issue: | 1 |
| ISSN: | 2329-4302 |
| Publisher: | SPIE |
| Date Published: | 2018-01-01 |
| Start Page: | 011003 |
| Language: | English |
| DOI: | 10.1117/1.jmi.5.1.011003 |
| PROVIDER: | scopus |
| PMCID: | PMC5633866 |
| PUBMED: | 29021993 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 4 December 2017 -- Source: Scopus |
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