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Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network
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 diffusio...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society of Photo-Optical Instrumentation Engineers
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633866/ https://www.ncbi.nlm.nih.gov/pubmed/29021993 http://dx.doi.org/10.1117/1.JMI.5.1.011003 |
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author | Newitt, David C. Malyarenko, Dariya Chenevert, Thomas L. Quarles, C. Chad Bell, Laura Fedorov, Andriy Fennessy, Fiona Jacobs, Michael A. Solaiyappan, Meiyappan Hectors, Stefanie Taouli, Bachir Muzi, Mark Kinahan, Paul E. Schmainda, Kathleen M. Prah, Melissa A. Taber, Erin N. Kroenke, Christopher Huang, Wei Arlinghaus, Lori R. Yankeelov, Thomas E. Cao, Yue Aryal, Madhava Yen, Yi-Fen Kalpathy-Cramer, Jayashree Shukla-Dave, Amita Fung, Maggie Liang, Jiachao Boss, Michael Hylton, Nola |
author_facet | Newitt, David C. Malyarenko, Dariya Chenevert, Thomas L. Quarles, C. Chad Bell, Laura Fedorov, Andriy Fennessy, Fiona Jacobs, Michael A. Solaiyappan, Meiyappan Hectors, Stefanie Taouli, Bachir Muzi, Mark Kinahan, Paul E. Schmainda, Kathleen M. Prah, Melissa A. Taber, Erin N. Kroenke, Christopher Huang, Wei Arlinghaus, Lori R. Yankeelov, Thomas E. Cao, Yue Aryal, Madhava Yen, Yi-Fen Kalpathy-Cramer, Jayashree Shukla-Dave, Amita Fung, Maggie Liang, Jiachao Boss, Michael Hylton, Nola |
author_sort | Newitt, David C. |
collection | PubMed |
description | 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 ([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 in vivo [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. In vivo [Formula: see text] concordance was good, with typical biases of [Formula: see text] 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 [Formula: see text] 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. |
format | Online Article Text |
id | pubmed-5633866 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Society of Photo-Optical Instrumentation Engineers |
record_format | MEDLINE/PubMed |
spelling | pubmed-56338662018-10-10 Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network Newitt, David C. Malyarenko, Dariya Chenevert, Thomas L. Quarles, C. Chad Bell, Laura Fedorov, Andriy Fennessy, Fiona Jacobs, Michael A. Solaiyappan, Meiyappan Hectors, Stefanie Taouli, Bachir Muzi, Mark Kinahan, Paul E. Schmainda, Kathleen M. Prah, Melissa A. Taber, Erin N. Kroenke, Christopher Huang, Wei Arlinghaus, Lori R. Yankeelov, Thomas E. Cao, Yue Aryal, Madhava Yen, Yi-Fen Kalpathy-Cramer, Jayashree Shukla-Dave, Amita Fung, Maggie Liang, Jiachao Boss, Michael Hylton, Nola J Med Imaging (Bellingham) Quantitative Imaging Methods and Translational Developments–Honoring the Memory of Dr. Larry Clarke 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 ([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 in vivo [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. In vivo [Formula: see text] concordance was good, with typical biases of [Formula: see text] 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 [Formula: see text] 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. Society of Photo-Optical Instrumentation Engineers 2017-10-10 2018-01 /pmc/articles/PMC5633866/ /pubmed/29021993 http://dx.doi.org/10.1117/1.JMI.5.1.011003 Text en © The Authors. https://creativecommons.org/licenses/by/3.0/ 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. |
spellingShingle | Quantitative Imaging Methods and Translational Developments–Honoring the Memory of Dr. Larry Clarke Newitt, David C. Malyarenko, Dariya Chenevert, Thomas L. Quarles, C. Chad Bell, Laura Fedorov, Andriy Fennessy, Fiona Jacobs, Michael A. Solaiyappan, Meiyappan Hectors, Stefanie Taouli, Bachir Muzi, Mark Kinahan, Paul E. Schmainda, Kathleen M. Prah, Melissa A. Taber, Erin N. Kroenke, Christopher Huang, Wei Arlinghaus, Lori R. Yankeelov, Thomas E. Cao, Yue Aryal, Madhava Yen, Yi-Fen Kalpathy-Cramer, Jayashree Shukla-Dave, Amita Fung, Maggie Liang, Jiachao Boss, Michael Hylton, Nola Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network |
title | Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network |
title_full | Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network |
title_fullStr | Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network |
title_full_unstemmed | Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network |
title_short | Multisite concordance of apparent diffusion coefficient measurements across the NCI Quantitative Imaging Network |
title_sort | multisite concordance of apparent diffusion coefficient measurements across the nci quantitative imaging network |
topic | Quantitative Imaging Methods and Translational Developments–Honoring the Memory of Dr. Larry Clarke |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5633866/ https://www.ncbi.nlm.nih.gov/pubmed/29021993 http://dx.doi.org/10.1117/1.JMI.5.1.011003 |
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