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The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II

This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients wer...

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Autores principales: Huang, Wei, Chen, Yiyi, Fedorov, Andriy, Li, Xia, Jajamovich, Guido H., Malyarenko, Dariya I., Aryal, Madhava P., LaViolette, Peter S., Oborski, Matthew J., O'Sullivan, Finbarr, Abramson, Richard G., Jafari-Khouzani, Kourosh, Afzal, Aneela, Tudorica, Alina, Moloney, Brendan, Gupta, Sandeep N., Besa, Cecilia, Kalpathy-Cramer, Jayashree, Mountz, James M., Laymon, Charles M., Muzi, Mark, Kinahan, Paul E., Schmainda, Kathleen, Cao, Yue, Chenevert, Thomas L., Taouli, Bachir, Yankeelov, Thomas E., Fennessy, Fiona, Li, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Grapho Publications, LLC 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6403046/
https://www.ncbi.nlm.nih.gov/pubmed/30854447
http://dx.doi.org/10.18383/j.tom.2018.00027
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author Huang, Wei
Chen, Yiyi
Fedorov, Andriy
Li, Xia
Jajamovich, Guido H.
Malyarenko, Dariya I.
Aryal, Madhava P.
LaViolette, Peter S.
Oborski, Matthew J.
O'Sullivan, Finbarr
Abramson, Richard G.
Jafari-Khouzani, Kourosh
Afzal, Aneela
Tudorica, Alina
Moloney, Brendan
Gupta, Sandeep N.
Besa, Cecilia
Kalpathy-Cramer, Jayashree
Mountz, James M.
Laymon, Charles M.
Muzi, Mark
Kinahan, Paul E.
Schmainda, Kathleen
Cao, Yue
Chenevert, Thomas L.
Taouli, Bachir
Yankeelov, Thomas E.
Fennessy, Fiona
Li, Xin
author_facet Huang, Wei
Chen, Yiyi
Fedorov, Andriy
Li, Xia
Jajamovich, Guido H.
Malyarenko, Dariya I.
Aryal, Madhava P.
LaViolette, Peter S.
Oborski, Matthew J.
O'Sullivan, Finbarr
Abramson, Richard G.
Jafari-Khouzani, Kourosh
Afzal, Aneela
Tudorica, Alina
Moloney, Brendan
Gupta, Sandeep N.
Besa, Cecilia
Kalpathy-Cramer, Jayashree
Mountz, James M.
Laymon, Charles M.
Muzi, Mark
Kinahan, Paul E.
Schmainda, Kathleen
Cao, Yue
Chenevert, Thomas L.
Taouli, Bachir
Yankeelov, Thomas E.
Fennessy, Fiona
Li, Xin
author_sort Huang, Wei
collection PubMed
description This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate K(trans) (volume transfer rate constant), v(e) (extravascular, extracellular volume fraction), k(ep) (efflux rate constant), and τ(i) (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T(1) values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for K(trans), v(e), k(ep), and τ(i), respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in K(trans) and v(e) (wCV = 0.50 and 0.10, respectively), but had smaller effects on k(ep) and τ(i) (wCV = 0.39 and 0.22, respectively). k(ep) is less sensitive to AIF variation than K(trans), suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τ(i) parameter may have advantages over the conventional PK parameters in a longitudinal study.
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spelling pubmed-64030462019-03-08 The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II Huang, Wei Chen, Yiyi Fedorov, Andriy Li, Xia Jajamovich, Guido H. Malyarenko, Dariya I. Aryal, Madhava P. LaViolette, Peter S. Oborski, Matthew J. O'Sullivan, Finbarr Abramson, Richard G. Jafari-Khouzani, Kourosh Afzal, Aneela Tudorica, Alina Moloney, Brendan Gupta, Sandeep N. Besa, Cecilia Kalpathy-Cramer, Jayashree Mountz, James M. Laymon, Charles M. Muzi, Mark Kinahan, Paul E. Schmainda, Kathleen Cao, Yue Chenevert, Thomas L. Taouli, Bachir Yankeelov, Thomas E. Fennessy, Fiona Li, Xin Tomography Research Articles This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate K(trans) (volume transfer rate constant), v(e) (extravascular, extracellular volume fraction), k(ep) (efflux rate constant), and τ(i) (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T(1) values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for K(trans), v(e), k(ep), and τ(i), respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in K(trans) and v(e) (wCV = 0.50 and 0.10, respectively), but had smaller effects on k(ep) and τ(i) (wCV = 0.39 and 0.22, respectively). k(ep) is less sensitive to AIF variation than K(trans), suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τ(i) parameter may have advantages over the conventional PK parameters in a longitudinal study. Grapho Publications, LLC 2019-03 /pmc/articles/PMC6403046/ /pubmed/30854447 http://dx.doi.org/10.18383/j.tom.2018.00027 Text en © 2019 The Authors. Published by Grapho Publications, LLC http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Articles
Huang, Wei
Chen, Yiyi
Fedorov, Andriy
Li, Xia
Jajamovich, Guido H.
Malyarenko, Dariya I.
Aryal, Madhava P.
LaViolette, Peter S.
Oborski, Matthew J.
O'Sullivan, Finbarr
Abramson, Richard G.
Jafari-Khouzani, Kourosh
Afzal, Aneela
Tudorica, Alina
Moloney, Brendan
Gupta, Sandeep N.
Besa, Cecilia
Kalpathy-Cramer, Jayashree
Mountz, James M.
Laymon, Charles M.
Muzi, Mark
Kinahan, Paul E.
Schmainda, Kathleen
Cao, Yue
Chenevert, Thomas L.
Taouli, Bachir
Yankeelov, Thomas E.
Fennessy, Fiona
Li, Xin
The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II
title The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II
title_full The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II
title_fullStr The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II
title_full_unstemmed The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II
title_short The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge, Part II
title_sort impact of arterial input function determination variations on prostate dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic modeling: a multicenter data analysis challenge, part ii
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6403046/
https://www.ncbi.nlm.nih.gov/pubmed/30854447
http://dx.doi.org/10.18383/j.tom.2018.00027
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