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

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dc.contributor.authorHuang, Wei
dc.contributor.authorChen, Yiyi
dc.contributor.authorFedorov, Andriy
dc.contributor.authorLi, Xia
dc.contributor.authorJajamovich, Guido H.
dc.contributor.authorMalyarenko, Dariya I.
dc.contributor.authorAryal, Madhava P.
dc.contributor.authorLaViolette, Peter S.
dc.contributor.authorOborski, Matthew J.
dc.contributor.authorO'Sullivan, Finbarr
dc.contributor.authorAbramson, Richard G.
dc.contributor.authorJafari-Khouzani, Kourosh
dc.contributor.authorAfzal, Aneela
dc.contributor.authorTudorica, Alina
dc.contributor.authorMoloney, Brendan
dc.contributor.authorGupta, Sandeep N.
dc.contributor.authorBesa, Cecilia
dc.contributor.authorKalpathy-Cramer, Jayashree
dc.contributor.authorMountz, James M.
dc.contributor.authorLaymon, Charles M.
dc.contributor.authorMuzi, Mark
dc.contributor.authorSchmainda, Kathleen
dc.contributor.authorCao, Yue
dc.contributor.authorChenevert, Thomas L.
dc.contributor.authorTaouli, Bachir
dc.contributor.authorYankeelov, Thomas E.
dc.contributor.authorFennessy, Fiona
dc.contributor.authorLi, Xin
dc.contributor.funderNational Institutes of Healthen
dc.contributor.funderOregon Health & Science University Center for Women's Healthen
dc.date.accessioned2019-09-23T09:56:47Z
dc.date.available2019-09-23T09:56:47Z
dc.date.issued2019-03
dc.description.abstractThis 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 Ktrans (volume transfer rate constant), ve (extravascular, extracellular volume fraction), kep (efflux rate constant), and τi (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T1 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 Ktrans, ve, kep, and τi, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in Ktrans and ve (wCV = 0.50 and 0.10, respectively), but had smaller effects on kep and τi (wCV = 0.39 and 0.22, respectively). kep is less sensitive to AIF variation than Ktrans, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τi parameter may have advantages over the conventional PK parameters in a longitudinal study.en
dc.description.sponsorshipNational Institutes of Health (Grants U01-CA154602, U01-CA151261, U01-CA183848, U01-CA154601, U01-CA148131, U01-CA176110, U01-CA172320, U01-CA142565, U01-CA166104, and U01-CA140230); Oregon Health & Science University Center for Women's Health (Circle of Giving award)en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationHuang, W., Chen, Y., Fedorov, A., Li, X., Jajamovich, G. H., Malyarenko, D. I., Aryal, M. P., LaViolette, P. S., Oborski, M. J., O'Sullivan, F., Abramson, R. G., Jafari-Khouzani, K., Afzal, A., Tudorica, A., Moloney, B., Gupta, S. N., Besa, C., Kalpathy-Cramer, J., Mountz, J. M., Laymon, C. M., Muzi, M., Kinahan, P. E., Schmainda, K., Cao, Y., Chenevert, T. L., Taouli, B., Yankeelov, T. E., Fennessy, F. and Li, X. (2019) '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', Tomography (Ann Arbor, Mich.), 5(1), pp. 99-109. (10pp.) DOI: 10.18383/j.tom.2018.00027en
dc.identifier.doi10.18383/j.tom.2018.00027en
dc.identifier.eissn2379-1381
dc.identifier.endpage109en
dc.identifier.issued1en
dc.identifier.journaltitleTomographyen
dc.identifier.startpage99en
dc.identifier.urihttps://hdl.handle.net/10468/8592
dc.identifier.volume5en
dc.language.isoenen
dc.publisherGrapho Publicationsen
dc.rights©2019 The Authors. Published by Grapho Publications, LLC This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectDCE-MRIen
dc.subjectArterial input functionen
dc.subjectVariationen
dc.subjectShutter-speed modelen
dc.subjectProstateen
dc.titleThe impact of arterial input function determination variations on prostate dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic modeling: a multicenter data analysis challenge, part IIen
dc.typeArticle (peer-reviewed)en
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