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Article

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

by
Wei Huang
1,*,
Yiyi Chen
1,
Andriy Fedorov
2,
Xia Li
3,
Guido H. Jajamovich
4,
Dariya I. Malyarenko
5,
Madhava P. Aryal
5,
Peter S. LaViolette
6,
Matthew J. Oborski
7,
Finbarr O'Sullivan
8,
Richard G. Abramson
9,
Kourosh Jafari-Khouzani
10,
Aneela Afzal
1,
Alina Tudorica
1,
Brendan Moloney
1,
Sandeep N. Gupta
3,
Cecilia Besa
4,
Jayashree Kalpathy-Cramer
10,
James M. Mountz
7,
Charles M. Laymon
7,
Mark Muzi
11,
Paul E. Kinahan
11,
Kathleen Schmainda
6,
Yue Cao
5,
Thomas L. Chenevert
5,
Bachir Taouli
4,
Thomas E. Yankeelov
12,
Fiona Fennessy
2 and
Xin Li
1,*add Show full author list remove Hide full author list
1
Oregon Health and Science University, Portland, OR 97239, USA; [email protected] (W.H.); [email protected] (X.L.)
2
Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
3
General Electric Global Research, Niskayuna, NY, USA
4
Icahn School of Medicine at Mt Sinai, New York, NY, USA
5
University of Michigan, Ann Arbor, MI, USA
6
Medical College of Wisconsin, Milwaukee, WI, USA
7
University of Pittsburgh, Pittsburgh, PA, USA
8
University College, Cork, Ireland
9
Vanderbilt University, Nashville, TN, USA
10
Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
11
University of Washington, Seattle, WA, USA
12
The University of Texas, Austin, TX, USA
 
add Show full affiliation list
 
remove Hide full affiliation list
*
Authors to whom correspondence should be addressed.
Tomography 2019, 5(1), 99-109; https://doi.org/10.18383/j.tom.2018.00027
Submission received: 12 December 2018 / Revised: 5 January 2019 / Accepted: 7 February 2019 / Published: 1 March 2019
Versions Notes

Abstract

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 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.
Keywords: DCE-MRI; arterial input function; variation; shutter-speed model; prostate DCE-MRI; arterial input function; variation; shutter-speed model; prostate

Share and Cite

MDPI and ACS Style

Huang, 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.; et al. 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 2019, 5, 99-109. https://doi.org/10.18383/j.tom.2018.00027

AMA Style

Huang W, Chen Y, Fedorov A, Li X, Jajamovich GH, Malyarenko DI, Aryal MP, LaViolette PS, Oborski MJ, O'Sullivan F, et al. 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. 2019; 5(1):99-109. https://doi.org/10.18383/j.tom.2018.00027

Chicago/Turabian Style

Huang, Wei, Yiyi Chen, Andriy Fedorov, Xia Li, Guido H. Jajamovich, Dariya I. Malyarenko, Madhava P. Aryal, Peter S. LaViolette, Matthew J. Oborski, Finbarr O'Sullivan, and et al. 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 5, no. 1: 99-109. https://doi.org/10.18383/j.tom.2018.00027

APA Style

Huang, 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., ... 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, 5(1), 99-109. https://doi.org/10.18383/j.tom.2018.00027

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