1 March 2016 Bolus arrival time and its effect on tissue characterization with dynamic contrast-enhanced magnetic resonance imaging
Alireza Mehrtash, Sandeep N. Gupta, Dattesh Shanbhag, James V. Miller, Tina Kapur, Fiona M. Fennessy M.D., Ron Kikinis, Andriy Fedorov
Author Affiliations +
Abstract
Matching the bolus arrival time (BAT) of the arterial input function (AIF) and tissue residue function (TRF) is necessary for accurate pharmacokinetic (PK) modeling of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). We investigated the sensitivity of volume transfer constant (Ktrans) and extravascular extracellular volume fraction (ve) to BAT and compared the results of four automatic BAT measurement methods in characterization of prostate and breast cancers. Variation in delay between AIF and TRF resulted in a monotonous change trend of Ktrans and ve values. The results of automatic BAT estimators for clinical data were all comparable except for one BAT estimation method. Our results indicate that inaccuracies in BAT measurement can lead to variability among DCE-MRI PK model parameters, diminish the quality of model fit, and produce fewer valid voxels in a region of interest. Although the selection of the BAT method did not affect the direction of change in the treatment assessment cohort, we suggest that BAT measurement methods must be used consistently in the course of longitudinal studies to control measurement variability.
© 2016 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2016/$25.00 © 2016 SPIE
Alireza Mehrtash, Sandeep N. Gupta, Dattesh Shanbhag, James V. Miller, Tina Kapur, Fiona M. Fennessy M.D., Ron Kikinis, and Andriy Fedorov "Bolus arrival time and its effect on tissue characterization with dynamic contrast-enhanced magnetic resonance imaging," Journal of Medical Imaging 3(1), 014503 (1 March 2016). https://doi.org/10.1117/1.JMI.3.1.014503
Published: 1 March 2016
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Cited by 11 scholarly publications.
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KEYWORDS
Tissues

Magnetic resonance imaging

Principal component analysis

Tumors

Data modeling

Prostate

Error analysis

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