Quantitative pharmacokinetic analysis of prostate cancer DCE-MRI at 3T: Comparison of two arterial input functions on cancer detection with digitized whole mount histopathological validation

Fiona M. Fennessy, Andriy Fedorov, Tobias Penzkofer, Kyung Won Kim, Michelle S. Hirsch, Mark G. Vangel, Paul Masry, Trevor A. Flood, Ming Ching Chang, Clare M. Tempany, Robert V. Mulkern, Sandeep N. Gupta

Research output: Contribution to journalArticle

Abstract

Accurate pharmacokinetic (PK) modeling of dynamic contrast enhanced MRI (DCE-MRI) in prostate cancer (PCa) requires knowledge of the concentration time course of the contrast agent in the feeding vasculature, the so-called arterial input function (AIF). The purpose of this study was to compare AIF choice in differentiating peripheral zone PCa from non-neoplastic prostatic tissue (NNPT), using PK analysis of high temporal resolution prostate DCE-MRI data and whole-mount pathology (WMP) validation. This prospective study was performed in 30 patients who underwent multiparametric endorectal prostate MRI at 3.0T and WMP validation. PCa foci were annotated on WMP slides and MR images using 3D Slicer. Foci ≥0.5cm3 were contoured as tumor regions of interest (TROIs) on subtraction DCE (early-arterial - pre-contrast) images. PK analyses of TROI and NNPT data were performed using automatic AIF (aAIF) and model AIF (mAIF) methods. A paired t-test compared mean and 90th percentile (p90) PK parameters obtained with the two AIF approaches. Receiver operating characteristic (ROC) analysis determined diagnostic accuracy (DA) of PK parameters. Logistic regression determined correlation between PK parameters and histopathology. Mean TROI and NNPT PK parameters were higher using aAIF vs. mAIF (ptrans) (aAIF differences in the area under the ROC curve (Az) = 0.827; mAIF Az=0.93). Tumor cell density correlated with aAIF Ktrans (p=0.03).Our results indicate that DCE-MRI using both AIF methods is excellent in discriminating PCa from NNPT. If quantitative DCE-MRI is to be used as a biomarker in PCa, the same AIF method should be used consistently throughout the study.

Original languageEnglish (US)
JournalMagnetic Resonance Imaging
Volume33
Issue number7
DOIs
StatePublished - Sep 1 2015
Externally publishedYes

Fingerprint

Pharmacokinetics
Magnetic resonance imaging
Prostatic Neoplasms
Tumors
Pathology
Neoplasms
Tissue
ROC Curve
Prostate
Biomarkers
Contrast Media
Logistics
Cell Count
Logistic Models
Cells
Prospective Studies

Keywords

  • Arterial input function
  • Dynamic contrast enhancement
  • Pharmacokinetic analysis
  • Prostate cancer

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging
  • Biomedical Engineering

Cite this

Quantitative pharmacokinetic analysis of prostate cancer DCE-MRI at 3T : Comparison of two arterial input functions on cancer detection with digitized whole mount histopathological validation. / Fennessy, Fiona M.; Fedorov, Andriy; Penzkofer, Tobias; Kim, Kyung Won; Hirsch, Michelle S.; Vangel, Mark G.; Masry, Paul; Flood, Trevor A.; Chang, Ming Ching; Tempany, Clare M.; Mulkern, Robert V.; Gupta, Sandeep N.

In: Magnetic Resonance Imaging, Vol. 33, No. 7, 01.09.2015.

Research output: Contribution to journalArticle

Fennessy, Fiona M. ; Fedorov, Andriy ; Penzkofer, Tobias ; Kim, Kyung Won ; Hirsch, Michelle S. ; Vangel, Mark G. ; Masry, Paul ; Flood, Trevor A. ; Chang, Ming Ching ; Tempany, Clare M. ; Mulkern, Robert V. ; Gupta, Sandeep N. / Quantitative pharmacokinetic analysis of prostate cancer DCE-MRI at 3T : Comparison of two arterial input functions on cancer detection with digitized whole mount histopathological validation. In: Magnetic Resonance Imaging. 2015 ; Vol. 33, No. 7.
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abstract = "Accurate pharmacokinetic (PK) modeling of dynamic contrast enhanced MRI (DCE-MRI) in prostate cancer (PCa) requires knowledge of the concentration time course of the contrast agent in the feeding vasculature, the so-called arterial input function (AIF). The purpose of this study was to compare AIF choice in differentiating peripheral zone PCa from non-neoplastic prostatic tissue (NNPT), using PK analysis of high temporal resolution prostate DCE-MRI data and whole-mount pathology (WMP) validation. This prospective study was performed in 30 patients who underwent multiparametric endorectal prostate MRI at 3.0T and WMP validation. PCa foci were annotated on WMP slides and MR images using 3D Slicer. Foci ≥0.5cm3 were contoured as tumor regions of interest (TROIs) on subtraction DCE (early-arterial - pre-contrast) images. PK analyses of TROI and NNPT data were performed using automatic AIF (aAIF) and model AIF (mAIF) methods. A paired t-test compared mean and 90th percentile (p90) PK parameters obtained with the two AIF approaches. Receiver operating characteristic (ROC) analysis determined diagnostic accuracy (DA) of PK parameters. Logistic regression determined correlation between PK parameters and histopathology. Mean TROI and NNPT PK parameters were higher using aAIF vs. mAIF (ptrans) (aAIF differences in the area under the ROC curve (Az) = 0.827; mAIF Az=0.93). Tumor cell density correlated with aAIF Ktrans (p=0.03).Our results indicate that DCE-MRI using both AIF methods is excellent in discriminating PCa from NNPT. If quantitative DCE-MRI is to be used as a biomarker in PCa, the same AIF method should be used consistently throughout the study.",
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AU - Penzkofer, Tobias

AU - Kim, Kyung Won

AU - Hirsch, Michelle S.

AU - Vangel, Mark G.

AU - Masry, Paul

AU - Flood, Trevor A.

AU - Chang, Ming Ching

AU - Tempany, Clare M.

AU - Mulkern, Robert V.

AU - Gupta, Sandeep N.

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