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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

Institution:
1Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: ffennessy@partners.org.
2Department of Radiology, Dana Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
3Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
4General Electric Global Research, Niskayuna, NY, USA.
5Department of Radiology, Children's Hospital, Harvard Medical School, Boston, MA, USA.
6Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Publisher:
Elsevier Science
Publication Date:
Sep-2015
Journal:
Magn Reson Imaging
Volume Number:
33
Issue Number:
4
Pages:
886-94
Citation:
Magn Reson Imaging. 2015 Sep;33(7):886-94.
PubMed ID:
25683515
PMCID:
PMC4465997
Keywords:
arterial input function, dynamic contrast enhancement, pharmacokinetic analysis, prostate cancer
Appears in Collections:
NCIGT, Prostate Group, SLICER, SPL
Sponsors:
R01 CA111288/CA/NCI NIH HHS/United States
P41 EB015898/EB/NIBIB NIH HHS/United States
U01 CA151261/CA/NCI NIH HHS/United States
Generated Citation:
Fennessy F.M., Fedorov A., Penzkofer T., Kim K.W., Hirsch M.S., Vangel M.G., Masry P., Flood T.A., Chang M-C., Tempany C.M., Mulkern R.V., Gupta S.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. Magn Reson Imaging. 2015 Sep;33(7):886-94. PMID: 25683515. PMCID: PMC4465997.
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Accurate pharmacokinetic (PK) modeling of Dynamic Contrast Enhanced MRI (DCE-MRI) in prostate cancer 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 prostate cancer (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. 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 (p<0.05). There was no significant difference in DA between AIF methods: highest for p90 Ktrans (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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