Analysis of Prostate DCE-MRI: Comparison of Fast Exchange Limit and Fast Exchange Regimen Pharmacokinetic Models in the Discrimination of Malignant From Normal Tissue

Objectives:The ability to detect and identify malignant lesions within the prostate with conventional T2-weighted imaging is still limited. Although lesion conspicuity is improved with dynamic contrast-enhanced imaging there still remains some ambiguity as all tissues within the prostate may enhance. The aim of the current study was to take advantage of the improved signal-to-noise ratio at 3 T and assess the ability of 2 alternative pharmacokinetic models to clearly identify malignant areas within the prostate. We also aspire to assess the impact of tissue heterogeneity on variation in estimated pharmacokinetic parameters. Materials and Methods:Quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the prostate was implemented using multiple flip angles for T1 determination, and a rapid dynamic 3D T1-weighted acquisition with parallel imaging and a temporal resolution of 6.7 s. Pharmacokinetic analysis was performed for regions of tumor, normal-appearing peripheral zone (PZ), and central gland (CG) using fast exchange limit (FXL) or fast exchange regimen (FXR) models. Cell density was obtained from hematoxylin and eosin stained whole mount radical prostatectomy specimens. Results:Native tissue T1 was significantly lower in tumor and PZ tissue than in CG. The FXL model revealed increased mean Ktrans, kep, and ve in tumor and CG compared with PZ. With the FXR model, fitting was improved and all parameters were significantly increased, however, there were no longer significant differences between regions for ve. The additional parameter of the FXR model, &tgr;i, nominally representing mean lifetime of intracellular water, was significantly decreased in tumor compared with both PZ and CG. Rate constants for CG were significantly lower than those of tumor for both models. In addition, for all tissues, Ktrans and ve were positively correlated with cell density. Conclusions:Accounting for a finite water exchange rate between cells and their environment improves the discrimination of malignant from benign tissues within the prostate and may aid staging accuracy and ability to monitor response to treatment.

[1]  V. Laudone,et al.  Angiogenesis and prostate cancer: in vivo and in vitro expression of angiogenesis factors by prostate cancer cells. , 1998, Urology.

[2]  G P Liney,et al.  Proton MR T2 Maps Correlate With The Citrate Concentration in the Prostate , 1996, NMR in biomedicine.

[3]  Ting-Yim Lee,et al.  An Adiabatic Approximation to the Tissue Homogeneity Model for Water Exchange in the Brain: I. Theoretical Derivation , 1998, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[4]  L. Kramer,et al.  Dynamic contrast‐enhanced MRI study of male pelvic perfusion at 3T: Preliminary clinical report , 2007, Journal of magnetic resonance imaging : JMRI.

[5]  Takeo Ishigaki,et al.  Differentiation of noncancerous tissue and cancer lesions by apparent diffusion coefficient values in transition and peripheral zones of the prostate , 2005, Journal of magnetic resonance imaging : JMRI.

[6]  Seong Ho Park,et al.  Wash‐in rate on the basis of dynamic contrast‐enhanced MRI: Usefulness for prostate cancer detection and localization , 2005, Journal of magnetic resonance imaging : JMRI.

[7]  Jae-Joon Chung,et al.  Prostate Cancer: Added Value of Subtraction Dynamic Imaging in 3T Magnetic Resonance Imaging with a Phased-array Body Coil , 2008, Yonsei medical journal.

[8]  H. Hricak,et al.  Chronic prostatitis: MR imaging and 1H MR spectroscopic imaging findings--initial observations. , 2004, Radiology.

[9]  P. Tofts Modeling tracer kinetics in dynamic Gd‐DTPA MR imaging , 1997, Journal of magnetic resonance imaging : JMRI.

[10]  Stefan A Reinsberg,et al.  Combined use of diffusion-weighted MRI and 1H MR spectroscopy to increase accuracy in prostate cancer detection. , 2007, AJR. American journal of roentgenology.

[11]  T. Tong,et al.  Cancer statistics, 1994 , 1994, CA: a cancer journal for clinicians.

[12]  M. Brawer,et al.  Predictors of pathologic stage in prostatic carcinoma. The role of neovascularity , 1994, Cancer.

[13]  Michael J. Wilson,et al.  Microvessel density as a molecular marker for identifying high-grade prostatic intraepithelial neoplasia precursors to prostate cancer. , 2004, Experimental and molecular pathology.

[14]  R Novario,et al.  Microvessel density in prostate carcinoma , 2002, Prostate Cancer and Prostatic Diseases.

[15]  Hai-Ling Margaret Cheng,et al.  T1 measurement of flowing blood and arterial input function determination for quantitative 3D T1‐weighted DCE‐MRI , 2007, Journal of magnetic resonance imaging : JMRI.

[16]  Rong Zhou,et al.  Simultaneous measurement of arterial input function and tumor pharmacokinetics in mice by dynamic contrast enhanced imaging: Effects of transcytolemmal water exchange , 2004, Magnetic resonance in medicine.

[17]  Harry Quon,et al.  Transcytolemmal water exchange in pharmacokinetic analysis of dynamic contrast‐enhanced MRI data in squamous cell carcinoma of the head and neck , 2007, Journal of magnetic resonance imaging : JMRI.

[18]  M Recht,et al.  Method for the quantitative assessment of contrast agent uptake in dynamic contrast‐enhanced MRI , 1994, Magnetic resonance in medicine.

[19]  Michael Brady,et al.  Extracting and visualizing physiological parameters using dynamic contrast-enhanced magnetic resonance imaging of the breast , 2005, Medical Image Anal..

[20]  Wei Huang,et al.  Evidence for shutter‐speed variation in CR bolus‐tracking studies of human pathology , 2005, NMR in biomedicine.

[21]  Gabriel P. Krestin,et al.  Contrast‐Enhanced Endorectal Coil MRI in Local Staging of Prostate Carcinoma , 1995, Journal of computer assisted tomography.

[22]  K. Uğurbil,et al.  Determination of blood longitudinal relaxation time (T1) at high magnetic field strengths. , 2007, Magnetic resonance imaging.

[23]  H. Schlemmer,et al.  Can pre-operative contrast-enhanced dynamic MR imaging for prostate cancer predict microvessel density in prostatectomy specimens? , 2004, European Radiology.

[24]  Olivier Rouvière,et al.  Characterization of time-enhancement curves of benign and malignant prostate tissue at dynamic MR imaging , 2003, European Radiology.

[25]  J. Kurhanewicz,et al.  1H MR spectroscopy of normal and malignant human prostates in Vivo , 1990 .

[26]  J C Waterton,et al.  Quantification of endothelial permeability, leakage space, and blood volume in brain tumors using combined T1 and T2* contrast‐enhanced dynamic MR imaging , 2000, Journal of magnetic resonance imaging : JMRI.

[27]  Jason A Koutcher,et al.  Prostate cancer: identification with combined diffusion-weighted MR imaging and 3D 1H MR spectroscopic imaging--correlation with pathologic findings. , 2008, Radiology.

[28]  C. Kim,et al.  Localization of Prostate Cancer Using 3T MRI: Comparison of T2-Weighted and Dynamic Contrast-Enhanced Imaging , 2006, Journal of computer assisted tomography.

[29]  B Hamm,et al.  [MRI for troubleshooting detection of prostate cancer]. , 2005, RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin.

[30]  L R Schad,et al.  Pharmacokinetic parameters in CNS Gd-DTPA enhanced MR imaging. , 1991, Journal of computer assisted tomography.

[31]  Thomas E Yankeelov,et al.  Incorporating the effects of transcytolemmal water exchange in a reference region model for DCE‐MRI analysis: Theory, simulations, and experimental results , 2008, Magnetic resonance in medicine.

[32]  Gary P Liney,et al.  Correlation of ADC and T2 Measurements With Cell Density in Prostate Cancer at 3.0 Tesla , 2009, Investigative radiology.

[33]  J F Debatin,et al.  Optimization of prostate carcinoma staging: comparison of imaging and clinical methods. , 1996, Clinical radiology.

[34]  H. Hricak,et al.  MR imaging of the prostate gland: normal anatomy. , 1987, AJR. American journal of roentgenology.

[35]  G. Parker,et al.  Prostate cancer: evaluation of vascular characteristics with dynamic contrast-enhanced T1-weighted MR imaging--initial experience. , 2004, Radiology.

[36]  Xavier Golay,et al.  Determining the longitudinal relaxation time (T1) of blood at 3.0 Tesla , 2004, Magnetic resonance in medicine.

[37]  J. Oesterling,et al.  Percent free prostate-specific antigen: the next frontier in prostate-specific antigen testing. , 1998, Urology.

[38]  J. Kurhanewicz,et al.  Citrate alterations in primary and metastatic human prostatic adenocarcinomas: 1H magnetic resonance spectroscopy and biochemical study , 1993, Magnetic resonance in medicine.

[39]  Silvia D. Chang,et al.  Combined diffusion‐weighted and dynamic contrast‐enhanced MRI for prostate cancer diagnosis—Correlation with biopsy and histopathology , 2006, Journal of magnetic resonance imaging : JMRI.

[40]  J. Overgaard,et al.  Immunohistochemical determination of tumor angiogenesis measured by the maximal microvessel density in human prostate cancer , 1998, APMIS : acta pathologica, microbiologica, et immunologica Scandinavica.

[41]  P. Carroll,et al.  Prostate cancer: effect of postbiopsy hemorrhage on interpretation of MR images. , 1995, Radiology.

[42]  M. Rifkin,et al.  MR imaging characteristics of noncancerous lesions of the prostate , 1992, Journal of magnetic resonance imaging : JMRI.

[43]  A. Heerschap,et al.  Characterization of human prostate cancer, benign prostatic hyperplasia and normal prostate by in vitro 1H and 31P magnetic resonance spectroscopy. , 1993, The Journal of urology.

[44]  Wei Huang,et al.  Shutter‐speed analysis of contrast reagent bolus‐tracking data: Preliminary observations in benign and malignant breast disease , 2005, Magnetic resonance in medicine.

[45]  Thomas E Yankeelov,et al.  Variation of the relaxographic “shutter‐speed” for transcytolemmal water exchange affects the CR bolus‐tracking curve shape , 2003, Magnetic resonance in medicine.

[46]  B. Nicolas Bloch,et al.  3 Tesla magnetic resonance imaging of the prostate with combined pelvic phased-array and endorectal coils; Initial experience(1). , 2004, Academic radiology.

[47]  D P Dearnaley,et al.  Dynamic contrast enhanced MRI of prostate cancer: correlation with morphology and tumour stage, histological grade and PSA. , 2000, Clinical radiology.

[48]  A. Hemal,et al.  Apparent diffusion coefficient of the prostate in men prior to biopsy: determination of a cut‐off value to predict malignancy of the peripheral zone , 2007, NMR in biomedicine.

[49]  Thomas Hambrock,et al.  Thirty-Two-Channel Coil 3T Magnetic Resonance-Guided Biopsies of Prostate Tumor Suspicious Regions Identified on Multimodality 3T Magnetic Resonance Imaging: Technique and Feasibility , 2008, Investigative radiology.

[50]  M. Knopp,et al.  Estimating kinetic parameters from dynamic contrast‐enhanced t1‐weighted MRI of a diffusable tracer: Standardized quantities and symbols , 1999, Journal of magnetic resonance imaging : JMRI.

[51]  Xin Li,et al.  Equilibrium transcytolemmal water‐exchange kinetics in skeletal muscle in vivo , 1999, Magnetic resonance in medicine.

[52]  J Kurhanewicz,et al.  Dynamic contrast‐enhanced MRI in normal and abnormal prostate tissues as defined by biopsy, MRI, and 3D MRSI , 2005, Magnetic resonance in medicine.

[53]  G P Liney,et al.  Differentiation of prostatic carcinoma and benign prostatic hyperplasia: Correlation between dynamic Gd‐DTPA‐enhanced MR imaging and histopathology , 1999, Journal of magnetic resonance imaging : JMRI.

[54]  M. Brawer,et al.  Quantitative microvessel density: A staging and prognostic marker for human prostatic carcinoma , 1996, Cancer.

[55]  Clare Allen,et al.  Dynamic contrast enhanced MRI in prostate cancer. , 2007, European journal of radiology.

[56]  P. Pasqualetti,et al.  Enhancement patterns of prostate cancer in dynamic MRI , 2003, European Radiology.

[57]  W. Tilley,et al.  Vascular endothelial growth factor (VEGF) expression in prostate cancer and benign prostatic hyperplasia. , 1997, The Journal of urology.