Top

Published in:

01-10-2014 | Urogenital

Correlation between dynamic contrast-enhanced MRI and quantitative histopathologic microvascular parameters in organ-confined prostate cancer

Authors: Cornelis G. van Niekerk, Jeroen A. W. M. van der Laak, Thomas Hambrock, Henk-Jan Huisman, J. Alfred Witjes, Jelle O. Barentsz, Christina A. Hulsbergen-van de Kaa

Published in: European Radiology | Issue 10/2014

Abstract

Objectives

To correlate pharmacokinetic parameters of 3-T dynamic contrast-enhanced (DCE-)MRI with histopathologic microvascular and lymphatic parameters in organ-confined prostate cancer.

Methods

In 18 patients with unilateral peripheral zone (pT2a) tumours who underwent DCE-MRI prior to radical prostatectomy (RP), the following pharmacokinetic parameters were assessed: permeability surface area volume transfer constant (K ^trans), extravascular extracellular volume (Ve) and rate constant (K _ep). In the RP sections blood and lymph vessels were visualised immunohistochemically and automatically examined and analysed. Parameters assessed included microvessel density (MVD), area (MVA) and perimeter (MVP) as well as lymph vessel density (LVD), area (LVA) and perimeter (LVP).

Results

A negative correlation was found between age and K ^trans and K _ep for tumour (r = −0.60, p = 0.009; r = −0.67, p = 0.002) and normal (r = −0.54, p = 0.021; r = −0.46, p = 0.055) tissue. No correlation existed between absolute values of microvascular parameters from histopathology and DCE-MRI. In contrast, the ratio between tumour and normal tissue (correcting for individual microvascularity variations) significantly correlated between K _ep and MVD (r = 0.61, p = 0.007) and MVP (r = 0.54, p = 0.022). The lymphovascular parameters showed only a correlation between LVA and K _ep (r = −0.66, p = 0.003).

Conclusions

Significant correlations between DCE-MRI and histopathologic parameters were found when correcting for interpatient variations in microvascularity.

Key Points

• Normal prostate tissue shows strong heterogeneity in microvascularity.

• Peripheral zone prostate cancer shows increased and less heterogeneous microvascularity.

• Normal and tumour tissue shows considerable variation in microvascularity between patients.

• DCE-MRI should take into account the interprostatic heterogeneity of microvasculature between patients.

Fine SW, Epstein JI (2008) A contemporary study correlating prostate needle biopsy and radical prostatectomy Gleason score. J Urol 179:1335–1338PubMedCrossRef

Barentsz JO, Richenberg J, Clements R et al (2012) ESUR prostate MR guidelines 2012. Eur Radiol 22:746–757PubMedCentralPubMedCrossRef

Baur AD, Maxeiner A, Franiel T et al (2014) Evaluation of the prostate imaging reporting and data system for the detection of prostate cancer by the results of targeted biopsy of the prostate. Invest Radiol 49:411–420PubMedCrossRef

Anastasiadis AG, Lichy MP, Nagele U et al (2006) MRI-guided biopsy of the prostate increases diagnostic performance in men with elevated or increasing PSA levels after previous negative TRUS biopsies. Eur Urol 50:738–748PubMedCrossRef

Hambrock T, Somford DM, Hoeks C et al (2010) Magnetic resonance imaging guided prostate biopsy in men with repeat negative biopsies and increased prostate specific antigen. J Urol 183:520–527PubMedCrossRef

Bigler SA, Deering RE, Brawer MK (1993) Comparison of microscopic vascularity in benign and malignant prostate tissue. Hum Pathol 24:220–226PubMedCrossRef

Pallares J, Rojo F, Iriarte J, Morote J, Armadans LI, de Torres I (2006) Study of microvessel density and the expression of the angiogenic factors VEGF, bFGF and the receptors Flt-1 and FLK-1 in benign, premalignant and malignant prostate tissues. Histol Histopathol 21:857–865PubMed

van Niekerk CG, van der Laak JA, Borger ME et al (2009) Computerized whole slide quantification shows increased microvascular density in pT2 prostate cancer as compared to normal prostate tissue. Prostate 69:62–69PubMedCrossRef

Dvorak HF, Nagy JA, Feng D, Brown LF, Dvorak AM (1999) Vascular permeability factor/vascular endothelial growth factor and the significance of microvascular hyperpermeability in angiogenesis. Curr Top Microbiol Immunol 237:97–132PubMed

10.

Puech P, Potiron E, Lemaitre L et al (2009) Dynamic contrast-enhanced-magnetic resonance imaging evaluation of intraprostatic prostate cancer: correlation with radical prostatectomy specimens. Urology 74:1094–1099PubMedCrossRef

11.

Yakar D, Hambrock T, Huisman H et al (2010) Feasibility of 3 T dynamic contrast-enhanced magnetic resonance-guided biopsy in localizing local recurrence of prostate cancer after external beam radiation therapy. Invest Radiol 45:121–125

12.

van Niekerk CG, Hulsbergen-van de Kaa CA, Barentsz JO, Witjes JA, van der Laak JA (2011) Quantitative analysis of lymph vessel characteristics in organ confined prostate cancer. Prostate 71:91–97PubMedCrossRef

13.

Brix G, Semmler W, Port R, Schad LR, Layer G, Lorenz WJ (1991) Pharmacokinetic parameters in CNS Gd-DTPA enhanced MR imaging. J Comput Assist Tomogr 15:621–628PubMedCrossRef

14.

Tofts PS, Brix G, Buckley DL et al (1999) Estimating kinetic parameters from dynamic contrast-enhanced T(1)-weighted MRI of a diffusible tracer: standardized quantities and symbols. J Magn Reson Imaging 10:223–232PubMedCrossRef

15.

Vos PC, Hambrock T, Hulsbergen-van de Kaa CA, Futterer JJ, Barentsz JO, Huisman HJ (2008) Computerized analysis of prostate lesions in the peripheral zone using dynamic contrast enhanced MRI. Med Phys 35:888–899PubMedCrossRef

16.

van Oort I, Bruins HM, Kiemeney LA, Knipscheer BC, Witjes JA, Hulsbergen-van de Kaa CA (2010) The length of positive surgical margins correlates with biochemical recurrence after radical prostatectomy. Histopathology 56:464–471PubMedCrossRef

17.

Epstein JI, Allsbrook WC Jr, Amin MB, Egevad LL, Grading Committee ISUP (2005) The 2005 International Society of Urological Pathology (ISUP) consensus conference on Gleason grading of prostatic carcinoma. Am J Surg Pathol 29:1228–1242PubMedCrossRef

18.

Hambrock T, Somford DM, Huisman HJ, van Oort IM, Witjes JA, Hulsbergen-van de Kaa CA, Scheenen T, Barentsz JO (2011) Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer. Radiology 259:453–461PubMedCrossRef

19.

Vos PC, Hambrock T, Barenstz JO, Huisman HJ (2009) Automated calibration for computerized analysis of prostate lesions using pharmacokinetic magnetic resonance images. Med Image Comput Comput Assist Interv 12:836–843PubMed

20.

Hambrock T, Vos PC, Hulsbergen-van de Kaa CA, Barentsz JO, Huisman HJ (2013) Prostate cancer: computer-aided diagnosis with multiparametric 3-T MR imaging–effect on observer performance. Radiology 266:521–530PubMedCrossRef

21.

Hlatky L, Hahnfeldt P, Folkman J (2002) Clinical application of antiangiogenic therapy: microvessel density, what it does and doesn’t tell us. J Natl Cancer Inst 94:883–893PubMedCrossRef

22.

Franiel T, Hamm B, Hricak H (2011) Dynamic contrast-enhanced magnetic resonance imaging and pharmacokinetic models in prostate cancer. Eur Radiol 21:616–626PubMedCrossRef

23.

Schlemmer HP, Merkle J, Grobholz R et al (2004) Can pre-operative contrast-enhanced dynamic MR imaging for prostate cancer predict microvessel density in prostatectomy specimens? Eur Radiol 14:309–317PubMedCrossRef

24.

Franiel T, Ludemann L, Rudolph B et al (2009) Prostate MR imaging: tissue characterization with pharmacokinetic volume and blood flow parameters and correlation with histologic parameters. Radiology 252:101–108PubMedCrossRef

25.

Bostwick DG, Grignon DJ, Hammond ME et al (2000) Prognostic factors in prostate cancer. College of American Pathologists Consensus Statement 1999. Arch Pathol Lab Med 124:995–1000PubMed

26.

Rosenkrantz AB, Sabach A, Babb JS et al (2013) Prostate cancer: comparison of dynamic contrast-enhanced MRI techniques for localisation of peripheral zone tumor. AJR Am J Roentgenol 201:W471–W478PubMedCrossRef

27.

Burton JB, Priceman SJ, Sung JL et al (2008) Suppression of prostate cancer nodal and systemic metastasis by blockade of the lymphangiogenic axis. Cancer Res 68:7828–7837PubMedCentralPubMedCrossRef

Title: Correlation between dynamic contrast-enhanced MRI and quantitative histopathologic microvascular parameters in organ-confined prostate cancer
Authors: Cornelis G. van Niekerk
Jeroen A. W. M. van der Laak
Thomas Hambrock
Henk-Jan Huisman
J. Alfred Witjes
Jelle O. Barentsz
Christina A. Hulsbergen-van de Kaa
Publication date: 01-10-2014
Publisher: Springer Berlin Heidelberg
Published in: European Radiology / Issue 10/2014
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-014-3301-z

At a glance: The STEP trials

Springer Medicine

Correlation between dynamic contrast-enhanced MRI and quantitative histopathologic microvascular parameters in organ-confined prostate cancer

Abstract

Objectives

Methods

Results

Conclusions

Key Points

At a glance: The STEP trials

Springer Medicine

Abstract

Objectives

Methods

Results

Conclusions

Key Points

Please log in to get access to this content

Other articles of this Issue 10/2014

Brain involvement in patients with inflammatory bowel disease: a voxel-based morphometry and diffusion tensor imaging study

Zoomed EPI-DWI of the head and neck with two-dimensional, spatially-selective radiofrequency excitation pulses

Granulomatous mastitis: changing clinical and imaging features with image-guided biopsy correlation

Aiming for a shorter rheumatoid arthritis MRI protocol: can contrast-enhanced MRI replace T2 for the detection of bone marrow oedema?

Prognosis of small hepatocellular nodules detected only at the hepatobiliary phase of Gd-EOB-DTPA-enhanced MR imaging as hypointensity in cirrhosis or chronic hepatitis

MR-sequences for prostate cancer diagnostics: validation based on the PI-RADS scoring system and targeted MR-guided in-bore biopsy