Dynamische kontrastmittelunterstützte MRT der Prostata: Vergleich von zwei Auswerteverfahren

 

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Zusammenfassung

Ziel: Der Wert eines kommerziell erhältlichen Nachverarbeitungsalgorithmus für eine dynamische kontrastmittelunterstützte MRT der Prostata für den Tumornachweis sollte durch eine Vergleichsuntersuchung mit einem klinisch erprobten selbstentwickelten Nachverarbeitungsalgorithmus geprüft werden. Material und Methoden: 48 Patienten mit gesichertem Prostatakarzinom wurden vor der Prostatektomie zusätzlich zur Standarduntersuchung mit der kombinierten Endorektal-Körper-Phased-Array-Spule mit T 1- und T 2-gewichteter Bildgebung mit der dynamischen kontrastmittelunterstützten Dual-Suszeptibilitätskontrast(DCE-DSC)-MRT untersucht. Die Datensätze wurden vergleichend mit einem selbstentwickelten Nachverarbeitungsalgorithmus und unter Nutzung lediglich der T 1-w dynamischen Bildgebung mit einem kommerziell erhältlichen Nachverarbeitungsalgorithmus der Firma INVIVO (Dyna CAD Prostata Workstation) ausgewertet und mit der Histologie verglichen. Ergebnisse: Die Sensitivität für den Tumornachweis lag für den selbstentwickelten Algorithmus bei 78 % und für den kommerziellen Auswertealgorithmus bei 60 %. Die Spezifität lag für den eigenen Algorithmus bei 79 versus 82 % für den kommerziellen Algorithmus. Die Treffsicherheit lag für den selbstentwickelten Algorithmus bei 79 versus 77,5 % für die kommerzielle Software. Der Chi-Qadrat-Test (McNemar-Bowker-Test) ergab jedoch keinen signifikanten Unterschied zwischen den Ergebnissen (p = 0,06). Schlussfolgerung: Für den Tumornachweis ergeben sich keine signifikanten Unterschiede zwischen dem selbstentwickelten experimentellen Nachverarbeitungsalgorithmus und dem kommerziellen Nachverarbeitungsalgorithmus. Die kommerzielle Auswertesoftware ermöglicht damit eine zuverlässige und zeitsparende Auswertung der dynamischen kontrastmittelunterstützten MRT der Prostata zum Tumornachweis.

Abstract

Purpose: To evaluate the usefulness of a commercially available post-processing software tool for detecting prostate cancer on dynamic contrast-enhanced magnetic resonance imaging (MRI) and to compare the results to those obtained with a custom-made post-processing algorithm already tested under clinical conditions. Materials and Methods: Forty-eight patients with proven prostate cancer were examined by standard MRI supplemented by dynamic contrast-enhanced dual susceptibility contrast (DCE-DSC) MRI prior to prostatectomy. A custom-made post-processing algorithm was used to analyze the MRI data sets and the results were compared to those obtained using a post-processing algorithm from Invivo Corporation (Dyna CAD for Prostate) applied to dynamic T 1-weighted images. Histology was used as the gold standard. Results: The sensitivity for prostate cancer detection was 78 % for the custom-made algorithm and 60 % for the commercial algorithm and the specificity was 79 % and 82 %, respectively. The accuracy was 79 % for our algorithm and 77.5 % for the commercial software tool. The chi-square test (McNemar-Bowker test) yielded no significant differences between the two tools (p = 0.06). Conclusion: The two investigated post-processing algorithms did not differ in terms of prostate cancer detection. The commercially available software tool allows reliable and fast analysis of dynamic contrast-enhanced MRI for the detection of prostate cancer.

Literatur

• 1 Ikonen S, Karkkainen P, Kivisaari L et al. Magnetic resonance imaging of clinically localized prostatic cancer.  J Urol. 1998;  159 915-919
  Google Scholar
• 2 Pegios W, Bentas W, Wittmann L et al. Kernspintomographisches Staging des Prostatakarzinoms mittels kombinierter Endorektal-Body-Phased-Array-Spule und histopathologische Korrelation.  Fortschr Röntgenstr. 2003;  175 1660-1666
  Google Scholar
• 3 Beyersdorff D, Darsow U, Stephan C et al. MRT des Prostatakarzinoms mit drei verschiedenen Spulensystemen: Abbildungsqualität des Tumors und Staging.  Fortschr Röntgenstr. 2003;  175 799-805
  Google Scholar
• 4 Gemeinhardt O, Lüdemann L, Prochnow D et al. Differentiation of prostate cancer from normal prostate tissue in an animal model: conventional MRI and dynamic contrast-enhanced MRI.  Fortschr Röntgenstr. 2005;  177 935-939
  Google Scholar
• 5 Mullerad M, Hricak H, Kuroiwa K et al. Comparison of endorectal magnetic resonance imaging, guided prostate biopsy and digital rectal examination in the preoperative anatomical localization of prostate cancer.  J Urol. 2005;  174 2158-2163
  Google Scholar
• 6 Beyersdorff D, Hamm B. MRT zur Problemlösung beim Nachweis des Prostatakarzinoms.  Fortschr Röntgenstr. 2005;  177 788-795
  Google Scholar
• 7 Beyersdorff D, Taupitz M, Winkelmann B et al. Patients with a history of elevated prostate-specific antigen levels and negative transrectal US-guided quadrant or sextant biopsy results: value of MR imaging.  Radiology. 2002;  224 701-706
  Google Scholar
• 8 Ikonen S, Kivisaari L, Tervahartiala P et al. Prostatic MR imaging. Accuracy in differentiating cancer from other prostatic disorders.  Acta Radiol. 2001;  42 348-354
  Google Scholar
• 9 Franiel T, Ludemann L, Rudolph B et al. Evaluation of normal prostate tissue, chronic prostatitis, and prostate cancer by quantitative perfusion analysis using a dynamic contrast-enhanced inversion-prepared dual-contrast gradient echo sequence.  Invest Radiol. 2008;  43 481-487
  Google Scholar
• 10 Franiel T, Ludemann L, Rudolph B et al. Prostate MR imaging: tissue characterization with pharmacokinetic volume and blood flow parameters and correlation with histologic parameters.  Radiology. 2009;  252 101-108
  Google Scholar
• 11 Franiel T, Ludemann L, Taupitz M et al. Pharmakokinetische MRT der Prostata: Parameter zur Unterscheidung von Low-grade- und High-grade-Prostatakarzinomen.  Fortschr Röntgenstr. 2009;  181 536-542
  Google Scholar
• 12 Shukla-Dave A, Hricak H, Ishill N M et al. Correlation of MR imaging and MR spectroscopic imaging findings with Ki-67, phospho-Akt, and androgen receptor expression in prostate cancer.  Radiology. 2009;  250 803-812
  Google Scholar
• 13 Zakian K L, Sircar K, Hricak H et al. Correlation of proton MR spectroscopic imaging with gleason score based on step-section pathologic analysis after radical prostatectomy.  Radiology. 2005;  234 804-814
  Google Scholar
• 14 Scheidler J, Vogel M, Gross P et al. Combined MRI and MRS in prostate cancer: improvement of spectral quality by susceptibility matching.  Fortschr Röntgenstr. 2009;  181 531-535
  Google Scholar
• 15 Schlemmer H P. Multiparametric MRI of the prostate: method for early detection of prostate cancer?.  Fortschr Röntgenstr. 2010;  182 1067-1075
  Google Scholar
• 16 Prochnow D, Beyersdorff D, Warmuth C et al. Implementation of a rapid inversion-prepared dual-contrast gradient echo sequence for quantitative dynamic contrast-enhanced magnetic resonance imaging of the human prostate.  Magn Reson Imaging. 2005;  23 983-990
  Google Scholar
• 17 Ludemann L, Prochnow D, Rohlfing T et al. Simultaneous quantification of perfusion and permeability in the prostate using dynamic contrast-enhanced magnetic resonance imaging with an inversion-prepared dual-contrast sequence.  Ann Biomed Eng. 2009;  37 749-762
  Google Scholar
• 18 Engelbrecht M R, Huisman H J, Laheij R J et al. Discrimination of prostate cancer from normal peripheral zone and central gland tissue by using dynamic contrast-enhanced MR imaging.  Radiology. 2003;  229 248-254
  Google Scholar
• 19 Kurhanewicz J, Swanson M G, Nelson S J et al. Combined magnetic resonance imaging and spectroscopic imaging approach to molecular imaging of prostate cancer.  J Magn Reson Imaging. 2002;  16 451-463
  Google Scholar
• 20 Kurhanewicz J, Vigneron D B, Nelson S J et al. Citrate as an in vivo marker to discriminate prostate cancer from benign prostatic hyperplasia and normal prostate peripheral zone: detection via localized proton spectroscopy.  Urology. 1995;  45 459-466
  Google Scholar
• 21 Scheidler J, Hricak H, Vigneron D B et al. Prostate cancer: localization with three-dimensional proton MR spectroscopic imaging – clinicopathologic study.  Radiology. 1999;  213 473-480
  Google Scholar
• 22 Shukla-Dave A, Hricak H, Eberhardt S C et al. Chronic prostatitis: MR imaging and 1 H MR spectroscopic imaging findings – initial observations.  Radiology. 2004;  231 717-724
  Google Scholar
• 23 Fütterer J J, Heijmink W TPJS, Scheenen W JT et al. Prostate Cancer Localization with Dynamic Contrast-enhanced MR Imaging and Proton MR Spectroscopic Imaging.  Radiology. 2006;  241 449-458
  Google Scholar
• 24 Brown G, Macvicar D A, Ayton V et al. The role of intravenous contrast enhancement in magnetic resonance imaging of prostatic carcinoma.  Clin-Radiol. 1995;  50 601-606
  Google Scholar
• 25 Huch Böni R A, Boner J A, Lutolf U M et al. Contrast-enhanced endorectal coil MRI in local staging of prostate carcinoma.  J-Comput-Assist-Tomogr. 1995;  19 232-237
  Google Scholar
• 26 Jager G J, Ruijter E T, Kaa C A et al. Dynamic TurboFLASH subtraction technique for contrast-enhanced MR imaging of the prostate: correlation with histopathologic results.  Radiology. 1997;  203 645-652
  Google Scholar
• 27 Padhani A R, Gapinski C J, Macvicar D A et al. Dynamic contrast enhanced MRI of prostate cancer: correlation with morphology and tumour stage, histological grade and PSA.  Clin Radiol. 2000;  55 99-109
  Google Scholar
• 28 Schlemmer H P, Merkle van de J, Grobholz R et al. Can pre-operative contrast-enhanced dynamic MR imaging for prostate cancer predict microvessel density in prostatectomy specimens?.  Eur Radiol. 2004;  14 309-317
  Google Scholar
• 29 Brix G, Semmler W, Port R et al. Pharmacokinetic parameters in CNS Gd-DTPA enhanced MR imaging.  J-Comput-Assist-Tomogr. 1991;  15 621-628
  Google Scholar
• 30 Kiessling F, Huber P E, Grobholz R et al. Dynamic magnetic resonance tomography and proton magnetic resonance spectroscopy of prostate cancers in rats treated by radiotherapy.  Invest Radiol. 2004;  39 34-44
  Google Scholar
• 31 Kiessling F, Lichy M, Grobholz R et al. Simple models improve the discrimination of prostate cancers from the peripheral gland by T 1-weighted dynamic MRI.  Eur Radiol. 2004;  14 1793-1801
  Google Scholar
• 32 Scherr M K, Seitz M, Muller-Lisse U G et al. MR-perfusion (MRP) and diffusion-weighted imaging (DWI) in prostate cancer: Quantitative and model-based gadobenate dimeglumine MRP parameters in detection of prostate cancer.  Eur J Radiol. 2010;  76 359-366
  Google Scholar
• 33 Perrotti M, Han K R, Epstein R E et al. Prospective evaluation of endorectal magnetic resonance imaging to detect tumor foci in men with prior negative prostastic biopsy: a pilot study.  J Urol. 1999;  162 1314-1317
  Google Scholar
• 34 Baltzer P A, Dietzel M, Vag T et al. Können farbkodierte parametrische Karten die Analyse dynamischer Anreicherungsmuster in der MR-Mammografie verbessern?.  Fortschr Röntgenstr. 2010;  182 254-260
  Google Scholar
• 35 Mullerad M, Hricak H, Wang L et al. Prostate cancer: detection of extracapsular extension by genitourinary and general body radiologists at MR imaging.  Radiology. 2004;  232 140-146
  Google Scholar
• 36 Carreira G C, Gemeinhardt O, Beyersdorff D et al. Effects of water exchange on MRI-based determination of relative blood volume using an inversion-prepared gradient echo sequence and a blood pool contrast medium.  Magn Reson Imaging. 2009;  27 360-369
  Google Scholar
• 37 Franiel T, Ludemann L, Taupitz M et al. MRI before and after external beam intensity-modulated radiotherapy of patients with prostate cancer: the feasibility of monitoring of radiation-induced tissue changes using a dynamic contrast-enhanced inversion-prepared dual-contrast gradient echo sequence.  Radiother Oncol. 2009;  93 241-245
  Google Scholar

Dr. Dirk Beyersdorff

Department of Radiology, Charité, Universitätsmedizin Berlin, Campus Mitte, Berlin

Charitéplatz 1

10117 Berlin

Phone: ++ 49/30/4 50 62 71 88

Fax: ++ 49/30/4 50 52 79 11

Email: dirk.beyersdorff@charite.de