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World Journal of Urology

, Volume 37, Issue 2, pp 327–335 | Cite as

Defining the target prior to prostate fusion biopsy: the effect of MRI reporting on cancer detection

  • Niklas WesthoffEmail author
  • Fabian Siegel
  • Christian Peter
  • Svetlana Hetjens
  • Stefan Porubsky
  • Thomas Martini
  • Jost von Hardenberg
  • Maurice Stephan Michel
  • Johannes Budjan
  • Manuel Ritter
Original Article
  • 93 Downloads

Abstract

Purpose

Definition of targets in multiparametric MRI (mpMRI) prior to MRI/TRUS fusion prostate biopsy either by urologist or radiologist, as a prose report or by illustration is crucial for accurate targeted biopsies (TB). The objective was to analyze the effect of MRI reporting on target definition and cancer detection.

Methods

202 patients underwent MRI/TRUS fusion biopsy with Artemis™ (Eigen, USA). mpMRI results were submitted in written form to urologists, who marked the targets in the proprietary software. An expert uroradiologist reviewed and marked mpMRI targets blinded to biopsy data. We compared number, localization and volume of targets between the observers and analyzed whether variations impaired TB results by bivariate and logistic regression models.

Results

Interobserver variability was moderate regarding number and low regarding localization of targets. Urologists overestimated target volumes significantly compared to radiologists (p = 0.045) and matching target volume between both observers was only 43.9%. Overall cancer detection rate was 69.8 and 52.0% by TB. A higher matching target volume was a significant predictor of cancer in TB (p < 0.001). Logistic regression revealed prostate volume and PI-RADS as independent predictors. Defining targets in incorrect T2w slices in the cranio-caudal axis are one presumable reason for missing cancer in TB.

Conclusions

A high concordance of the target definition between radiologist and urologist is mandatory for accurate TB. Optimized ROI definition is recommended to improve TB results, preferably as contouring in MRI sequences by the radiologist or, if not feasible, by precise MRI reports including specific localization in sequence and slice as well as an illustration. High prostate volume and low PI-RADS score have to be considered as limiting factors for target definition.

Keywords

Prostatic neoplasms Multiparametric MRI Biopsy Fusion Interobserver variability 

Notes

Author contributions

NW: project development, data collection, data analysis, manuscript writing. FPS: project development, data analysis, manuscript editing. CP: data collection, manuscript editing. SH: data analysis, manuscript editing. SP: data collection, manuscript editing. TM: manuscript editing. JvH: manuscript editing. MSM: manuscript editing. JB: data collection, manuscript editing. MR: project development, manuscript editing.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standards

For this type of study formal consent is not required.

Supplementary material

345_2018_2400_MOESM1_ESM.pdf (25 kb)
Supplementary material 1 (PDF 24 kb)
345_2018_2400_MOESM2_ESM.pdf (32 kb)
Supplementary material 2 (PDF 31 kb)
345_2018_2400_MOESM3_ESM.pdf (29 kb)
Supplementary material 3 (PDF 29 kb)

References

  1. 1.
    Bjurlin MA, Meng X, Le Nobin J, Wysock JS, Lepor H, Rosenkrantz AB, Taneja SS (2014) Optimization of prostate biopsy: the role of magnetic resonance imaging targeted biopsy in detection, localization and risk assessment. J Urol 192(3):648–658.  https://doi.org/10.1016/j.juro.2014.03.117 CrossRefGoogle Scholar
  2. 2.
    Siddiqui MM, Rais-Bahrami S, Turkbey B, George AK, Rothwax J, Shakir N, Okoro C, Raskolnikov D, Parnes HL, Linehan WM, Merino MJ, Simon RM, Choyke PL, Wood BJ, Pinto PA (2015) Comparison of MR/ultrasound fusion-guided biopsy with ultrasound-guided biopsy for the diagnosis of prostate cancer. JAMA 313(4):390–397.  https://doi.org/10.1001/jama.2014.17942 CrossRefGoogle Scholar
  3. 3.
    Weinreb JC, Barentsz JO, Choyke PL, Cornud F, Haider MA, Macura KJ, Margolis D, Schnall MD, Shtern F, Tempany CM, Thoeny HC, Verma S (2016) PI-RADS prostate imaging—reporting and data system: 2015, Version 2. Eur Urol 69(1):16–40.  https://doi.org/10.1016/j.eururo.2015.08.052 CrossRefGoogle Scholar
  4. 4.
    Barentsz JO, Richenberg J, Clements R, Choyke P, Verma S, Villeirs G, Rouviere O, Logager V, Futterer JJ, European Society of Urogenital R (2012) ESUR prostate MR guidelines 2012. Eur Radiol 22(4):746–757.  https://doi.org/10.1007/s00330-011-2377-y CrossRefGoogle Scholar
  5. 5.
    Woo S, Suh CH, Kim SY, Cho JY, Kim SH (2017) Diagnostic performance of prostate imaging reporting and data system version 2 for detection of prostate cancer: a systematic review and diagnostic meta-analysis. Eur Urol.  https://doi.org/10.1016/j.eururo.2017.01.042 Google Scholar
  6. 6.
    Hamoen EH, de Rooij M, Witjes JA, Barentsz JO, Rovers MM (2015) Use of the prostate imaging reporting and data system (PI-RADS) for prostate cancer detection with multiparametric magnetic resonance imaging: a diagnostic meta-analysis. Eur Urol 67(6):1112–1121.  https://doi.org/10.1016/j.eururo.2014.10.033 CrossRefGoogle Scholar
  7. 7.
    European Association of Urology (EAU) (2017) Guidelines on prostate cancer. http://uroweb.org/guideline/prostate-cancer/. Accessed 8 Apr 2018
  8. 8.
    Deutsche Gesellschaft für Urologie e.V. (DGU) (2018) Interdisziplinäre Leitlinie der Qualität S3 zur Früherkennung, Diagnose und Therapie der verschiedenen Stadien des Prostatakarzinoms. https://www.awmf.org/uploads/tx_szleitlinien/043-022OLl_S3_Prostatakarzinom_2018-04.pdf. Accessed 8 Apr 2018
  9. 9.
    Ahmed HU, El-Shater Bosaily A, Brown LC, Gabe R, Kaplan R, Parmar MK, Collaco-Moraes Y, Ward K, Hindley RG, Freeman A, Kirkham AP, Oldroyd R, Parker C, Emberton M, Group PS (2017) Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet 389(10071):815–822.  https://doi.org/10.1016/s0140-6736(16)32401-1 CrossRefGoogle Scholar
  10. 10.
    Filson CP, Natarajan S, Margolis DJ, Huang J, Lieu P, Dorey FJ, Reiter RE, Marks LS (2016) Prostate cancer detection with magnetic resonance-ultrasound fusion biopsy: the role of systematic and targeted biopsies. Cancer 122(6):884–892.  https://doi.org/10.1002/cncr.29874 CrossRefGoogle Scholar
  11. 11.
    de Rooij M, Hamoen EH, Futterer JJ, Barentsz JO, Rovers MM (2014) Accuracy of multiparametric MRI for prostate cancer detection: a meta-analysis. AJR Am J Roentgenol 202(2):343–351.  https://doi.org/10.2214/AJR.13.11046 CrossRefGoogle Scholar
  12. 12.
    Shin T, Smyth TB, Ukimura O, Ahmadi N, de Castro Abreu AL, Ohe C, Oishi M, Mimata H, Gill IS (2017) Diagnostic accuracy of a five-point Likert scoring system for magnetic resonance imaging (MRI) evaluated according to results of MRI/ultrasonography image-fusion targeted biopsy of the prostate. BJU Int.  https://doi.org/10.1111/bju.13972 Google Scholar
  13. 13.
    Wysock JS, Rosenkrantz AB, Huang WC, Stifelman MD, Lepor H, Deng FM, Melamed J, Taneja SS (2014) A prospective, blinded comparison of magnetic resonance (MR) imaging-ultrasound fusion and visual estimation in the performance of MR-targeted prostate biopsy: the PROFUS trial. Eur Urol 66(2):343–351.  https://doi.org/10.1016/j.eururo.2013.10.048 CrossRefGoogle Scholar
  14. 14.
    Delongchamps NB, Peyromaure M, Schull A, Beuvon F, Bouazza N, Flam T, Zerbib M, Muradyan N, Legman P, Cornud F (2013) Prebiopsy magnetic resonance imaging and prostate cancer detection: comparison of random and targeted biopsies. J Urol 189(2):493–499.  https://doi.org/10.1016/j.juro.2012.08.195 CrossRefGoogle Scholar
  15. 15.
    Hausmann D, Aksoz N, von Hardenberg J, Martini T, Westhoff N, Buettner S, Schoenberg SO, Riffel P (2017) Prostate cancer detection among readers with different degree of experience using ultra-high b-value diffusion-weighted Imaging: is a non-contrast protocol sufficient to detect significant cancer? Eur Radiol.  https://doi.org/10.1007/s00330-017-5004-8 Google Scholar
  16. 16.
    Natarajan S, Marks LS, Margolis DJ, Huang J, Macairan ML, Lieu P, Fenster A (2011) Clinical application of a 3D ultrasound-guided prostate biopsy system. Urol Oncol 29(3):334–342.  https://doi.org/10.1016/j.urolonc.2011.02.014 CrossRefGoogle Scholar
  17. 17.
    Sonn GA, Natarajan S, Margolis DJ, MacAiran M, Lieu P, Huang J, Dorey FJ, Marks LS (2013) Targeted biopsy in the detection of prostate cancer using an office based magnetic resonance ultrasound fusion device. J Urol 189(1):86–91.  https://doi.org/10.1016/j.juro.2012.08.095 CrossRefGoogle Scholar
  18. 18.
    Moore CM, Kasivisvanathan V, Eggener S, Emberton M, Futterer JJ, Gill IS, Grubb Iii RL, Hadaschik B, Klotz L, Margolis DJ, Marks LS, Melamed J, Oto A, Palmer SL, Pinto P, Puech P, Punwani S, Rosenkrantz AB, Schoots IG, Simon R, Taneja SS, Turkbey B, Ukimura O, van der Meulen J, Villers A, Watanabe Y, Consortium S (2013) Standards of reporting for MRI-targeted biopsy studies (START) of the prostate: recommendations from an International Working Group. Eur Urol 64(4):544–552.  https://doi.org/10.1016/j.eururo.2013.03.030 CrossRefGoogle Scholar
  19. 19.
    Calio B, Sidana A, Sugano D, Gaur S, Jain A, Maruf M, Xu S, Yan P, Kruecker J, Merino M, Choyke P, Turkbey B, Wood B, Pinto P (2017) Changes in prostate cancer detection rate of MRI-TRUS fusion vs systematic biopsy over time: evidence of a learning curve. Prostate Cancer Prostatic Dis.  https://doi.org/10.1038/pcan.2017.34 Google Scholar
  20. 20.
    Gaziev G, Wadhwa K, Barrett T, Koo BC, Gallagher FA, Serrao E, Frey J, Seidenader J, Carmona L, Warren A, Gnanapragasam V, Doble A, Kastner C (2016) Defining the learning curve for multiparametric magnetic resonance imaging (MRI) of the prostate using MRI-transrectal ultrasonography (TRUS) fusion-guided transperineal prostate biopsies as a validation tool. BJU Int 117(1):80–86.  https://doi.org/10.1111/bju.12892 CrossRefGoogle Scholar
  21. 21.
    Le Nobin J, Rosenkrantz AB, Villers A, Orczyk C, Deng FM, Melamed J, Mikheev A, Rusinek H, Taneja SS (2015) Image guided focal therapy for magnetic resonance imaging visible prostate cancer: defining a 3-dimensional treatment margin based on magnetic resonance imaging histology co-registration analysis. J Urol 194(2):364–370.  https://doi.org/10.1016/j.juro.2015.02.080 CrossRefGoogle Scholar
  22. 22.
    de Gorski A, Roupret M, Peyronnet B, Le Cossec C, Granger B, Comperat E, Cussenot O, Renard-Penna R, Mozer P (2015) Accuracy of magnetic resonance imaging/ultrasound fusion targeted biopsies to diagnose clinically significant prostate cancer in enlarged compared to smaller prostates. J Urol 194(3):669–673.  https://doi.org/10.1016/j.juro.2015.03.025 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Niklas Westhoff
    • 1
    Email author
  • Fabian Siegel
    • 1
  • Christian Peter
    • 1
  • Svetlana Hetjens
    • 2
  • Stefan Porubsky
    • 3
  • Thomas Martini
    • 4
  • Jost von Hardenberg
    • 1
  • Maurice Stephan Michel
    • 1
  • Johannes Budjan
    • 5
  • Manuel Ritter
    • 1
  1. 1.Department of Urology, University Medical Center Mannheim, Medical Faculty MannheimUniversity of HeidelbergMannheimGermany
  2. 2.Institute of Medical Statistics and Biometry, University Medical Center Mannheim, Medical Faculty MannheimUniversity of HeidelbergMannheimGermany
  3. 3.Department of Pathology, University Medical Center Mannheim, Medical Faculty MannheimUniversity of HeidelbergMannheimGermany
  4. 4.Department of UrologyUniversity Medical Center UlmUlmGermany
  5. 5.Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty MannheimUniversity of HeidelbergMannheimGermany

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