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La radiologia medica

, Volume 123, Issue 10, pp 778–787 | Cite as

Multiparametric magnetic resonance imaging versus Partin tables and the Memorial Sloan-Kettering cancer center nomogram in risk stratification of patients with prostate cancer referred to external beam radiation therapy

  • Rossano Girometti
  • Martina Pancot
  • Marco Andrea Signor
  • Martina Urbani
  • Luca Balestreri
  • Chiara Zuiani
MAGNETIC RESONANCE IMAGING

Abstract

Purpose

To evaluate the agreement between multiparametric Magnetic Resonance Imaging (mpMRI), Partin tables (PT) and the Memorial Sloan Kettering Cancer Center nomogram (MSKCCn) in assessing risk category in prostate cancer (PCa) patients referred to External Beam Radiotherapy (EBRT).

Materials and methods

In this bicentric study, we prospectively enrolled 80 PCa patients who underwent pre-EBRT mpMRI on a 3.0T magnet with a multiparametric protocol including high-resolution, multiplanar T2-weighted sequences, diffusion-weighted imaging and dynamic contrast-enhanced imaging. National comprehensive cancer network risk categories were assessed using prostate-specific-antigen level, Gleason score and the T-stage as defined by mpMRI or nomograms. Cohen’s kappa statistic was used to calculate the agreement between mpMRI and nomograms in assessing the T-stage (organ-confined (OC) vs. non-organ-confined (nOC) disease) and risk category (≤ low risk vs. intermediate risk vs. ≥ high risk).

Results

mpMRI showed poor agreement with PT and MSKCCn in assessing nOC versus OC (k = 0.16 for both), translating into an mpMRI-induced reclassification of PT- and MSKCCn-related risk category in 36.3% (k = 0.43) and 41.3% (k = 0.31) of cases, respectively, with most changes occurring towards intermediate risk category.

Conclusions

mpMRI showed low agreement with nomograms as a tool to stratify PCa risk, leading to significant risk reclassification. Assuming that mpMRI is a more reliable surrogate standard of reference for pathology, this technique should refine or replace nomograms in risk classification before EBRT.

Keywords

Prostate cancer Magnetic resonance imaging Nomograms Cancer T stage Risk assessment External beam radiation therapy 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have conflict of interest to disclose.

Ethical standards

All the procedures performed in the study were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments. Moreover, this study was approved by our referring Ethical Committee, and patients gave informed consent to participation.

References

  1. 1.
    American Cancer Society (2015). Cancer facts and figs. American Cancer Society Inc., Atlanta. http://www.cancer.org/research/cancerfactsstatistics/cancerfactsfigures2015/index. Accessed 28 Dec 2016
  2. 2.
    Mottet N, Bellmunt J, Bolla M et al (2017) EAU-ESTRO-SIOG guidelines on prostate cancer. Part 1: screening, diagnosis, and local treatment with curative intent. Eur Urol 71:618–629CrossRefGoogle Scholar
  3. 3.
    Pullini S, Signor MA, Pancot M et al (2016) Impact of multiparametric magnetic resonance imaging on risk group assessment of patients with prostate cancer addressed to external beam radiation therapy. Eur J Radiol 85:764–770CrossRefGoogle Scholar
  4. 4.
    Girometti R, Signor MA, Pancot M, Cereser L, Zuiani C (2016) Can multiparametric MRI replace Roach equations in staging prostate cancer before external beam radiation therapy? Eur J Radiol 85:2231–2237CrossRefGoogle Scholar
  5. 5.
    National Comprehensive Cancer Network (NCCN) clinical practice guidelines in Oncology (2016) Prostate cancer, version 3. http://www.nccn.org. Accessed 28 Dec 2016
  6. 6.
    Rodriguez G, Warde P, Picklest T et al (2012) Pre-treatment risk stratification of prostate cancer patients: a critical review. Can Urol Assoc J 6:121–127CrossRefGoogle Scholar
  7. 7.
    Counhago F, Recio M, del Cerro E et al (2014) Role of 3.0T multiparametric MRI in local staging on prostate cancer and clinical implications for radiation oncology. Clin Transl Oncol 16:993–999CrossRefGoogle Scholar
  8. 8.
    Counhago F, del Cerro E, Diaz-Gavela AA et al (2015) Tumor staging using 3.0T multiparametric MRI in prostate cancer: impact on treatment decisions for radical radiotherapy. Springerplus 4:789–796CrossRefGoogle Scholar
  9. 9.
    Eifler JB, Feng Z, Lin BN et al (2013) An updated prostate cancer staging nomogram (Partin Table) based on cases from 2006 to 2011. BJU Int 111:22–29CrossRefGoogle Scholar
  10. 10.
    Gupta RT, Faridi KF, Singh AA et al (2014) Comparing 3-T multiparametric MRI and the Partin tables to predict organ-confined prostate cancer after radical prostatectomy. Urol Oncol Semin Orig Investig 32:1292–1299CrossRefGoogle Scholar
  11. 11.
    Augustin H, Fritz GA, Ehammer T, Auprich M, Pummer K (2009) Accuracy of 3-Tesla magnetic resonance imaging for the staging of prostate cancer in comparison to the Partin tables. Acta Radiol 5:562–569CrossRefGoogle Scholar
  12. 12.
    Gupta RT, Flanagan Brown A, Kloss Silverman R et al (2016) Can radiologic staging with multiparametric MRI enhance the accuracy of the Partin tables in predicting organ-confined prostate cancer? AJR 207:87–95CrossRefGoogle Scholar
  13. 13.
    Feng TS, Sharif-Afshar AR, Wu J et al (2015) Multiparametric MRI improves accuracy of clinical nomograms for predicting extracapsular extension of prostate cancer. Urology 86:332–337CrossRefGoogle Scholar
  14. 14.
    Sobin LH, Gosporidariwicz M, Wittekind C (2009) TNM classification of malignant tumors. UICC International Union Against Cancer, 7th edn. Wiley, New York, pp 243–248Google Scholar
  15. 15.
    Barentsz JO, Richenberg J, Clements R et al (2012) ESUR prostate MR guidelines 2012. Eur Radiol 22:746–757CrossRefGoogle Scholar
  16. 16.
    Weinreb J, Barentsz JO, Choyke PL et al (2016) PI-RADS prostate imaging—reporting and data system: 2015, version 2. Eur Urol 69:16–40CrossRefGoogle Scholar
  17. 17.
    Rothke M, Blondin D, Schlemmer HP, Franiel T (2013) PI-RADS classification: structured reporting for MRI of the prostate. RoFo Fortschritte auf dem Gebiet der Rontgenstrahlen und der Bildgebenden Verfahren 185:253–261CrossRefGoogle Scholar
  18. 18.
    Kido A, Tamada T, Sone T et al (2017) Incremental value of high b value diffusion-weighted magnetic resonance imaging at 3-T for prediction of extracapsular extension in patients with prostate cancer: preliminary experience. Radiol Med 122:228–238CrossRefGoogle Scholar
  19. 19.
    Hinev AI, Anakievski D, Kolev N, Marianovski V, Hadjiev V (2011) Validation of pre- and postoperative nomograms used to predict the pathological stage and prostate cancer recurrence after radical prostatectomy: a multi-institutional study. J BUON 16:316–322PubMedGoogle Scholar
  20. 20.
    Panje C, Panje T, Putora PM et al (2015) Guidance of treatment decisions in risk-adapted primary radiotherapy for prostatde cancer using multiparamentric magnetic resonance imaging: a single center experience. Radiat Oncol 10:47–56CrossRefGoogle Scholar
  21. 21.
    Liauw SL, Kropp LM, Dess RT, Oto A (2016) Endoectal MRI for risk classification of localized prostate cancer: radiographic findings and influence on treatment decisions. Urol Oncol Semin Orig Investig 34:416e15–416e21CrossRefGoogle Scholar
  22. 22.
    Shariat SF, Kattan MW, Vickers AJ, Karakiewicz PI, Scardino PT (2009) Critical review of prostate cancer predictive tools. Future Oncol 5:1555–1584CrossRefGoogle Scholar
  23. 23.
    Di Blasio CJ, Rhee AC, Cho D, Scardino PT, Kattan MW (2003) Predicting clinical endpoints: treatment nomograms in prostate cancer. Semin Oncol 30:567–586CrossRefGoogle Scholar
  24. 24.
    Jambor I, Kuisma A, Kähkönen E et al (2018) Prospective evaluation of 18F-FACBC PET/CT and PET/MRI versus multiparametric MRI in intermediate- to high-risk prostate cancer patients/FLUCIPRO trial). Eur J Nucl Med Mol Imaging 45:355–364CrossRefGoogle Scholar
  25. 25.
    Piert M, Montgomery J, Kunju LP et al (2016) 18F-choline PET/MRI: the additional value of PET for MRI-guided transrectal prostate biopsies. J Nucl Med 57(7):1065–1070CrossRefGoogle Scholar
  26. 26.
    Turkbey B, Mena E, Lindenberg L et al (2017) 18F-DCFBC prostate-specific membrane antigen-targeted PET/CT imaging in localized prostate cancer. Clin Nucl Med 42:735–740CrossRefGoogle Scholar
  27. 27.
    Pasqualetti F, Panichi M, Saniato A et al (2016) [18F]Choline PET/CT ans stereotactic body radiotherapy on treatment decision making of oligometastatic prostate cancer patients: preliminary results. Radiat Oncol 11:9CrossRefGoogle Scholar
  28. 28.
    de Rooij M, Hamoen HJ, Witjes JA, Barentsz JO, Rovers MM (2016) Accuracy of magnetic resonance imaging for local staging of prostate cancer: a diagnostic meta-analysis. Eur Urol 70:233–245CrossRefGoogle Scholar
  29. 29.
    Chao KK, Goldstein NS, Yan D et al (2006) Clinicopathologic analysis of extracapsular extension in prostate cancer: should the clinical target volume be expanded posterolaterally to account for microscopic extension? Int J Radiat Oncol Biol Phys 65:999–1007CrossRefGoogle Scholar

Copyright information

© Italian Society of Medical Radiology 2018

Authors and Affiliations

  1. 1.Institute of Radiology, Department of MedicineUniversity of UdineUdineItaly
  2. 2.Department of Oncological Radiation TherapyAzienda Ospedaliero-Universitaria Santa Maria della MisericordiaUdineItaly
  3. 3.Department of Oncologic Radiation Therapy and Diagnostic ImagingCentro di Riferimento OncologicoAvianoItaly

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