Skip to main content
Log in

Improvement of prostate cancer detection combining a computer-aided diagnostic system with TRUS-MRI targeted biopsy

  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

To validate a novel consensus method, called target-in-target, combining human analysis of mpMRI with automated CAD system analysis, with the aim to increasing the prostate cancer detection rate of targeted biopsies.

Methods

A cohort of 420 patients was enrolled and 253 patients were rolled out, due to exclusion criteria. 167 patients, underwent diagnostic 3T MpMRI. Two expert radiologists evaluated the exams adopting PI-RADSv2 and CAD system. When a CAD target overlapped with a radiologic one, we performed the biopsy in the overlapping area which we defined as target-in-target. Targeted TRUS-MRI fusion biopsy was performed in 63 patients with a total of 212 targets. The MRI data of all targets were quantitatively analyzed, and diagnostic findings were compared to pathologist’s biopsy reports.

Results

CAD system diagnostic performance exhibited sensitivity and specificity scores of 55.2% and 74.1% [AUC = 0.63 (0.54 ÷ 0.71)] , respectively. Human readers achieved an AUC value, in ROC analysis, of 0.71 (0.63 ÷ 0.79). The target-in-target method provided a detection rate per targeted biopsy core of 81.8 % vs. a detection rate per targeted biopsy core of 68.6 % for pure PI-RADS based on target definitions. The higher per-core detection rate of the target-in-target approach was achieved irrespective of the presence of technical flaws and artifacts.

Conclusions

A novel consensus method combining human reader evaluation with automated CAD system analysis of mpMRI to define prostate biopsy targets was shown to improve the detection rate per biopsy core of TRUS-MRI fusion biopsies. Results suggest that the combination of CAD system analysis and human reader evaluation is a winning strategy to improve targeted biopsy efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. De Angelis R, et al. (2014) Cancer survival in Europe 1999–2007 by country and age: results of EUROCARE-5—A population-based study. Lancet Oncol 15(1):23–34

    Article  PubMed  Google Scholar 

  2. Mottet N, et al. (2017) EAU-ESTRO-SIOG guidelines on prostate cancer. Part 1: screening, diagnosis, and local treatment with curative intent. Eur Urol. 71(4):618–629

    Article  PubMed  Google Scholar 

  3. Cancer Facts & Figures (2017). American Cancer Society.

  4. Itatani R, et al. (2014) Negative predictive value of multiparametric MRI for prostate cancer detection: outcome of 5-year follow-up in men with negative findings on initial MRI studies. Eur J Radiol 83(10):1740–1745

    Article  CAS  PubMed  Google Scholar 

  5. Schimmöller L, et al. (2014) Predictive power of the ESUR scoring system for prostate cancer diagnosis verified with targeted MR-guided in-bore biopsy. Eur J Radiol 83(12):2103–2108

    Article  PubMed  Google Scholar 

  6. Moore CM, et al. (2013) Image-guided prostate biopsy using magnetic resonance imaging-derived targets: a systematic review. Eur Urol 63(1):125–140

    Article  PubMed  Google Scholar 

  7. Thompson J, Lawrentschuk N, Frydenberg M, et al. (2013) The role of magnetic resonance imaging in the diagnosis and management of prostate cancer: the role of magnetic resonance imaging in the diagnosis and management of prostate cancer. BJU Int 112:6–20

    Article  PubMed  Google Scholar 

  8. Panebianco V, et al. (2018) Negative multiparametric magnetic resonance imaging for prostate cancer: what’s next? Eur Urol 74(1):48–54

    Article  PubMed  Google Scholar 

  9. Ahmed HU, et al. (2017) Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet 389(10071):815–822

    Article  PubMed  Google Scholar 

  10. Siddiqui MM, et al. (2015) Comparison of MR/ultrasound fusion-guided biopsy with ultrasound-guided biopsy for the diagnosis of prostate cancer. JAMA 313(4):390

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Radtke JP, et al. (2016) Multiparametric magnetic resonance imaging (MRI) and MRI–transrectal ultrasound fusion biopsy for index tumor detection: correlation with radical prostatectomy specimen. Eur Urol 70(5):846–853

    Article  PubMed  Google Scholar 

  12. Filson CP, et al. (2016) Prostate cancer detection with magnetic resonance-ultrasound fusion biopsy: the role of systematic and targeted biopsies: CaP detection with MR-US fusion biopsy. Cancer 122(6):884–892

    Article  PubMed  PubMed Central  Google Scholar 

  13. Salami SS, et al. (2015) In patients with a previous negative prostate biopsy and a suspicious lesion on magnetic resonance imaging, is a 12-core biopsy still necessary in addition to a targeted biopsy?: performance of mpMRI in predicting prostate cancer on repeat biopsy. BJU Int 115(4):562–570

    Article  PubMed  Google Scholar 

  14. Barentsz JO, et al. (2016) Synopsis of the PI-RADS v2 guidelines for multiparametric prostate magnetic resonance imaging and recommendations for use. Eur Urol 69(1):41–49

    Article  PubMed  Google Scholar 

  15. Kasivisvanathan V, et al. (2018) MRI-targeted or standard biopsy for prostate-cancer diagnosis. N Engl J Med. https://doi.org/10.1056/NEJMoa1801993

    Article  PubMed  Google Scholar 

  16. 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(2):521–530

    Article  PubMed  Google Scholar 

  17. Doi K (2007) Computer-aided diagnosis in medical imaging: historical review, current status and future potential. Comput Med Imaging Graph 31(4–5):198–211

    Article  PubMed  PubMed Central  Google Scholar 

  18. Vos PC, Hambrock T, Barenstz JO, Huisman HJ (2010) Computer-assisted analysis of peripheral zone prostate lesions using T2-weighted and dynamic contrast enhanced T1-weighted MRI. Phys Med Biol 55(6):1719–1734

    Article  PubMed  Google Scholar 

  19. Epstein JI (1994) Pathologic and clinical findings to predict tumor extent of nonpalpable (Stage T1 c) prostate cancer. JAMA 271(5):368

    Article  CAS  PubMed  Google Scholar 

  20. Simonetti G (2010) Imaging RM della prostata. Milan: Springer

    Google Scholar 

  21. Roethke MC, et al. (2016) Evaluation of an automated analysis tool for prostate cancer prediction using multiparametric magnetic resonance imaging. PLoS ONE 11(7):e0159803

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Panebianco V, et al. (2015) Multiparametric magnetic resonance imaging vs. standard care in men being evaluated for prostate cancer: a randomized study. Urol Oncol Semin Orig Investig 33(17):1–7

    Google Scholar 

  23. Wysock JS, et al. (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

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Valeria Panebianco.

Ethics declarations

Funding

No funding was received for this research.

Conflict of interest

All the authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the institutional board and the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Campa, R., Del Monte, M., Barchetti, G. et al. Improvement of prostate cancer detection combining a computer-aided diagnostic system with TRUS-MRI targeted biopsy. Abdom Radiol 44, 264–271 (2019). https://doi.org/10.1007/s00261-018-1712-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-018-1712-z

Keywords

Navigation