Insights on detecting clinically significant prostate cancer in PI-RADS v2.1 scores of 4 and 5

Main Article Content

Reza Habibi Tirtashi Narges Tamaskani Fatemeh Salamat Behrouz Ghazimoghaddam Babak Niakan Nematollah Nematollahi Mohammad Hadi Gharib, MD

Abstract

Background: Previous studies have identified various predictors for clinically significant prostate cancer in biopsy-naïve patients.


Aims: To identify clinical variables associated with clinically significant prostate cancer diagnosis using systematic biopsy combined with cognitive targeted biopsy.


Methods: This retrospective study analyzed data from 76 biopsy-naïve men who underwent systematic biopsy combined with cognitive targeted biopsy due to Prostate Imaging Reporting and Data System (PI-RADS) 4 or 5 lesions detected on prebiopsy prostate multiparametric magnetic resonance imaging between March 2020 and September 2022. Binary logistic regression was used to identify independent predictors of clinically significant prostate cancer, with odds ratio and 95% confidence intervals.


Results: The overall detection rate for clinically significant prostate cancer was 44.7%. In univariable analyses, prostate-specific antigen density ≥0.16 ng/ml2 (odds ratio 57.6 [95% confidence intervals 7.13-464.77]), PI-RADS 5 (odds ratio 10.41 [95% confidence intervals 3.47-31.2]), peripheral zone lesions (odds ratio 3.85 [95% confidence intervals 1.32-11.24]), and biopsy density ≥ 0.26 core/ml (odds ratio 2.95 [95% confidence intervals 1.09-8.01]) were significantly associated with clinically significant prostate cancer (p<0.05) and were entered to multivariable analysis. Considering p<0.2 for selecting variables for multivariable analysis, a single lesion (odds ratio 2.09 [95% confidence intervals 0.81-5.34]) and transition zone lesions (odds ratio 0.45 [95% confidence intervals 0.17-1.14) were also included. According to Multivariable analysis results, prostate-specific antigen density ≥0.16 ng/ml2 (odds ratio 49.88 [95% confidence intervals 4.96-501.47]) and PI-RADS 5 (odds ratio 19.89 [95% confidence intervals 3.36-117.55]) were significant independent predictors of clinically significant prostate cancer, while peripheral zone lesions (odds ratio 0.97 [95% confidence intervals 0.09-10.05]), biopsy density ≥0.26 core/ml (odds ratio 3.44 [95% confidence intervals 0.46-25.68]), a single lesion (odds ratio 3.34 [95% confidence intervals 0.72-15.5]), and transition zone lesions (odds ratio 1.18 [95% confidence intervals 0.15-8.88]) were not.


Conclusions: The clinical implementation of PI-RADS version 2.1 combined with systematic biopsy combined with cognitive targeted biopsy yielded an acceptable overall detection rate for clinically significant prostate cancer. Moreover, PI-RADS 5 and prostate-specific antigen density ≥0.16 ng/ml2 were significant predictors of positive systematic biopsy combined with cognitive targeted biopsy results.

Keywords: Prostate Cancer, Clinically Significant Prostate Cancer, Multiparametric Magnetic Resonance Imaging, Prostate-Specific Antigen Density, Biopsy Density, Prostate Imaging Reporting and Data System, PI-RADS v2.1, Cancer Detection Rate

Article Details

How to Cite
TIRTASHI, Reza Habibi et al. Insights on detecting clinically significant prostate cancer in PI-RADS v2.1 scores of 4 and 5. Medical Research Archives, [S.l.], v. 12, n. 10, oct. 2024. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/5974>. Date accessed: 05 dec. 2024. doi: https://doi.org/10.18103/mra.v12i10.5974.
Section
Research Articles

References

1. Organization WH. Cancer. World Health Organization. Accessed 3 February, 2022. https://www.who.int/news-room/fact-sheets/detail/cancer

2. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2018;68(6):394-424.

3. Abbasi-Kangevari M, Ghamari S, Azangou-Khyavy M, Malekpour M, Rezaei N, Kolahi A, et al. The burden of prostate cancer in North Africa and Middle East, 1990-2019: Findings from the global burden of disease study. Frontiers in Oncology. 2022;12:961086-961086.

4. Moradi A, Zamani M, Moudi E. A systematic review and meta-analysis on incidence of prostate cancer in Iran. Health promotion perspectives. 2019;9(2):92.

5. Weinreb JC, Barentsz JO, Choyke PL, Cornud F, Haider MA, Macura KJ, et al. PI-RADS prostate imaging–reporting and data system: 2015, version 2. European urology. 2016;69(1):16-40.

6. Turkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, et al. Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2. European urology. 2019;76(3):340-351.

7. Park KJ, Choi SH, Kim Mh, Kim JK, Jeong IG. Performance of Prostate Imaging Reporting and Data System Version 2.1 for Diagnosis of Prostate Cancer: A Systematic Review and Meta‐Analysis. Journal of Magnetic Resonance Imaging. 2021;54 (1):103-112.

8. Oerther B, Engel H, Bamberg F, Sigle A, Gratzke C, Benndorf M. Cancer detection rates of the PI-RADSv2. 1 assessment categories: systematic review and meta-analysis on lesion level and patient level. Prostate cancer and prostatic diseases. 2022;25(2):256-263.

9. Schlemmer H-P, Bittencourt LK, D’Anastasi M, Domingues R, Khong P-L, Lockhat Z, et al. Global challenges for cancer imaging. Journal of Global Oncology. 2017;4:1-10.

10. Cata E, Andras I, Ferro M, Kadula P, Leucuta D, Musi G, et al. Systematic sampling during MRI-US fusion prostate biopsy can overcome errors of targeting—prospective single center experience after 300 cases in first biopsy setting. Translational Andrology and Urology. 2020;9(6):2510.

11. Koparal MY, Sözen TS, Karşıyakalı N, Aslan G, Akdoğan B, Şahin B, et al. Comparison of transperineal and transrectal targeted prostate biopsy using Mahalanobis distance matching within propensity score caliper method: A multicenter study of Turkish Urooncology Association. The Prostate. 2022;82(4):425-432.

12. Vural M, Coskun B, Kilic M, Durmaz S, Gumus T, Cengiz D, et al. In-bore MRI-guided prostate biopsy in a patient group with PI-RADS 4 and 5 targets: A single center experience. European Journal of Radiology. 2021;141:109785.

13. Coşkun M, Dönmez EMH, Akın Y, Öcal İ, Gümüş C, Uluç ME. Predictors of Clinically Significant Prostate Cancer: A Comparative Study of PSA, PSA Density, and MRI Parameters. Istanbul Medical Journal. 2021;22(1)

14. Tirtashi RH, Gharib MH, Tamaskani N. The real-life challenges in prebiopsy prostate mp-MRI: Experiences from a Middle Eastern Country. Medical Research Archives. 2024;12(5)

15. Brancato V, Di Costanzo G, Basso L, Tramontano L, Puglia M, Ragozzino A, et al. Assessment of DCE utility for PCa diagnosis using PI-RADS v2. 1: Effects on diagnostic accuracy and reproducibility. Diagnostics. 2020;10(3):164.

16. Chen Y, Ruan M, Zhou B, Hu X, Wang H, Liu H, et al. Cutoff Values of Prostate Imaging Reporting and Data System Version 2.1 Score in Men With Prostate-specific Antigen Level 4 to 10 ng/mL: Importance of Lesion Location. Clinical Genitourinary Cancer. 2021;19(4):288-295.

17. Kim HS, Kwon GY, Kim MJ, Park SY. Prostate imaging-reporting and data system: comparison of the diagnostic performance between version 2.0 and 2.1 for prostatic peripheral zone. Korean Journal of Radiology. 2021;22(7):1100.

18. Wei X, Xu J, Zhong S, Zou J, Cheng Z, Ding Z, et al. Diagnostic value of combining PI-RADS v2. 1 with PSAD in clinically significant prostate cancer. Abdominal Radiology. 2022;47(10):3574-3582.

19. Ge Q, Zhang S, Xu H, Zhang J, Fan Z, Li W, et al. Development and validation of a novel nomogram predicting clinically significant prostate cancer in biopsy‐naive men based on multi‐institutional analysis. Cancer Medicine. 2023;12 (24):21820-21829.

20. Haj-Mirzaian A, Burk KS, Lacson R, Glazer DI, Saini S, Kibel AS, et al. Magnetic Resonance Imaging, Clinical, and Biopsy Findings in Suspected Prostate Cancer: A Systematic Review and Meta-Analysis. JAMA Network Open. 2024;7 (3):e244258-e244258.

21. Wang S, Kozarek J, Russell R, Drescher M, Khan A, Kundra V, et al. Diagnostic performance of prostate-specific antigen density for detecting clinically significant prostate cancer in the era of magnetic resonance imaging: a systematic review and meta-analysis. European Urology Oncology. 2023;

22. Ma Z, Wang X, Zhang W, Gao K, Wang L, Qian L, et al. Developing a predictive model for clinically significant prostate cancer by combining age, PSA density, and mpMRI. World Journal of Surgical Oncology. 2023;21(1):83.

23. Stone NN, Crawford ED, Skouteris VM, Arangua P, Metsinis P-M, Lucia MS, et al. The ratio of the number of biopsy specimens to prostate volume (biopsy density) greater than 1.5 improves the prostate cancer detection rate in men undergoing transperineal biopsy of the prostate. The Journal of Urology. 2019;202(2):264-271.

24. Feng J, Chen K, Tian H, Abdulkarem A-qM, Tuo Y, Wang X, et al. Investigation of the Effectiveness of Prostate Biopsy Density in Predicting Prostate Cancer Under Cognitive and Systematic Biopsy in Multi-Parametric Magnetic Resonance Imaging (mpMRI). Cancer Management and Research. 2024:883-890.