Applicability of PIRADs 2.1 scoring system to screen Prostate Cancer in a Ugandan population, a cross-sectional study.

Authors

  • Professor Michael Kawooya Ernest Cook University Author
  • Richard Malumba Ernest Cook University Author
  • Professor Samuel Kaggwa Mulago National Referral Hospital Author
  • Dr. Samson Lubowa K. Kamya Ernest Cook University Author
  • Dr. Henry Musinguzi Dabanja Uganda Cancer Institute image/svg+xml Author

DOI:

https://doi.org/10.51168/c3q1rs78

Keywords:

Prostate, cancer, Magnetic Resonance Imaging (MRI), Sub-Saharan Africa, BI-Parametric Magnetic Resonance Imaging (MRI), Prostate Imaging Reporting and Data System (PIRADS), Prostate Cancer, Uganda

Abstract

Background/Objectives:

Prostate Cancer (PCa) is highly prevalent in Africa. The Prostate Imaging Reporting and Data System (PIRADS) is used for detecting, staging, standardizing the acquisition, and reporting of BI-Parametric Magnetic Resonance Imaging (MRI) (Bp-MRI). The PIRADS is a “living” document and, through research, should be tested and validated for different healthcare settings. There is hardly any literature on the applicability and accuracy of the PIRADS 2.1 to screen for PCa in sub-Saharan Africa. The study sought to assess the applicability of the PIRADS 2.1 scoring system to screen PCa in sub-Saharan Africa.

Methods:

A retrospective review of imaging requisitions was done, including Bp-MRI, MRI reports, and histology reports, including the Gleason score, at an imaging institution in Uganda. The study assessed the ability of PIRADS alone, PIRADS and prostate specific antigen density (PSAD), PIRADS and Apparent Diffusion Coefficient (ADC), and PIRADS, PSAD, and ADC-combination to discriminate a positive histological prostate case. The study used the Area Under the Curve to determine the ability of PIRADS 2.1 to discriminate PCa.

Results:

The study reviewed 234 patient records, and of these, 99 were aged 65-74 years, and 48.7% were PCa histology-confirmed cases.  PIRADS alone had an AUC 0.70, a combination of PIRADS V2.1 and PSAD had an AUC score 0.73, while a combination of PIRADS V2.1, PSAD, and ADC had an AUC 0.72. 

Conclusions:

 The accuracy of PIRADS for PCa discrimination is acceptable with an AUC 70%. Predominantly peripheral zone location, together with the low Gleason score and the background changes of chronic prostatitis, may account for the low PIRADS cancer prediction.

Author Biographies

  • Professor Michael Kawooya, Ernest Cook University

    is a Professor of Radiology and a senior academic clinician with over 30 years of practice and academia in diagnostic imaging, medical education, and health systems strengthening in low- and middle-income settings. His work has focused on advancing radiology practice, imaging-based diagnosis, and capacity building, particularly in resource-limited environments. He has played a leading role in postgraduate training, research supervision, and the development of imaging services, with interests spanning MRI, ultrasound, and quality improvement in diagnostic care. Professor Kawooya has contributed significantly to regional and international collaborations aimed at improving access to safe, effective, and appropriate medical imaging in sub-Saharan Africa.

  • Richard Malumba, Ernest Cook University

    is a public health researcher with training in Health Services Research and interests in epidemiology and biostatistics. His work focuses on disease surveillance, diagnostic pathways, and the application of data-driven and artificial intelligence methods to priority health challenges in low- and middle-income settings. He has conducted research on infectious and chronic diseases, including tuberculosis, prostate cancer, chronic respiratory diseases, and HIV-related conditions. His research emphasizes improving screening, risk stratification, and health system performance using routinely collected health data, with a particular focus on strengthening evidence to inform clinical practice and policy in sub-Saharan Africa

  • Professor Samuel Kaggwa , Mulago National Referral Hospital

    is a senior Ugandan surgeon and urologist with extensive expertise in prostate cancer, general surgery, and surgical education. He is a Professor of Surgery at Makerere University and a Senior Consultant Urologist at Mulago Hospital and Mengo Hospital. His research focuses on improving surgical outcomes in resource-limited settings, including refinements in open retropubic radical prostatectomy and preoperative prostate assessment. He has led and co-investigated studies on urinary continence recovery, prostate volume measurement, and health system strategies to expand access to essential surgical services. Prof. Kaggwa is actively involved in postgraduate teaching, mentorship, and regional capacity building in urology and surgery.

  • Dr. Samson Lubowa K. Kamya, Ernest Cook University

    is a radiologist and medical imaging specialist with extensive experience in clinical diagnostic radiology and hospital-based imaging services. Dr. Kamya has also served as an assistant lecturer at Makerere University and held administrative and clinical roles at Mulago and Rubaga Hospitals. His training includes apprenticeships in pediatric and MR imaging, a Master’s degree in Medicine from Makerere University, and a Postgraduate Diploma in Management from UMI Kampala. He is actively engaged in community service and professional mentorship in Uganda.

  • Dr. Henry Musinguzi Dabanja , Uganda Cancer Institute

     is a Ugandan urologist and clinician-scientist specializing in urologic oncology. He is currently Consultant Urologist and Head of Surgical Urologic Oncology at the Uganda Cancer Institute and a visiting urologist at Kampala Hospital. Dr. Dabanja holds a Fellowship in Urologic Oncology (UCI–UCSF) and a Master of Medicine in General Surgery (Makerere University). His work focuses on clinical care, surgical training, and research in urology, with interests in prostate and bladder cancers, reconstructive urology, and minimally invasive techniques. He has presented and published research internationally and actively contributes to surgical education and capacity building in sub-Saharan Africa.

References

1. Wang, L., Lu, B., He, M., Wang, Y., Wang, Z., & Du, L. (2022). Prostate cancer incidence and mortality: global status and temporal trends in 89 countries from 2000 to 2019. Frontiers in Public Health, 10, 811044.

2. Okuku, F., Orem, J., Holoya, G., De Boer, C., Thompson, C. L., & Cooney, M. M. (2016). Prostate cancer burden at the Uganda cancer institute. Journal of global oncology, 2(4), 181–185.

3. Stenman, U.-H., Leinonen, J., Alfthan, H., Rannikko, S., Tuhkanen, K., & Alfthan, O. (1991). A complex between prostate-specific antigen and α1-antichymotrypsin is the major form of prostate-specific antigen in serum of patients with prostatic cancer: assay of the complex improves clinical sensitivity for cancer. Cancer research, 51(1), 222–226.

4. Murphy, G., Haider, M., Ghai, S., & Sreeharsha, B. (2013). The expanding role of MRI in prostate cancer. AJR Am J Roentgenol, 201(6), 1229–38.

5. Pesapane, F., Acquasanta, M., Meo, R. D., Agazzi, G. M., Tantrige, P., Codari, M., … Sardanelli, F. (2021). Comparison of sensitivity and specificity of biparametric versus multiparametric prostate mri in the detection of prostate cancer in 431 men with elevated prostate-specific antigen levels. Diagnostics, 11(7), 1223.

6. Bass, E. J., Pantovic, A., Connor, M., Gabe, R., Padhani, A. R., Rockall, A., … Ahmed, H. U. (2021). A systematic review and meta-analysis of the diagnostic accuracy of biparametric prostate MRI for prostate cancer in men at risk. Prostate Cancer and Prostatic Diseases, 24(3), 596–611.

7. Weinreb, J. C., Barentsz, J. O., Choyke, P. L., Cornud, F., Haider, M. A., Macura, K. J., … Tempany, C. M. (2016). PI-RADS prostate imaging–reporting and data system: 2015, version 2. European urology, 69(1), 16–40.

8. Park, K. J., Choi, S. H., Kim, M., Kim, J. K., & Jeong, I. G. (2021). 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, 54(1), 103–112.

9. Distler, F. A., Radtke, J. P., Bonekamp, D., Kesch, C., Schlemmer, H.-P., Wieczorek, K., … Hadaschik, B. A. (2017). The value of PSA density in combination with PI-RADSTM for the accuracy of prostate cancer prediction. The Journal of urology, 198(3), 575–582.

10. Jordan, E. J., Fiske, C., Zagoria, R., & Westphalen, A. C. (2018). PI-RADS v2 and ADC values: is there room for improvement? Abdominal Radiology, 43(11), 3109–3116.

11. Walker, S. M., Mehralivand, S., Harmon, S. A., Sanford, T., Merino, M. J., Wood, B. J., … Turkbey, B. (2020). Prospective evaluation of PI-RADS version 2.1 for prostate cancer detection. AJR. American journal of roentgenology, 1.

12. Danneman, D., Drevin, L., Robinson, D., Stattin, P., & Egevad, L. (2015). Gleason inflation 1998–2011: a registry study of 97 168 men. BJU International, 115(2), 248–255. https://doi.org/10.1111/bju.12671

13. Rawla, P. (2019). Epidemiology of prostate cancer. World journal of oncology, 10(2), 63.

14. Vickers, A. J., Sjoberg, D. D., Ulmert, D., Vertosick, E., Roobol, M. J., Thompson, I., … Scardino, P. T. (2014). Empirical estimates of prostate cancer overdiagnosis by age and prostate-specific antigen. BMC medicine, 12(1), 1–7.

15. Schröder, F. H., Hugosson, J., Carlsson, S., Tammela, T., Määttänen, L., Auvinen, A., … Roobol, M. J. (2012). Screening for prostate cancer decreases the risk of developing metastatic disease: findings from the European Randomized Study of Screening for Prostate Cancer (ERSPC). European urology, 62(5), 745–752.

16. ACR. (2019). Prostate Imaging – Reporting and Data System Version 2.1. Retrieved from https://www.acr.org/-/media/ACR/Files/RADS/Pi-RADS/PIRADS-V2-1.pdf

17. Yu, X., Liu, R., Song, L., Gao, W., Wang, X., & Zhang, Y. (2023). Differences in the pathogenetic characteristics of prostate cancer in the transitional and peripheral zones and the possible molecular biological mechanisms. Frontiers in Oncology, 13, 1165732.

18. Danneman, D., Drevin, L., Robinson, D., Stattin, P., & Egevad, L. (2015). Gleason inflation 1998–2011: a registry study of 97 168 men. BJU international, 115(2), 248–255.

19. Manetta, R., Palumbo, P., Gianneramo, C., Bruno, F., Arrigoni, F., Natella, R., … Di Cesare, E. (2019). Correlation between ADC values and Gleason score in evaluation of prostate cancer: multicentre experience and review of the literature. Gland surgery, 8(Suppl 3), S216.

20. Nagarajan, R., Margolis, D., Raman, S., Sheng, K., King, C., Reiter, R., & Thomas, M. A. (2012). Correlation of Gleason scores with diffusion-weighted imaging findings of prostate cancer. Advances in urology, 2012.

21. Anwar, S. S. M., Anwar Khan, Z., Shoaib Hamid, R., Haroon, F., Sayani, R., Beg, M., & Khattak, Y. J. (2014). Assessment of apparent diffusion coefficient values as predictor of aggressiveness in peripheral zone prostate cancer: comparison with Gleason score. International Scholarly Research Notices, 2014.

22. Fine, S. W., Al-Ahmadie, H. A., Vertosick, E., Vickers, A. J., Chen, Y.-B., Gopalan, A., … Reuter, V. E. (2022). Impact of Zone of Origin in Anterior Dominant Prostate Cancer: Long-Term Biochemical Recurrence-Free Survival in an Anatomically Well-Characterized Cohort. Urology Practice, 9(5), 459–465. https://doi.org/10.1097/UPJ.0000000000000322

23. Kasel-Seibert, M., Lehmann, T., Aschenbach, R., Guettler, F. V., Abubrig, M., Grimm, M.-O., … Franiel, T. (2016). Assessment of PI-RADS v2 for the detection of prostate cancer. European journal of radiology, 85(4), 726–731.

24. Cai, G.-H., Yang, Q.-H., Chen, W.-B., Liu, Q.-Y., Zeng, Y.-R., & Zeng, Y.-J. (2021). Diagnostic Performance of PI-RADS v2, Proposed Adjusted PI-RADS v2 and Biparametric Magnetic Resonance Imaging for Prostate Cancer Detection: A Preliminary Study. Current Oncology, 28(3), 1823–1834.

25. Hötker, A. M., Blüthgen, C., Rupp, N. J., Schneider, A. F., Eberli, D., & Donati, O. F. (2020). Comparison of the PI-RADS 2.1 scoring system to PI-RADS 2.0: Impact on diagnostic accuracy and inter-reader agreement. Plos one, 15(10), e0239975.

26. Nadler, R. B., Collins, M. M., Propert, K. J., Mikolajczyk, S. D., Knauss, J. S., Landis, J. R., … Network, C. P. C. R. (2006). Prostate-specific antigen test in diagnostic evaluation of chronic prostatitis/chronic pelvic pain syndrome. Urology, 67(2), 337–342.

27. Stevens, E., Truong, M., Bullen, J. A., Ward, R. D., Purysko, A. S., & Klein, E. A. (2020). Clinical utility of PSAD combined with PI-RADS category for the detection of clinically significant prostate cancer. In Urologic Oncology: Seminars and Original Investigations (Vol. 38, pp. 846-e9). Elsevier.

28. Lin, W. C., Westphalen, A. C., Silva, G. E., Chodraui Filho, S., Reis, R. B. dos, & Muglia, V. F. (2016). Comparison of PI-RADS 2, ADC histogram-derived parameters, and their combination for the diagnosis of peripheral zone prostate cancer. Abdominal Radiology, 41(11), 2209–2217.

29. Yu, J., Fulcher, A. S., Turner, M. A., Cockrell, C. H., Cote, E. P., & Wallace, T. J. (2014). Prostate cancer and its mimics at multiparametric prostate MRI. The British journal of radiology, 87(1037), 20130659.

30. Wen, J., Liu, W., Shen, X., & Hu, W. (2024). PI-RADS v2. 1 and PSAD for the prediction of clinically significant prostate cancer among patients with PSA levels of 4–10 ng/ml. Scientific Reports, 14(1), 6570.

Downloads

Published

2026-03-14

Issue

Vol. 3 No. 3 (2026): March 2026 Issue

Section

Section of peer-reviewed articles

License

Copyright (c) 2026 Professor Michael Kawooya, Richard Malumba, Professor Samuel Kaggwa , Dr. Samson Lubowa K. Kamya, Dr. Henry Musinguzi Dabanja (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite

Kawooya, M., Malumba, R. ., Kaggwa, S., Kamya, S., & Dabanja, H. . (2026). Applicability of PIRADs 2.1 scoring system to screen Prostate Cancer in a Ugandan population, a cross-sectional study. Journal of Imaging Science for Diagnosis, 3(3), 12. https://doi.org/10.51168/c3q1rs78

Most read articles by the same author(s)

Similar Articles

You may also start an advanced similarity search for this article.