Research Article
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Diffusion-Weighted Imaging and Multiparametric Prostate MRI in the Differentiation of PI-RADS 3, 4, and 5 Peripheral Zone Lesions

Year 2026, Volume: 21 Issue: 1 , 15 - 22 , 28.03.2026
https://doi.org/10.17517/ksutfd.1686570
https://izlik.org/JA57CS85HC

Abstract

Objective: PI-RADS (Prostate Imaging Reporting and Data System, Version) categorization based on multiparametric magnetic resonance imaging is an accepted method that has been revised several times for the early detection of prostate cancer. PI-RADS 2.1 is a scoring system designed to standardize assessment between centers. Based on the experience gained after the announcement of PI-RADS 2.0, version 2.1 offers important updates and clarifications, although it is an active scoring that continues to be updated. However, even the latest revision has introduced subjective concepts such as mild or marked. Improving the categorization may involve reorganization with objective numerical data. Continued advances in the study of prostate cancer and innovations in imaging technology will undoubtedly shape the future version of the reporting system. Material and Methods: Digital ADC (Apparent diffusion coefficient) mapping measurements, the basis of PI-RADS categorization for the peripheral zone, were determined in 91 pathologically diagnosed peripheral zone lesions with PI-RADS categories 3, 4, and 5. The mean values of these lesions were measured on ADC imaging, including at least 5 mm in the most prominent slice in the axial plane. Results: Statistically significant numerical cut-off values were determined based on ADC mapping characteristics, and an objective value was obtained that can be used instead of the terms mild or prominent in peripheral zone lesions. Conclusion: The obtained cut-off can be used in the scoring of peripheral zone lesions by predicting the malignancy risk of the lesion. The data obtained can also be used to revise the PI-RADS categorization. Thus, the accuracy of both the radiologist and the clinician can be proven. In addition, unnecessary biopsies can be prevented.

References

  • Raychaudhuri R, Lin DW, Montgomery RB. Prostate Cancer: A Review. JAMA. 2025;333(16):1433-1446. doi:10.1001/jama.2025.0228
  • Dee EC, Iyengar R, Narayan A, et al. National Cancer System Characteristics and Prostate Cancer Outcomes: An Analysis of Global Data. Prostate. 2025. doi:10.1002/pros.24901
  • Dai J, Tang X, Zhang T, et al. A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound. J Vis Exp. 2025;(217):10.3791/67873. doi:10.3791/67873
  • Barentsz JO, Richenberg J, Clements R, et al. ESUR prostate MR guidelines 2012. Eur Radiol. 2012;22:746-757. doi:10.1007/s00330-011-2377-y
  • Turkbey B, Rosenkrantz AB, Haider MA, et al. Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2. Eur Urol. 2019;76(3):340-351. doi:10.1016/j.eururo.2019.02.033
  • Greer MD, Brown AM, Shih JH, et al. Interobserver Variability of PI-RADS v2.1: A Multireader Study. Radiology. 2021;299(2):385-394. doi:10.1148/radiol.2021203290
  • Purasang V, Srisuwan T, Chaiyasoot K, et al. Quantitative MRI Biomarkers in Prostate Cancer: An AI-Driven Approach. Eur Radiol. 2022;32(1):512-523. doi:10.1007/s00330-021-08144-w
  • Padhani AR, Liu G, Koh DM, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 2009;11(2):102-125. doi:10.1593/neo.81328
  • Paudyal P, Mete U, Gorsi U, Kumar S, Kakkar N. Usefulness of multiparametric MRI for local staging of bladder cancer. Urologia. 2025;92(2):231-236. doi:10.1177/03915603241310390
  • Korbmacher M, Tranfa M, Pontillo G, et al. White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life. Neuroimage. 2025;310:121132. doi:10.1016/j.neuroimage.2025.121132
  • Lee S, Palmquist S, Ma J, Kaur H. Rectal MR Imaging. Radiol Clin North Am. 2025;63(3):419-434. doi:10.1016/j.rcl.2024.11.006
  • Girometti R, Cereser L, Bonato F, et al. Negative predictive value for cancer in patients with "Gray-Zone" PSA level and prior negative biopsy: Preliminary results with multiparametric 3.0 tesla MR. J Magn Reson Imaging. 2012;36(4):943-950. doi:10.1002/jmri.23703
  • Isebaert S, Van den Bergh L, Haustermans K, et al. Multiparametric MRI for prostate cancer localization in correlation to whole-mount histopathology. J Magn Reson Imaging. 2013;37(6):1392-1401. doi:10.1002/jmri.23938
  • Zhang S, Wan J, Xu Y, et al. Predictive Value of Multiparametric Magnetic Resonance Imaging (T2-weighted Imaging and Apparent Diffusion Coefficient) for Pathological Grading of Prostate Cancer: a Meta-Analysis. Int Braz J Urol. 2025;51(3):e20240509. doi:10.1590/S1677-5538.IBJU.2024.0509
  • Garcia-Becerra CA, Arias-Gallardo MI, Soltero-Molinar V, et al. Is biparametric MRI a feasible option for detecting clinically significant prostate cancer?: A systematic review and meta-analysis. Urol Oncol. 2025. doi:10.1016/j.urolonc.2024.12.262
  • Wang Y, Wang W, Yi N, et al. Detection of intermediate- and high-risk prostate cancer with biparametric magnetic resonance imaging: a systematic review and meta-analysis. Quant Imaging Med Surg. 2023;13(5):2791-2806. doi:10.21037/qims-22-1024
  • Bass EJ, Pantovic A, Connor M, et al. A systematic review and meta-analysis of the diagnostic accuracy of biparametric prostate MRI for prostate cancer in men at risk. Prostate Cancer Prostatic Dis. 2021;24(3):596-611. doi:10.1038/s41391-020-00298-w
  • Yang L, Tan Y, Dan H, Hu L, Zhang J. Diagnostic performance of diffusion-weighted imaging combined with dynamic contrast-enhanced magnetic resonance imaging for prostate cancer: a systematic review and meta-analysis. Acta Radiol. 2021;62(9):1238-1247. doi:10.1177/0284185120956269
  • Deforche M, Lefebvre Y, Diamand R, et al. Improved diagnostic accuracy of readout-segmented echo-planar imaging for peripheral zone clinically significant prostate cancer: a retrospective 3T MRI study. Sci Rep. 2024;14(1):3299. doi:10.1038/s41598-024-53898-0
  • De Perrot T, Sadjo Zoua C, Glessgen CG, et al. Diffusion-Weighted MRI in the Genitourinary System. J Clin Med. 2022;11(7):1921. doi:10.3390/jcm11071921
  • Fokkinga E, Hernandez-Tamames JA, Ianus A, et al. Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology. J Magn Reson Imaging. 2024;60(4):1278-1304. doi:10.1002/jmri.29144
  • Hambrock T, Somford DM, Huisman HJ, et al. Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer. Radiology. 2011;259(2):453-461. doi:10.1148/radiol.11091409
  • Kim TH, Kim CK, Park BK, et al. Relationship between Gleason score and apparent diffusion coefficients of diffusion-weighted magnetic resonance imaging in prostate cancer patients. Can Urol Assoc J. 2016;10(11-12):E377. doi:10.5489/cuaj.3896
  • Salami SS, Ben-Levi E, Yaskiv O, et al. Risk stratification of prostate cancer utilizing apparent diffusion coefficient value and lesion volume on multiparametric MRI. J Magn Reson Imaging. 2017;45(2):610-616. doi:10.1002/jmri.25363
  • Kido A, Kataoka M, Yamamoto A, et al. 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. 2017;122:228-238. doi:10.1007/s11547-016-0712-8
  • Nakamoto A, Onishi H, Tsuboyama T, et al. High-resolution Diffusion-weighted Imaging of the Prostate Using Multiplexed Sensitivity-encoding: Comparison with the Conventional and Reduced Field-of-view Techniques. Magn Reson Med Sci. 2025;24(1):58-65. doi:10.2463/mrms.mp.2023-0039
  • Bengtsson J, Thimansson E, Baubeta E, et al. Correlation between ADC, ADC ratio, and Gleason Grade group in prostate cancer patients undergoing radical prostatectomy: Retrospective multicenter study with different MRI scanners. Front Oncol. 2023;13:1079040. doi:10.3389/fonc.2023.1079040
  • Azeemuddin M, Awais M, ul Haq T, et al. Role of ADC values and ratios of MRI scan in differentiating typical from atypical/anaplastic meningiomas. J Pak Med Assoc. 2018;68(9):1403. doi:10.5455/JPMA.300645
  • Zhao S, Li Y, Ning N, et al. Association of peritumoral region features assessed on breast MRI and prognosis of breast cancer: a systematic review and meta-analysis. Eur Radiol. 2024;34(9):6108-6120. doi:10.1007/s00330-024-10612-y
  • Zabihollahy F, Naim S, Wibulpolprasert P, et al. Understanding Spatial Correlation Between Multiparametric MRI Performance and Prostate Cancer. J Magn Reson Imaging. 2024;60(5):2184-2195. doi:10.1002/jmri.29287
  • Jin P, Wang X, Ding Z, et al. Development and validation of risk-stratified biopsy decision pathways incorporating MRI and PSA-derived indicators. Ann Med. 2025;57(1):2446695. doi:10.1080/07853890.2024.2446695
  • Sridhar S, Abouelfetouh Z, Codreanu I, et al. The Role of Dynamic Contrast Enhanced Magnetic Resonance Imaging in Evaluating Prostate Adenocarcinoma: A Partially-Blinded Retrospective Study of a Prostatectomy Patient Cohort With Whole Gland Histopathology Correlation and Application of PI-RADS or TNM Staging. Prostate. 2025;85(5):413-423. doi:10.1002/pros.24843
  • Johnson PM, Dutt T, Ginocchio LA, et al. Prostate Cancer Risk Stratification and Scan Tailoring Using Deep Learning on Abbreviated Prostate MRI. J Magn Reson Imaging. 2025. doi:10.1002/jmri.29798

Periferik Zon Lezyonlarında PI-RADS 3, 4 ve 5 Ayrımında Difüzyon Ağırlıklı Görüntüleme ve Multiparametrik Prostat MR

Year 2026, Volume: 21 Issue: 1 , 15 - 22 , 28.03.2026
https://doi.org/10.17517/ksutfd.1686570
https://izlik.org/JA57CS85HC

Abstract

Amaç: Multiparametrik manyetik rezonans görüntülemeye dayalı PI-RADS (Prostate Imaging Reporting and Data System) kategorizasyonu, prostat kanserinin erken saptanmasında kabul görmüş bir yöntem olup çeşitli revizyonlardan geçmiştir. PI-RADS 2.1, merkezler arası değerlendirmeyi standardize etmeyi amaçlayan bir skorlama sistemidir. PI-RADS 2.0 sonrası kazanılan deneyime dayanarak geliştirilen 2.1 sürümü önemli güncellemeler ve açıklamalar sunmakla birlikte, güncellenmeye devam eden dinamik bir yapıya sahiptir. Bununla birlikte, en güncel revizyonda dahi “hafif” veya “belirgin” gibi öznel kavramlar yer almaktadır. Kategorizasyonun iyileştirilmesi, objektif sayısal verilerle yeniden düzenlemeyi gerektirebilir. Prostat kanseri araştırmalarındaki ilerlemeler ve görüntüleme teknolojisindeki yenilikler, raporlama sisteminin gelecekteki sürümlerini şekillendirecektir. Gereç ve Yöntemler: Periferik zon kategorizasyonunun temelini oluşturan dijital ADC (Apparent Diffusion Coefficient) haritalama ölçümleri, patolojik olarak tanı almış PI-RADS 3, 4 ve 5 kategorilerindeki 91 periferik zon lezyonunda gerçekleştirildi. Ortalama ADC değerleri, aksiyel planda en belirgin kesitte en az 5 mm’lik alanı kapsayacak şekilde ölçüldü. Bulgular: ADC haritalama özelliklerine dayalı olarak istatistiksel açıdan anlamlı sayısal eşik (cut-off) değerleri belirlendi ve periferik zon lezyonlarında “hafif” veya “belirgin” tanımlamaları yerine kullanılabilecek objektif bir değer elde edildi. Sonuç: Elde edilen eşik değer, periferik zon lezyonlarının malignite riskinin öngörülmesine dayalı skorlama sürecinde kullanılabilir. Bu veriler, PI-RADS kategorizasyonunun revizyonuna katkı sağlayabilir. Böylece hem radyolog hem de klinisyen açısından tanısal doğruluk artırılabilir ve gereksiz biyopsilerin önüne geçilebilir.

References

  • Raychaudhuri R, Lin DW, Montgomery RB. Prostate Cancer: A Review. JAMA. 2025;333(16):1433-1446. doi:10.1001/jama.2025.0228
  • Dee EC, Iyengar R, Narayan A, et al. National Cancer System Characteristics and Prostate Cancer Outcomes: An Analysis of Global Data. Prostate. 2025. doi:10.1002/pros.24901
  • Dai J, Tang X, Zhang T, et al. A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound. J Vis Exp. 2025;(217):10.3791/67873. doi:10.3791/67873
  • Barentsz JO, Richenberg J, Clements R, et al. ESUR prostate MR guidelines 2012. Eur Radiol. 2012;22:746-757. doi:10.1007/s00330-011-2377-y
  • Turkbey B, Rosenkrantz AB, Haider MA, et al. Prostate imaging reporting and data system version 2.1: 2019 update of prostate imaging reporting and data system version 2. Eur Urol. 2019;76(3):340-351. doi:10.1016/j.eururo.2019.02.033
  • Greer MD, Brown AM, Shih JH, et al. Interobserver Variability of PI-RADS v2.1: A Multireader Study. Radiology. 2021;299(2):385-394. doi:10.1148/radiol.2021203290
  • Purasang V, Srisuwan T, Chaiyasoot K, et al. Quantitative MRI Biomarkers in Prostate Cancer: An AI-Driven Approach. Eur Radiol. 2022;32(1):512-523. doi:10.1007/s00330-021-08144-w
  • Padhani AR, Liu G, Koh DM, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 2009;11(2):102-125. doi:10.1593/neo.81328
  • Paudyal P, Mete U, Gorsi U, Kumar S, Kakkar N. Usefulness of multiparametric MRI for local staging of bladder cancer. Urologia. 2025;92(2):231-236. doi:10.1177/03915603241310390
  • Korbmacher M, Tranfa M, Pontillo G, et al. White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life. Neuroimage. 2025;310:121132. doi:10.1016/j.neuroimage.2025.121132
  • Lee S, Palmquist S, Ma J, Kaur H. Rectal MR Imaging. Radiol Clin North Am. 2025;63(3):419-434. doi:10.1016/j.rcl.2024.11.006
  • Girometti R, Cereser L, Bonato F, et al. Negative predictive value for cancer in patients with "Gray-Zone" PSA level and prior negative biopsy: Preliminary results with multiparametric 3.0 tesla MR. J Magn Reson Imaging. 2012;36(4):943-950. doi:10.1002/jmri.23703
  • Isebaert S, Van den Bergh L, Haustermans K, et al. Multiparametric MRI for prostate cancer localization in correlation to whole-mount histopathology. J Magn Reson Imaging. 2013;37(6):1392-1401. doi:10.1002/jmri.23938
  • Zhang S, Wan J, Xu Y, et al. Predictive Value of Multiparametric Magnetic Resonance Imaging (T2-weighted Imaging and Apparent Diffusion Coefficient) for Pathological Grading of Prostate Cancer: a Meta-Analysis. Int Braz J Urol. 2025;51(3):e20240509. doi:10.1590/S1677-5538.IBJU.2024.0509
  • Garcia-Becerra CA, Arias-Gallardo MI, Soltero-Molinar V, et al. Is biparametric MRI a feasible option for detecting clinically significant prostate cancer?: A systematic review and meta-analysis. Urol Oncol. 2025. doi:10.1016/j.urolonc.2024.12.262
  • Wang Y, Wang W, Yi N, et al. Detection of intermediate- and high-risk prostate cancer with biparametric magnetic resonance imaging: a systematic review and meta-analysis. Quant Imaging Med Surg. 2023;13(5):2791-2806. doi:10.21037/qims-22-1024
  • Bass EJ, Pantovic A, Connor M, et al. A systematic review and meta-analysis of the diagnostic accuracy of biparametric prostate MRI for prostate cancer in men at risk. Prostate Cancer Prostatic Dis. 2021;24(3):596-611. doi:10.1038/s41391-020-00298-w
  • Yang L, Tan Y, Dan H, Hu L, Zhang J. Diagnostic performance of diffusion-weighted imaging combined with dynamic contrast-enhanced magnetic resonance imaging for prostate cancer: a systematic review and meta-analysis. Acta Radiol. 2021;62(9):1238-1247. doi:10.1177/0284185120956269
  • Deforche M, Lefebvre Y, Diamand R, et al. Improved diagnostic accuracy of readout-segmented echo-planar imaging for peripheral zone clinically significant prostate cancer: a retrospective 3T MRI study. Sci Rep. 2024;14(1):3299. doi:10.1038/s41598-024-53898-0
  • De Perrot T, Sadjo Zoua C, Glessgen CG, et al. Diffusion-Weighted MRI in the Genitourinary System. J Clin Med. 2022;11(7):1921. doi:10.3390/jcm11071921
  • Fokkinga E, Hernandez-Tamames JA, Ianus A, et al. Advanced Diffusion-Weighted MRI for Cancer Microstructure Assessment in Body Imaging, and Its Relationship With Histology. J Magn Reson Imaging. 2024;60(4):1278-1304. doi:10.1002/jmri.29144
  • Hambrock T, Somford DM, Huisman HJ, et al. Relationship between apparent diffusion coefficients at 3.0-T MR imaging and Gleason grade in peripheral zone prostate cancer. Radiology. 2011;259(2):453-461. doi:10.1148/radiol.11091409
  • Kim TH, Kim CK, Park BK, et al. Relationship between Gleason score and apparent diffusion coefficients of diffusion-weighted magnetic resonance imaging in prostate cancer patients. Can Urol Assoc J. 2016;10(11-12):E377. doi:10.5489/cuaj.3896
  • Salami SS, Ben-Levi E, Yaskiv O, et al. Risk stratification of prostate cancer utilizing apparent diffusion coefficient value and lesion volume on multiparametric MRI. J Magn Reson Imaging. 2017;45(2):610-616. doi:10.1002/jmri.25363
  • Kido A, Kataoka M, Yamamoto A, et al. 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. 2017;122:228-238. doi:10.1007/s11547-016-0712-8
  • Nakamoto A, Onishi H, Tsuboyama T, et al. High-resolution Diffusion-weighted Imaging of the Prostate Using Multiplexed Sensitivity-encoding: Comparison with the Conventional and Reduced Field-of-view Techniques. Magn Reson Med Sci. 2025;24(1):58-65. doi:10.2463/mrms.mp.2023-0039
  • Bengtsson J, Thimansson E, Baubeta E, et al. Correlation between ADC, ADC ratio, and Gleason Grade group in prostate cancer patients undergoing radical prostatectomy: Retrospective multicenter study with different MRI scanners. Front Oncol. 2023;13:1079040. doi:10.3389/fonc.2023.1079040
  • Azeemuddin M, Awais M, ul Haq T, et al. Role of ADC values and ratios of MRI scan in differentiating typical from atypical/anaplastic meningiomas. J Pak Med Assoc. 2018;68(9):1403. doi:10.5455/JPMA.300645
  • Zhao S, Li Y, Ning N, et al. Association of peritumoral region features assessed on breast MRI and prognosis of breast cancer: a systematic review and meta-analysis. Eur Radiol. 2024;34(9):6108-6120. doi:10.1007/s00330-024-10612-y
  • Zabihollahy F, Naim S, Wibulpolprasert P, et al. Understanding Spatial Correlation Between Multiparametric MRI Performance and Prostate Cancer. J Magn Reson Imaging. 2024;60(5):2184-2195. doi:10.1002/jmri.29287
  • Jin P, Wang X, Ding Z, et al. Development and validation of risk-stratified biopsy decision pathways incorporating MRI and PSA-derived indicators. Ann Med. 2025;57(1):2446695. doi:10.1080/07853890.2024.2446695
  • Sridhar S, Abouelfetouh Z, Codreanu I, et al. The Role of Dynamic Contrast Enhanced Magnetic Resonance Imaging in Evaluating Prostate Adenocarcinoma: A Partially-Blinded Retrospective Study of a Prostatectomy Patient Cohort With Whole Gland Histopathology Correlation and Application of PI-RADS or TNM Staging. Prostate. 2025;85(5):413-423. doi:10.1002/pros.24843
  • Johnson PM, Dutt T, Ginocchio LA, et al. Prostate Cancer Risk Stratification and Scan Tailoring Using Deep Learning on Abbreviated Prostate MRI. J Magn Reson Imaging. 2025. doi:10.1002/jmri.29798
There are 33 citations in total.

Details

Primary Language Turkish
Subjects Health Care Administration
Journal Section Research Article
Authors

Abdullah Enes Berksoy 0009-0000-9890-1285

Kamil Doğan 0000-0002-8558-6295

Adem Doğaner 0000-0002-0270-9350

Submission Date April 29, 2025
Acceptance Date August 5, 2025
Publication Date March 28, 2026
DOI https://doi.org/10.17517/ksutfd.1686570
IZ https://izlik.org/JA57CS85HC
Published in Issue Year 2026 Volume: 21 Issue: 1

Cite

AMA 1.Berksoy AE, Doğan K, Doğaner A. Periferik Zon Lezyonlarında PI-RADS 3, 4 ve 5 Ayrımında Difüzyon Ağırlıklı Görüntüleme ve Multiparametrik Prostat MR. KSU Medical Journal. 2026;21(1):15-22. doi:10.17517/ksutfd.1686570