Cribriform Pattern of The Prostate Adenocarcinoma: Sensitivity of Multiparametric MRI
Urology Journal,
Vol. 20 No. 01 (2023),
25 December 2022
,
Page 34-40
https://doi.org/10.22037/uj.v20i01.7382
Abstract
Background: The aim of this study was to investigate the diagnostic performance of mpMRI for detecting cribriform
pattern prostate cancer.
Materials and Methods: This study retrospectively enrolled 33 patients who were reported cribriform pattern
prostate cancer at final pathology. The localization, grade and volumetric properties of the dominant tumors and
areas with cribriform pattern at the final pathological specimens were recorded and the diagnostic value of mpMRI
was evaluated on the basis of the cribriform morphology detection rate. It was analyzed using Wilcoxon test, the
Chi-square test and Fisher's Exact test. The significance level (P-value) was set at .05 in all statistical analyses.
Results: A total of 58 prostate cancer foci were (38 cribriform, 20 non-cribriform foci) identified on the final pathology.
mpMRI identified 36 of the 38 cribriform morphology harboring tumor foci with a sensitivity of 94.7%
(95% confidence interval 82.7–98.5%). In 17 of the 33 patients mpMRI detected single lesion and for these lesions;
mpMRI identified cribriform morphology positive areas precisely in 15 patients with significantly low ADCmean
and ADCmin values compared to the non-cribriform cancer areas within the primary index lesion (P < .001). For
the remaining 16 patients with multiple lesions; all of the tumor foci that harboring cribriform morphology were
identified by mpMRI but in none of them any ADCmean and ADCmin value divergence were detected between
the cribriform and non-cribriform pattern tumor foci within the primary index lesion.
Conclusion: Cribiform pattern should be considered in single lesions with an area of lower ADC value on mpMRI.
Keywords:
- cribriform pattern
- multiparametric prostate MRI
- , prostate cancer
How to Cite
Tuna, M. B., Arslan, A. ., Kök, Y. B. ., Doganca, T. ., Argun, O. B. ., Tufek, I. ., Pirdal, B. Z. ., Saglican, Y. ., Obek, C. ., Karaarslan, E. ., & Kural, A. R. . (2022). Cribriform Pattern of The Prostate Adenocarcinoma: Sensitivity of Multiparametric MRI. Urology Journal, 20(01), 34–40. https://doi.org/10.22037/uj.v20i01.7382
References
REFERENCES
1) Weinreb JC, Barentsz JO, Choyke PL, Cornud F, Haider MA, Macura KJ, Margolis D, Schnall MD, Shtern F, Tempany CM, Thoeny HC, Verma S. PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol. 2016 Jan;69(1):16-40. doi: 10.1016/j.eururo.2015.08.052. Epub 2015 Oct 1. PMID: 26427566; PMCID: PMC6467207.
2) Ahmed HU, El-Shater Bosaily A, Brown LC, Gabe R, Kaplan R, Parmar MK, Collaco-Moraes Y, Ward K, Hindley RG, Freeman A, Kirkham AP, Oldroyd R, Parker C, Emberton M; PROMIS study group. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet. 2017 Feb 25;389(10071):815-822. doi: 10.1016/S0140-6736(16)32401-1. Epub 2017 Jan 20. PMID: 28110982.
3) Kasivisvanathan V, Rannikko AS, Borghi M, Panebianco V, Mynderse LA, Vaarala MH, Briganti A, Budäus L, Hellawell G, Hindley RG, Roobol MJ, Eggener S, Ghei M, Villers A, Bladou F, Villeirs GM, Virdi J, Boxler S, Robert G, Singh PB, Venderink W, Hadaschik BA, Ruffion A, Hu JC, Margolis D, Crouzet S, Klotz L, Taneja SS, Pinto P, Gill I, Allen C, Giganti F, Freeman A, Morris S, Punwani S, Williams NR, Brew-Graves C, Deeks J, Takwoingi Y, Emberton M, Moore CM; PRECISION Study Group Collaborators. MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis. N Engl J Med. 2018 May 10;378(19):1767-1777. doi: 10.1056/NEJMoa1801993. Epub 2018 Mar 18. PMID: 29552975.
4) Turkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, Tempany CM, Choyke PL, Cornud F, Margolis DJ, Thoeny HC, Verma S, Barentsz J, Weinreb JC. Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2. Eur Urol. 2019 Sep;76(3):340-351. doi: 10.1016/j.eururo.2019.02.033. Epub 2019 Mar 18. PMID: 30898406.
5) Iczkowski KA, Torkko KC, Kotnis GR, Wilson RS, Huang W, Wheeler TM, Abeyta AM, La Rosa FG, Cook S, Werahera PN, Lucia MS. Digital quantification of five high-grade prostate cancer patterns, including the cribriform pattern, and their association with adverse outcome. Am J Clin Pathol. 2011 Jul;136(1):98-107. doi: 10.1309/AJCPZ7WBU9YXSJPE. PMID: 21685037; PMCID: PMC4656017.
6) Dong F, Yang P, Wang C, Wu S, Xiao Y, McDougal WS, Young RH, Wu CL. Architectural heterogeneity and cribriform pattern predict adverse clinical outcome for Gleason grade 4 prostatic adenocarcinoma. Am J Surg Pathol. 2013 Dec;37(12):1855-61. doi: 10.1097/PAS.0b013e3182a02169. PMID: 24145642.
7) Kweldam CF, Kümmerlin IP, Nieboer D, Verhoef EI, Steyerberg EW, Incrocci L, Bangma CH, van der Kwast TH, Roobol MJ, van Leenders GJ. Prostate cancer outcomes of men with biopsy Gleason score 6 and 7 without cribriform or intraductal carcinoma. Eur J Cancer. 2016 Oct;66:26-33. doi: 10.1016/j.ejca.2016.07.012. Epub 2016 Aug 11. PMID: 27522247.
8) Truong M, Frye T, Messing E, Miyamoto H. Historical and contemporary perspectives on cribriform morphology in prostate cancer. Nat Rev Urol. 2018 Aug;15(8):475-482. doi: 10.1038/s41585-018-0013-1. PMID: 29713007.
9) Truong M, Hollenberg G, Weinberg E, Messing EM, Miyamoto H, Frye TP. Impact of Gleason Subtype on Prostate Cancer Detection Using Multiparametric Magnetic Resonance Imaging: Correlation with Final Histopathology. J Urol. 2017 Aug;198(2):316-321. doi: 10.1016/j.juro.2017.01.077. Epub 2017 Feb 3. PMID: 28163032.
10) Truong M, Feng C, Hollenberg G, Weinberg E, Messing EM, Miyamoto H, Frye TP. A Comprehensive Analysis of Cribriform Morphology on Magnetic Resonance Imaging/Ultrasound Fusion Biopsy Correlated with Radical Prostatectomy Specimens. J Urol. 2018 Jan;199(1):106-113. doi: 10.1016/j.juro.2017.07.037. Epub 2017 Jul 18. Erratum in: J Urol. 2017 Dec 8;: PMID: 28728994.
11) Miyai K, Mikoshi A, Hamabe F, Nakanishi K, Ito K, Tsuda H, Shinmoto H. Histological differences in cancer cells, stroma, and luminal spaces strongly correlate with in vivo MRI-detectability of prostate cancer. Mod Pathol. 2019 Oct;32(10):1536-1543. doi: 10.1038/s41379-019-0292-y. Epub 2019 Jun 7. PMID: 31175330.
12) Schieda N, Coffey N, Gulavita P, Al-Dandan O, Shabana W, Flood TA. Prostatic ductal adenocarcinoma: an aggressive tumour variant unrecognized on T2 weighted magnetic resonance imaging (MRI). Eur Radiol. 2014 Jun;24(6):1349-56. doi: 10.1007/s00330-014-3150-9. Epub 2014 Apr 1. PMID: 24687527.
13) Arslan A, Alis D, Tuna MB, Sağlıcan Y, Kural AR, Karaarslan E. The visibility of prostate cancer concerning underlying histopathological variances: A single-center multiparametric magnetic resonance imaging study. Eur J Radiol. 2021 Aug;141:109791. doi: 10.1016/j.ejrad.2021.109791. Epub 2021 May 27. PMID: 34062471.
14) Gleason DF. Classification of prostatic carcinomas. Cancer Chemother Rep. 1966 Mar;50(3):125-8. PMID: 5948714.
15) Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA; Grading Committee. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System. Am J Surg Pathol. 2016 Feb;40(2):244-52. doi: 10.1097/PAS.0000000000000530. PMID: 26492179.
16) Roobol MJ, Verbeek JFM, van der Kwast T, Kümmerlin IP, Kweldam CF, van Leenders GJLH. Improving the Rotterdam European Randomized Study of Screening for Prostate Cancer Risk Calculator for Initial Prostate Biopsy by Incorporating the 2014 International Society of Urological Pathology Gleason Grading and Cribriform growth. Eur Urol. 2017 Jul;72(1):45-51. doi: 10.1016/j.eururo.2017.01.033. Epub 2017 Feb 2. PMID: 28162815.
17) Gao J, Zhang Q, Fu Y, Wang W, Zhang C, Kan Y, Huang H, Li D, Shi J, Guo H, Zhang B. Combined clinical characteristics and multiparametric MRI parameters for prediction of cribriform morphology in intermediate-risk prostate cancer patients. Urol Oncol. 2020 Apr;38(4):216-224. doi: 10.1016/j.urolonc.2019.09.002. Epub 2019 Oct 7. PMID: 31601518.
18) Prendeville S, Gertner M, Maganti M, Pintilie M, Perlis N, Toi A, Evans AJ, Finelli A, van der Kwast TH, Ghai S. Role of Magnetic Resonance Imaging Targeted Biopsy in Detection of Prostate Cancer Harboring Adverse Pathological Features of Intraductal Carcinoma and Invasive Cribriform Carcinoma. J Urol. 2018 Jul;200(1):104-113. doi: 10.1016/j.juro.2018.01.081. Epub 2018 Feb 2. PMID: 29408568.
19) Tonttila PP, Ahtikoski A, Kuisma M, Pääkkö E, Hirvikoski P, Vaarala MH. Multiparametric MRI prior to radical prostatectomy identifies intraductal and cribriform growth patterns in prostate cancer. BJU Int. 2019 Dec;124(6):992-998. doi: 10.1111/bju.14812. Epub 2019 Jun 19. PMID: 31102571.
20) Hurrell SL, McGarry SD, Kaczmarowski A, Iczkowski KA, Jacobsohn K, Hohenwalter MD, Hall WA, See WA, Banerjee A, Charles DK, Nevalainen MT, Mackinnon AC, LaViolette PS. Optimized b-value selection for the discrimination of prostate cancer grades, including the cribriform pattern, using diffusion weighted imaging. J Med Imaging (Bellingham). 2018 Jan;5(1):011004. doi: 10.1117/1.JMI.5.1.011004. Epub 2017 Oct 27. PMID: 29098169; PMCID: PMC5658575.
21) Gao J, Zhang C, Zhang Q, Fu Y, Zhao X, Chen M, Zhang B, Li D, Shi J, Wang F, Guo H. Diagnostic performance of 68Ga-PSMA PET/CT for identification of aggressive cribriform morphology in prostate cancer with whole-mount sections. Eur J Nucl Med Mol Imaging. 2019 Jul;46(7):1531-1541. doi: 10.1007/s00259-019-04320-9. Epub 2019 Apr 25. PMID: 31025048.
1) Weinreb JC, Barentsz JO, Choyke PL, Cornud F, Haider MA, Macura KJ, Margolis D, Schnall MD, Shtern F, Tempany CM, Thoeny HC, Verma S. PI-RADS Prostate Imaging - Reporting and Data System: 2015, Version 2. Eur Urol. 2016 Jan;69(1):16-40. doi: 10.1016/j.eururo.2015.08.052. Epub 2015 Oct 1. PMID: 26427566; PMCID: PMC6467207.
2) Ahmed HU, El-Shater Bosaily A, Brown LC, Gabe R, Kaplan R, Parmar MK, Collaco-Moraes Y, Ward K, Hindley RG, Freeman A, Kirkham AP, Oldroyd R, Parker C, Emberton M; PROMIS study group. Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study. Lancet. 2017 Feb 25;389(10071):815-822. doi: 10.1016/S0140-6736(16)32401-1. Epub 2017 Jan 20. PMID: 28110982.
3) Kasivisvanathan V, Rannikko AS, Borghi M, Panebianco V, Mynderse LA, Vaarala MH, Briganti A, Budäus L, Hellawell G, Hindley RG, Roobol MJ, Eggener S, Ghei M, Villers A, Bladou F, Villeirs GM, Virdi J, Boxler S, Robert G, Singh PB, Venderink W, Hadaschik BA, Ruffion A, Hu JC, Margolis D, Crouzet S, Klotz L, Taneja SS, Pinto P, Gill I, Allen C, Giganti F, Freeman A, Morris S, Punwani S, Williams NR, Brew-Graves C, Deeks J, Takwoingi Y, Emberton M, Moore CM; PRECISION Study Group Collaborators. MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis. N Engl J Med. 2018 May 10;378(19):1767-1777. doi: 10.1056/NEJMoa1801993. Epub 2018 Mar 18. PMID: 29552975.
4) Turkbey B, Rosenkrantz AB, Haider MA, Padhani AR, Villeirs G, Macura KJ, Tempany CM, Choyke PL, Cornud F, Margolis DJ, Thoeny HC, Verma S, Barentsz J, Weinreb JC. Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2. Eur Urol. 2019 Sep;76(3):340-351. doi: 10.1016/j.eururo.2019.02.033. Epub 2019 Mar 18. PMID: 30898406.
5) Iczkowski KA, Torkko KC, Kotnis GR, Wilson RS, Huang W, Wheeler TM, Abeyta AM, La Rosa FG, Cook S, Werahera PN, Lucia MS. Digital quantification of five high-grade prostate cancer patterns, including the cribriform pattern, and their association with adverse outcome. Am J Clin Pathol. 2011 Jul;136(1):98-107. doi: 10.1309/AJCPZ7WBU9YXSJPE. PMID: 21685037; PMCID: PMC4656017.
6) Dong F, Yang P, Wang C, Wu S, Xiao Y, McDougal WS, Young RH, Wu CL. Architectural heterogeneity and cribriform pattern predict adverse clinical outcome for Gleason grade 4 prostatic adenocarcinoma. Am J Surg Pathol. 2013 Dec;37(12):1855-61. doi: 10.1097/PAS.0b013e3182a02169. PMID: 24145642.
7) Kweldam CF, Kümmerlin IP, Nieboer D, Verhoef EI, Steyerberg EW, Incrocci L, Bangma CH, van der Kwast TH, Roobol MJ, van Leenders GJ. Prostate cancer outcomes of men with biopsy Gleason score 6 and 7 without cribriform or intraductal carcinoma. Eur J Cancer. 2016 Oct;66:26-33. doi: 10.1016/j.ejca.2016.07.012. Epub 2016 Aug 11. PMID: 27522247.
8) Truong M, Frye T, Messing E, Miyamoto H. Historical and contemporary perspectives on cribriform morphology in prostate cancer. Nat Rev Urol. 2018 Aug;15(8):475-482. doi: 10.1038/s41585-018-0013-1. PMID: 29713007.
9) Truong M, Hollenberg G, Weinberg E, Messing EM, Miyamoto H, Frye TP. Impact of Gleason Subtype on Prostate Cancer Detection Using Multiparametric Magnetic Resonance Imaging: Correlation with Final Histopathology. J Urol. 2017 Aug;198(2):316-321. doi: 10.1016/j.juro.2017.01.077. Epub 2017 Feb 3. PMID: 28163032.
10) Truong M, Feng C, Hollenberg G, Weinberg E, Messing EM, Miyamoto H, Frye TP. A Comprehensive Analysis of Cribriform Morphology on Magnetic Resonance Imaging/Ultrasound Fusion Biopsy Correlated with Radical Prostatectomy Specimens. J Urol. 2018 Jan;199(1):106-113. doi: 10.1016/j.juro.2017.07.037. Epub 2017 Jul 18. Erratum in: J Urol. 2017 Dec 8;: PMID: 28728994.
11) Miyai K, Mikoshi A, Hamabe F, Nakanishi K, Ito K, Tsuda H, Shinmoto H. Histological differences in cancer cells, stroma, and luminal spaces strongly correlate with in vivo MRI-detectability of prostate cancer. Mod Pathol. 2019 Oct;32(10):1536-1543. doi: 10.1038/s41379-019-0292-y. Epub 2019 Jun 7. PMID: 31175330.
12) Schieda N, Coffey N, Gulavita P, Al-Dandan O, Shabana W, Flood TA. Prostatic ductal adenocarcinoma: an aggressive tumour variant unrecognized on T2 weighted magnetic resonance imaging (MRI). Eur Radiol. 2014 Jun;24(6):1349-56. doi: 10.1007/s00330-014-3150-9. Epub 2014 Apr 1. PMID: 24687527.
13) Arslan A, Alis D, Tuna MB, Sağlıcan Y, Kural AR, Karaarslan E. The visibility of prostate cancer concerning underlying histopathological variances: A single-center multiparametric magnetic resonance imaging study. Eur J Radiol. 2021 Aug;141:109791. doi: 10.1016/j.ejrad.2021.109791. Epub 2021 May 27. PMID: 34062471.
14) Gleason DF. Classification of prostatic carcinomas. Cancer Chemother Rep. 1966 Mar;50(3):125-8. PMID: 5948714.
15) Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA; Grading Committee. The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma: Definition of Grading Patterns and Proposal for a New Grading System. Am J Surg Pathol. 2016 Feb;40(2):244-52. doi: 10.1097/PAS.0000000000000530. PMID: 26492179.
16) Roobol MJ, Verbeek JFM, van der Kwast T, Kümmerlin IP, Kweldam CF, van Leenders GJLH. Improving the Rotterdam European Randomized Study of Screening for Prostate Cancer Risk Calculator for Initial Prostate Biopsy by Incorporating the 2014 International Society of Urological Pathology Gleason Grading and Cribriform growth. Eur Urol. 2017 Jul;72(1):45-51. doi: 10.1016/j.eururo.2017.01.033. Epub 2017 Feb 2. PMID: 28162815.
17) Gao J, Zhang Q, Fu Y, Wang W, Zhang C, Kan Y, Huang H, Li D, Shi J, Guo H, Zhang B. Combined clinical characteristics and multiparametric MRI parameters for prediction of cribriform morphology in intermediate-risk prostate cancer patients. Urol Oncol. 2020 Apr;38(4):216-224. doi: 10.1016/j.urolonc.2019.09.002. Epub 2019 Oct 7. PMID: 31601518.
18) Prendeville S, Gertner M, Maganti M, Pintilie M, Perlis N, Toi A, Evans AJ, Finelli A, van der Kwast TH, Ghai S. Role of Magnetic Resonance Imaging Targeted Biopsy in Detection of Prostate Cancer Harboring Adverse Pathological Features of Intraductal Carcinoma and Invasive Cribriform Carcinoma. J Urol. 2018 Jul;200(1):104-113. doi: 10.1016/j.juro.2018.01.081. Epub 2018 Feb 2. PMID: 29408568.
19) Tonttila PP, Ahtikoski A, Kuisma M, Pääkkö E, Hirvikoski P, Vaarala MH. Multiparametric MRI prior to radical prostatectomy identifies intraductal and cribriform growth patterns in prostate cancer. BJU Int. 2019 Dec;124(6):992-998. doi: 10.1111/bju.14812. Epub 2019 Jun 19. PMID: 31102571.
20) Hurrell SL, McGarry SD, Kaczmarowski A, Iczkowski KA, Jacobsohn K, Hohenwalter MD, Hall WA, See WA, Banerjee A, Charles DK, Nevalainen MT, Mackinnon AC, LaViolette PS. Optimized b-value selection for the discrimination of prostate cancer grades, including the cribriform pattern, using diffusion weighted imaging. J Med Imaging (Bellingham). 2018 Jan;5(1):011004. doi: 10.1117/1.JMI.5.1.011004. Epub 2017 Oct 27. PMID: 29098169; PMCID: PMC5658575.
21) Gao J, Zhang C, Zhang Q, Fu Y, Zhao X, Chen M, Zhang B, Li D, Shi J, Wang F, Guo H. Diagnostic performance of 68Ga-PSMA PET/CT for identification of aggressive cribriform morphology in prostate cancer with whole-mount sections. Eur J Nucl Med Mol Imaging. 2019 Jul;46(7):1531-1541. doi: 10.1007/s00259-019-04320-9. Epub 2019 Apr 25. PMID: 31025048.
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