The role of gadolinium in magnetic resonance imaging for early prostate cancer diagnosis: A diagnostic accuracy study

Autoři: Ilinca Cosma aff001;  Cornelia Tennstedt-Schenk aff003;  Sven Winzler aff002;  Marios Nikos Psychogios aff004;  Alexander Pfeil aff005;  Ulf Teichgraeber aff001;  Ansgar Malich aff002;  Ismini Papageorgiou aff001
Působiště autorů: Institute of Diagnostic and Interventional Radiology, University Hospital Jena, Jena, Germany aff001;  Institute of Radiology, Suedharz Hospital Nordhausen, Nordhausen, Germany aff002;  Institute for Pathology, Muehlhausen, Germany aff003;  Department of Neuroradiology, Clinic of Radiology and Nuclear Medicine, University Hospital Basel, Basel, Switzerland aff004;  Department of Internal Medicine, University Hospital Jena, Jena, Germany aff005
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227031



Prostate lesions detected with multiparametric magnetic resonance imaging (mpMRI) are classified for their malignant potential according to the Prostate Imaging-Reporting And Data System (PI-RADS™2). In this study, we evaluate the diagnostic accuracy of the mpMRI with and without gadolinium, with emphasis on the added diagnostic value of the dynamic contrast enhancement (DCE).

Materials and methods

The study was retrospective for 286 prostate lesions / 213 eligible patients, n = 116/170, and 49/59% malignant for the peripheral (Pz) and transitional zone (Tz), respectively. A stereotactic MRI-guided prostate biopsy served as the histological ground truth. All patients received a mpMRI with DCE. The influence of DCE in the prediction of malignancy was analyzed by blinded assessment of the imaging protocol without DCE and the DCE separately.


Significant (CSPca) and insignificant (IPca) prostate cancers were evaluated separately to enhance the potential effects of the DCE in the detection of CSPca. The Receiver Operating Characteristics Area Under Curve (ROC-AUC), sensitivity (Se) and specificity (Spe) of PIRADS-without-DCE in the Pz was 0.70/0.47/0.86 for all cancers (IPca and CSPca merged) and 0.73/0.54/0.82 for CSPca. PIRADS-with-DCE for the same patients showed ROC-AUC/Se/Spe of 0.70/0.49/0.86 for all Pz cancers and 0.69/0.54/0.81 for CSPca in the Pz, respectively, p>0.05 chi-squared test. Similar results for the Tz, AUC/Se/Spe for PIRADS-without-DCE was 0.75/0.61/0.79 all cancers and 0.67/0.54/0.71 for CSPca, not influenced by DCE (0.66/0.47/0.81 for all Tz cancers and 0.61/0.39/0.75 for CSPca in Tz). The added Se and Spe of DCE for the detection of CSPca was 88/34% and 78/33% in the Pz and Tz, respectively.


DCE showed no significant added diagnostic value and lower specificity for the prediction of CSPca compared to the non-enhanced sequences. Our results support that gadolinium might be omitted without mitigating the diagnostic accuracy of the mpMRI for prostate cancer.

Klíčová slova:

Biopsy – Cancer detection and diagnosis – Diffusion weighted imaging – Chi square tests – Lesions – Magnetic resonance imaging – Prostate cancer – Prostate gland


1. Vargas HA, Hötker AM, Goldman DA, Moskowitz CS, Gondo T, Matsumoto K, et al. Updated prostate imaging reporting and data system (PIRADS v2) recommendations for the detection of clinically significant prostate cancer using multiparametric MRI: critical evaluation using whole-mount pathology as standard of reference. Eur Radiol. 2016;26: 1606–1612. doi: 10.1007/s00330-015-4015-6 26396111

2. Mottet N, Bellmunt J, Bolla M, Briers E, Cumberbatch MG, De Santis M, et al. EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Part 1: Screening, Diagnosis, and Local Treatment with Curative Intent. Eur Urol. 2017;71: 618–629. doi: 10.1016/j.eururo.2016.08.003 27568654

3. Prostate cancer: diagnosis and management | Guidance and guidelines | NICE. [cited 10 Dec 2017]. Available:

4. Parker C, Gillessen S, Heidenreich A, Horwich A, ESMO Guidelines Committee. Cancer of the prostate: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol Off J Eur Soc Med Oncol. 2015;26 Suppl 5: v69–77. doi: 10.1093/annonc/mdv222 26205393

5. Barentsz JO, Richenberg J, Clements R, Choyke P, Verma S, Villeirs G, et al. ESUR prostate MR guidelines 2012. Eur Radiol. 2012;22: 746–757. doi: 10.1007/s00330-011-2377-y 22322308

6. 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. Eur Urol. 2016;69: 16–40. doi: 10.1016/j.eururo.2015.08.052 26427566

7. Barrett T, Rajesh A, Rosenkrantz AB, Choyke PL, Turkbey B. PI-RADS version 2.1: one small step for prostate MRI. Clin Radiol. 2019;74: 841–852. doi: 10.1016/j.crad.2019.05.019 31239107

8. 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. Eur Urol. 2019;76: 340–351. doi: 10.1016/j.eururo.2019.02.033 30898406

9. Futterer JJ, Heijmink SWTPJ, Scheenen TWJ, Veltman J, Huisman HJ, Vos P, et al. Prostate cancer localization with dynamic contrast-enhanced MR imaging and proton MR spectroscopic imaging. Radiology. 2006;241: 449–458. doi: 10.1148/radiol.2412051866 16966484

10. Langer DL, van der Kwast TH, Evans AJ, Trachtenberg J, Wilson BC, Haider MA. Prostate cancer detection with multi-parametric MRI: logistic regression analysis of quantitative T2, diffusion-weighted imaging, and dynamic contrast-enhanced MRI. J Magn Reson Imaging JMRI. 2009;30: 327–334. doi: 10.1002/jmri.21824 19629981

11. Obmann VC, Pahwa S, Tabayayong W, Jiang Y, O’Connor G, Dastmalchian S, et al. Diagnostic Accuracy of a Rapid Biparametric MRI Protocol for Detection of Histologically Proven Prostate Cancer. Urology. 2018;122: 133–138. doi: 10.1016/j.urology.2018.08.032 30201301

12. Ramalho J, Ramalho M. Gadolinium Deposition and Chronic Toxicity. Magn Reson Imaging Clin N Am. 2017;25: 765–778. doi: 10.1016/j.mric.2017.06.007 28964466

13. Fraum TJ, Ludwig DR, Bashir MR, Fowler KJ. Gadolinium-based contrast agents: A comprehensive risk assessment. J Magn Reson Imaging JMRI. 2017;46: 338–353. doi: 10.1002/jmri.25625 28083913

14. Scialpi M, Martorana E, Aisa MC, Rondoni V, D’Andrea A, Bianchi G. Score 3 prostate lesions: a gray zone for PI-RADS v2. Turk J Urol. 2017;43: 237. doi: 10.5152/tud.2017.01058 28861291

15. Scialpi M, Rondoni V, Aisa MC, Martorana E, D’Andrea A, Malaspina CM, et al. Is contrast enhancement needed for diagnostic prostate MRI? Transl Androl Urol. 2017;6: 499–509. doi: 10.21037/tau.2017.05.31 28725592

16. Kozlowski P, Chang SD, Jones EC, Goldenberg SL. Assessment of the need for DCE MRI in the detection of dominant lesions in the whole gland: Correlation between histology and MRI of prostate cancer. NMR Biomed. 2018;31. doi: 10.1002/nbm.3882 29266527

17. De Visschere P, Lumen N, Ost P, Decaestecker K, Pattyn E, Villeirs G. Dynamic contrast-enhanced imaging has limited added value over T2-weighted imaging and diffusion-weighted imaging when using PI-RADSv2 for diagnosis of clinically significant prostate cancer in patients with elevated PSA. Clin Radiol. 2017;72: 23–32. doi: 10.1016/j.crad.2016.09.011 27726850

18. Choi MH, Kim CK, Lee YJ, Jung SE. Prebiopsy Biparametric MRI for Clinically Significant Prostate Cancer Detection With PI-RADS Version 2: A Multicenter Study. AJR Am J Roentgenol. 2019;212: 839–846. doi: 10.2214/AJR.18.20498 30779662

19. Kuess P, Andrzejewski P, Nilsson D, Georg P, Knoth J, Susani M, et al. Association between pathology and texture features of multi parametric MRI of the prostate. Phys Med Biol. 2017;62: 7833–7854. doi: 10.1088/1361-6560/aa884d 28837046

20. Woo S, Suh CH, Kim SY, Cho JY, Kim SH, Moon MH. Head-to-Head Comparison Between Biparametric and Multiparametric MRI for the Diagnosis of Prostate Cancer: A Systematic Review and Meta-Analysis. AJR Am J Roentgenol. 2018;211: W226–W241. doi: 10.2214/AJR.18.19880 30240296

21. Junker D, Steinkohl F, Fritz V, Bektic J, Tokas T, Aigner F, et al. Comparison of multiparametric and biparametric MRI of the prostate: are gadolinium-based contrast agents needed for routine examinations? World J Urol. 2018. doi: 10.1007/s00345-018-2428-y 30078170

22. Hectors SJ, Besa C, Wagner M, Jajamovich GH, Haines GK, Lewis S, et al. DCE-MRI of the prostate using shutter-speed vs. Tofts model for tumor characterization and assessment of aggressiveness. J Magn Reson Imaging JMRI. 2017;46: 837–849. doi: 10.1002/jmri.25631 28092414

23. Alabousi M, Salameh J-P, Gusenbauer K, Samoilov L, Jafri A, Yu H, et al. Biparametric vs multiparametric prostate magnetic resonance imaging for the detection of prostate cancer in treatment-naïve patients: a diagnostic test accuracy systematic review and meta-analysis. BJU Int. 2019;124: 209–220. doi: 10.1111/bju.14759 30929292

24. Cristel G, Esposito A, Briganti A, Damascelli A, Brembilla G, Freschi M, et al. MpMRI of the prostate: is there a role for semi-quantitative analysis of DCE-MRI and late gadolinium enhancement in the characterisation of prostate cancer? Clin Radiol. 2019;74: 259–267. doi: 10.1016/j.crad.2018.08.017 30739715

25. Parra AN, Lu H, Li Q, Stoyanova R, Pollack A, Punnen S, et al. Predicting clinically significant prostate cancer using DCE-MRI habitat descriptors. Oncotarget. 2018;9: 37125–37136. doi: 10.18632/oncotarget.26437 30647849

26. Taghipour M, Ziaei A, Alessandrino F, Hassanzadeh E, Harisinghani M, Vangel M, et al. Investigating the role of DCE-MRI, over T2 and DWI, in accurate PI-RADS v2 assessment of clinically significant peripheral zone prostate lesions as defined at radical prostatectomy. Abdom Radiol N Y. 2019;44: 1520–1527. doi: 10.1007/s00261-018-1807-6 30361870

27. Schieda N, Krishna S, Davenport MS. Update on Gadolinium-Based Contrast Agent-Enhanced Imaging in the Genitourinary System. AJR Am J Roentgenol. 2019; 1–11. doi: 10.2214/AJR.19.21137 30973785

28. Gatti M, Faletti R, Calleris G, Giglio J, Berzovini C, Gentile F, et al. Prostate cancer detection with biparametric magnetic resonance imaging (bpMRI) by readers with different experience: performance and comparison with multiparametric (mpMRI). Abdom Radiol N Y. 2019. doi: 10.1007/s00261-019-01934-3 30788558

29. Abreu-Gomez J, Krishna S, Narayanasamy S, Flood TA, McInnes MDF, Schieda N. Dynamic Contrast-Enhanced MRI–Upgraded Prostate Imaging Reporting and Data System Version 2 Category 3 Peripheral Zone Observations Stratified by a Size Threshold of 15 mm. Am J Roentgenol. 2019;213: 836–843. doi: 10.2214/AJR.18.21005 31120786

30. Thon A, Teichgräber U, Tennstedt-Schenk C, Hadjidemetriou S, Winzler S, Malich A, et al. Computer aided detection in prostate cancer diagnostics: A promising alternative to biopsy? A retrospective study from 104 lesions with histological ground truth. PloS One. 2017;12: e0185995. doi: 10.1371/journal.pone.0185995 29023572

31. Cohen JF, Korevaar DA, Altman DG, Bruns DE, Gatsonis CA, Hooft L, et al. STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. BMJ Open. 2016;6: e012799. doi: 10.1136/bmjopen-2016-012799 28137831

32. Porter KK, King A, Galgano SJ, Sherrer RL, Gordetsky JB, Rais-Bahrami S. Financial implications of biparametric prostate MRI. Prostate Cancer Prostatic Dis. 2019. doi: 10.1038/s41391-019-0158-x 31239513

33. Franiel T, Lüdemann L, Rudolph B, Rehbein H, Staack A, Taupitz M, et al. Evaluation of normal prostate tissue, chronic prostatitis, and prostate cancer by quantitative perfusion analysis using a dynamic contrast-enhanced inversion-prepared dual-contrast gradient echo sequence. Invest Radiol. 2008;43: 481–487. doi: 10.1097/RLI.0b013e31816b2f63 18580330

34. Jung Y-J, Isaacs JS, Lee S, Trepel J, Neckers L. IL-1beta-mediated up-regulation of HIF-1alpha via an NFkappaB/COX-2 pathway identifies HIF-1 as a critical link between inflammation and oncogenesis. FASEB J Off Publ Fed Am Soc Exp Biol. 2003;17: 2115–2117. doi: 10.1096/fj.03-0329fje 12958148

35. Alonzi R, Padhani AR, Allen C. Dynamic contrast enhanced MRI in prostate cancer. Eur J Radiol. 2007;63: 335–350. doi: 10.1016/j.ejrad.2007.06.028 17689907

36. Zeligs KP, Neuman MK, Annunziata CM. Molecular Pathways: The Balance between Cancer and the Immune System Challenges the Therapeutic Specificity of Targeting Nuclear Factor-κB Signaling for Cancer Treatment. Clin Cancer Res Off J Am Assoc Cancer Res. 2016;22: 4302–4308. doi: 10.1158/1078-0432.CCR-15-1374 27422962

37. Sherrer RL, Glaser ZA, Gordetsky JB, Nix JW, Porter KK, Rais-Bahrami S. Comparison of biparametric MRI to full multiparametric MRI for detection of clinically significant prostate cancer. Prostate Cancer Prostatic Dis. 2018. doi: 10.1038/s41391-018-0107-0 30413806

38. Greer MD, Brown AM, Shih JH, Summers RM, Marko J, Law YM, et al. Accuracy and agreement of PIRADSv2 for prostate cancer mpMRI: A multireader study: PIRADSv2 for Prostate Tumor Detection. J Magn Reson Imaging. 2017;45: 579–585. doi: 10.1002/jmri.25372 27391860

39. Sun C, Chatterjee A, Yousuf A, Antic T, Eggener S, Karczmar GS, et al. Comparison of T2-Weighted Imaging, DWI, and Dynamic Contrast-Enhanced MRI for Calculation of Prostate Cancer Index Lesion Volume: Correlation With Whole-Mount Pathology. AJR Am J Roentgenol. 2019;212: 351–356. doi: 10.2214/AJR.18.20147 30540213

40. Kozlowski P, Chang SD, Jones EC, Berean KW, Chen H, Goldenberg SL. Combined diffusion-weighted and dynamic contrast-enhanced MRI for prostate cancer diagnosis—correlation with biopsy and histopathology. J Magn Reson Imaging JMRI. 2006;24: 108–113. doi: 10.1002/jmri.20626 16767709

41. van Niekerk CG, Witjes JA, Barentsz JO, van der Laak JAWM, Hulsbergen-van de Kaa CA. Microvascularity in transition zone prostate tumors resembles normal prostatic tissue. The Prostate. 2013;73: 467–475. doi: 10.1002/pros.22588 22996830

42. Tretiakova M, Antic T, Binder D, Kocherginsky M, Liao C, Taxy JB, et al. Microvessel density is not increased in prostate cancer: digital imaging of routine sections and tissue microarrays. Hum Pathol. 2013;44: 495–502. doi: 10.1016/j.humpath.2012.06.009 23069258

43. Oto A, Yang C, Kayhan A, Tretiakova M, Antic T, Schmid-Tannwald C, et al. Diffusion-weighted and dynamic contrast-enhanced MRI of prostate cancer: correlation of quantitative MR parameters with Gleason score and tumor angiogenesis. AJR Am J Roentgenol. 2011;197: 1382–1390. doi: 10.2214/AJR.11.6861 22109293

44. Wisniewski T, Zyromska A, Makarewicz R, Zekanowska E. Osteopontin And Angiogenic Factors As New Biomarkers Of Prostate Cancer. Urol J. 2018. doi: 10.22037/uj.v0i0.4282 30178447

45. Ghinea N, Robin B, Pichon C, Leclere R, Nicolas A, Chnecker C, et al. Vasa nervorum angiogenesis in prostate cancer with perineural invasion. The Prostate. 2019;79: 640–646. doi: 10.1002/pros.23771 30663097

46. Song Y, Yang Y, Liu L, Liu X. Association between five polymorphisms in vascular endothelial growth factor gene and urinary bladder cancer risk: A systematic review and meta-analysis involving 6671 subjects. Gene. 2019;698: 186–197. doi: 10.1016/j.gene.2019.02.070 30849545

47. Becker AS, Cornelius A, Reiner CS, Stocker D, Ulbrich EJ, Barth BK, et al. Direct comparison of PI-RADS version 2 and version 1 regarding interreader agreement and diagnostic accuracy for the detection of clinically significant prostate cancer. Eur J Radiol. 2017;94: 58–63. doi: 10.1016/j.ejrad.2017.07.016 28941761

48. Tewes S, Mokov N, Hartung D, Schick V, Peters I, Schedl P, et al. Standardized Reporting of Prostate MRI: Comparison of the Prostate Imaging Reporting and Data System (PI-RADS) Version 1 and Version 2. PloS One. 2016;11: e0162879. doi: 10.1371/journal.pone.0162879 27657729

49. Krishna S, McInnes M, Lim C, Lim R, Hakim SW, Flood TA, et al. Comparison of Prostate Imaging Reporting and Data System versions 1 and 2 for the Detection of Peripheral Zone Gleason Score 3 + 4 = 7 Cancers. AJR Am J Roentgenol. 2017;209: W365–W373. doi: 10.2214/AJR.17.17964 28981356

50. Gupta RT, Mehta KA, Turkbey B, Verma S. PI-RADS: Past, present, and future. J Magn Reson Imaging JMRI. 2019. doi: 10.1002/jmri.26896 31397038

Článek vyšel v časopise


2019 Číslo 12