Investigative Magnetic Resonance Imaging

Korean Society of Magnetic Resonance in Medicine (대한자기공명의과학회)
권호 표지
DOI QR코드

DOI QR Code

Dynamic Contrast-Enhanced MRI of the Prostate: Can Auto-Generated Wash-in Color Map Be Useful in Detecting Focal Lesion Enhancement?

  • Yoon, Ji Min (Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Choi, Moon Hyung (Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Lee, Young Joon (Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea) ;
  • Jung, Seung Eun (Department of Radiology, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea)
  • Received : 2019.04.17
  • Accepted : 2019.07.29
  • Published : 2019.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

Purpose: To evaluate the usefulness of wash-in color map in detecting early enhancement of prostate focal lesion compared to whole dynamic contrast-enhanced MRI (DEC MRI) images. Materials and Methods: This study engaged 50 prostate cancer patients who underwent multiparametric MRI and radical prostatectomy as subjects. An expert [R1] and a trainee [R2] independently evaluated early enhancement and recorded the time needed to review 1) a wash-in color map and 2) whole DCE MRI images. Results: The review of whole DCE images by R1 showed fair agreement with color map by R1, whole images by R2, and color map by R2 (weighted kappa values = 0.59, 0.44, and 0.58, respectively). Both readers took a significantly shorter time to review the color maps as compared to whole images (P < 0.001). Conclusion: A trainee could achieve better agreement with an expert when using wash-in color maps than when using whole DCE MRI images. Also, color maps took a significantly shorter evaluation time than whole images.

Keywords

References

  1. Futterer JJ, Briganti A, De Visschere P, et al. Can clinically significant prostate cancer be detected with multiparametric magnetic resonance imaging? A systematic review of the literature. Eur Urol 2015;68:1045-1053 https://doi.org/10.1016/j.eururo.2015.01.013
  2. Weinreb JC, Barentsz JO, Choyke PL, et al. PI-RADS Prostate Imaging - Reporting and Data System: 2015, version 2. Eur Urol 2016;69:16-40 https://doi.org/10.1016/j.eururo.2015.08.052
  3. 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 https://doi.org/10.2214/AJR.18.19880
  4. Purysko AS, Rosenkrantz AB, Barentsz JO, Weinreb JC, Macura KJ. PI-RADS version 2: a pictorial update. Radiographics 2016;36:1354-1372 https://doi.org/10.1148/rg.2016150234
  5. Iwazawa J, Mitani T, Sassa S, Ohue S. Prostate cancer detection with MRI: is dynamic contrast-enhanced imaging necessary in addition to diffusion-weighted imaging? Diagn Interv Radiol 2011;17:243-248
  6. Tamada T, Sone T, Higashi H, et al. Prostate cancer detection in patients with total serum prostate-specific antigen levels of 4-10 ng/mL: diagnostic efficacy of diffusion-weighted imaging, dynamic contrast-enhanced MRI, and T2-weighted imaging. AJR Am J Roentgenol 2011;197:664-670 https://doi.org/10.2214/AJR.10.5923
  7. Greer MD, Shih JH, Lay N, et al. Validation of the dominant sequence paradigm and role of dynamic contrast-enhanced imaging in PI-RADS version 2. Radiology 2017;285:859-869 https://doi.org/10.1148/radiol.2017161316
  8. Turco S, Lavini C, Heijmink S, Barentsz J, Wijkstra H, Mischi M. Evaluation of dispersion MRI for improved prostate cancer diagnosis in a multicenter study. AJR Am J Roentgenol 2018;211:W242-W251 https://doi.org/10.2214/AJR.17.19215
  9. Sanz-Requena R, Marti-Bonmati L, Perez-Martinez R, Garcia-Marti G. Dynamic contrast-enhanced casecontrol analysis in 3T MRI of prostate cancer can help to characterize tumor aggressiveness. Eur J Radiol 2016;85:2119-2126 https://doi.org/10.1016/j.ejrad.2016.09.022
  10. Vos EK, Litjens GJ, Kobus T, et al. Assessment of prostate cancer aggressiveness using dynamic contrast-enhanced magnetic resonance imaging at 3 T. Eur Urol 2013;64:448-455 https://doi.org/10.1016/j.eururo.2013.05.045
  11. Ocak I, Bernardo M, Metzger G, et al. Dynamic contrastenhanced MRI of prostate cancer at 3 T: a study of pharmacokinetic parameters. AJR Am J Roentgenol 2007;189:849 https://doi.org/10.2214/AJR.06.1329
  12. Kim JK, Hong SS, Choi YJ, et al. Wash-in rate on the basis of dynamic contrast-enhanced MRI: usefulness for prostate cancer detection and localization. J Magn Reson Imaging 2005;22:639-646 https://doi.org/10.1002/jmri.20431
  13. Oto A, Kayhan A, Jiang Y, et al. Prostate cancer: differentiation of central gland cancer from benign prostatic hyperplasia by using diffusion-weighted and dynamic contrast-enhanced MR imaging. Radiology 2010;257:715-723 https://doi.org/10.1148/radiol.10100021
  14. Padhani AR, Gapinski CJ, Macvicar DA, et al. Dynamic contrast enhanced MRI of prostate cancer: correlation with morphology and tumour stage, histological grade and PSA. Clin Radiol 2000;55:99-109 https://doi.org/10.1053/crad.1999.0327
  15. Riches SF, Payne GS, Morgan VA, et al. MRI in the detection of prostate cancer: combined apparent diffusion coefficient, metabolite ratio, and vascular parameters. AJR Am J Roentgenol 2009;193:1583-1591 https://doi.org/10.2214/AJR.09.2540
  16. Rosenkrantz AB, Kim S, Campbell N, Gaing B, Deng FM, Taneja SS. Transition zone prostate cancer: revisiting the role of multiparametric MRI at 3 T. AJR Am J Roentgenol 2015;204:W266-272 https://doi.org/10.2214/AJR.14.12955
  17. Schlemmer HP, Merkle J, Grobholz R, et al. Can preoperative contrast-enhanced dynamic MR imaging for prostate cancer predict microvessel density in prostatectomy specimens? Eur Radiol 2004;14:309-317 https://doi.org/10.1007/s00330-003-2025-2
  18. Franiel T, Hamm B, Hricak H. Dynamic contrast-enhanced magnetic resonance imaging and pharmacokinetic models in prostate cancer. Eur Radiol 2011;21:616-626 https://doi.org/10.1007/s00330-010-2037-7
  19. Rosenkrantz AB, Ginocchio LA, Cornfeld D, et al. Interobserver reproducibility of the PI-RADS version 2 lexicon: a multicenter study of six experienced prostate radiologists. Radiology 2016;280:793-804 https://doi.org/10.1148/radiol.2016152542
  20. Hansford BG, Peng Y, Jiang Y, et al. Dynamic contrastenhanced MR imaging curve-type analysis: is it helpful in the differentiation of prostate cancer from healthy peripheral zone? Radiology 2015;275:448-457 https://doi.org/10.1148/radiol.14140847
  21. Feinstein AR, Cicchetti DV. High agreement but low kappa: I. The problems of two paradoxes. J Clin Epidemiol 1990;43:543-549 https://doi.org/10.1016/0895-4356(90)90158-L
  22. Cicchetti DV, Feinstein AR. High agreement but low kappa: II. Resolving the paradoxes. J Clin Epidemiol 1990;43:551-558 https://doi.org/10.1016/0895-4356(90)90159-M
  23. Oto A, Yang C, Kayhan A, 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 https://doi.org/10.2214/AJR.11.6861
  24. Preziosi P, Orlacchio A, Di Giambattista G, et al. Enhancement patterns of prostate cancer in dynamic MRI. Eur Radiol 2003;13:925-930 https://doi.org/10.1007/s00330-002-1703-9

Cited by

  1. Optimization of Multi-Atlas Segmentation with Joint Label Fusion Algorithm for Automatic Segmentation in Prostate MR Imaging vol.24, pp.3, 2020, https://doi.org/10.13104/imri.2020.24.3.123