Skip to main content

Advertisement

Log in

Comparison of diagnostic performance between diffusion kurtosis imaging parameters and mono-exponential ADC for determination of clinically significant cancer in patients with prostate cancer

  • Pelvis
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

To compare the diagnostic performance between diffusion kurtosis imaging (DKI) parameters and mono-exponential apparent diffusion coefficient (ADC) for determination of clinically significant cancer (CSC, Gleason score (GS) ≥ 7) in patients with histologically proven prostate cancer (PCa).

Methods

A total of 92 patients (mean age: 71.5 years, range: 47–89 years) who had been diagnosed as PCa and undergone 3 T-MRI including DWI (b values, 0, 100, 1000, 2000s/mm2) were included in this study. The DKI parameters, namely apparent diffusion for non-Gaussian distribution (Dapp) and apparent kurtosis coefficient (Kapp), were calculated by dedicated software using mono-exponential and diffusion kurtosis models for quantitation. The measurement was performed for a whole tumor after segmentation, and pathologic topographic maps or systemic biopsy results served as the reference standard for segmentation. To compare the diagnostic performance of each parameter for determination of CSC, pair-wise comparison of receiver operating characteristic (ROC) curves was performed.

Results

The study population consisted of GS 6 (n = 18), GS 7 (n = 31), GS 8 (n = 25), GS 9 (n = 15) and GS 10 (n = 3) patients. The area under the ROC curve of Kapp (0.707, 95% CI 0.603–0.798) for discriminating CSC from non-CSC was not significantly different from those of mono-exponential ADC (0.725, 0.622–0.813, P = 0.2175) or Dapp (0.726, 0.623–0.814, P = 0.9628). Diagnostic predictive values of Kapp were estimated to a maximum accuracy of 78%, a sensitivity of 86%, and a specificity of 47%, while those of mono-exponential ADC were 75, 81, and 53%, respectively.

Conclusion

The DKI parameters showed a diagnostic performance comparable to mono-exponential ADC for determination of CSC in patients with PCa.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018-2020) Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 68:394-424. https://doi.org/10.3322/caac.21492

  2. Corcoran NM, Hong MK, Casey RG, Hurtado-Coll A, Peters J, Harewood L, Goldenberg SL, Hovens CM, Costello AJ, Gleave ME (2011) Upgrade in Gleason score between prostate biopsies and pathology following radical prostatectomy significantly impacts upon the risk of biochemical recurrence. BJU international 108 (8b):E202-E210. https://doi.org/https://doi.org/10.1111/j.1464-410X.2011.10119.x

  3. Borghesi M, Ahmed H, Nam R, Schaeffer E, Schiavina R, Taneja S, Weidner W, Loeb S (2017) Complications after systematic, random, and image-guided prostate biopsy. European urology 71 (3):353-365. https://doi.org/https://doi.org/10.1016/j.eururo.2016.08.004

  4. Vargas HA, Akin O, Franiel T, Mazaheri Y, Zheng J, Moskowitz C, Udo K, Eastham J, Hricak H (2011) Diffusion-weighted endorectal MR imaging at 3 T for prostate cancer: tumor detection and assessment of aggressiveness. Radiology 259 (3):775-784. https://doi.org/https://doi.org/10.1148/radiol.11102066

  5. Jung SI, Donati OF, Vargas HA, Goldman D, Hricak H, Akin O (2013) Transition zone prostate cancer: incremental value of diffusion-weighted endorectal MR imaging in tumor detection and assessment of aggressiveness. Radiology 269 (2):493-503. https://doi.org/https://doi.org/10.1148/radiol.13130029

  6. Si Y, Liu R-b (2018) Diagnostic performance of Monoexponential DWI versus diffusion kurtosis imaging in prostate Cancer: a systematic review and meta-analysis. American Journal of Roentgenology 211 (2):358-368. https://doi.org/https://doi.org/10.2214/AJR.17.18934

  7. Rosenkrantz AB, Padhani AR, Chenevert TL, Koh DM, De Keyzer F, Taouli B, Le Bihan D (2015) Body diffusion kurtosis imaging: basic principles, applications, and considerations for clinical practice. Journal of Magnetic Resonance Imaging 42 (5):1190-1202. https://doi.org/https://doi.org/10.1002/jmri.24985

  8. Jensen JH, Helpern JA, Ramani A, Lu H, Kaczynski K (2005) Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magnetic Resonance in Medicine: An Official Journal of the International Society for Magnetic Resonance in Medicine 53 (6):1432-1440. https://doi.org/https://doi.org/10.1002/mrm.20508

  9. Van Cauter S, Veraart J, Sijbers J, Peeters RR, Himmelreich U, De Keyzer F, Van Gool SW, Van Calenbergh F, De Vleeschouwer S, Van Hecke W (2012) Gliomas: diffusion kurtosis MR imaging in grading. Radiology 263 (2):492-501. https://doi.org/https://doi.org/10.1148/radiol.12110927

  10. Barrett T, McLean M, Priest AN, Lawrence EM, Patterson AJ, Koo BC, Patterson I, Warren AY, Doble A, Gnanapragasam VJ (2018) Diagnostic evaluation of magnetization transfer and diffusion kurtosis imaging for prostate cancer detection in a re-biopsy population. European radiology 28 (8):3141-3150. https://doi.org/https://doi.org/10.1007/s00330-017-5169-1

  11. Roethke MC, Kuder TA, Kuru TH, Fenchel M, Hadaschik BA, Laun FB, Schlemmer H-P, Stieltjes B (2015) Evaluation of diffusion kurtosis imaging versus standard diffusion imaging for detection and grading of peripheral zone prostate cancer. Investigative radiology 50 (8):483-489. https://doi.org/https://doi.org/10.1097/RLI.0000000000000155

  12. Toivonen J, Merisaari H, Pesola M, Taimen P, Bostrom PJ, Pahikkala T, Aronen HJ, Jambor I (2015) Mathematical models for diffusion-weighted imaging of prostate cancer using b values up to 2000s/mm2: Correlation with Gleason score and repeatability of region of interest analysis. Magnetic resonance in medicine 74 (4):1116-1124. https://doi.org/https://doi.org/10.1002/mrm.25482

  13. Wang Q, Li H, Yan X, Wu C-J, Liu X-S, Shi H-B, Zhang Y-D (2015) Histogram analysis of diffusion kurtosis magnetic resonance imaging in differentiation of pathologic Gleason grade of prostate cancer. In: Urologic oncology: seminars and original investigations. vol 8. Elsevier, pp 337. e315-337. e324. https://doi.org/https://doi.org/10.1016/j.urolonc.2015.05.005

  14. Rosenkrantz AB, Sigmund EE, Johnson G, Babb JS, Mussi TC, Melamed J, Taneja SS, Lee VS, Jensen JH (2012) Prostate cancer: feasibility and preliminary experience of a diffusional kurtosis model for detection and assessment of aggressiveness of peripheral zone cancer. Radiology 264 (1):126-135. https://doi.org/https://doi.org/10.1148/radiol.12112290

  15. Suo S, Chen X, Wu L, Zhang X, Yao Q, Fan Y, Wang H, Xu J (2014) Non-Gaussian water diffusion kurtosis imaging of prostate cancer. Magnetic resonance imaging 32 (5):421-427. https://doi.org/https://doi.org/10.1016/j.mri.2014.01.015

  16. Wu C-J, Zhang Y-D, Bao M-L, Li H, Wang X-N, Liu X-S, Shi H-B (2017) Diffusion kurtosis imaging helps to predict upgrading in biopsy-proven prostate Cancer with a Gleason score of 6. American Journal of Roentgenology 209 (5):1081-1087. https://doi.org/https://doi.org/10.2214/AJR.16.17781

  17. Epstein JI, Egevad L, Amin MB, Delahunt B, Srigley JR, Humphrey PA (2016-2020) The 2014 International Society of Urological Pathology (ISUP) consensus conference on Gleason grading of prostatic carcinoma. The American journal of surgical pathology 40 (2):244-252. https://doi.org/10.1097/PAS.0000000000000530

  18. Tamada T, Prabhu V, Li J, Babb JS, Taneja SS, Rosenkrantz AB (2017) Prostate cancer: diffusion-weighted MR imaging for detection and assessment of aggressiveness - comparison between conventional and kurtosis models. Radiology 284 (1):100-108. https://doi.org/https://doi.org/10.1148/radiol.2017162321

  19. Shan Y, Chen X, Liu K, Zeng M, Zhou J (2019) Prostate cancer aggressive prediction: preponderant diagnostic performances of intravoxel incoherent motion (IVIM) imaging and diffusion kurtosis imaging (DKI) beyond ADC at 3.0 T scanner with gleason score at final pathology. Abdominal Radiology 44 (10):3441-3452. https://doi.org/https://doi.org/10.1007/s00261-019-02075-3

  20. Ding K, Yao Y, Gao Y, Lu X, Chen H, Tang Q, Hua C, Zhou M, Zou X, Yin Q (2019) Diagnostic evaluation of diffusion kurtosis imaging for prostate cancer: Detection in a biopsy population. European journal of radiology 118:138-146. https://doi.org/https://doi.org/10.1016/j.ejrad.2019.07.009

  21. Park SY, Jung DC, Oh YT, Cho NH, Choi YD, Rha KH, Hong SJ, Han K (2016) Prostate cancer: PI-RADS version 2 helps preoperatively predict clinically significant cancers. Radiology 280 (1):108-116. https://doi.org/https://doi.org/10.1148/radiol.16151133

  22. Chen S, Yang Y, Peng T, Yu X, Deng H, Guo Z (2020) The prediction value of PI-RADS v2 score in high-grade Prostate Cancer: a multicenter retrospective study. International journal of medical sciences 17 (10):1366-1374. https://doi.org/https://doi.org/10.7150/ijms.45730

  23. Epstein JI (2010) An update of the Gleason grading system. The Journal of urology 183 (2):433-440. https://doi.org/https://doi.org/10.1016/j.juro.2009.10.046

  24. Bourne R, Kurniawan N, Cowin G, Sved P, Watson G (2011) 16 T diffusion microimaging of fixed prostate tissue: preliminary findings. Magnetic resonance in medicine 66 (1):244-247. https://doi.org/https://doi.org/10.1002/mrm.22778

  25. Jia G, Abaza R, Williams JD, Zynger DL, Zhou J, Shah ZK, Patel M, Sammet S, Wei L, Bahnson RR (2011) Amide proton transfer MR imaging of prostate cancer: a preliminary study. Journal of Magnetic Resonance Imaging 33 (3):647-654. https://doi.org/https://doi.org/10.1002/jmri.22480

  26. Takayama Y, Nishie A, Sugimoto M, Togao O, Asayama Y, Ishigami K, Ushijima Y, Okamoto D, Fujita N, Yokomizo A, Keupp J, Honda H (2016) Amide proton transfer (APT) magnetic resonance imaging of prostate cancer: comparison with Gleason scores. Magnetic Resonance Materials in Physics 29 (4):671-679. https://doi.org/https://doi.org/10.1007/s10334-016-0537-4

  27. Jensen JH, Helpern JA (2010) MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR in Biomedicine 23 (7):698-710. https://doi.org/https://doi.org/10.1002/nbm.1518

  28. Sun K, Chen X, Chai W, Fei X, Fu C, Yan X, Zhan Y, Chen K, Shen K, Yan F (2015) Breast cancer: diffusion kurtosis MR imaging - diagnostic accuracy and correlation with clinical-pathologic factors. Radiology 277 (1):46-55. https://doi.org/https://doi.org/10.1148/radiol.15141625

Download references

Funding

Not applicable.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Seung Ho Kim.

Ethics declarations

Conflict of interest

All authors declare that they have no conflict of interest.

Ethical approval

This retrospective study was approved by the institutional review board, and informed consent was waived. (Approval Protocol Number: HPIRB 2020–01-001).

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Park, H., Kim, S.H., Lee, Y. et al. Comparison of diagnostic performance between diffusion kurtosis imaging parameters and mono-exponential ADC for determination of clinically significant cancer in patients with prostate cancer. Abdom Radiol 45, 4235–4243 (2020). https://doi.org/10.1007/s00261-020-02776-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-020-02776-0

Keywords

Navigation