Skip to main content
Log in

Diagnostic performance of diffusion-weighted magnetic resonance imaging in differentiating human renal lesions (benignity or malignancy): a meta-analysis

  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

This study aims to quantitatively evaluate the potential of diffusion-weighted magnetic resonance imaging (DW-MRI) for differentiating malignant and benign human renal lesions.

Materials and methods

A systematic literature was performed to identify previous research related to the diagnostic performance of DW-MRI for determining whether human renal lesions were benign or malignant. ADC values were extracted from normal renal tissue and different lesion types. Data were extracted to assess the diagnostic performance of DW-MRI for differentiating malignant and benign human renal lesions, as well as running threshold effect and heterogeneity.

Results

Nine publications with 11 subsets were eligible for data extraction and diagnostic performance calculation. A total of 988 apparent diffusion coefficient (ADC) measurements were included. The differences in ADC values between benign lesions (2.47 ± 0.81 × 10−3 mm2/s) and malignant lesions (1.81 ± 0.41 × 10−3 mm2/s) were statistically significant (P < 0.001). The diagnostic odds ratio, the overall positive, negative likelihood ratios, pooled weighted sensitivity and specificity with 95% CI were 20.05 (95% CI 12.56–32.02), 3.32 (95% CI 2.13–5.18), 0.20 (95% CI 0.15–0.27), 88% (95% CI 0.84–0.91) and 72% (95% CI 0.67–0.76), respectively. The area under the curve of the summary receiver operating characteristic was 0.90.

Conclusions

This meta-analysis indicated that DW-MRI had a relatively good diagnostic accuracy in differentiating malignant and benign human renal lesions. We preliminarily recommend that DW-MRI is performed with a maximum b value ranging from 800 to 1000 s/mm2 at 3.0 T for imaging protocol, and that DW-MRI should be used with caution when the study population includes children.

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
Fig. 5

Similar content being viewed by others

References

  1. Goyal A, Sharma R, Bhalla AS, Gamanagatti S, Seth A (2013) Diffusion-weighted MRI in inflammatory renal lesions: all that glitters is not RCC!. Eur Radiol 23(1):272–279

    Article  PubMed  Google Scholar 

  2. Agnello F, Roy C, Bazille G, et al. (2013) Small solid renal masses: characterization by diffusion-weighted MRI at 3 T. Clin Radiol 68(6):e301–e308

    Article  CAS  PubMed  Google Scholar 

  3. Mehran R, Nikolsky E (2006) Contrast-induced nephropathy: definition, epidemiology, and patients at risk. Kidney Int Suppl 100:S11–S15

    Article  CAS  PubMed  Google Scholar 

  4. Sadowski EA, Bennett LK, Chan MR, et al. (2007) Nephrogenic systemic fibrosis: risk factors and incidence estimation. Radiology 243(1):148–157

    Article  PubMed  Google Scholar 

  5. Goyal A, Sharma R, Bhalla AS, et al. (2012) Diffusion-weighted MRI in renal cell carcinoma: a surrogate marker for predicting nuclear grade and histological subtype. Acta Radiol 53(3):349–358

    Article  PubMed  Google Scholar 

  6. Jacobs MA, Pan L, Macura KJ (2009) Whole-body diffusion-weighted and proton imaging: a review of this emerging technology for monitoring metastatic cancer. Semin Roentgenol 44(2):111–122

    Article  PubMed  PubMed Central  Google Scholar 

  7. Wu LM, Xu JR, Ye YQ, Lu Q, Hu JN (2012) The clinical value of diffusion-weighted imaging in combination with T2-weighted imaging in diagnosing prostate carcinoma: a systematic review and meta-analysis. AJR Am J Roentgenol 199(1):103–110

    Article  PubMed  Google Scholar 

  8. Wang H, Cheng L, Zhang X, et al. (2010) Renal cell carcinoma: diffusion-weighted MR imaging for subtype differentiation at 3.0 T. Radiology 257(1):135–143

    Article  PubMed  Google Scholar 

  9. Lassel EA, Rao R, Schwenke C, Schoenberg SO, Michaely HJ (2014) Diffusion-weighted imaging of focal renal lesions: a meta-analysis. Eur Radiol 24(1):241–249

    Article  CAS  PubMed  Google Scholar 

  10. Wang QB, Zhu H, Liu HL, Zhang B (2012) Performance of magnetic resonance elastography and diffusion-weighted imaging for the staging of hepatic fibrosis: a meta-analysis. Hepatology 56(1):239–247

    Article  PubMed  Google Scholar 

  11. Jin G, Su DK, Luo NB, et al. (2013) Meta-analysis of diffusion-weighted magnetic resonance imaging in detecting prostate cancer. J Comput Assist Tomogr 37(2):195–202

    Article  PubMed  Google Scholar 

  12. Deville WL, Buntinx F, Bouter LM, et al. (2002) Conducting systematic reviews of diagnostic studies: didactic guidelines. BMC Med Res Methodol 2:9

    Article  PubMed  PubMed Central  Google Scholar 

  13. Zamora J, Abraira V, Muriel A, Khan K, Coomarasamy A (2006) Meta-DiSc: a software for meta-analysis of test accuracy data. BMC Med Res Methodol 6:31

    Article  PubMed  PubMed Central  Google Scholar 

  14. Tang Y, Zhou Y, Du W, et al. (2014) Standard b-value versus low b-value diffusion-weighted MRI in renal cell carcinoma: a systematic review and meta-analysis. BMC Cancer 14:843

    Article  PubMed  PubMed Central  Google Scholar 

  15. Higgins JP, Thompson SG (2002) Quantifying heterogeneity in a meta-analysis. Stat Med 21:1539–1558

    Article  PubMed  Google Scholar 

  16. Vamvakas EC (1998) Meta-analyses of studies of the diagnostic accuracy of laboratory tests: a review of the concepts and methods. Arch Pathol Lab Med 122(8):675–686

    CAS  PubMed  Google Scholar 

  17. Dinnes J, Deeks J, Kirby J, Roderick P (2005) A methodological review of how heterogeneity has been examined in systematic reviews of diagnostic test accuracy. Health Technol Assess 9(12):1–113

    Article  CAS  Google Scholar 

  18. Deeks JJ, Macaskill P, Irwig L (2005) The performance of tests of publication bias and other sample size effects in systematic reviews of diagnostic test accuracy was assessed. J Clin Epidemiol 58(9):882–893

    Article  PubMed  Google Scholar 

  19. Song F, Khan KS, Dinnes J, Sutton AJ (2002) Asymmetric funnel plots and publication bias in meta-analyses of diagnostic accuracy. Int J Epidemiol 31(1):88–95

    Article  PubMed  Google Scholar 

  20. Doganay S, Kocakoc E, Cicekci M, et al. (2011) Ability and utility of diffusion-weighted MRI with different b values in the evaluation of benign and malignant renal lesions. Clin Radiol 66(5):420–425

    Article  CAS  PubMed  Google Scholar 

  21. Erbay G, Koc Z, Karadeli E, et al. (2012) Evaluation of malignant and benign renal lesions using diffusion-weighted MRI with multiple b values. Acta Radiol 53(3):359–365

    Article  PubMed  Google Scholar 

  22. Kim S, Jain M, Harris AB, et al. (2009) T1 hyperintense renal lesions: characterization with diffusion-weighted MR imaging versus contrast-enhanced MR imaging. Radiology 251(3):796–807

    Article  PubMed  Google Scholar 

  23. Razek A, Farouk A, Mousa A, Nabil N (2011) Role of diffusion-weighted magnetic resonance imaging in characterization of renal tumors. J Comput Assist Tomogr 35(3):332–336

    Article  PubMed  Google Scholar 

  24. Rheinheimer S, Stieltjes B, Schneider F, et al. (2012) Investigation of renal lesions by diffusion-weighted magnetic resonance imaging applying intravoxel incoherent motion-derived parameters–initial experience. Eur J Radiol 81(3):e310–e316

    Article  CAS  PubMed  Google Scholar 

  25. Sandrasegaran K, Sundaram CP, Ramaswamy R, et al. (2010) Usefulness of diffusion-weighted imaging in the evaluation of renal masses. AJR Am J Roentgenol 194(2):438–445

    Article  PubMed  Google Scholar 

  26. Taouli B, Thakur RK, Mannelli L, et al. (2009) Renal lesions: characterization with diffusion-weighted imaging versus contrast-enhanced MR imaging. Radiology 251(2):398–407

    Article  PubMed  Google Scholar 

  27. Zhang YL, Yu BL, Ren J, et al. (2013) EADC values in diagnosis of renal lesions by 3.0 T diffusion-weighted magnetic resonance imaging: compared with the ADC values. Appl Magn Reson 44(3):349–363

    Article  CAS  PubMed  Google Scholar 

  28. Yano C, Iwata M, Uchiyama S (2011) Risk factors for small cortical infarction on diffusion-weighted magnetic resonance imaging in patients with acute ischemic stroke. J Stroke Cerebrovasc Dis 20(1):68–74

    Article  PubMed  Google Scholar 

  29. Jie C, Rongbo L, Ping T (2014) The value of diffusion-weighted imaging in the detection of prostate cancer: a meta-analysis. Eur Radiol 24(8):1929–1941

    Article  PubMed  PubMed Central  Google Scholar 

  30. Khuroo MS, Khuroo NS, Khuroo MS (2014) Accuracy of rapid point-of-care diagnostic tests for hepatitis B surface antigen—a systematic review and meta-analysis. J Clin Exp Hepatol 4(3):226–240

    Article  PubMed  PubMed Central  Google Scholar 

  31. Mutsaerts HJ, van Osch MJ, Zelaya FO, et al. (2015) Multi-vendor reliability of arterial spin labeling perfusion MRI using a near-identical sequence: implications for multi-center studies. Neuroimage 113:143–152

    Article  PubMed  Google Scholar 

  32. Chen JH, Chan S, Liu YJ, et al. (2012) Consistency of breast density measured from the same women in four different MR scanners. Med Phys 39(8):4886–4895

    Article  PubMed  PubMed Central  Google Scholar 

  33. Reig S, Sanchez-Gonzalez J, Arango C, et al. (2009) Assessment of the increase in variability when combining volumetric data from different scanners. Hum Brain Mapp 30(2):355–368

    Article  PubMed  Google Scholar 

  34. Lagemaat MW, Scheenen TW (2014) Role of high-field MR in studies of localized prostate cancer. NMR Biomed 27(1):67–79

    Article  PubMed  Google Scholar 

  35. Saremi F, Knoll AN, Bendavid OJ, Schultze-Haakh H, et al. (2009) Characterization of genitourinary lesions with diffusion-weighted imaging. Radiographics 29(5):1295–1317

    Article  PubMed  Google Scholar 

  36. Koh DM, Takahara T, Imai Y, Collins DJ (2007) Practical aspects of assessing tumors using clinical diffusion-weighted imaging in the body. Magn Reson Med Sci 6(4):211–224

    Article  PubMed  Google Scholar 

  37. Lohi O, Jahnukainen K, Huttunen P, et al. (2014) Solid tumors in children. Duodecim 130(20):2050–2059

    PubMed  Google Scholar 

  38. Malkan AD, Loh A, Bahrami A, et al. (2015) An approach to renal masses in pediatrics. Pediatrics 135(1):142–158

    Article  PubMed  Google Scholar 

  39. Sevcenco S, Heinz-Peer G, Ponhold L, et al. (2014) Utility and limitations of 3-Tesla diffusion-weighted magnetic resonance imaging for differentiation of renal tumors. Eur J Radiol 83(6):909–913

    Article  CAS  PubMed  Google Scholar 

  40. Tanaka H, Yoshida S, Fujii Y, et al. (2011) Diffusion-weighted magnetic resonance imaging in differentiation of angiomyolipoma with minimal fat from clear cell renal cell carcinoma. Int J Urol 18(10):727–730

    Article  PubMed  Google Scholar 

  41. Rao RK, Riffel P, Meyer M, et al. (2012) Implementation of dual-source RF excitation in 3 T MR-scanners allows for nearly identical ADC values compared to 1.5 T MR scanners in the abdomen. PLoS One 7(2):e32613

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Wu GY, Lu Q, Wu LM, et al. (2014) Imaging of upper urinary tract cancer: using conventional MRI and diffusion-weighted MRI with different b values. Acta Radiol 55(7):882–889

    Article  PubMed  Google Scholar 

  43. Park SY, Kim CK, Park BK, Kwon GY (2014) Comparison of apparent diffusion coefficient calculation between two-point and multipoint B value analyses in prostate cancer and benign prostate tissue at 3 T: preliminary experience. AJR Am J Roentgenol 203(3):W287–W294

    Article  PubMed  Google Scholar 

  44. Chandarana H, Kang SK, Wong S, et al. (2012) Diffusion-weighted intravoxel incoherent motion imaging of renal tumors with histopathologic correlation. Invest Radiol 47(12):688–696

    Article  PubMed  Google Scholar 

  45. Golshahi J, Nasri H, Gharipour M (2014) Contrast-induced nephropathy: a literature review. J Nephropathol 3(2):51–56

    PubMed  PubMed Central  Google Scholar 

  46. Ho VB, Allen SF, Hood MN, Choyke PL (2002) Renal masses: quantitative assessment of enhancement with dynamic MR imaging. Radiology 224(3):695–700

    Article  PubMed  Google Scholar 

  47. Scialpi M, Di Maggio A, Midiri M, et al. (2000) Small renal masses: assessment of lesion characterization and vascularity on dynamic contrast-enhanced MR imaging with fat suppression. AJR Am J Roentgenol 175(3):751–757

    Article  CAS  PubMed  Google Scholar 

  48. Yamashita Y, Miyazaki T, Hatanaka Y, Takahashi M (1995) Dynamic MRI of small renal cell carcinoma. J Comput Assist Tomogr 19(5):759–765

    Article  CAS  PubMed  Google Scholar 

  49. Sevcenco S, Ponhold L, Javor D, et al. (2014) Three-Tesla dynamic contrast-enhanced MRI: a critical assessment of its use for differentiation of renal lesion subtypes. World J Urol 32(1):215–220

    Article  CAS  PubMed  Google Scholar 

  50. Cornelis F, Tricaud E, Lasserre AS, et al. (2014) Routinely performed multiparametric magnetic resonance imaging helps to differentiate common subtypes of renal tumours. Eur Radiol 24(5):1068–1080

    Article  CAS  PubMed  Google Scholar 

  51. Schunk K, Schild H, Strunk H, et al. (1994) Computerized tomography of kidney tumors. Aktuelle Radiol 4(5):235–242

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to thank Moira R. Hitchens (Department of Radiology, University of Pittsburgh) for revising our manuscript. This work was supported by Sichuan Provincial Science and Technology plan Grants 2011SZ0160.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bin Song.

Ethics declarations

Conflict of Interest

Hanmei Zhang, Qi Gan, Yinghua Wu, Rongbo Liu, Xijiao Liu, Zixing Huang, Fang Yuan, Min Kuang, Bin Song declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. For this type of study formal consent is not required.

Informed consent

All analyses are based on previous published studies; thus, no informed consent is required.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 15 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, H., Gan, Q., Wu, Y. et al. Diagnostic performance of diffusion-weighted magnetic resonance imaging in differentiating human renal lesions (benignity or malignancy): a meta-analysis. Abdom Radiol 41, 1997–2010 (2016). https://doi.org/10.1007/s00261-016-0790-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-016-0790-z

Keywords

Navigation