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Chemical shift magnetic resonance imaging for distinguishing minimal-fat renal angiomyolipoma from renal cell carcinoma: a meta-analysis

  • Magnetic Resonance
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Abstract

Objectives

To determine the performance of chemical shift signal intensity index (CS-SII) values for distinguishing minimal-fat renal angiomyolipoma (mfAML) from renal cell carcinoma (RCC) and to assess RCC subtype characterisation.

Methods

We identified eligible studies on CS magnetic resonance imaging (CS-MRI) of focal renal lesions via PubMed, Embase, and the Cochrane Library. CS-SII values were extracted by lesion type and evaluated using linear mixed model-based meta-regression. RCC subtypes were analysed. Two-sided p value <0.05 indicated statistical significance. Methodological quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool.

Results

Eleven articles involving 850 patients were included. Minimal-fat AML had significantly higher CS-SII value than RCC (p < 0.05); there were no significant differences between mfAML and clear cell RCC (cc-RCC) (p = 0.112). Clear cell RCC had a significantly higher CS-SII value than papillary RCC (p-RCC) (p < 0.001) and chromophobe RCC (ch-RCC) (p = 0.045). The methodological quality was relatively high, and Begg’s test data points indicated no obvious publication bias.

Conclusions

The CS-SII value for differentiating mfAML from cc-RCC remains unproven, but is a promising method for differentiating cc-RCC from p-RCC and ch-RCC.

Key Points

RCC CS-SII values are significantly lower than those of mfAML overall.

CS-SII values cannot aid differentiation between mfAML and cc-RCC.

CS-SII values might help characterise RCC subtypes.

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References

  1. Bissler JJ, Kingswood JC (2004) Renal angiomyolipomata. Kidney Int 66:924–934

    Article  PubMed  Google Scholar 

  2. Bosniak MA, Megibow AJ, Hulnick DH et al (1988) CT diagnosis of renal angiomyolipoma: the importance of detecting small amounts of fat. AJR Am J Roentgenol 151:497–501

    Article  CAS  PubMed  Google Scholar 

  3. Catalano OA, Samir AE, Sahani DV et al (2008) Pixel distribution analysis: can it be used to distinguish clear cell carcinomas from angiomyolipomas with minimal fat? Radiology 247:738–746

    Article  PubMed  Google Scholar 

  4. Israel GM, Hindman N, Hecht E et al (2005) The use of opposed-phase chemical shift MRI in the diagnosis of renal angiomyolipomas. AJR Am J Roentgenol 184:1868–1872

    Article  PubMed  Google Scholar 

  5. Jinzaki M, Tanimoto A, Narimatsu Y et al (1997) Angiomyolipoma: imaging findings in lesions with minimal fat. Radiology 205:497–502

    Article  CAS  PubMed  Google Scholar 

  6. Thoenes W, Störkel S, Rumpelt HJ et al (1986) Histopathology and classification  of renal cell tumors (adenomas, oncocytomas and carcinomas). The basic cytological and histopathological elements and their use for diagnostics. Pathol Res Pract 181:125–143

    Article  CAS  PubMed  Google Scholar 

  7. O’Toole KM, Brown M, Hoffmann P et al (1993) Pathology of benign and  malignant kidney tumors. Urol Clin North Am 20:193–205

    PubMed  Google Scholar 

  8. Hajdu SI, Savino A, Hajdu EO et al (1971) Cytologic diagnosis of renal cell carcinoma with the aid of fat stain. Acta Cytol 15:31–33

    CAS  PubMed  Google Scholar 

  9. Krishnan B, Truong LD (2002) Renal epithelial neoplasms: the diagnostic  implications of electron microscopic study in 55 cases. Hum Pathol 33:68–79

    Article  PubMed  Google Scholar 

  10. Hood MN, Ho VB, Smirniotopoulos JG et al (1999) Chemical shift: the artifact and clinical tool revisited. Radiographics 19:357–371

    Article  CAS  PubMed  Google Scholar 

  11. Namimoto T, Yamashita Y, Mitsuzaki K et al (2001) Adrenal masses: quantification of fat content with double-echo chemical shift in-phase and opposed-phase FLASH MR images for differentiation of adrenal adenomas. Radiology 218:642–646

    Article  CAS  PubMed  Google Scholar 

  12. Haider MA, Ghai S, Jhaveri K et al (2004) Chemical shift MR imaging of hyperattenuating (10 HU) adrenal asses: does it still have a role? Radiology 231:711–716

    Article  PubMed  Google Scholar 

  13. Hosokawa Y, Kinouchi T, Sawai Y et al (2002) Renal angiomyolipoma with minimal fat. Int J Clin Oncol 7:120–123

    PubMed  Google Scholar 

  14. Delfaut EM, Beltran J, Johnson G et al (1999) Fat suppression in MR imaging: techniques and pitfalls. Radiographics 19:373–382

    Article  CAS  PubMed  Google Scholar 

  15. Karlo CA, Donati OF, Burger IA et al (2013) MR imaging of renal cortical tumours: qualitative and quantitative chemical shift imaging parameters. Eur Radiol 23:1738–1744

    Article  PubMed  Google Scholar 

  16. Outwater EK, Bhatia M, Siegelman ES et al (1997) Lipid in renal clear cell carcinoma: detection on opposed-phase gradient-echo MR images. Radiology 205:103–107

    Article  CAS  PubMed  Google Scholar 

  17. Peng XG, Ju S, Qin Y et al (2011) Quantification of liver fat in mice: comparing dual-echo Dixon imaging, chemical shift imaging, and 1H-MR spectroscopy. J Lipid Res 52:1847–1855

    Article  CAS  PubMed  Google Scholar 

  18. Kim JK, Kim SH, Jang YJ et al (2006) Renal angiomyolipoma with minimal fat: differentiation from other neoplasms at double-echo chemical shift FLASH MR imaging. Radiology 239:174–180

    Article  PubMed  Google Scholar 

  19. Sasiwimonphan K, Takahashi N, Leibovich BC et al (2012) Small (<4 cm) renal mass: differentiation of angiomyolipoma without visible fat from renal cell carcinoma utilizing MR imaging. Radiology 263:160–168

    Article  PubMed  Google Scholar 

  20. Hindman N, Ngo L, Genega EM et al (2012) Angiomyolipoma with minimal fat: can it be differentiated from clear cell renal cell carcinoma by using standard MR techniques? Radiology 265:468–477

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ferré R, Cornelis F, Verkarre V et al (2015) Double-echo gradient chemical shift MR imaging fails to differentiate minimal fat renal angiomyolipomas from other homogeneous solid renal tumors. Eur J Radiol 84:360–365

    Article  PubMed  Google Scholar 

  22. Schieda N, Dilauro M, Moosavi B et al (2016) MRI evaluation of small (<4 cm) solid renal masses: multivariate modeling improves diagnostic accuracy for angiomyolipoma without visible fat compared to univariate analysis. Eur Radiol 26:2242–2251

    Article  PubMed  Google Scholar 

  23. Park JJ, Kim CK (2017) Small (<4 cm) renal tumors with predominantly low signal intensity on T2-weighted images: differentiation of minimal-fat angiomyolipoma from renal cell carcinoma. AJR Am J Roentgenol 208:124–130

    Article  PubMed  Google Scholar 

  24. Jhaveri KS, Elmi A, Hosseini-Nik H et al (2015) Predictive value of chemical-shift MRI in distinguishing clear cell renal cell carcinoma from non–clear cell renal cell carcinoma and minimal-fat angiomyolipoma. AJR Am J Roentgenol 205:W79–W86

    Article  PubMed  Google Scholar 

  25. Whiting PF, Rutjes AW, Westwood ME et al (2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155:529–536

    Article  PubMed  Google Scholar 

  26. Hafron J, Fogarty JD, Hoenig DM et al (2005) Imaging characteristics of minimal fat renal angiomyolipoma with histologic correlations. Urology 66:1155–1159

    Article  PubMed  Google Scholar 

  27. Milner J, McNeil B, Alioto J et al (2006) Fat poor renal angiomyolipoma: patient, computerized tomography and histological findings. J Urol 176:905–909

    Article  PubMed  Google Scholar 

  28. Simpfendorfer C, Herts BR, Motta-Ramirez GA et al (2009) Angiomyolipoma with minimal fat on MDCT: can counts of negative-attenuation pixels aid diagnosis? AJR Am J Roentgenol 192:438–443

    Article  PubMed  Google Scholar 

  29. Roy C, Sauer B, Lindner V et al (2007) MR Imaging of papillary renal neoplasms: potential application for characterization of small renal masses. Eur Radiol 17:193–200

    Article  PubMed  Google Scholar 

  30. Pedrosa I, Sun MR, Spencer M et al (2008) MR imaging of renal masses: correlation with findings at surgery and pathologic analysis. Radiographics 28:985–1003

    Article  PubMed  Google Scholar 

  31. Kohl CA, Chivers FS, Lorans R et al (2014) Accuracy of chemical shift MR imaging in diagnosing indeterminate bone marrow lesions in the pelvis: review of a single institution's experience. Skelet Radiol 43:1079–1084

    Article  Google Scholar 

  32. Wang X, Hernando D, Reeder SB et al (2016) Sensitivity of chemical shift-encoded fat quantification to calibration of fat MR spectrum. Magn Reson Med 75:845–851

    Article  PubMed  Google Scholar 

  33. Priola AM, Priola SM, Ciccone G et al (2015) Differentiation of rebound and lymphoid thymic hyperplasia from anterior mediastinal tumors with dual echo chemical-shift MR imaging in adulthood: reliability of the chemical shift ratio and signal intensity index. Radiology 274:238–249

    Article  PubMed  Google Scholar 

  34. Tsushima Y, Ishizaka H, Matsumoto M et al (2015) Adrenal masses: differentiation with chemical shift, fast low-angle shot MR imaging. Radiology 186:705–709

    Article  Google Scholar 

  35. Fujiyoshi F, Nakajo M, Fukukura Y et al (2003) Characterization of adrenal tumors by chemical shift fast low-angle shot MR imaging: comparison of four methods of quantitative evaluation. AJR Am J Roentgenol 180:1649–1657

    Article  PubMed  Google Scholar 

  36. Reuter VE (2003) The pathology of renal epithelial neoplasms. Semin Oncol 33:534–543

    Article  Google Scholar 

  37. Lim RS, Flood TA, McInnes MDF et al (2017) Renal angiomyolipoma without visible fat: Can we make the diagnosis using CT and MRI? Eur Radiol. https://doi.org/10.1007/s 00330-017-4988-4

  38. Kang SK, Huang WC, Pandharipande PV et al (2014) Solid renal masses: what the numbers tell us. AJR Am J Roentgenol 202:1196–1206

    Article  PubMed  PubMed Central  Google Scholar 

  39. Amin MB, Amin MB, Tamboli P et al (2002) Prognostic impact of histologic subtyping of adult renal epithelial neoplasms: an experience of 405 cases. Am J Surg Pathol 26:281–291

    Article  PubMed  Google Scholar 

  40. Cheville JC, Lohse CM, Zincke H et al (2002) Comparisons of outcome and prognostic features among histologic subtypes of renal cell carcinoma. Am J Surg Pathol 27:612–624

    Article  Google Scholar 

  41. Delahunt B, Bethwaite PB, Nacey JN (2007) Outcome prediction for renal cell carcinoma: evaluation of prognostic factors for tumours divided according to histological subtype. Pathology 39:459–465

    Article  CAS  PubMed  Google Scholar 

  42. Escudier B, Eisen T, Stadler WM et al (2007) Sorafenib in advanced clear-cell renal-cell carcinoma. N Engl J Med 356:125–134

    Article  CAS  PubMed  Google Scholar 

  43. Motzer RJ, Hutson TE, Tomczak P et al (2007) Sunitinib versus interferon alfa in metastatic renal-cell carcinoma. N Engl J Med 356:115–124

    Article  CAS  PubMed  Google Scholar 

  44. Chowdhury S, Choueiri TK (2009) Recent advances in the systemic treatment of metastatic papillary renal cancer. Expert Rev Anticancer Ther 9:373–379

    Article  CAS  PubMed  Google Scholar 

  45. Sun MR, Ngo L, Genega EM et al (2009) Renal cell carcinoma: dynamic contrast -enhanced MR imaging for differentiation of tumor subtypes—correlation with pathologic findings. Radiology 250:793–802

    Article  PubMed  Google Scholar 

  46. Mytsyk Y, Dutka I, Borys Y et al (2016) Renal cell carcinoma: applicability of the apparent coefficient of the diffusion‑weighted estimated by MRI for improving their differential diagnosis, histologic subtyping, and differentiation grade. Int Urol Nephrol 49:215–224

    Article  PubMed  Google Scholar 

  47. Pedrosa I, Chou MT, Ngo L et al (2007) MR classification of renal masses with pathologic correlation. Eur Radiol 18:365–375

    Article  PubMed  Google Scholar 

  48. Childs DD, Clingan MJ, Zagoria RJ et al (2014) In-phase signal intensity loss in solid renal masses on dual-echo gradient-echo MRI: association with malignancy and pathologic classification. AJR Am J Roentgenol 203:W421–W428

    Article  PubMed  Google Scholar 

  49. Yoshimitsu K, Kakihara D, Irie H et al (2006) Papillary renal carcinoma: diagnostic approach by chemical shift gradient echo and echo-planar MR imaging. J Magn Reson Imaging 23:339–344

    Article  PubMed  Google Scholar 

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Funding

This study has received funding by the National Natural Science Foundation of China (81471705).

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Corresponding author

Correspondence to Zhong-Qiu Wang.

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Guarantor

The scientific guarantor of this publication is Zhong-Qiu Wang, MD, PhD, (Department of Radiology, Affiliated Hospital of Nanjing University of CM, Nanjing 210029, China).

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

Pin Wang, PhD, (Department of Endocrinology, Sichuan Academy of Medical Science and Sichuan Provincial People’s Hospital, Chengdu, Sichuan, China) kindly provided statistical advice for this manuscript.

Ethical approval

Institutional Review Board approval was not required because we only performed data analysis based on the published studies.

Informed consent

Informed consent was not required because this is a meta-analysis of several published papers and therefore data of our cohorts have been published already in these papers.

Methodology

• Diagnostic or prognostic study

• Performed at one institution

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Chen, LS., Zhu, ZQ., Wang, ZT. et al. Chemical shift magnetic resonance imaging for distinguishing minimal-fat renal angiomyolipoma from renal cell carcinoma: a meta-analysis. Eur Radiol 28, 1854–1861 (2018). https://doi.org/10.1007/s00330-017-5141-0

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  • DOI: https://doi.org/10.1007/s00330-017-5141-0

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