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European Radiology

Erschienen in:

24.11.2017 | Magnetic Resonance

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

verfasst von: Ling-Shan Chen, Zheng-Qiu Zhu, Zhi-Tao Wang, Jing Li, Li-Feng Liang, Ji-Yang Jin, Zhong-Qiu Wang

Erschienen in: European Radiology | Ausgabe 5/2018

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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.

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

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 151:497–501CrossRefPubMed

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 247:738–746CrossRefPubMed

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 184:1868–1872CrossRefPubMed

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

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 181:125–143CrossRefPubMed

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

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

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

10.

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

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 218:642–646CrossRefPubMed

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 231:711–716CrossRefPubMed

13.

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

14.

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

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 23:1738–1744CrossRefPubMed

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 205:103–107CrossRefPubMed

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 52:1847–1855CrossRefPubMed

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 239:174–180CrossRefPubMed

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 263:160–168CrossRefPubMed

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 265:468–477CrossRefPubMedPubMedCentral

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 84:360–365CrossRefPubMed

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 26:2242–2251CrossRefPubMed

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 208:124–130CrossRefPubMed

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–W86CrossRefPubMed

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 155:529–536CrossRefPubMed

26.

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

27.

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

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 192:438–443CrossRefPubMed

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 17:193–200CrossRefPubMed

30.

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

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 43:1079–1084CrossRef

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 75:845–851CrossRefPubMed

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 274:238–249CrossRefPubMed

34.

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

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 180:1649–1657CrossRefPubMed

36.

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

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 202:1196–1206CrossRefPubMedPubMedCentral

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 26:281–291CrossRefPubMed

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 27:612–624CrossRef

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 39:459–465CrossRefPubMed

42.

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

43.

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

44.

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

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 250:793–802CrossRefPubMed

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 49:215–224CrossRefPubMed

47.

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

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–W428CrossRefPubMed

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 23:339–344CrossRefPubMed

Titel: Chemical shift magnetic resonance imaging for distinguishing minimal-fat renal angiomyolipoma from renal cell carcinoma: a meta-analysis
verfasst von: Ling-Shan Chen
Zheng-Qiu Zhu
Zhi-Tao Wang
Jing Li
Li-Feng Liang
Ji-Yang Jin
Zhong-Qiu Wang
Publikationsdatum: 24.11.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: European Radiology / Ausgabe 5/2018
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-017-5141-0

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