Chemical shift magnetic resonance imaging for distinguishing minimal-fat renal angiomyolipoma from renal cell carcinoma: a meta-analysis
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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.
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.
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.
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.
• 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.
KeywordsRenal cell carcinoma Minimal-fat angiomyolipoma Chemical shift magnetic resonance imaging Chemical shift signal intensity index Differentiation
Compliance with ethical standards
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.
Institutional Review Board approval was not required because we only performed data analysis based on the published studies.
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.
• Diagnostic or prognostic study
• Performed at one institution
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