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BioScientifica, European Journal of Endocrinology, 2(175), p. R51-R64, 2016

DOI: 10.1530/eje-16-0461

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MANAGEMENT OF ENDOCRINE DISEASE: Imaging for the diagnosis of malignancy in incidentally discovered adrenal masses: a systematic review and meta-analysis

This paper is available in a repository.
This paper is available in a repository.

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Abstract

ObjectiveAdrenal masses are incidentally discovered in 5% of CT scans. In 2013/2014, 81 million CT examinations were undertaken in the USA and 5 million in the UK. However, uncertainty remains around the optimal imaging approach for diagnosing malignancy. We aimed to review the evidence on the accuracy of imaging tests for differentiating malignant from benign adrenal masses.DesignA systematic review and meta-analysis was conducted.MethodsWe searched MEDLINE, EMBASE, Cochrane CENTRAL Register of Controlled Trials, Science Citation Index, Conference Proceedings Citation Index, and ZETOC (January 1990 to August 2015). We included studies evaluating the accuracy of CT, MRI, or18F-fluoro-deoxyglucose (FDG)-PET compared with an adequate histological or imaging-based follow-up reference standard.ResultsWe identified 37 studies suitable for inclusion, after screening 5469 references and 525 full-text articles. Studies evaluated the accuracy of CT (n=16), MRI (n=15), and FDG-PET (n=9) and were generally small and at high or unclear risk of bias. Only 19 studies were eligible for meta-analysis. Limited data suggest that CT density >10HU has high sensitivity for detection of adrenal malignancy in participants with no prior indication for adrenal imaging, that is, masses with ≤10HU are unlikely to be malignant. All other estimates of test performance are based on too small numbers.ConclusionsDespite their widespread use in routine assessment, there is insufficient evidence for the diagnostic value of individual imaging tests in distinguishing benign from malignant adrenal masses. Future research is urgently needed and should include prospective test validation studies for imaging and novel diagnostic approaches alongside detailed health economics analysis.