The diagnostic accuracy of O-(2-F-18-fluoroethyl)-L-tyrosine parameters for the differentiation of brain tumour progression from treatment-related changes

NUCLEAR MEDICINE COMMUNICATIONS(2022)

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摘要
Background F-18-fluoro-ethyl-tyrosine (F-18-FET) is recommended to distinguish brain tumours post-therapeutic true progression (including recurrent and metastatic brain tumours) and treatment-related change (TRC). However, many parameters of F-18-FET can be used for this differential diagnosis. Our purpose was to investigate the diagnostic accuracy of various F-18-FET parameters to differentiate true progression from TRC. Methods We performed a literature search using the following databases: the PubMed, Embase and Web of Science databases up to 29 November 2020. We included studies that reported the diagnostic test results of F-18-FET to distinguish true progression from TRC. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to evaluate the quality of the included studies. The diagnostic accuracy of various parameters was pooled using a random-effects model. Results We included 17 eligible studies (nine parameters). For static parameters of F-18-FET, the maximum and mean tumour-to-brain ratios (TBRmax and TBRmean) showed similar pooled sensitivities of 82% [95% confidence interval (CI), 80-85%) and 82% (95% CI, 78-85%), respectively. Among the three kinetic parameters (slope, time to peak and kinetic pattern), the kinetic pattern presented the optimal diagnostic value with a pooled sensitivity of 81% (95% CI, 75-86%). When combining the static and kinetic parameters, the diagnostic performance of F-18-FET was significantly improved, with a pooled sensitivity of 90% (95% CI, 84-94%) in the combination of TBR and kinetic patterns. Conclusions F-18-FET static parameters alone showed a comparably high sensitivity in the differentiation between brain tumour true progression and TRC. Combining static and kinetic parameters provided improved diagnostic performance.
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关键词
F-18-fluoro-ethyl-tyrosine, brain tumour, diagnostic accuracy, meta-analysis, PET, pseudoprogression
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