Our meta-analysis aimed to evaluate the diagnostic performance of surveillance magnetic resonance imaging (sMRI) for detecting hepatocellular carcinoma (HCC), and to compare the diagnostic performance of sMRI between different protocols. Original articles about the diagnostic accuracy of sMRI for detecting HCC were found in major databases. The meta-analytic pooled sensitivity and specificity of sMRI for detecting HCC were determined using a bivariate random effects model. The pooled sensitivity and specificity of full MRI and abbreviated MRI protocols were compared using bivariate meta-regression. In the total seven included studies (1830 patients), the pooled sensitivity of sMRI for any-stage HCC and very early-stage HCC were 85% (95% confidence interval, 79–90%; I2 = 0%) and 77% (66–85%; I2 = 32%), respectively. The pooled specificity for any-stage HCC and very early-stage HCC were 94% (90–97%; I2 = 94%) and 94% (88–97%; I2 = 96%), respectively. The pooled sensitivity and specificity of abbreviated MRI protocols were 87% (80–94%) and 94% (90–98%), values that were comparable with those of full MRI protocols (84% [76–91%] and 94% [89–99%]; p = 0.83). In conclusion, sMRI had good sensitivity for detecting HCC, particularly very early-stage HCC. Abbreviated MRI protocols for HCC surveillance had comparable diagnostic performance to full MRI protocols.
Proof-of-concept use of machine learning to predict tumor recurrence of early-stage hepatocellular carcinoma before therapy using baseline magnetic resonance imaging
