Abstract
Abstract
Background
High early recurrence (ER) of hepatocellular carcinoma (HCC) after microwave ablation (MWA) represents a sign of aggressive behavior and severely worsens prognosis. The aim of this study was to estimate the outcome of HCC following MWA and develop a response algorithmic strategy based on multiparametric MRI and clinical variables.
Methods
In this retrospective study, we reviewed the records of 339 patients (mean age, 62 ± 12 years; 106 men) treated with percutaneous MWA for HCC between January 2014 and December 2017 that were evaluated by multiparametric MRI. These patients were randomly split into a development and an internal validation group (3:1). Logistic regression analysis was used to screen imaging features. Multivariate Cox regression analysis was then performed to determine predictors of ER (within 2 years) of MWA. The response algorithmic strategy to predict ER was developed and validated using these data sets. ER rates were also evaluated by Kaplan–Meier analysis.
Results
Based on logistic regression analyses, we established an image response algorithm integrating ill-defined margins, lack of capsule enhancement, pre-ablative ADC, ΔADC, and EADC to calculate recurrence scores and define the risk of ER. In a multivariate Cox regression model, the independent risk factors of ER (p < 0.05) were minimal ablative margin (MAM) (HR 0.57; 95% CI 0.35 – 0.95; p < 0.001), the recurrence score (HR: 9.25; 95% CI 4.25 – 16.56; p = 0.021), and tumor size (HR 6.21; 95% CI 1.25 – 10.82; p = 0.014). Combining MAM and tumor size, the recurrence score calculated by the response algorithmic strategy provided predictive accuracy of 93.5%, with sensitivity of 92.3% and specificity of 83.1%. Kaplan–Meier estimates of the rates of ER in the low-risk and high-risk groups were 6.8% (95% CI 4.0 – 9.6) and 30.5% (95% CI 23.6 – 37.4), respectively.
Conclusion
A response algorithmic strategy based on multiparametric MRI and clinical variables was useful for predicting the ER of HCC after MWA.
Funder
the National Scientific Foundation Committee of Beijing
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,Oncology,General Medicine,Radiological and Ultrasound Technology
Cited by
1 articles.
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