Preoperative Prediction Power of Imaging Methods for Microvascular Invasion in Hepatocellular Carcinoma: A Systemic Review and Meta-Analysis - Huang, Jiacheng; Tian, Wuwei; Zhang, Lele; Huang, Qiang; Lin, Shengzhang; Ding, Yong; Liang, Wenjie; Zheng, Shusen (Frontiers in Oncology, 2020)
Background: To compare the predictive power between radiomics and non-radiomics (conventional imaging and functional imaging methods) for preoperative evaluation of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: Comprehensive publications were screened in PubMed, Embase and Cochrane Library. Studies focusing on the discrimination values of imaging methods, including radiomics and non-radiomics methods, for MVI evaluation were included in our meta-analysis. Results: Thirty-three imaging studies with 5462 cases, focusing on preoperative evaluation of MVI status in HCC, were included. The sensitivity and specificity of MVI prediction in HCC were 0.78 (95% confidence interval (CI): 0.75-0.80; I2=70.7%) and 0.78 (95%CI: 0.76-0.81; I2=0.0%) for radiomics, respectively, and were 0.73 (95%CI: 0.71-0.75; I2=83.7%) and 0.82 (95%CI: 0.80-0.83; I2=86.5%) for non-radiomics, respectively. The areas under the receiver operation curves for radiomics and non-radiomics to predict MVI status in HCC were 0.8550 and 0.8601, respectively, showing no significant difference. Conclusion: The imaging method is feasible to predict the MVI state of HCC. Radiomics method based on medical image data is promising applications in clinical practice and can provide quantifiable image features. With the help of these features, highly-consistent prediction performance will be achieved in anticipation.