Preoperative Prediction of Microvascular Invasion of Hepatocellular Carcinoma: Radiomics Algorithm Based on Ultrasound Original Radio Frequency Signals

Yi Dong; Qing-Min Wang; Qian Li; Le-Yin Li; Qi Zhang; Zhao Yao; Meng Dai; Jinhua Yu; Wen-Ping Wang

doi:10.3389/fonc.2019.01203

Preoperative Prediction of Microvascular Invasion of Hepatocellular Carcinoma: Radiomics Algorithm Based on Ultrasound Original Radio Frequency Signals

Front Oncol. 2019 Nov 14:9:1203. doi: 10.3389/fonc.2019.01203. eCollection 2019.

Authors

Yi Dong¹, Qing-Min Wang², Qian Li³, Le-Yin Li², Qi Zhang¹, Zhao Yao², Meng Dai², Jinhua Yu², Wen-Ping Wang¹

Affiliations

¹ Zhongshan Hospital, Fudan University, Shanghai, China.
² Department of Electronic Engineering, Fudan University, Shanghai, China.
³ Harvard Medical School, Massachusetts General Hospital, Boston, MA, United States.

Abstract

Background: To evaluate the accuracy of radiomics algorithm based on original radio frequency (ORF) signals for prospective prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) lesions. Methods: In this prospective study, we enrolled 42 inpatients diagnosed with HCC from January 2018 to December 2018. All HCC lesions were proved by surgical resection and histopathology results, including 21 lesions with MVI. Ultrasound ORF data and grayscale ultrasound images of HCC lesions were collected before operation for further radiomics analysis. Three ultrasound feature maps were calculated using signal analysis and processing (SAP) technology in first feature extraction. The diagnostic accuracy of model based on ORF signals was compared with the model based on grayscale ultrasound images. Results: A total of 1,050 radiomics features were extracted from ORF signals of each HCC lesion. The performance of MVI prediction model based on ORF was better than those based on grayscale ultrasound images. The best area under curve, accuracy, sensitivity, and specificity of ultrasound radiomics in prediction of MVI were 95.01, 92.86, 85.71, and 100%, respectively. Conclusions: Radiomics algorithm based on ultrasound ORF data combined with SAP technology can effectively predict MVI, which has potential clinical application value for non-invasively preoperative prediction of MVI in HCC patients.

Keywords: hepatocellular carcinoma; microvascular invasion; original radio frequency signals; prediction; radiomics analysis.