Computer-aided diagnosis for estimating the malignancy grade of hepatocellular carcinoma using contrast-enhanced ultrasound: an ROC observer study.

Abstract

We are developing a computer-aided diagnosis (CAD) system for estimating the malignancy grade of hepatocellular carcinoma (HCC) using contrast-enhanced ultrasound (CEUS). In this study, observers estimated the malignancy grade of HCC with and without the cues provided by CAD. Institutional review board approval was obtained and informed consent was waived. A total of 232 histologically confirmed HCCs were studied: 76 well-differentiated HCC (w-HCC), 133 moderately differentiated HCC (m-HCC), and 23 poorly differentiated HCC (p-HCC). In this observer study, CEUS vascular images acquired using the maximum intensity projection technique were displayed together with static B-mode and Kupffer-phase (defined as 10min after injection) images. Five hepatologists independently assigned confidence ratings for the malignancy grade of each HCC. Each hepatologist first read each case without CAD and then immediately afterwards with CAD. The observers' rating data were evaluated by multireader multicase receiver operating characteristic (ROC) analysis. The overall sensitivity of our CAD system for discrimination between three histological differentiation grades of HCC was 87.5% (203/232). For discrimination between w-HCC and m/p-HCC, the mean area under the ROC curve (AUC) for the five observers was significantly improved from 0.779±0.074 to 0.872±0.090 with CAD (P=0.0069). For discrimination between m-HCC and p-HCC, the mean AUC was also significantly improved from 0.713±0.107 to 0.863±0.101 with CAD (P=0.0321). The use of our CAD system can significantly improve the diagnostic performance of hepatologists in discriminating between three histological differentiation grades of HCC using CEUS.