Differentiating hepatic hemangiomas from hepatocellular carcinomas using Sonazoid-enhanced ultrasonography: a
Taewon Han1, Jeong Ah Hwang1, Woo Kyoung Jeong1
1Department of Radiology and Center for Imaging Sciences, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
Purpose:
This study aimed to develop a diagnostic algorithm for differentiating hepatic hemangiomas from hepatocellular carcinoma (HCC) using Sonazoid-enhanced ultrasonography (SEUS).
Methods:
A retrospective analysis was conducted of SEUS examinations from 159 patients with 110 hemangiomas and 49 HCCs between January 2011 and December 2022. The evaluated imaging features included lesion hyperechogenicity, typical grayscale features of hemangioma, defined as a hyperechoic lesion or echogenic border without a hypoechoic rim or nodule-in-nodule appearance, and typical globular enhancement of hemangioma. In the Kupffer phase (KP), the lesion-to-liver ratio (KP ratio) was calculated, and receiver operating characteristic analysis was performed to determine the optimal KP ratio cutoff for predicting hemangioma. A two-step diagnostic algorithm was developed and compared with typical globular enhancement of hemangioma using the McNemar test.
Results:
The optimal KP ratio cutoff for predicting hemangioma was 0.85. The two-step algorithm first identified hemangiomas based on typical globular enhancement and then applied typical grayscale features and a KP ratio ≥0.85 to lesions without typical globular enhancement. The algorithm showed higher sensitivity than typical globular enhancement alone (90.0% vs. 81.8%, P=0.008) while maintaining 100% specificity. In hyperechoic lesions, the algorithm also showed higher sensitivity than typical globular enhancement alone (91.9% vs. 77.4%, P=0.008).
Conclusion:
The proposed two-step algorithm may improve sensitivity while maintaining specificity in clinical settings that require differentiation between hemangiomas and HCC.
