肝细胞癌
超声科
对比度(视觉)
医学
放射科
内科学
计算机科学
人工智能
作者
Shibo Qiu,Jianmin Ding,Yandong Wang,Hongyu Zhou,Lin Zhao,Lei Zhao,Yan Zhou,Yaling Fu,Xiang Jing
标识
DOI:10.1016/j.ultrasmedbio.2024.03.016
摘要
Objective We aimed to investigate the value of quantitative parameters derived from dynamic contrast-enhanced ultrasonography (DCE-US) and a combination of these quantitative parameters with the LR-M classification criteria in distinguishing hepatocellular carcinoma (HCC) nodules and non-HCC malignancies. Methods HCC and non-HCC malignant nodules were grouped using pathologic results, and each nodule was classified using CEUS LI-RADS 2017. Quantitative CEUS analysis of each nodule was performed using VueBox, and quantitative parameters were compared between the HCC and non-HCC groups. The diagnostic efficacy of the LR-5 category for HCC was analyzed using the LR-M classification criteria along with time-related quantitative parameters. Results Of the 190 malignant liver nodules, 137 and 53 were HCCs and non-HCC malignancies, respectively. The median values of quantitative parameters RT (rise time), TTP (time to peak), mTTl (mean transit time local), and FT (fall time) in the non-HCC malignant group were lower than those in the HCC group, with p < 0.05. There was a statistically significant difference in WiAUC (wash-in area under the curve), WoAUC (wash-out area under the curve), WiWoAUC (wash-in and wash-out area under the curve), and WoR (wash-out rate) values between HCC and non-HCC malignant groups, with p < 0.05. Using LR-M washout time <60 s and FT ≤21.2 s as the new diagnostic standard, the LR-5 category showed a sensitivity of 83.9%, specificity of 96.2%, and positive predictive value of 98.3% for HCC diagnosis. Conclusion DCE-US can facilitate the distinction of HCCs and non-HCC malignancies. Non-HCC malignancies present with earlier peak enhancement and more rapid and marked washout than HCC nodules. The combination of the LR-M classification criteria and FT ≤21.2 s can significantly improve the diagnostic sensitivity of the LR-5 category for HCC.
科研通智能强力驱动
Strongly Powered by AbleSci AI