| 摘要: |
| 目的 基于sonazoid超声造影（CEUS）枯否期图像构建预测肝细胞肝癌（HCC）微血管侵犯（MVI）的影像组学术前预测模型，并探讨其应用价值。方法 前瞻性纳入于我院拟诊为肝恶性肿瘤并行术前sonazoid CEUS检查的患者，分别提取基于灰阶超声图像和CEUS枯否期静态图像的肿瘤区域（TR）、瘤周5 mm区域（PR）及肿瘤+瘤周5 mm区域（ER）的特征。应用支持向量机法构建影像组学预测模型并评估其对MVI的预测效能。结果 最终纳入50例经手术及病理证实的HCC患者（MVI阳性31例，MVI阴性19例），分别从灰阶图像和枯否期图像的TR、PR及ER提取并筛选出5个最具预测效力的影像组学特征构建预测模型，其中枯否期PR影像组学模型对MVI的独立预测效能最佳，其准确率为84%，敏感性为90.3%，特异性为73.7%。决策收益曲线分析显示当该模型预测MVI的概率阈值为0.05~0.85时，枯否期PR影像组学评分能提供更高的临床收益。结论 基于sonazoid CEUS枯否期图像构建的影像组学模型是术前无创预测HCC病灶MVI的潜在方法。 |
| 关键词: 超声造影 肝细胞肝癌 微血管侵犯 术前预测 枯否期 |
| DOI： |
| 投稿时间：2022-03-28修订日期：2022-06-10 |
| 基金项目:国家自然科学基金（82071942）；上海市浦江人才计划（D类）（2020PJD008）；促进市级医院临床技能与临床创新能力三年行动计划（SHDC2020CR4060，SHDC2020CR1031B） |
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| Predictive Model of Microvascular Invasion (MVI) in Hepatocellular Carcinoma (HCC) Based on Radiomics Signatures during Kupffer Phase of Sonazoid Contrast Enhanced Ultrasound (CEUS) |
| Dan Zuo,Jia-Ying Cao,Yi-Jie Qiu,Yi Dong,Han-Zhang Wang,Xiao-Fan Tian,Wen-Ping Wang |
| (Department of Ultrasound,Zhongshan Hospital,Fudan University) |
| Abstract: |
| Objective To establish radiomics models of preoperative prediction of microvascular invasion （MVI） in hepatocellular carcinoma （HCC） lesions based on Kupffer phase features of sonazoid contrast enhanced ultrasound （CEUS）and evaluate its clinical value. Methods Patients who were diagnosed with hepatic malignant tumors and who underwent sonazoid CEUS examinations were prospectively enrolled. Radiomics signatures were extracted from 6 regions of interest （ROIs） respectively，including tumor region（TR），peritumoral 5mm region （PR） and entire region （ER，TR+PR） on gray scale images and Kupffer phase images of sonazoid CEUS. Support vector machine method was used to establish predictive radiomics models and the predictive efficiency of 6 radiomics models were compared. Results A total of 50 patients with histologically confirmed single HCC lesion were prospectively enrolled （MVI-positive：31，MVI-negative：19）.Five radiomics features were extracted and screened from TR，PR and ER of gray scale images and Kupffer phase images, respectively. Among the 6 radiomics models，the performance of PR of Kupffer phase images performed the best （Accuracy 84%，Sensitivity 90.3% and Specificity 73.7%）.The decision curve analysis showed that PR of Kupffer phase provided a significantly higher clinical benefit than other models，when probability threshold value was set between 0.05 and 0.85. Conclusion The radiomics model based on Kupffer phase image of sonazoid CEUS is a potential method for preoperative prediction of MVI in HCC lesions. |
| Key words: Contrast enhanced ultrasound (CEUS) hepatocellular carcinoma (HCC) microvascular invasion (MVI) preoperative prediction Kupffer phase |
