Zhang Yubo, Ma Hongyan, Lei Peng, Li Zhiyuan, Yan Zhao, Wang Xinqing
Department of Hepatobiliary Surgery, General Hospital of Ningxia Medical University, Yinchuan, China.
School of Clinical Medicine, General Hospital of Ningxia Medical University, Yinchuan, China.
Front Oncol. 2025 Jan 3;14:1522501. doi: 10.3389/fonc.2024.1522501. eCollection 2024.
To develop a habitat imaging method for preoperative prediction of early postoperative recurrence of hepatocellular carcinoma.
A retrospective cohort study was conducted to collect data on 344 patients who underwent liver resection for HCC. The internal subregion of the tumor was objectively delineated and the clinical features were also analyzed to construct clinical models. Radiomics feature extraction was performed on tumor subregions of arterial and portal venous phase images. Machine learning classification models were constructed as a fusion model combining the three different models, and the models were assessed.
A comprehensive retrospective analysis was conducted on a cohort of 344 patients who underwent hepatic cancer resection at one of the two centers. it was found that the combined SVM model yielded superior results after comparing various metrics, such as the AUC, accuracy, sensitivity, specificity, and DCA.
Habitat analysis of sequential CT images can delineate distinct subregions within a tumor, offering valuable insights for early prediction of postoperative HCC recurrence.
开发一种用于术前预测肝细胞癌术后早期复发的瘤灶成像方法。
进行一项回顾性队列研究，收集344例行肝癌肝切除术患者的数据。客观划定肿瘤的内部亚区域，并分析临床特征以构建临床模型。对动脉期和门静脉期图像的肿瘤亚区域进行影像组学特征提取。构建机器学习分类模型作为三种不同模型的融合模型，并对模型进行评估。
对在两个中心之一接受肝癌切除术的344例患者队列进行了全面的回顾性分析。发现比较各种指标（如AUC、准确性、敏感性、特异性和DCA）后，组合支持向量机模型产生了更好的结果。
对连续CT图像进行瘤灶分析可划定肿瘤内不同的亚区域，为肝癌术后复发的早期预测提供有价值的见解。
