Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Department of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China; Department of Ultrasound, Nanjing Drum Tower Hospital, Nanjing, China.
Ultrasound Med Biol. 2024 Dec;50(12):1964-1972. doi: 10.1016/j.ultrasmedbio.2024.09.002. Epub 2024 Sep 26.
The aim of this study was to explore the value of ultrasound-based radiomics analysis for early recurrence after surgical resection of hepatocellular carcinoma (HCC).
This retrospective study included 127 patients who underwent primary surgical resection for HCC between October 2019 and November 2021. The patients were subsequently divided into training and validation sets (7:3 ratio). All patients received preoperative routine ultrasound and contrast-enhanced ultrasound examination, with postoperative pathological confirmation of HCC. Radiomics features were extracted from maximum section of a two-dimensional ultrasound image. The least absolute shrinkage and selection operation logistic regression algorithm with 10-fold cross-validation was used to establish ultrasonic radiomics features. Logistic regression modelling was used to build models based on clinical and ultrasonic features (model 1, clinical-ultrasonic model), radiomics signature (model 2, ultrasonic radiomics model), and the combination (model 3, clinical-ultrasonic-radiomics model). Then, a nomogram model was established to predict the risk of early recurrence, and the application value of nomogram through internal verification was evaluated.
Model 3 showed optimal diagnostic performance in both training set (area under the curve [AUC], 0.907) and validation set (AUC, 0.925), followed by the model 1 in training set (AUC, 0.846) and validation set (AUC, 0.855), both above two models performed better than model 2 in training set (AUC, 0.751) and validation set (AUC, 0.702) (p < 0.05). In the training set and validation set of model 3, the sensitivity were 83.3%, 77.8%, the specificity ware 95.8%, 100.0% and the C-index were 0.791, 0.778.
The preoperative clinical-ultrasonic-radiomics model is anticipated to be a reliable tool for predicting the early recurrence of surgical resection of HCC.
本研究旨在探讨基于超声的放射组学分析在肝癌（HCC）手术后早期复发中的价值。
本回顾性研究纳入了 2019 年 10 月至 2021 年 11 月期间接受原发性 HCC 手术切除的 127 例患者。随后将患者分为训练集和验证集（比例为 7:3）。所有患者均接受术前常规超声和对比增强超声检查，并经术后 HCC 病理证实。从二维超声图像的最大截面提取放射组学特征。采用 10 折交叉验证的最小绝对收缩和选择操作逻辑回归算法建立超声放射组学特征。基于临床和超声特征（模型 1，临床-超声模型）、放射组学特征（模型 2，超声放射组学模型）和组合（模型 3，临床-超声-放射组学模型）建立模型。然后建立列线图模型预测早期复发风险，并通过内部验证评估列线图的应用价值。
模型 3 在训练集（曲线下面积 [AUC]，0.907）和验证集（AUC，0.925）中表现出最佳的诊断性能，其次是模型 1 在训练集（AUC，0.846）和验证集（AUC，0.855），均优于训练集（AUC，0.751）和验证集（AUC，0.702）中的模型 2（p<0.05）。在模型 3 的训练集和验证集中，敏感性分别为 83.3%、77.8%，特异性分别为 95.8%、100.0%，C 指数分别为 0.791、0.778。
术前临床-超声-放射组学模型有望成为预测 HCC 手术切除后早期复发的可靠工具。
