Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, No. 218 Jixi Road, Hefei, 230022, Anhui, China.
Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Jiefang Avenue No. 1095, Wuhan, 430030, Hubei, China.
Abdom Radiol (NY). 2024 May;49(5):1419-1431. doi: 10.1007/s00261-024-04191-1. Epub 2024 Mar 10.
To develop a contrast-enhanced ultrasound (CEUS) clinic-radiomics nomogram for individualized assessment of Ki-67 expression in hepatocellular carcinoma (HCC).
A retrospective cohort comprising 310 HCC individuals who underwent preoperative CEUS (using SonoVue) at three different centers was partitioned into a training set, a validation set, and an external test set. Radiomics signatures indicating the phenotypes of the Ki-67 were extracted from multiphase CEUS images. The radiomics score (Rad-score) was calculated accordingly after feature selection and the radiomics model was constructed. A clinic-radiomics nomogram was established utilizing multiphase CEUS Rad-score and clinical risk factors. A clinical model only incorporated clinical factors was also developed for comparison. Regarding clinical utility, calibration, and discrimination, the predictive efficiency of the clinic-radiomics nomogram was evaluated.
Seven radiomics signatures from multiphase CEUS images were selected to calculate the Rad-score. The clinic-radiomics nomogram, comprising the Rad-score and clinical risk factors, indicated a good calibration and demonstrated a better discriminatory capacity compared to the clinical model (AUCs: 0.870 vs 0.797, 0.872 vs 0.755, 0.856 vs 0.749 in the training, validation, and external test set, respectively) and the radiomics model (AUCs: 0.870 vs 0.752, 0.872 vs 0.733, 0.856 vs 0.729 in the training, validation, and external test set, respectively). Furthermore, both the clinical impact curve and the decision curve analysis displayed good clinical application of the nomogram.
The clinic-radiomics nomogram constructed from multiphase CEUS images and clinical risk parameters can distinguish Ki-67 expression in HCC patients and offer useful insights to guide subsequent personalized treatment.
开发一种基于对比增强超声(CEUS)的临床放射组学列线图,用于个体化评估肝细胞癌(HCC)中 Ki-67 的表达。
回顾性纳入了在三个不同中心接受术前 CEUS(使用 SonoVue)检查的 310 例 HCC 患者,将其分为训练集、验证集和外部测试集。从多期 CEUS 图像中提取提示 Ki-67 表型的放射组学特征。通过特征选择计算放射组学评分(Rad-score),并构建放射组学模型。利用多期 CEUS Rad-score 和临床危险因素构建临床放射组学列线图。同时建立仅纳入临床因素的临床模型进行比较。评估临床放射组学列线图的预测效能,包括校准度、区分度。
从多期 CEUS 图像中提取了 7 个放射组学特征,用于计算 Rad-score。临床放射组学列线图包括 Rad-score 和临床危险因素,与临床模型相比,具有更好的校准度和区分度(训练集、验证集和外部测试集的 AUC 分别为 0.870 比 0.797、0.872 比 0.755、0.856 比 0.749),也优于放射组学模型(训练集、验证集和外部测试集的 AUC 分别为 0.870 比 0.752、0.872 比 0.733、0.856 比 0.729)。此外,临床影响曲线和决策曲线分析均显示该列线图具有良好的临床应用价值。
基于多期 CEUS 图像和临床风险参数构建的临床放射组学列线图,可区分 HCC 患者的 Ki-67 表达水平,为指导后续个体化治疗提供有价值的信息。