机构：[1]Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, People's Republic of China.[2]Jinan University, Guangzhou 510632, Guangdong, People's Republic of China.[3]Department of Radiology, Foshan Hospital of Traditional Chinese Medicine, Foshan 528000, Guangdong, People's Republic of China.
The noninvasive detection of tumor proliferation is of great value and the Ki-67 is a biomarker of tumor proliferation. We hypothesized that radiomics characteristics may be related to tumor proliferation. To evaluate whether computed tomography (CT) radiomics feature analyses could aid in assessing the Ki-67 marker index in hepatocellular carcinoma (HCC), we retrospectively analyzed preoperative CT findings of 74 patients with HCC. The texture feature calculations were computed from MaZda 4.6 software, and the sequential forward selection algorithm was used as the selection method. The correlation between radiomics features and the Ki-67 marker index, as well as the difference between low Ki-67 (<10%) and high Ki-67 (≥10%) groups were evaluated. A simple logistic regression model was used to evaluate the associations between texture features and high Ki-67, and receiver operating characteristic analysis was performed on important parameters to assess the ability of radiomics characteristics to distinguish the high Ki-67 group from the low Ki-67 group. Contrast, correlation, and inverse difference moment (IDM) were significantly different (P < 0.001) between the low and high Ki-67 groups. Contrast (odds ratio [OR] = 0.957; 95% confidence interval [CI]: 0.926-0.990, P = 0.01) and correlation (OR = 2.5☆105; 95% CI: 7.560-8.9☆109; P = 0.019) were considered independent risk factors for combined model building with logistic regression. Angular second moment (r = -0.285, P = 0.014), contrast (r = -0.449, P < 0.001), correlation (r = 0.552, P < 0.001), IDM (r = 0.458, P < 0.001), and entropy (r = 0.285, P = 0.014) strongly correlated with the Ki-67 scores. Contrast, correlation, and the combined predictor were predictive of Ki-67 status (P < 0.001), with areas under the curve ranging from 0.777 to 0.836. The radiomics characteristics of CT have potential as biomarkers for predicting Ki-67 status in patients with HCC. These findings suggest that the radiomics features of CT might be used as a noninvasive measure of cellular proliferation in HCC.
基金：
Science Foundation of Guangzhou First People’s Hospital (M2019013),
Guangzhou Science and Technology Project of Health (20201A011013) and Guangzhou Planned Project of
Science and Technology(201904010422).
语种：
外文
PubmedID：
中科院(CAS)分区：
出版当年[2019]版：
大类|3 区医学
小类|3 区工程：生物医学3 区核医学
最新[2025]版：
大类|3 区医学
小类|3 区工程：生物医学3 区核医学
第一作者：
第一作者机构：[1]Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, People's Republic of China.[2]Jinan University, Guangzhou 510632, Guangdong, People's Republic of China.
通讯作者：
通讯机构：[1]Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, People's Republic of China.[2]Jinan University, Guangzhou 510632, Guangdong, People's Republic of China.
推荐引用方式(GB/T 7714)：
Wu Hongzhen,Han Xiaorui,Wang Zihua,et al.Prediction of the Ki-67 marker index in hepatocellular carcinoma based on CT radiomics features.[J].Physics in medicine and biology.2020,doi:10.1088/1361-6560/abac9c.
APA：
Wu Hongzhen,Han Xiaorui,Wang Zihua,Mo Lei,Liu Weifeng...&Jiang Xinqing.(2020).Prediction of the Ki-67 marker index in hepatocellular carcinoma based on CT radiomics features..Physics in medicine and biology,,
MLA：
Wu Hongzhen,et al."Prediction of the Ki-67 marker index in hepatocellular carcinoma based on CT radiomics features.".Physics in medicine and biology .(2020)
