Clinical Value of Predicting Moderate and Low Differentiation of Cervical Squamous Cell
Carcinoma Based on MRI Radiomics Characteristic
DANG Junming1,2, ZHU Chaohua2, HUANG Huixian2, LU Heming2
1. Ruikang Clinical Medical College, Guangxi University of Chinese Medicine, Nanning Guangxi 530000, China
2. Department of Radiation Oncology, People’s Hospital of Guangxi Zhuang Autonomous Region, Nanning Guangxi 530000, China
Abstract:Objective To explore the feasibility of predicting moderate and low differentiation of cervical squamous cell carcinoma
based on MRI-T2WI radiomics characteristics before treatment. Methods MRI images of 72 patients with cervical cancer before
treatment were retrospectively analyzed, including 40 cases with moderate differentiation and 32 cases with low differentiation.
IBEX toolbox was used to extract the radiomics features of the gross tumor volume of patients’ tumor. The t test was used for feature
screening, LASSO algorithm was used for feature dimension reduction, Pearson correlation was used to analyze the correlation
between radiomics features and pathological types. The receiver operating characteristic curve was drawn and the area under the
receiver operating characteristic (ROC) curve was calculated. ROC was used to analyze the maximum YOUDEN index of each
coordinate and calculate the sensitivity, specificity and optimal threshold of the omics characteristics. Results A total of the 682
radiomics features extracted, 8 features were correlated with moderate and low differentiation pathological grades of cervical
squamous cell carcinoma, with correlation coefficients greater than 0.4 and AUC values higher than 0.7. Among them the 333_4
correlation and the 2_1 correlation showed the best predictive performance in moderate differentiated and low differentiation
pathological types, with AUC values of 0.808 and 0.828, respectively. The sensitivity and specificity were 0.667, 0.663 and 0.867, 0.917,
respectively. Conclusion The radiomics features of MRI-T2WI can be used as a non-invasive and effective adjunct to the pathological
grade diagnosis of moderate and low differentiation of pretherapeutic heterogeneity of cervical squamous cell carcinoma.
党俊明1,2,朱超华2,黄慧娴2,陆合明2. 基于MRI影像组学预测宫颈鳞癌中、低分化的临床价值[J]. 中国医疗设备, 2022, 37(11): 71-75.
DANG Junming1,2, ZHU Chaohua2, HUANG Huixian2, LU Heming2. Clinical Value of Predicting Moderate and Low Differentiation of Cervical Squamous Cell
Carcinoma Based on MRI Radiomics Characteristic. China Medical Devices, 2022, 37(11): 71-75.