Computed Tomographic Radiomics in Differentiating Histologic Subtypes of Epithelial Ovarian Carcinoma

Wang, Mandi1,2,3; Perucho, Jose A. U.4; Hu, Yangling5; Choi, Moon Hyung6; Han, Lujun7; Wong, Esther M. F.8; Ho, Grace9; Zhang, Xiaoling5; Ip, Philip10; Lee, Elaine Y. P.3

2022-12-21

10.1001/jamanetworkopen.2022.45141

JAMA Network Open   Impact Factor & Quartile

2574-3805

["IMPORTANCE Epithelial ovarian carcinoma is heterogeneous and classified according to the World Health Organization Tumour Classification, which is based on histologic features and molecular alterations. Preoperative prediction of the histologic subtypes could aid in clinical management and disease prognostication.","OBJECTIVE To assess the value of radiomics based on contrast-enhanced computed tomography (CT) in differentiating histologic subtypes of epithelial ovarian carcinoma in multicenter data sets.","DESIGN, SETTING, AND PARTICIPANTS In this diagnostic study, 665 patients with histologically confirmed epithelial ovarian carcinoma were retrospectively recruited from 4 centers (Hong Kong, Guangdong Province of China, and Seoul, South Korea) between January 1, 2012, and February 28, 2022. The patients were randomly divided into a training cohort (n = 532) and a testing cohort (n = 133) with a ratio of 8:2. This process was repeated 100 times. Tumor segmentation was manually delineated on each section of contrast-enhanced CT images to encompass the entire tumor. The Mann-Whitney U test and voted least absolute shrinkage and selection operator were performed for feature reduction and selection. Selected features were used to build the logistic regression model for differentiating high-grade serous carcinoma and non-high-grade serous carcinoma.","EXPOSURES Contrast-enhanced CT-based radiomics.","MAIN OUTCOMES AND MEASURES Intraobserver and interobserver reproducibility of tumor segmentation were measured by Dice similarity coefficients. The diagnostic efficiency of the model was assessed by receiver operating characteristic curve and area under the curve.","RESULTS In this study, 665 female patients (mean [SD] age, 53.6 [10.9] years) with epithelial ovarian carcinoma were enrolled and analyzed. The Dice similarity coefficients of intraobserver and interobserver were all greater than 0.80. Twenty radiomic features were selected for modeling. The areas under the curve of the logistic regression model in differentiating high-grade serous carcinoma and non-high-grade serous carcinoma were 0.837 (95% CI, 0.835-0.838) for the training cohort and 0.836 (95% CI, 0.833-0.840) for the testing cohort.","CONCLUSIONS AND RELEVANCE In this diagnostic study, radiomic features extracted from contrast-enhanced CT were useful in the classification of histologic subtypes in epithelial ovarian carcinoma. Intraobserver and interobserver reproducibility of tumor segmentation was excellent. The proposed logistic regression model offered excellent discriminative ability among histologic subtypes."]

SCI

English

Others

General & Internal Medicine

Medicine, General & Internal

WOS:000937072600012

AMER MEDICAL ASSOC

Web of Science

1.Jinan Univ, Shenzhen Peoples Hosp, Clin Med Coll 2, Dept Radiol, Shenzhen, Guangdong, Peoples R China
2.Southern Univ Sci & Technol, Affiliated Hosp 1, Shenzhen, Guangdong, Peoples R China
3.Univ Hong Kong, Sch Clin Med, Dept Diagnost Radiol, Hong Kong, Peoples R China
4.Univ Alabama Birmingham, Heersink Sch Med, Dept Radiol, Birmingham, W Midlands, England
5.Sun Yat Sen Univ, Affiliated Hosp 1, Dept Radiol, Guangzhou, Peoples R China
6.Catholic Univ Korea, Eunpyeong St Marys Hosp, Coll Med, Dept Radiol, Seoul, South Korea
7.Sun Yat Sen Univ Canc Ctr, Dept Radiol, Guangzhou, Peoples R China
8.Pamela Youde Nethersole Eastern Hosp, Dept Radiol, Hong Kong, Peoples R China
9.Queen Mary Hosp, Dept Radiol, Hong Kong, Peoples R China
10.Univ Hong Kong, Queen Mary Hosp, Sch Clin Med, Dept Pathol, Hong Kong, Peoples R China

Wang, Mandi,Perucho, Jose A. U.,Hu, Yangling,et al. Computed Tomographic Radiomics in Differentiating Histologic Subtypes of Epithelial Ovarian Carcinoma[J]. JAMA Network Open,2022,5(12).

Wang, Mandi.,Perucho, Jose A. U..,Hu, Yangling.,Choi, Moon Hyung.,Han, Lujun.,...&Lee, Elaine Y. P..(2022).Computed Tomographic Radiomics in Differentiating Histologic Subtypes of Epithelial Ovarian Carcinoma.JAMA Network Open,5(12).

Wang, Mandi,et al."Computed Tomographic Radiomics in Differentiating Histologic Subtypes of Epithelial Ovarian Carcinoma".JAMA Network Open 5.12(2022).