Models based on contrast enhanced CT radiomics and imaging genomics for predicting prognosis of ovarian serous cystadenocarcinoma
10.13929/j.issn.1003-3289.2024.05.024
- VernacularTitle:基于增强CT影像组学及基因组学模型预测卵巢浆液性囊腺癌预后
- Author:
Diliang HE
1
;
Jianxin ZHAO
;
Nini PAN
;
Liuyan SHI
;
Lianqiu XIONG
;
Lili MA
;
Zhiping ZHAO
;
Lianping ZHAO
;
Gang HUANG
Author Information
1. 甘肃中医药大学第一临床医学院,甘肃兰州 730000
- Keywords:
ovary;
cystadenocarcinoma,serous;
prognosis;
imaging genomics;
tomography,X-ray computed
- From:
Chinese Journal of Medical Imaging Technology
2024;40(5):745-751
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the value of model established with radiomics features based on contrast enhanced arterial phase CT and model with radiogenomics for predicting prognosis of ovarian serous cystadenocarcinoma(OSC).Methods Enhanced arterial phase CT images of 110 OSC patients were retrospectively collected from 2 centers and The Cancer Imaging Archive(TCIA)database.The radiomics features were extracted,among those related to prognosis were selected to establish a radiomics Cox regression model.Genes data of 399 OSC patients were obtained from The Cancer Genome Atlas(TCGA)database,and genes related to the radiomics features included in the above radiomics model were identified with high Pearson correlation coefficient,and then enrichment gene analyses were performed.For 57 OSC cases with complete enhanced CT and gene data,the hub genes which had the highest connectivity with radiomics prognosis predicting model were detected using Cox regression and protein-protein interaction(PPI).Furthermore,a radiogenomics prognosis predicting model was established with the hub genes.The efficiencies of these 2 models for predicting prognosis of OSC patients were analyzed.Results Finally,the radiomics model included 5 OSC prognosis-related radiomics features,with C-index of 0.782 and 0.735 in corresponding training and test set,respectively.Meanwhile,the radiogenomics model included 30 prognostic hub genes,with C-index of 0.673 and 0.659 in corresponding training and test set,respectively.The survival rates of patients with better predicted prognosis according to radiomics model and radiogenomics model were both higher compared with the others(both P＜0.05).Totally 1 135 mRNA genes were found being associated with radiomics model,including biological behaviors such as cell adhesion,and signaling pathways such as PI3K-Akt,extracellular matrix receptor interaction pathway and type 1 diabetes pathway.Conclusion The radiomics model was effective for predicting prognosis of OSC patients.Analysis of mRNA bioinformatics in OSC patients might provide biological interpretations for the radiomics model.
