AUTHOR=Chen Shuxiang , Zhang Huijuan , Wei Hong , Tong Yongxiu , Chen Xiaofang 

TITLE=Practical nomogram based on comprehensive CT texture analysis to preoperatively predict peritoneal occult metastasis of gastric cancer patients

JOURNAL=Frontiers in Oncology

VOLUME=Volume 12 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2022.882584

DOI=10.3389/fonc.2022.882584

ISSN=2234-943X

ABSTRACT=Objectives: To evaluate whether nomogram based on comprehensive CT texture analysis of primary tumor and peritoneotome combind with conventional CT signs can preoperatively predicting occult peritoneal metastasis in gastric cancer patients.
Methods: A Total of 1251 patients with gastric cancer were retrospectively analyzed in Fujian Province Hospital between 2008 and 2020. Occult peritoneal metastasis group patients were initially diagnosed as PM negative by CT and later confirmed as positive of PM through surgery or laparoscopy. Preoperative clinical factors, CT signs and texture features of each patient were analyzed. Risk factors for occult PM were identified by univariate analysis and multivariate logistic regression analysis, then used to create prediction models. A nomogram was developed based on the model with the best predictive efficiency and clinical utility. The performance of the nomogram was evaluated by using a bootstrapped-concordance index and calibration plots.
Results: Totally 31 patients with occult PM and 165 patients without PM were enrolled in this study. We separately constructed 5 prediction models using CT signs, primary tumor texture, peritoneum texture, primary tumor texture + peritoneum texture and their combination for predicting occult PM. These 5 prediction models achieved AUC of 0.832, 0.70, 0.784, 0.838, 0.941 respectively. The DeLong test and DCA showed that the combined model, consisting of 3 meaningful CT signs(max size, thickness and ascites) and 2 meaningful texture parameters(Inhomogenity of primary tumor, Inhomogenity of peritoneum), held the highest predictive efficiency and clinical utility (p < 0.05). A prediction nomogram was subsequently developed from the model above mentioned. The calibration curves of the nomogram indicated a good consistency (concordance index of 0.807) between the actual observations and predictions for occult PM.
Conclusions: A practical prediction nomogram based on the texture analysis of whole peritoneal, the entire tumor and conventional CT signs was constructed in our study, which can be conveniently used for the preoperative personalized prediction of occult PM for GC patients, and serve as a reference for optimizing clinical management.