Prediction of peritoneal free cancer cells in gastric cancer patients by golden-angle radial sampling dynamic contrast-enhanced magnetic resonance imaging
- Author:
YIN XUEQING
1
;
RUAN XINZHONG
;
ZHU YONGMENG
;
YIN YONGFANG
;
HUANG RUI
;
LIANG CHAO
Author Information
- Keywords: Gastric cancer; Magnetic resonance; Golden-angle radial sampling; Nomogram model; Peritoneal free cancer cells
- From: Journal of Zhejiang University. Science. B 2024;25(7):617-627
- CountryChina
- Language:Chinese
- Abstract: Objective:Peritoneal free cancer cells can negatively impact disease progression and patient outcomes in gastric cancer.This study aimed to investigate the feasibility of using golden-angle radial sampling dynamic contrast-enhanced magnetic resonance imaging(GRASP DCE-MRI)to predict the presence of peritoneal free cancer cells in gastric cancer patients.Methods:All enrolled patients were consecutively divided into analysis and validation groups.Preoperative magnetic resonance imaging(MRI)scans and perfusion were performed in patients with gastric cancer undergoing surgery,and peritoneal lavage specimens were collected for examination.Based on the peritoneal lavage cytology(PLC)results,patients were divided into negative and positive lavage fluid groups.The data collected included clinical and MR information.A nomogram prediction model was constructed to predict the positive rate of peritoneal lavage fluid,and the validity of the model was verified based on data from the verification group.Results:There was no statistical difference between the proportion of PLC-positive cases predicted by GRASP DCE-MR and the actual PLC test.MR tumor stage,tumor thickness,and perfusion parameter Tofts-Ketty model volume transfer constant(Ktrans)were independent predictors of positive peritoneal lavage fluid.The nomogram model featured a concordance index(C-index)of 0.785 and 0.742 for the modeling and validation groups,respectively.Conclusions:GRASP DCE-MR could effectively predict peritoneal free cancer cells in gastric cancer patients.The nomogram model constructed using these predictors may help clinicians to better predict the risk of peritoneal free cancer cells being present in gastric cancer patients.
