Preoperative assessment and prognostic prediction of gastric cancer patients with peritoneal metastasis using 18F-FDG PET/CT before conversion surgery
Year: 2025
Type: article
Study design: Observational Study
Abstract: Conversion therapy followed by conversion surgery (CS) can improve the prognosis of gastric cancer (GC) patients with peritoneal metastasis (PM). However, patients benefit differently. There is no way to confirm the prognostic benefit non-invasively and early. This retrospective study assessed the value of 18 F-FDG PET/CT after conversion therapy in preoperative assessment and prognostic prediction of GC patients with PM. Fifty-one GC patients with PM were enrolled. 18 F-FDG PET/CT after conversion therapy helped in preoperative assessment. Its diagnostic accuracy for residual peritoneal lesions was slightly better than contrast-enhanced CT (72.5% vs. 61.2%, P = 0.229), although the difference was not statistically significant. TBR of peritoneal lesions could help preoperative assessment, with TBR of peritoneal lesions to the mediastinal blood pool SUVmax (TBRAmaxp) as the best predictor (cutoff = 0.705, specificity 80%, sensitivity 80%, AUC 0.825, P < 0.001). Additionally, PET/CT could predict prognosis and assess surgical benefit. SUVmax of peritoneal lesions (SUVmaxp) was the best predictor of 24 months survival (cutoff = 1.466, AUC 0.870, P = 0.002, Specificity 77.8%, Sensitivity 83.3%) and metabolic parameters of peritoneal lesions could predict OS and the prognosis of patients who underwent CS. 18 F-FDG PET/CT provides quantitative imaging indicators for preoperative evaluation and prognostic prediction in GC patients with PM.
Source: EJNMMI Research
Authors: Yao Peng, Min Shi, Daxi Xiong, Sheng Lu, Ying Miao, Hong Yuan, Chao Yan, Zhenggang Zhu, Biao Li, Zhongyin Yang, Jiajia Hu
Institutions: Shanghai Jiao Tong University, Ruijin Hospital
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,190
Awards: G8939183728, G982273913
OpenAlex ID: W4409626416
