Radiomics model based on preoperative 18F-fluorodeoxyglucose PET predicts N2-3b lymph node metastasis in gastric cancer patients.

Objective: The aim of the study was to construct and validate 18F-fluorodeoxyglucose (18F-FDG) PET-based radiomics nomogram and use it to predict N2-3b lymph node metastasis in Chinese patients with gastric cancer (GC).

Methods: A total of 127 patients with pathologically confirmed GC who underwent preoperative 18F-FDG PET/CT imaging between January 2014 and September 2020 were enrolled as subjects in this study. We use the LIFEx software to extract PET radiomic features. A radiomics signature (Rad-score) was developed with the least absolute shrinkage and selection operator algorithm. Then a prediction model, which incorporated the Rad-score and independent clinical risk factors, was constructed and presented with a radiomics nomogram. Receiver operating characteristic (ROC) analysis was used to assess the performance of Rad-score and the nomogram. Finally, decision curve analysis (DCA) was applied to evaluate the clinical usefulness of the nomogram.

Results: The PET Rad-score, which includes four selected features, was significantly related to pN2-3b (all P < 0.05). The prediction model, which comprised the Rad-score and carcinoembryonic antigen (CEA) level, showed good calibration and discrimination [area under the ROC curve: 0.81(95% confidence interval: 0.74-0.89), P < 0.001)]. The DCA also indicated that the prediction model was clinically useful.

Conclusion: This study presents a radiomics nomogram consisting of a radiomics signature based on PET images and CEA level that can be conveniently used for personalized prediction of high-risk N2-3b metastasis in Chinese GC patients.