The Role of 18F-FDG PET/CT in Predicting the Pathological Response to Neoadjuvant Immunochemotherapy and Prognosis...

Accurately predicting tumor response to neoadjuvant immunochemotherapy (NICT) and patient prognosis remains challenging in esophageal cancer. This study aimed to explore the value of ¹⁸F-FDG PET/CT in predicting the pathological response and prognosis of patients with resectable esophageal squamous cell carcinoma (ESCC) undergoing NICT.

Patients who underwent NICT between January 2020 and April 2024 were retrospectively analyzed. ¹⁸F-FDG PET/CT scans were performed before (scan-1) and after NICT (scan-2). Parameters derived from ¹⁸F-FDG PET/CT and enhanced CT were analyzed for response evaluation and survival prediction. The pathological tumor regression grade served as the gold standard for response evaluation.

Among the 94 patients, 41 patients (43.6%) achieved a major pathological response (MPR). ¹⁸F-FDG PET/CT identified more responders than CT. Compared with non-MPR patients, those achieving MPR demonstrated significantly lower uptake on scan-2 and a greater relative reduction (Δ%) between scan-1 and scan-2. The SUV_max of scan-2 demonstrated the best predictive performance for MPR (AUC = 0.829). The SUL_peak of scan-2 showed the highest sensitivity for predicting MPR (90.2%). Multivariate analysis indicated that CPS, SUV_max-2, and ΔSUV_max% were independent predictors of MPR, while pathological stage, PERCIST, and TLG-2 were independent predictors of PFS; further, the pathological stage, PERCIST, and ΔMTV% were independent predictors of OS. Patients with TLG-2 < 8.1 or ΔMTV% > 75.5% indicated better treatment response and longer survival.

Parameters after NICT and their changes before and after treatment were valuable in identifying patients achieving MPR and predicting prognosis. ¹⁸F-FDG PET/CT is a potentially valuable method for predicting the pathological response to NICT and the prognosis of resectable ESCC.

Metabolic parameters after NICT and their changes from baseline were valuable for identifying MPR and predicting prognosis. Post-treatment SUV_max and SUL_peak may serve as effective predictors of MPR, while a favorable PERCIST or lower TLG-2 relates to improved PFS, and a favorable PERCIST or higher ΔMTV% correlates with prolonged OS.