Predictive Value of [¹⁸F]FDG PET/CT for Neoadjuvant Chemoradiotherapy Response in Nasopharyngeal Carcinoma

Introduction: Nasopharyngeal carcinoma (NPC) is a distinct malignancy of the head and neck with high prevalence in endemic regions and a strong association with Epstein-Barr virus (EBV). In locally advanced stages, neoadjuvant chemotherapy (NAC) followed by chemoradiotherapy improves outcomes, but response rates vary. Identifying early predictors of NAC response is essential for guiding personalized treatment strategies. This study aims to assess whether baseline [¹⁸F]FDG PET/CT parameters can predict NAC response in NPC patients. Methods: In this retrospective study, 27 patients with histologically confirmed, locally advanced (stage III) NPC underwent baseline [¹⁸F]FDG PET/CT prior to NAC between 2015 and 2023. Quantitative PET parameters including SUVmax, SUVmean, metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were extracted from the primary tumor. NAC response was assessed using RECIST 1.1 criteria and classified as responders (CR + PR) or non-responders (SD + PD). Group comparisons were performed using Student's t-test. ROC analysis was used to identify optimal cut-off values. A p-value < 0.05 was considered significant. Results: The cohort included 20 males and 7 females (mean age: 60.8 ± 15.2 years). The predominant histotype was undifferentiated non-keratinizing carcinoma (92.6%). A total of 19 patients (70.4%) responded to NAC. Responders had significantly lower baseline SUVmax (10.9 ± 4.8 vs. 15.8 ± 4.1, p = 0.021), MTV (16.2 ± 12.4 vs. 27.8 ± 19.5 cm³, p = 0.045), and TLG (128.6 ± 98.2 vs. 218.7 ± 152.4, p = 0.038). SUVmean was also lower in responders (6.1 ± 2.1 vs. 9.3 ± 2.8), although not statistically reported. ROC analysis identified SUVmax > 12.5 and MTV > 20.0 cm³ as thresholds associated with poor NAC response. Conclusions: Baseline metabolic parameters from [¹⁸F]FDG PET/CT, particularly SUVmax and MTV, may assist stratification of NAC response in nasopharyngeal carcinoma. These biomarkers may facilitate pre-treatment stratification and guide more personalized therapeutic approaches. However, the limited sample size may affect the generalizability of these findings, and larger prospective studies are needed to confirm the results.