Mid-treatment changes in intra-tumoural metabolic heterogeneity correlate to outcomes in oropharyngeal squamous cell carcinoma patients

Background: This study evaluated mid-treatment changes in intra-tumoural metabolic heterogeneity and quantitative FDG-PET/CT imaging parameters and correlated the changes with treatment outcomes in oropharyngeal squamous cell cancer (OPSCC) patients. 114 patients from two independent cohorts underwent baseline and mid-treatment (week 3) FDG-PET. Standardized uptake value maximum (SUV_max), standardized uptake value mean (SUV_mean), metabolic tumour volume (MTV), and total lesional glycolysis (TLG) were measured. Intra-tumoural metabolic heterogeneity was quantified as the area under a cumulative SUV-volume histogram curve (AUC-CSH). Baseline and relative change (%∆) in imaging features were correlated to locoregional recurrence free survival (LRRFS) using multivariate Cox regression analysis. Patients were stratified into three risk groups utilising ∆AUC-CSH and known prognostic features, then compared using Kaplan-Meier analysis. Results: Median follow up was 39 months. 18% of patients developed locoregional recurrence at 2 years. A decrease in heterogeneity (∆AUC-CSH: 24%) was observed mid-treatment. There was no statistically significant difference in tumour heterogeneity (AUC-CSH) at baseline (p = 0.134) and change at week 3 (p = 0.306) between p16 positive and p16 negative patients. Baseline imaging features did not correlate to LRRFS. However, ∆MTV (aHR 1.04; 95% CI 1.03–1.06; p < 0.001) and ∆AUC-CSH (aHR 0.96; 95% CI 0.94–0.98; p = 0.004) were correlated to LRRFS. Stratification using ∆AUC-CSH and p16 status into three groups showed significant differences in LRR (2 year LRRFS 94%, 79%, 17%; log rank p < 0.001). Stratification using ∆AUC-CSH and ∆MTV into three groups showed significant differences in LRR (2 year LRRFS 93%, 70%, 17%; log rank p < 0.001). Conclusion: Mid-treatment changes in intra-tumoural FDG-PET/CT heterogeneity correlated with treatment outcomes in OPSCC and may help with response prediction. These findings suggest potential utility in designing future risk adaptive clinical trials.