Prospective Evaluation of a Tumor Control Probability Model Based on Dynamic F-FMISO PET for Head and Neck Cancer Radiotherapy.

Our purpose was to evaluate an imaging parameter-response relationship between the extent of tumor hypoxia quantified by dynamic F-fluoromisonidazole (F-FMISO) PET/CT and the risk of relapse after radiotherapy in patients with head and neck cancer. Before a prospective cohort of 25 head and neck cancer patients started radiotherapy, they were examined with dynamic F-FMISO PET/CT 0-240 min after tracer injection. F-FMISO image parameters, including a hypoxia metric, derived from pharmacokinetic modeling of dynamic F-FMISO and maximum tumor-to-muscle ratio (TMR) at 4 h after injection, gross tumor volume (GTV), relative hypoxic volume based on and a logistic regression model combining GTV and TMR, were assessed and compared with a previous training cohort ( = 15). Dynamic F-FMISO was used to validate a tumor control probability model based on The prognostic potential with respect to local control of all potential parameters was validated using the concordance index for univariate Cox regression models determined from the training cohort, in addition to Kaplan-Meier analysis including the log-rank test. The tumor control probability model was confirmed, indicating that dynamic F-FMISO allows stratification of patients into different risk groups according to radiotherapy outcome. In this study, was the only parameter that was confirmed as prognostic in the independent validation cohort (concordance index, 0.71; = 0.004). All other investigated parameters, such as TMR, GTV, relative hypoxic volume, and the combination of GTV and TMR, were not able to stratify patient groups according to outcome in this validation cohort ( = not statistically significant). In this study, the relationship between and the risk of relapse was prospectively validated. The data support further evaluation and external validation of dynamic F-FMISO PET/CT as a promising method for patient stratification and hypoxia-based radiotherapy personalization, including dose painting.