abstract
- BACKGROUND AND PURPOSE: Hypoxia is a known prognostic factor in head and neck cancer. Hypoxia imaging PET radiotracers such as 18F-FMISO are promising but not widely available. The aim of this study was therefore to design a surrogate for 18F-FMISO TBRmax based on 18F-FDG PET and contrast-enhanced CT radiomics features, and to study its performance in the context of hypoxia-based patient stratification. METHODS: 121 lesions from 75 head and neck cancer patients were used in the analysis. Patients received pre-treatment 18F-FDG and 18F-FMISO PET/CT scans. 79 lesions were used to train a cross-validated LASSO regression model based on radiomics features, while the remaining 42 were held out as an internal test subset. RESULTS: In the training subset, the highest AUC (0.873±0.008) was obtained from a signature combining CT and 18F-FDG PET features. The best performance on the unseen test subset was also obtained from the combined signature, with an AUC of 0.833, while the model based on the 90th percentile of 18F-FDG uptake had a test AUC of 0.756. CONCLUSION: A radiomics signature built from 18F-FDG PET and contrast-enhanced CT features correlates with 18F-FMISO TBRmax in head and neck cancer patients, providing significantly better performance with respect to models based on 18F-FDG PET only. Such a biomarker could potentially be useful to personalize head and neck cancer treatment at centers for which dedicated hypoxia imaging PET radiotracers are unavailable.