Predicting hypoxia status using a combination of contrast-enhanced computed tomography and [F]-Fluorodeoxyglucose positron emission tomography radiomics features.

BACKGROUND AND PURPOSE

Hypoxia is a known prognostic factor in head and neck cancer. Hypoxia imaging PET radiotracers such as F-FMISO are promising but not widely available. The aim of this study was therefore to design a surrogate for F-FMISO TBR based on F-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 F-FDG and F-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 F-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 F-FDG uptake had a test AUC of 0.756.

CONCLUSION

A radiomics signature built from F-FDG PET and contrast-enhanced CT features correlates with F-FMISO TBR in head and neck cancer patients, providing significantly better performance with respect to models based on F-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.