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Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Predicting hypoxia status using a combination of contrast-enhanced computed tomography and [ 18 F]-Fluorodeoxyglucose positron emission tomography radiomics features.
Radiotherapy and Oncology 2018 April
BACKGROUND AND PURPOSE: Hypoxia is a known prognostic factor in head and neck cancer. Hypoxia imaging PET radiotracers such as 18 F-FMISO are promising but not widely available. The aim of this study was therefore to design a surrogate for 18 F-FMISO TBRmax based on 18 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 18 F-FDG and 18 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 18 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 18 F-FDG uptake had a test AUC of 0.756.
CONCLUSION: A radiomics signature built from 18 F-FDG PET and contrast-enhanced CT features correlates with 18 F-FMISO TBRmax in head and neck cancer patients, providing significantly better performance with respect to models based on 18 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.
METHODS: 121 lesions from 75 head and neck cancer patients were used in the analysis. Patients received pre-treatment 18 F-FDG and 18 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 18 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 18 F-FDG uptake had a test AUC of 0.756.
CONCLUSION: A radiomics signature built from 18 F-FDG PET and contrast-enhanced CT features correlates with 18 F-FMISO TBRmax in head and neck cancer patients, providing significantly better performance with respect to models based on 18 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.
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