Figures & data
Table 1. Detailed patients characteristic.
Table 2. The scanning parameters for training and validation cohorts and two image modalities.
Figure 1. Radiomics-based local tumor control prognostic models: (a) CT-based radiomics, (b) PET-based radiomics, (c) CT- and PET-based radiomics. Tumor control curves split significantly (G-rho test p-value < 0.05) in both training and validation cohorts based on the optimal sensitivity-specificity thresholds at 18 months.
![Figure 1. Radiomics-based local tumor control prognostic models: (a) CT-based radiomics, (b) PET-based radiomics, (c) CT- and PET-based radiomics. Tumor control curves split significantly (G-rho test p-value < 0.05) in both training and validation cohorts based on the optimal sensitivity-specificity thresholds at 18 months.](/cms/asset/6c61181c-d7df-4424-8556-7bf368d6e1f8/ionc_a_1346382_f0001_c.jpg)
Figure 2. The comparison of risk group stratification in the validation cohort by CT- and PET-based radiomics models (a) the repeatability of patients’ ranking based on CT and PET radiomics models and differences in risk group stratification, (b) the relation between observed and radiomics model-based estimated probabilities of local tumor control at 18 months for risk groups defined using the radiomics models.
![Figure 2. The comparison of risk group stratification in the validation cohort by CT- and PET-based radiomics models (a) the repeatability of patients’ ranking based on CT and PET radiomics models and differences in risk group stratification, (b) the relation between observed and radiomics model-based estimated probabilities of local tumor control at 18 months for risk groups defined using the radiomics models.](/cms/asset/adb5cada-0f0a-4e1e-b961-2e3e925a61ec/ionc_a_1346382_f0002_c.jpg)