External validation of a CT-based radiomics signature in oropharyngeal cancer: Assessing sources of variation

Background and purpose: Radiomics is a high-throughput approach that allows for quantitative analysis of imaging data for prognostic applications. Medical images are used in oropharyngeal cancer (OPC) diag-nosis and treatment planning and these images may contain prognostic information allowing for treat-ment personalization. However, the lack of validated models has been a barrier to the translation of radiomic research to the clinic. We hypothesize that a previously developed radiomics model for risk stratification in OPC can be validated in a local dataset.Materials and methods: The radiomics signature predicting overall survival incorporates features derived from the primary gross tumor volume of OPC patients treated with radiation +/-chemotherapy at a single institution (n = 343). Model fit, calibration, discrimination, and utility were evaluated. The signature was compared with a clinical model using overall stage and a model incorporating both radiomics and clinical data. A model detecting dental artifacts on computed tomography images was also validated.Results: The radiomics signature had a Concordance index (C-index) of 0.66 comparable to the clinical model's C-index of 0.65. The combined model significantly outperformed (C-index of 0.69, p = 0.024) the clinical model, suggesting that radiomics provides added value. The dental artifact model demon-strated strong ability in detecting dental artifacts with an area under the curve of 0.87.Conclusion: This work demonstrates model performance comparable to previous validation work and provides a framework for future independent and multi-center validation efforts. With sufficient valida-tion, radiomic models have the potential to improve traditional systems of risk stratification, treatment personalization and patient outcomes.(c) 2022 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 178 (2023) 109434