Computed Tomography Radiomics Predicts HPV Status and Local Tumor Control After Definitive Radiochemotherapy in Head and Neck Squamous Cell Carcinoma

Publication date: 15 November 2017
Source:International Journal of Radiation Oncology*Biology*Physics, Volume 99, Issue 4
Author(s): Marta Bogowicz, Oliver Riesterer, Kristian Ikenberg, Sonja Stieb, Holger Moch, Gabriela Studer, Matthias Guckenberger, Stephanie Tanadini-Lang
PurposeThis study aimed to predict local tumor control (LC) after radiochemotherapy of head and neck squamous cell carcinoma (HNSCC) and human papillomavirus (HPV) status using computed tomography (CT) radiomics.Methods and MaterialsHNSCC patients treated with definitive radiochemotherapy were included in the retrospective study approved by the local ethical commission (93 and 56 patients in the training and validation cohorts, respectively). Three hundred seventeen CT radiomic features, including those based on shape, intensity, texture, and wavelet transform, were calculated in the primary tumor region. Cox and logistic regression models were built to predict LC and HPV status, respectively. The best-performing features in the univariable analysis were included in the multivariable analysis after the exclusion of redundant features. The quality of the models was assessed using the concordance index (CI) for modeling of LC and receiver operating characteristics area under the curve (AUC) for HPV status prediction. The radiomics LC model was compared to a model incorporating clinical parameters (tumor stage, volume, and HPV status) and a mixed model.ResultsA radiomic signature comprising 3 features was significantly associated with LC (CItraining = 0.75 and CIvalidation = 0.78), showing that tumors with a more heterogeneous CT density distribution are at risk for decreased LC. The addition of clinical parameters to the radiomics model slightly improved the model in the training cohort but not in the validation cohort. Another radiomic signature showed good performance in HPV status prediction (AUCtraining = 0.85 and AUCvalidation = 0.78) and indicated that HPV-positive tumors have a more homogenous CT density distribution.ConclusionsHeterogeneity of HNSCC tumor density, quantified by CT radiomics, is associated with LC after radiochemotherapy and HPV status.



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