Radiomic Biomarkers to Refine Risk Models for Distant Metastasis in HPV-related Oropharyngeal Carcinoma

Publication date: Available online 1 February 2018
Source:International Journal of Radiation Oncology*Biology*Physics
Author(s): Jennifer Yin Yee Kwan, Jie Su, Shao Hui Huang, Laleh S. Ghoraie, Wei Xu, Biu Chan, Kenneth W. Yip, Meredith Giuliani, Andrew Bayley, John Kim, Andrew J. Hope, Jolie Ringash, John Cho, Andrea McNiven, Aaron Hansen, David Goldstein, John de Almeida, Hugo J. Aerts, John N. Waldron, Benjamin Haibe-Kains, Brian O'Sullivan, Scott V. Bratman, Fei-Fei Liu
PurposeDistant metastasis (DM) is the main cause of death for patients with human papillomavirus (HPV)-related oropharyngeal cancers (OPC); yet there are few reliable predictors of DM in this disease. The role of quantitative imaging (i.e. radiomic) analysis was examined to determine whether there are primary tumor features discernible on imaging studies that associate with a higher risk of developing DM.MethodsRadiotherapy planning CT scans were retrieved for all non-metastatic p16-positive OPC patients treated with radiotherapy or chemoradiotherapy at a single institution between 2005 and 2010. Radiomic biomarkers were derived from each gross tumor volume (GTV). Biomarkers included four representative radiomic features from tumor first order statistics, shape, texture, and wavelet groups as well as a combined four-feature signature. Univariable Cox proportional hazards models for DM risk were identified. Discriminative performance of prognostic univariable and multivariable models was compared using the concordance index (C-index). Subgroup analyses were performed.ResultsThere were 300 HPV-related OPC patients who were eligible for the analysis. A total of 36 DM events occurred within a median follow-up of five years. On univariable analysis, top results included the four representative radiomic features (C-index=0.670-0.686; p<0.001), the radiomic signature (C-index=0.670; p<0.001), tumor stage (C-index=0.633; p<0.001), tumor diameter (C-index=0.653; p<0.001), and tumor volume (C-index=0.674; p<0.001); which demonstrated moderate discrimination of DM risk. Combined clinical-radiomic models yielded significantly improved performance (C-index=0.701-0.714; p<0.05). In subgroup analyses, the radiomic biomarkers consistently stratified patients for DM risk, particularly for those cohorts with greater risks (C-index=0.663-0.796), such as patients with stage III disease.ConclusionsRadiomic biomarkers appear to classify DM risk for patients with non-metastatic HPV-related OPC. Radiomic biomarkers could be used either alone or with other clinical characteristics in assignment of DM risk in future HPV-related OPC clinical trials.



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