PET/CT radiomics signature of human papilloma virus association in oropharyngeal squamous cell carcinoma

Haider, Stefan P.; Mahajan, Amit; Zeevi, Tal; Baumeister, Philipp; Reichel, Christoph; Sharaf, Kariem; Forghani, Reza; Kucukkaya, Ahmet S.; Kann, Benjamin H.; Judson, Benjamin L.; Prasad, Manju L.; Burtness, Barbara und Payabvash, Seyedmehdi (2020): PET/CT radiomics signature of human papilloma virus association in oropharyngeal squamous cell carcinoma. In: European Journal of Nuclear Medicine and Molecular Imaging, Bd. 47, Nr. 13: S. 2978-2991

Abstract

Purpose: To devise, validate, and externally test PET/CT radiomics signatures for human papillomavirus (HPV) association in primary tumors and metastatic cervical lymph nodes of oropharyngeal squamous cell carcinoma (OPSCC). Methods We analyzed 435 primary tumors (326 for training, 109 for validation) and 741 metastatic cervical lymph nodes (518 for training, 223 for validation) using FDG-PET and non-contrast CT from a multi-institutional and multi-national cohort. Utilizing 1037 radiomics features per imaging modality and per lesion, we trained, optimized, and independently validated machine-learning classifiers for prediction of HPV association in primary tumors, lymph nodes, and combined "virtual" volumes of interest (VOI). PET-based models were additionally validated in an external cohort. Results Single-modality PET and CT final models yielded similar classification performance without significant difference in independent validation;however, models combining PET and CT features outperformed single-modality PET- or CT-based models, with receiver operating characteristic area under the curve (AUC) of 0.78, and 0.77 for prediction of HPV association using primary tumor lesion features, in cross-validation and independent validation, respectively. In the external PET-only validation dataset, final models achieved an AUC of 0.83 for a virtual VOI combining primary tumor and lymph nodes, and an AUC of 0.73 for a virtual VOI combining all lymph nodes. Conclusion We found that PET-based radiomics signatures yielded similar classification performance to CT-based models, with potential added value from combining PET- and CT-based radiomics for prediction of HPV status. While our results are promising, radiomics signatures may not yet substitute tissue sampling for clinical decision-making.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Medizin
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• ISSN: 1619-7070
• Sprache: Englisch