PET/CT radiomics signature of human papilloma virus association in oropharyngeal squamous cell carcinoma.
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 validati...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 47; no. 13; pp. 2978 - 2992 |
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| Autores principales: | , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=147137002&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 147137002 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: 2020 vid: 47 iid: 13 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 147137002 144053880 10.1007/s00259-020-04839-2 147137002 ppf: 2978 ppct: 14 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: PET/CT radiomics signature of human papilloma virus association in oropharyngeal squamous cell carcinoma. aug: au: 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 Payabvash, Seyedmehdi affil: Section of Neuroradiology, Department of Radiology and Biomedical Imaging, Yale School of Medicine, PO Box 208042, 789 Howard Ave, 06519, New Haven, CT, USA sug: ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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