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

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European Journal of Nuclear Medicine and Molecular Imaging Aims and scope Submit manuscript

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.

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Code availability

Our code is publicly available from our “OPSCC-Radiomics” GitHub-repository (https://github.com/nafets200/OPSCC-Radiomics).

Abbreviations

AJCC:

American Joint Committee on Cancer

AUC:

area under the receiver operating characteristic curve

CI:

confidence interval

CT:

computed tomography

HNSCC:

head-and-neck squamous cell carcinoma

HPV:

human papillomavirus

HU:

Hounsfield unit

ICC:

inter-/intra-class correlation coefficient

ISH:

in situ hybridization

LoG:

Laplacian of Gaussian

OPSCC:

oropharyngeal squamous cell carcinoma

PCR:

polymerase chain reaction

PET:

[18F]fluorodeoxyglucose positron emission tomography

GTV:

gross tumor volume

ROC:

receiver operating characteristic

SD:

standard deviation

TCIA:

The Cancer Imaging Archive

UICC:

Union for International Cancer Control

VOI:

volume of interest

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Author notes

  1. Stefan P. Haider and Amit Mahajan contributed equally to this work.

Authors and Affiliations

  1. Section of Neuroradiology, Department of Radiology and Biomedical Imaging, Yale School of Medicine, 789 Howard Ave, PO Box 208042, New Haven, CT, 06519, USA

    Stefan P. Haider, Amit Mahajan, Ahmet S. Kucukkaya & Seyedmehdi Payabvash

  2. Department of Otorhinolaryngology, University Hospital of Ludwig Maximilians Universität München, Munich, Germany

    Stefan P. Haider, Philipp Baumeister, Christoph Reichel & Kariem Sharaf

  3. Center for Translational Imaging Analysis and Machine Learning, Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA

    Tal Zeevi

  4. Department of Diagnostic Radiology and Augmented Intelligence & Precision Health Laboratory, McGill University Health Centre & Research Institute, Montreal, Quebec, Canada

    Reza Forghani

  5. Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA

    Benjamin H. Kann

  6. Division of Otolaryngology, Department of Surgery, Yale School of Medicine, New Haven, CT, USA

    Benjamin L. Judson

  7. Department of Pathology, Yale School of Medicine, New Haven, CT, USA

    Manju L. Prasad

  8. Section of Medical Oncology, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA

    Barbara Burtness

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  1. Stefan P. Haider
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Corresponding author

Correspondence to Seyedmehdi Payabvash.

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Conflict of interest

SPH has nothing to disclose. AM has nothing to disclose. TZ has nothing to disclose. PB has nothing to disclose. CR has nothing to disclose. KS has nothing to disclose. RF has acted as speaker and consultant for GE Healthcare and has a research agreement (beta tester) and support from GE Healthcare. RF is also a founder and stockholder of 4intelligent Inc., and a clinical research scholar (chercheur-boursier clinician) supported by the Fonds de recherche en santé du Québec (FRQS). ASK has nothing to disclose. BHK has nothing to disclose. BLJ has nothing to disclose. MLP has nothing to disclose. BB has nothing to disclose. SP has nothing to disclose.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the corresponding institutional research committees and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all participants in prospective trials. The Yale University ethics committee waived consent for retrospective analysis of patients’ information under IRB protocol #2000024295 (“Imaging biomarkers for tumor classifications in brain and head/neck tumors using radiomics and machine-learning algorithms”).

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Haider, S.P., Mahajan, A., Zeevi, T. et al. PET/CT radiomics signature of human papilloma virus association in oropharyngeal squamous cell carcinoma. Eur J Nucl Med Mol Imaging 47, 2978–2991 (2020). https://doi.org/10.1007/s00259-020-04839-2

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