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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Discover the latest articles, news and stories from top researchers in related subjects.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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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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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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DOI: https://doi.org/10.1007/s00259-020-04839-2