AUTHOR=Song Bolin , Yang Kailin , Garneau Jonathan , Lu Cheng , Li Lin , Lee Jonathan , Stock Sarah , Braman Nathaniel M. , Koyuncu Can Fahrettin , Toro Paula , Fu Pingfu , Koyfman Shlomo A. , Lewis James S. , Madabhushi Anant TITLE=Radiomic Features Associated With HPV Status on Pretreatment Computed Tomography in Oropharyngeal Squamous Cell Carcinoma Inform Clinical Prognosis JOURNAL=Frontiers in Oncology VOLUME=11 YEAR=2021 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.744250 DOI=10.3389/fonc.2021.744250 ISSN=2234-943X ABSTRACT=Purpose

There is a lack of biomarkers for accurately prognosticating outcome in both human papillomavirus-related (HPV+) and tobacco- and alcohol-related (HPV−) oropharyngeal squamous cell carcinoma (OPSCC). The aims of this study were to i) develop and evaluate radiomic features within (intratumoral) and around tumor (peritumoral) on CT scans to predict HPV status; ii) investigate the prognostic value of the radiomic features for both HPV− and HPV+ patients, including within individual AJCC eighth edition-defined stage groups; and iii) develop and evaluate a clinicopathologic imaging nomogram involving radiomic, clinical, and pathologic factors for disease-free survival (DFS) prediction for HPV+ patients.

Experimental Design

This retrospective study included 582 OPSCC patients, of which 462 were obtained from The Cancer Imaging Archive (TCIA) with available tumor segmentation and 120 were from Cleveland Clinic Foundation (CCF, denoted as SCCF) with HPV+ OPSCC. We subdivided the TCIA cohort into training (ST, 180 patients) and validation (SV, 282 patients) based on an approximately 3:5 ratio for HPV status prediction. The top 15 radiomic features that were associated with HPV status were selected by the minimum redundancy–maximum relevance (MRMR) using ST and evaluated on SV. Using 3 of these 15 top HPV status-associated features, we created radiomic risk scores for both HPV+ (RRSHPV+) and HPV− patients (RRSHPV−) through a Cox regression model to predict DFS. RRSHPV+ was further externally validated on SCCF. Nomograms for the HPV+ population (Mp+RRS) were constructed. Both RRSHPV+ and Mp+RRS were used to prognosticate DFS for the AJCC eighth edition-defined stage I, stage II, and stage III patients separately.

Results

RRSHPV+ was prognostic for DFS for i) the whole HPV+ population [hazard ratio (HR) = 1.97, 95% confidence interval (CI): 1.35–2.88, p < 0.001], ii) the AJCC eighth stage I population (HR = 1.99, 95% CI: 1.04–3.83, p = 0.039), and iii) the AJCC eighth stage II population (HR = 3.61, 95% CI: 1.71–7.62, p < 0.001). HPV+ nomogram Mp+RRS (C-index, 0.59; 95% CI: 0.54–0.65) was also prognostic of DFS (HR = 1.86, 95% CI: 1.27–2.71, p = 0.001).

Conclusion

CT-based radiomic signatures are associated with both HPV status and DFS in OPSCC patients. With additional validation, the radiomic signature and its corresponding nomogram could potentially be used for identifying HPV+ OPSCC patients who might be candidates for therapy deintensification.