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Development and validation of a radiomic signature to predict HPV (p16) status from standard CT imaging: a multicenter study


Leijenaar, Ralph T H; Bogowicz, Marta; Jochems, Arthur; Hoebers, Frank J P; Wesseling, Frederik W R; Huang, Sophie H; Chan, Biu; Waldron, John N; O'Sullivan, Brian; Rietveld, Derek; Leemans, C Rene; Brakenhoff, Ruud H; Riesterer, Oliver; Tanadini-Lang, Stephanie; Guckenberger, Matthias; Ikenberg, Kristian; Lambin, Philippe (2018). Development and validation of a radiomic signature to predict HPV (p16) status from standard CT imaging: a multicenter study. British Journal of Radiology, 91(1086):20170498.

Abstract

OBJECTIVES Human papillomavirus (HPV) positive oropharyngeal cancer (oropharyngeal squamous cell carcinoma, OPSCC) is biologically and clinically different from HPV negative OPSCC. Here, we evaluate the use of a radiomic approach to identify the HPV status of OPSCC.
METHODS Four independent cohorts, totaling 778 OPSCC patients with HPV determined by p16 were collected. We randomly assigned 80% of all data for model training (N = 628) and 20% for validation (N = 150). On the pre-treatment CT images, 902 radiomic features were calculated from the gross tumor volume. Multivariable modeling was performed using least absolute shrinkage and selection operator. To assess the impact of CT artifacts in predicting HPV (p16), a model was developed on all training data (M) and on the artifact-free subset of training data (M). Models were validated on all validation data (V), and the subgroups with (V) and without (V) artifacts. Kaplan-Meier survival analysis was performed to compare HPV status based on p16 and radiomic model predictions.
RESULTS The area under the receiver operator curve for M and M ranged between 0.70 and 0.80 and was not significantly different for all validation data sets. There was a consistent and significant split between survival curves with HPV status determined by p16 [p = 0.007; hazard ratio (HR): 0.46], M (p = 0.036; HR: 0.55) and M (p = 0.027; HR: 0.49).
CONCLUSION This study provides proof of concept that molecular information can be derived from standard medical images and shows potential for radiomics as imaging biomarker of HPV status. Advances in knowledge: Radiomics has the potential to identify clinically relevant molecular phenotypes.

Abstract

OBJECTIVES Human papillomavirus (HPV) positive oropharyngeal cancer (oropharyngeal squamous cell carcinoma, OPSCC) is biologically and clinically different from HPV negative OPSCC. Here, we evaluate the use of a radiomic approach to identify the HPV status of OPSCC.
METHODS Four independent cohorts, totaling 778 OPSCC patients with HPV determined by p16 were collected. We randomly assigned 80% of all data for model training (N = 628) and 20% for validation (N = 150). On the pre-treatment CT images, 902 radiomic features were calculated from the gross tumor volume. Multivariable modeling was performed using least absolute shrinkage and selection operator. To assess the impact of CT artifacts in predicting HPV (p16), a model was developed on all training data (M) and on the artifact-free subset of training data (M). Models were validated on all validation data (V), and the subgroups with (V) and without (V) artifacts. Kaplan-Meier survival analysis was performed to compare HPV status based on p16 and radiomic model predictions.
RESULTS The area under the receiver operator curve for M and M ranged between 0.70 and 0.80 and was not significantly different for all validation data sets. There was a consistent and significant split between survival curves with HPV status determined by p16 [p = 0.007; hazard ratio (HR): 0.46], M (p = 0.036; HR: 0.55) and M (p = 0.027; HR: 0.49).
CONCLUSION This study provides proof of concept that molecular information can be derived from standard medical images and shows potential for radiomics as imaging biomarker of HPV status. Advances in knowledge: Radiomics has the potential to identify clinically relevant molecular phenotypes.

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Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Radiation Oncology
04 Faculty of Medicine > University Hospital Zurich > Institute of Pathology and Molecular Pathology
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:June 2018
Deposited On:05 Sep 2018 11:55
Last Modified:24 Sep 2019 23:35
Publisher:British Institute of Radiology
ISSN:0007-1285
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1259/bjr.20170498
PubMed ID:29451412

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