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Clin Transl Radiat Oncol. 2017 Nov 6;7:49-54. doi: 10.1016/j.ctro.2017.10.001. eCollection 2017 Dec.

Radiomic analysis in prediction of Human Papilloma Virus status.

Author information

1
Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, United States.
2
Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, United States.
3
Department of Biostatistics, University of North Carolina at Chapel Hill, United States.

Abstract

Human Papilloma Virus (HPV) has been associated with oropharyngeal cancer prognosis. Traditionally the HPV status is tested through invasive lab test. Recently, the rapid development of statistical image analysis techniques has enabled precise quantitative analysis of medical images. The quantitative analysis of Computed Tomography (CT) provides a non-invasive way to assess HPV status for oropharynx cancer patients. We designed a statistical radiomics approach analyzing CT images to predict HPV status. Various radiomics features were extracted from CT scans, and analyzed using statistical feature selection and prediction methods. Our approach ranked the highest in the 2016 Medical Image Computing and Computer Assisted Intervention (MICCAI) grand challenge: Oropharynx Cancer (OPC) Radiomics Challenge, Human Papilloma Virus (HPV) Status Prediction. Further analysis on the most relevant radiomic features distinguishing HPV positive and negative subjects suggested that HPV positive patients usually have smaller and simpler tumors.

KEYWORDS:

CT image; HPV status; Oropharynx cancer; Radiomics; Statistical method

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