Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8922461 | Clinical and Translational Radiation Oncology | 2017 | 6 Pages |
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.
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Authors
Kaixian Yu, Youyi Zhang, Yang Yu, Chao Huang, Rongjie Liu, Tengfei Li, Liuqing Yang, Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Hongtu Zhu,