Radiomic analysis in prediction of Human Papilloma Virus status

Kaixian Yu, Youyi Zhang, Yang Yu, Chao Huang, Rongjie Liu, Tengfei Li, Liuqing Yang, Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Hongtu Zhu

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)49-54
Number of pages6
JournalClinical and Translational Radiation Oncology
Volume7
DOIs
StatePublished - Dec 1 2017

Keywords

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

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging

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