Radiomics in head and neck cancer: From exploration to application

Andrew J. Wong, Aasheesh Kanwar, Abdallah S. Mohamed, Clifton D. Fuller

Research output: Contribution to journalReview articlepeer-review

103 Scopus citations

Abstract

In the context of clinical oncology, a fundamental goal of radiomics is the extraction of large amounts of quantitative features whose subsequent analysis can be used for decision support towards personalized and actionable cancer care. Head and neck cancers present a unique set of diagnostic and therapeutic challenges by nature of its complex anatomy and heterogeneity. Radiomics holds the potential to address these barriers, but only if as a collective field we direct future effort towards investigating specific oncologic function and oncologic outcomes, with external validation and collaborative multi-institutional efforts to begin standardizing and refining radiomic signatures. Here we present an overview of radiomic texture analysis methods as well as the software infrastructure, review the developments of radiomics in head and neck cancer applications, discuss unmet challenges, and propose key recommendations for moving the field forward.

Original languageEnglish (US)
Pages (from-to)371-382
Number of pages12
JournalTranslational Cancer Research
Volume5
Issue number4
DOIs
StatePublished - Aug 1 2016

Keywords

  • Head and neck cancer
  • Imaging biomarker
  • Machine learning
  • Radiomics
  • Texture analysis

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research

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