“Radio-oncomics”: The potential of radiomics in radiation oncology

Translated title of the contribution: “Radio-oncomics”: The potential of radiomics in radiation oncology

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55 Scopus citations

Abstract

Introduction: Radiomics, a recently introduced concept, describes quantitative computerized algorithm-based feature extraction from imaging data including computer tomography (CT), magnetic resonance imaging (MRT), or positron-emission tomography (PET) images. For radiation oncology it offers the potential to significantly influence clinical decision-making and thus therapy planning and follow-up workflow. Methods: After image acquisition, image preprocessing, and defining regions of interest by structure segmentation, algorithms are applied to calculate shape, intensity, texture, and multiscale filter features. By combining multiple features and correlating them with clinical outcome, prognostic models can be created. Results: Retrospective studies have proposed radiomics classifiers predicting, e. g., overall survival, radiation treatment response, distant metastases, or radiation-related toxicity. Besides, radiomics features can be correlated with genomic information (“radiogenomics”) and could be used for tumor characterization. Discussion: Distinct patterns based on data-based as well as genomics-based features will influence radiation oncology in the future. Individualized treatments in terms of dose level adaption and target volume definition, as well as other outcome-related parameters will depend on radiomics and radiogenomics. By integration of various datasets, the prognostic power can be increased making radiomics a valuable part of future precision medicine approaches. Conclusion: This perspective demonstrates the evidence for the radiomics concept in radiation oncology. The necessity of further studies to integrate radiomics classifiers into clinical decision-making and the radiation therapy workflow is emphasized.

Translated title of the contribution“Radio-oncomics”: The potential of radiomics in radiation oncology
Original languageEnglish
Pages (from-to)767-779
Number of pages13
JournalStrahlentherapie und Onkologie
Volume193
Issue number10
DOIs
StatePublished - 1 Oct 2017
Externally publishedYes

Keywords

  • Precision medicine
  • Radiation Oncology
  • Radiogenomics
  • Radiotherapy
  • Radiomics
  • Toxicity

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