Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.

Journal: International journal of radiation oncology, biology, physics
Published Date: Apr 1, 2020

Abstract

PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes associated with radiation-induced dermatitis, such as inflammation, may also increase body-surface temperature, which can be detected by thermal imaging. Quantitative thermal imaging markers were identified and used in supervised machine learning to develop a predictive model for radiation dermatitis.

Authors

  • Khadijeh Saednia
    Radiogenomics Laboratory, Sunnybrook Health Sciences Centre, Toronto, Canada; Department of Electrical Engineering and Computer Science, Lassonde School of Engineering, York University, Toronto, Canada.
  • Sami Tabbarah
    Odette Cancer Program, Sunnybrook Health Sciences Centre, Toronto, Canada; Radiogenomics Laboratory, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Andrew Lagree
    Odette Cancer Program, Sunnybrook Health Sciences Centre, Toronto, Canada; Radiogenomics Laboratory, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Tina Wu
    Odette Cancer Program, Sunnybrook Health Sciences Centre, Toronto, Canada; Radiogenomics Laboratory, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Jonathan Klein
    Department of Radiation Oncology, Albert Einstein College of Medicine, Bronx, USA.
  • Eduardo Garcia
    Institute of Biomedical Research of Barcelona (IIBB), Spanish National Research Council (CSIC), Barcelona, Spain.
  • Michael Hall
    Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Edward Chow
    Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Canada.
  • Eileen Rakovitch
    Department of Radiation Oncology, Sunnybrook Health Sciences Centre, Toronto, Canada; Department of Radiation Oncology, University of Toronto, Toronto, Canada.
  • Charmaine Childs
    Department of Radiotherapy & Oncology, Sheffield Hallam University, Sheffield, United Kingdom.
  • Ali Sadeghi-Naini
    Physical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • William T Tran
    Odette Cancer Program, Sunnybrook Health Sciences Centre, Toronto, Canada; Faculty of Medicine, Department Radiation Oncology, University of Toronto, Toronto, Canada; Faculty of Health and Wellbeing, Sheffield Hallam University, Sheffield, United Kingdom; Radiogenomics Laboratory, Sunnybrook Health Sciences Centre, Toronto, Canada. Electronic address: william.tran@sunnybrook.ca.

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