Machine learning analysis of breast ultrasound to classify triple negative and HER2+ breast cancer subtypes.

Journal: Breast disease
PMID: 36911927

Abstract

OBJECTIVES: Early diagnosis of triple-negative (TN) and human epidermal growth factor receptor 2 positive (HER2+) breast cancer is important due to its increased risk of micrometastatic spread necessitating early treatment and for guiding targeted therapies. This study aimed to evaluate the diagnostic performance of machine learning (ML) classification of newly diagnosed breast masses into TN versus non-TN (NTN) and HER2+ versus HER2 negative (HER2-) breast cancer, using radiomic features extracted from grayscale ultrasound (US) b-mode images.

Authors

  • Romuald Ferre
    Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Janne Elst
    Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Seanthan Senthilnathan
    Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
  • Andrew Lagree
    Odette Cancer Program, Sunnybrook Health Sciences Centre, Toronto, Canada; Radiogenomics Laboratory, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Sami Tabbarah
    Odette Cancer Program, Sunnybrook Health Sciences Centre, Toronto, Canada; Radiogenomics Laboratory, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • Fang-I Lu
    Odette Cancer Program, Sunnybrook Health Sciences Centre, Toronto, Canada; Anatomic Pathology, Sunnybrook Health Sciences Centre, Toronto, Canada.
  • 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.
  • Belinda Curpen
    Division of Breast Imaging, 71545Sunnybrook Health Sciences Centre, Toronto, Canada.

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