Machine learning-based prediction of breast cancer growth rate in vivo.

Journal: British journal of cancer
Published Date: Sep 1, 2019

Abstract

BACKGROUND: Determining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the rate of in vivo tumour growth using a unique study cohort of BC patients who had two serial mammograms wherein the tumour, visible in the diagnostic mammogram, was missed in the first screen.

Authors

  • Shristi Bhattarai
    Department of Biology, Georgia State University, Atlanta, GA, 30303, USA.
  • Sergey Klimov
    Department of Biomedical Sciences, Cedars Sinai Medical Center, Los Angeles, CA, USA.
  • Mohammed A Aleskandarany
    Nottingham Breast Cancer Research Centre, Division of Cancer and Stem Cells, School of Medicine, University of Nottingham and Nottingham University Hospitals NHS Trust, City Hospital Campus, Nottingham, NG5 1PB, UK.
  • Helen Burrell
    Nottingham Breast Institute, Nottingham University Hospitals NHS Trust, Nottingham City hospital, Nottingham, NG5 1PB, UK.
  • Anthony Wormall
    Nottingham Breast Cancer Research Centre, Division of Cancer and Stem Cells, School of Medicine, University of Nottingham and Nottingham University Hospitals NHS Trust, City Hospital Campus, Nottingham, NG5 1PB, UK.
  • Andrew R Green
    Nottingham Breast Cancer Research Centre, Division of Cancer and Stem Cells, School of Medicine, University of Nottingham and Nottingham University Hospitals NHS Trust, City Hospital Campus, Nottingham, NG5 1PB, UK.
  • Padmashree Rida
    Department of Biology, Georgia State University, Atlanta, GA, 30303, USA.
  • Ian O Ellis
  • Remus M Osan
    Mathematics and Statistics, Georgia State University, Atlanta, GA, 30303, USA.
  • Emad A Rakha
    Department of Cellular Pathology, University of Nottingham, Nottingham, UK. Emad.Rakha@Nottingham.Ac.Uk.
  • Ritu Aneja
    Department of Biology, Georgia State University, Atlanta, GA, 30303, USA. raneja@gsu.edu.

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