Using decision curve analysis to benchmark performance of a magnetic resonance imaging-based deep learning model for prostate cancer risk assessment.

Journal: European radiology
Published Date: Jun 26, 2020

Abstract

OBJECTIVES: To benchmark the performance of a calibrated 3D convolutional neural network (CNN) applied to multiparametric MRI (mpMRI) for risk assessment of clinically significant prostate cancer (csPCa) using decision curve analysis (DCA).

Authors

  • Dominik Deniffel
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
  • Nabila Abraham
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
  • Khashayar Namdar
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
  • Xin Dong
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
  • Emmanuel Salinas
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
  • Laurent Milot
    Body and VIR Radiology Department, Hospices Civils de Lyon, Hôpital Edouard Herriot, Lyon, France.
  • Farzad Khalvati
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada. farzad.khalvati@utoronto.ca.
  • Masoom A Haider
    Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.

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