Neo-adjuvant chemoradiotherapy response prediction using MRI based ensemble learning method in rectal cancer patients.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Published Date: Jun 1, 2019

Abstract

OBJECTIVES: The aim of this study was to investigate and validate the performance of individual and ensemble machine learning models (EMLMs) based on magnetic resonance imaging (MRI) to predict neo-adjuvant chemoradiation therapy (nCRT) response in rectal cancer patients. We also aimed to study the effect of Laplacian of Gaussian (LOG) filter on EMLMs predictive performance.

Authors

  • Sajad P Shayesteh
    Department of Physiology, Pharmacology and Medical Physics, Faculty of Medicine, Alborz University of Medical Sciences, Karaj, Iran.
  • Afsaneh Alikhassi
    Department of Radiology, Faculty of medicine, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: a-alikhasi@sina.tums.ac.ir.
  • Armaghan Fard Esfahani
    Research Center for Nuclear Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
  • M Miraie
    Cancer Research Centre & Radiation Oncology Department, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran.
  • Parham Geramifar
    Research Center for Nuclear Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.
  • Ahmad Bitarafan-Rajabi
    Cardiovascular Intervention Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran; Echocardiography Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran.
  • Peiman Haddad
    Radiation Oncology Research Center, Cancer Institute, Tehran University of Medical Sciences, Tehran, Iran. Electronic address: haddad@tums.ac.ir.

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