Intelligent Imaging: Radiomics and Artificial Neural Networks in Heart Failure.

Journal: Journal of medical imaging and radiation sciences
Published Date: Oct 3, 2019

Abstract

BACKGROUND: Our previous work with iodine meta-iodobenzylguanidine (I-mIBG) radionuclide imaging among patients with cardiomyopathy reported limitations associated with the prognostic power of global parameters derived from planar imaging [1]. Employing multivariate analysis, we further showed the regional washout associated with territories adjacent to infarcted myocardium obtained from single-photon emission computed tomography imaging (SPECT) yielded superior prognostic power over the other planar and SPECT indices in predicting future cardiac events [1]. The aim of this study was to apply an artificial neural network (Neural Analyser version 2.9.5) to the original data from the same patient cohort to evaluate the most potent prognostic index for future cardiac events among patient with cardiomyopathy.

Authors

  • Geoff Currie
    School of Dentistry and Health Sciences, Charles Sturt University, Wagga Wagga, Australia gcurrie@csu.edu.au.
  • Basit Iqbal
    School of Dentistry & Health Sciences, Charles Sturt University, Wagga Wagga, Australia; Gujranwala Institute of Nuclear Medicine & Radiotherapy, Gujranwala, Pakistan.
  • Hosen Kiat
    Cardiac Health Institute, Sydney, Australia; UNSW Faculty of Medicine, Sydney, Australia; Faculty of Medicine and Health Science, Macquarie University, Sydney, Australia.

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