A novel algorithm developed using machine learning and a J-ACCESS database can estimate defect scores from myocardial perfusion single-photon emission tomography images.

Journal: Annals of nuclear medicine
PMID: 39210200

Abstract

BACKGROUND: Stress myocardial perfusion single-photon emission computed tomography (SPECT) imaging (MPI) has been used to diagnose and predict the prognoses of patients with coronary artery disease (CAD). An ongoing multicenter collaboration established a Japanese database (J-ACCESS) in 2001 that includes a risk model and expert interpretations. The present study aimed to develop a novel algorithm using machine learning (ML) and resources from the J-ACCESS database to aid SPECT image interpretation.

Authors

  • Keisuke Kiso
    National Cerebral and Cardiovascular Center, Suita, Japan.
  • Kenichi Nakajima
    Department of Nuclear Medicine, Kanazawa University Hospital.
  • Yukitaka Nimura
    Information Strategy Office, Information and Communications, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Aichi, Japan.
  • Tsunehiko Nishimura
    Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan.

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