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Creation of a Standardized Myocardial Perfusion Single-photon Emission Computed Tomography Database to Enhance

Abdurrahim Rahimian1, Masoud Moslehi2, Hossein Rabbani1

  • 1Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Journal of Medical Signals and Sensors
|July 11, 2026
PubMed

Insights

This study analyzed coronary artery disease (CAD) using myocardial perfusion imaging (MPI) and found sex-specific differences in presentation. A new standardized dataset was created to advance AI in nuclear cardiology.

Area of Science:

  • Nuclear Cardiology
  • Cardiovascular Imaging
  • Artificial Intelligence in Medicine

Background:

  • Coronary artery disease (CAD) is a leading cause of cardiovascular mortality worldwide.
  • Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a key diagnostic tool.
  • Development of AI diagnostic tools is limited by a lack of high-quality, labeled SPECT MPI datasets.

Purpose of the Study:

  • To create a standardized, annotated SPECT MPI dataset for AI model development.
  • To investigate sex-specific differences in CAD presentation using MPI.
  • To improve reproducibility and support research into CAD phenotypes.

Main Methods:

  • Retrospective analysis of 144 rest-stress MIBI SPECT MPI studies.
  • Images reconstructed using filtered back projection.
  • Independent interpretation by three nuclear cardiology specialists; statistical analysis using SPSS v26.

Main Results:

  • Observed significant sex-specific differences in CAD presentation and perfusion patterns.
  • Women with CAD were older, showing more microvascular dysfunction; men had larger territorial defects.
  • Perfusion abnormalities correlated with cardiovascular risk burden; excellent interobserver agreement (ICC=0.87).

Conclusions:

  • Introduced a standardized SPECT MPI dataset for explainable AI in nuclear cardiology.
  • The sex-stratified dataset facilitates research into CAD phenotypes.
  • Enhances reproducibility in AI model development for cardiovascular imaging.
Abstract

Keywords:
Artificial intelligenceSPECTcoronary artery diseasedatasetmyocardial perfusion

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