A Multi-Modality Attention Network for Coronary Artery Disease Evaluation from Routine Myocardial Perfusion Imaging and Clinical Data.

Myocardial perfusion imaging (MPI) is an essential tool for diagnosing and evaluating coronary artery disease (CAD). However, the diagnosis using MPI remains laborious as it involves multi-step readouts and meticulous image processing. These challenges impact current attempts at automating image interpretation of MPI.

Going beyond summed stress scores: Correlating global and territorial coronary flow reserve by single photon emission tomography with routine myocardial perfusion imaging.

A Background: Technological advancement in the recent years has enabled the application of single photon emission tomography (SPECT) to evaluate myocardial blood flow (MBF). This method offers increased sensitivity in the assessment of coronary health, quantifiable through non-invasive imaging beyond the more conventional methods such as with myocardial perfusion imaging (MPI).

B Aims: To correlate MBF, derived by dynamic SPECT, both global and by coronary territories to the summed stress scores (SSS) on conventional MPI.