Abstract Body: Objective: Optical coherence tomography (OCT) is an intravascular imaging technology that can provide cross-sectional images of coronary arteries, which can more accurately assess the condition of coronary artery lesions and the degree of vascular stenosis. It is an important method for the anatomical evaluation of coronary artery lesions. Radionuclide myocardial perfusion imaging (MPI) is a commonly used non-invasive method for functional evaluation of myocardial ischemia in clinical practice. The clinical application of these two methods is greatly limited due to operational risk and high cost. This study aimed to explore the potential predictive value of the MCG-based Nomogram model for the anatomical and functional evaluation of coronary artery lesions.
Methods: We reviewed the patients who were hospitalized in the cardiovascular department of our hospital from October 2021 to July 2023 for MCG test. A total of 137 patients were included in the OCT subgroup, including 48 patients in the severe coronary artery stenosis group (inclusion criteria: OCT showed coronary artery area stenosis ≥70.0%) and 89 patients in the control group (inclusion criteria: OCT showed coronary artery area stenosis <50.0% or CCTA showed no coronary artery stenosis). A total of 46 patients were included in the MPI subgroup, including 10 patients in the severe myocardial ischemia group (inclusion criteria: MPI showed abnormal perfusion scores of at least one ventricular segment ≥3 points) and 36 patients in the control group (inclusion criteria: MPI showed abnormal perfusion scores of all ventricular segments ≤2 points). The Nomogram model was used to predict the results of patients in the two subgroups, and the results were compared with the OCT and MPI results. The sensitivity, specificity and Youden index were calculated.
Results: The Nomogram model based on MCG had a sensitivity of 70.8%, a specificity of 85.4%, and a Youden index of 0.562 for predicting OCT results. The sensitivity, specificity and Youden index of Nomogram model for predicting MPI results were 70.0%, 72.2% and 0.422, respectively.
Conclusions: The MCG-based Nomogram model has good prediction accuracy for the anatomical and functional evaluation of coronary artery lesions, which has potential application value.