Document Type : Research Paper
Authors
1
Department of Internal Medicine, School of Medicine, Al-Zahra Hospital, Isfahan University of Medical Sciences
2
School of Medicine, Birjand University of Medical Sciences, Birjand, Iran
3
Cardiovascular Diseases Research Center, Birjand University of Medical Sciences, Birjand, Iran
4
Nuclear Medicine Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
5
Department of Nuclear Medicine, Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
6
Kidney Transplantation Complications Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
7
Department of Nuclear Medicine, School of Medicine, Iran University of Medical Science, Tehran 14496-14535, Iran
Abstract
Introduction: Coronary artery disease (CAD) is one of the leading causes of mortality worldwide, necessitating accurate diagnostic methods. One of the primary goals of researchers is to find a method for diagnosing coronary artery disease before its manifestation and to determine the prevalence of potential risk factors. The first step in secondary prevention is screening and identifying the disease before the onset of severe disabilities. The present study aimed to assess the correlation (accuracy) between myocardial perfusion scan results and angiography at the Birjand Nuclear Medicine Center.
Methods: A retrospective analysis was conducted on 96 patients who underwent MPI and coronary angiography between 2016 and 2018 at the Birjand Nuclear Medicine Center. Diagnostic performance criteria were calculated using angiography as the gold standard. Required data were extracted from patients' medical records using a checklist. After collection, the data were entered into SPSS software. Statistical analyses were performed using the Chi-square and Mann-Whitney tests at a significance level of 0.05. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were also calculated.
Results: The mean age of participants was 57.9 ± 10.9 years. MPI demonstrated a sensitivity of 33.33% to 51.85%, specificity of 88.71% to 97.01%, positive predictive value of 60% to 80%, and a positive likelihood ratio of 4.59 to 11.17.
Conclusion: MPI has moderate sensitivity but high specificity and positive predictive value, supporting its use as a non-invasive diagnostic tool for CAD, particularly when combined with other diagnostic methods.
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