Prognostic value of myocardial perfusion imaging in Iranian patients using total perfusion deficits: Comparison with semi-quantitative assessment

سال انتشار: 1401
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 326

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شناسه ملی سند علمی:

JR_IRJNM-30-2_004

تاریخ نمایه سازی: 8 تیر 1401

چکیده مقاله:

Introduction: Considering that quantitative methods are usually more reproducible with lower inter-observer variability, the purpose of this research was to compare the prognostic value of the two quantitative method with quantitative perfusion SPECT (QPS) software. Methods: This study was performed prospectively and included ۲۰۰ participants who were referred for myocardial perfusion imaging. These participants were selected by the convenience sampling method. All patients were followed up after one year. Patients were classified as those with and without major cardiac events, including cardiac death, non-fatal myocardial infarction, open-heart surgery, abnormal angiographic findings, and unstable angina.Results: There were ۶۲ male (۳۱.۰%) and ۱۳۸ female (۶۹.۰%) patients, ranging in age from ۳۰ to ۸۶ years. The results indicated that the major cardiac events were significantly higher in moderate and severe categories based on summed stress score (SSS) (P=۰.۰۲۴) and total perfusion deficit (TPDs) (P=۰.۰۰۲) scores. SSS score with TPDs score (P = ۰.۷۶۴), summed rest score (SRS) with TPDr score (P = ۰.۵۸۳) and SDS with ΔTPD (P = ۰.۱۱۸) were compatible for predicting major heart events within a year.Conclusion: Total perfusion deficits obtained from QPS software is a useful method for predicting major cardiac events in patients with suspected cardiovascular disease (CVD). Predictive ability of TPD was similar to that of the semi-quantitative method with an expert interpreter's help. Moreover, this method can be helpful for CAD diagnosis and therapeutic evaluation of patients.

کلیدواژه ها:

Myocardial perfusion imaging ، Total perfusion deficits ، Quantitative perfusion SPECT software

نویسندگان

Mahdi Haghighatafshar

Nuclear Medicine and Molecular Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

Banafsheh Sarmadi

Nuclear Medicine and Molecular Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

Hossein Akbarialiabad

Nuclear Medicine and Molecular Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

Fatemeh Shekoohi-Shooli

Department of Neuroscience, Imaging and Clinical Sciences, “G. d’Annunzio” University of Chieti-Pescara, Chieti, Italy

Tahereh Ghaedian

Nuclear Medicine and Molecular Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

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