Maffeis C, Dondi F, Ribichini FL, Giubbini R, Gimelli A. Clinical Application of Myocardial Perfusion SPECT in Patients with Suspected or Known Coronary Artery Disease. What Role in the Multimodality Imaging Era?
Rev Cardiovasc Med 2023;
24:48. [PMID:
39077399 PMCID:
PMC11273120 DOI:
10.31083/j.rcm2402048]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 12/30/2022] [Accepted: 01/03/2023] [Indexed: 07/31/2024] Open
Abstract
Myocardial perfusion single photon emission computed tomography (SPECT) is widely used in assessing coronary artery disease (CAD) owing to its proven efficacy in extensive clinical experience. Like other functional tests, myocardial SPECT is recommended for the diagnosis of obstructive CAD, risk stratification assessment, and treatment decision making. Besides quantifying left ventricular volume, global and regional function by electrocardiography (ECG)-gated acquisition, myocardial SPECT can identify myocardial ischemia, scars, stunning, and viable hibernating myocardium. It provides comprehensive functional data across the spectrum of CAD and a cost-effective strategy in patients with intermediate pre-test probability of CAD or with a history of ischemic cardiomyopathy. With ongoing advances in cardiovascular prevention and risk factor management many patients referred for testing now have a low-to-intermediate probability of CAD. Besides, CAD has become a chronic condition resulting from novel therapeutic strategies. Against this background, approaches combining anatomical and functional tests in sequence or simultaneously include coronary artery calcium score integrated with perfusion imaging or fusion SPECT/coronary computed tomography angiography (CCTA). In this review we summarize current indications for myocardial perfusion SPECT and integration of SPECT with other imaging techniques to improve diagnostic performance, patient management, and outcome prediction in CAD.
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