Andrew Van Tosh1,2, J Jane Cao1, John R Votaw3, C David Cooke3, Christopher J Palestro4, Kenneth J Nichols5. 1. St. Francis Hospital, Roslyn, NY, USA. 2. Research Department, St. Francis Hospital, 100 Port Washington Blvd., Roslyn, NY, 11576-1348, USA. 3. Emory University, Atlanta, GA, USA. 4. Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA. 5. Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA. knichols@northwell.edu.
Abstract
BACKGROUND: We wished to document the prevalence and quantitative effects of compromised 82Rb PET data acquisitions on myocardial flow reserve (MFR). METHODS AND RESULTS: Data were analyzed retrospectively for 246 rest and regadenoson-stress studies of 123 patients evaluated for known or suspected CAD. An automated injector delivered pre-determined activities of 82Rb. Automated quality assurance algorithms identified technical problems for 7% (9/123) of patients. Stress data exhibited 2 instances of scanner saturation, 1 blood peak detection, 1 blood peak width, 1 gradual patient motion, and 2 abrupt patient motion problems. Rest data showed 1 instance of blood peak width and 2 abrupt patient motion problems. MFR was lower for patients with technical problems flagged by the quality assurance algorithms than those without technical problems (1.5 ± 0.5 versus 2.1 ± 0.7, P = 0.01), even though rest and stress ejection fraction, asynchrony and relative myocardial perfusion measures were similar for these two groups (P > 0.05), suggesting that MFR accuracy was adversely affected by technical errors. CONCLUSION: It is important to verify integrity of 82Rb data to ensure MFR computation quality.
BACKGROUND: We wished to document the prevalence and quantitative effects of compromised 82Rb PET data acquisitions on myocardial flow reserve (MFR). METHODS AND RESULTS: Data were analyzed retrospectively for 246 rest and regadenoson-stress studies of 123 patients evaluated for known or suspected CAD. An automated injector delivered pre-determined activities of 82Rb. Automated quality assurance algorithms identified technical problems for 7% (9/123) of patients. Stress data exhibited 2 instances of scanner saturation, 1 blood peak detection, 1 blood peak width, 1 gradual patient motion, and 2 abrupt patient motion problems. Rest data showed 1 instance of blood peak width and 2 abrupt patient motion problems. MFR was lower for patients with technical problems flagged by the quality assurance algorithms than those without technical problems (1.5 ± 0.5 versus 2.1 ± 0.7, P = 0.01), even though rest and stress ejection fraction, asynchrony and relative myocardial perfusion measures were similar for these two groups (P > 0.05), suggesting that MFR accuracy was adversely affected by technical errors. CONCLUSION: It is important to verify integrity of 82Rb data to ensure MFR computation quality.
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