Automated myocardial perfusion imaging improves MACE risk stratification
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Adding quantitative analysis from automated myocardial perfusion imaging to visual reading improved risk stratification for prediction of major adverse cardiac events, according to new data from the REFINE SPECT registry.
The researchers analyzed 19,495 patients from the REFINE SPECT registry (mean age, 64 years; 56% men) who underwent stress Tc-99m-labeled single-photon emission CT myocardial perfusion imaging.
Visual, automated assessment
All patients had perfusion abnormalities assessed visually, stratified by normal, probably normal, equivocal or abnormal; and stress total perfusion deficit quantified automatically, stratified by 0%, > 0% to < 1%, 1% to < 3%, 3% to < 5%, 5% to 10% or > 10%. MACE was defined as death, nonfatal MI, unstable angina or revascularization after 90 days.
During 4.5 years of follow-up, 14.2% of patients experienced MACE, Yuka Otaki, MD, PhD, project scientist in the division of nuclear medicine at Cedars-Sinai Medical Center, and colleagues wrote.
The rates of MACE increased with increasing severity of visual assessment (normal, 2%; probably normal, 3.2%; equivocal, 4.2%; abnormal, 7.4%; P < .001 for all), according to the researchers.
In addition, the rates of MACE increased with increasing category of stress total perfusion deficit, ranging from 1.3% in the category of 0% to 7.8% in the category of greater than 10% (P < .0001), Otaki and colleagues wrote.
The adjusted HR for MACE was elevated in the moderate-risk categories compared with the lowest-risk categories (adjusted HR for equivocal vs. normal = 1.56; 95% CI, 1.37-1.78; aHR for total perfusion deficit 3% to < 5% vs. 0% = 1.74; 95% CI, 1.41-2.14; P < .001 for all).
Among patients classified as normal on visual assessment, MACE rates were 1.3% in those with total perfusion deficit 0% but 3.4% in those with total perfusion deficit of at least 5% (P < .0001), according to the researchers.
“Importantly, quantitative analysis further stratified risk in a significant number of patients with normal visual perfusion assessment or a summed stress score of 0,” Otaki and colleagues wrote.
Combined approach beneficial
In a related editorial, Todd D. Miller, MD, professor of medicine at Mayo Clinic, and Michael K. O’Connor, PhD, consultant in the department of radiology and professor of medical physics at Mayo Clinic, wrote that “the authors demonstrated that both visual analysis and quantitative assessment individually provide accurate, meaningful risk stratification using the newer ultrafast camera imaging systems,” noting that the accuracy of the visual analysis may be related to the highly experienced readers used in the study, so in laboratories with less experience, “quantitative assessment may be more accurate than visual image interpretation.”
They concluded that, “Perhaps the most interesting finding from this study is that the prognostic accuracy of neither approach was superior to the other, but both approaches combined were better than either one alone.” – by Erik Swain
Disclosures: Otaki, Miller and O’Connor report no relevant financial disclosures. Please see the study for all other authors’ relevant financial disclosures.
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