Diagnostic performance of stress myocardial perfusion imaging for coronary artery disease: a systematic review and meta-analysis

Abstract

ObjectivesTo determine and compare the diagnostic performance of stress myocardial perfusion imaging (MPI) for the diagnosis of obstructive coronary artery disease (CAD), using conventional coronary angiography (CCA) as the reference standard.MethodsWe searched Medline and Embase for literature that evaluated stress MPI for the diagnosis of obstructive CAD using magnetic resonance imaging (MRI), contrast-enhanced echocardiography (ECHO), single-photon emission computed tomography (SPECT) and positron emission tomography (PET).ResultsAll pooled analyses were based on random effects models. Articles on MRI yielded a total of 2,970 patients from 28 studies, articles on ECHO yielded a sample size of 795 from 10 studies, articles on SPECT yielded 1,323 from 13 studies. For CAD defined as either at least 50 %, at least 70 % or at least 75 % lumen diameter reduction on CCA, the natural logarithms of the diagnostic odds ratio (lnDOR) for MRI (3.63; 95 % CI 3.26–4.00) was significantly higher compared to that of SPECT (2.76; 95 % CI 2.28–3.25; P = 0.006) and that of ECHO (2.83; 95 % CI 2.29–3.37; P = 0.02). There was no significant difference between the lnDOR of SPECT and ECHO (P = 0.52).ConclusionOur results suggest that MRI is superior for the diagnosis of obstructive CAD compared with ECHO and SPECT. ECHO and SPECT demonstrated similar diagnostic performance.Key Points• MRI can assess myocardial perfusion.• MR perfusion diagnoses coronary artery disease better than echocardiography or SPECT.• Echocardiography and SPECT have similar diagnostic performance.• MRI can save coronary artery disease patients from more invasive tests.• MRI and SPECT show evidence of publication bias, implying possible overestimation.Electronic supplementary materialThe online version of this article (doi:10.1007/s00330-012-2434-1) contains supplementary material, which is available to authorized users.

Stress Cardiac MRI in Women With Myocardial Infarction and Nonobstructive Coronary Artery Disease

“…[16][17][18][19]30,31 Adenosine stress perfusion CMR is highly sensitive, specific, and reproducible for identification of obstructive CAD and has been reported to be superior to other stress imaging methods for this purpose. [32][33][34][35][36][37][38] In the setting of stable, nonobstructive CAD, patients with proven microvascular disease based on invasive coronary reactivity testing had lower MPRI as compared with healthy controls. 39 In our study, when stress perfusion was abnormal in patients with LGE or T2+, abnormal perfusion was typically identified in the affected myocardial segments.…”

Cardiac Imaging Modalities in the Diagnosis of Coronary Artery Disease

“…Coronary CT angiography serves as an excellent anatomic gatekeeper as it has a very high negative predictive value, while stress perfusion cardiac MRI is a regarded as a physiologic gatekeeper. Stress perfusion cardiac MRI has been proved to be a robust and accurate diagnostic test for CAD when invasive coronary angiography is used as the reference standard [25][26][27][28]. Several systematic reviews and meta-analyses have shown that the sensitivity and specificity of stress perfusion MRI ranged from 89% to 91% and 76% to 81%, using invasive coronary angiography as the reference standard [26][27][28].…”

“…Stress perfusion cardiac MRI has been proved to be a robust and accurate diagnostic test for CAD when invasive coronary angiography is used as the reference standard [25][26][27][28]. Several systematic reviews and meta-analyses have shown that the sensitivity and specificity of stress perfusion MRI ranged from 89% to 91% and 76% to 81%, using invasive coronary angiography as the reference standard [26][27][28]. Desai and Jha recently conducted a meta-analysis of 12 studies regarding the cardiac stress perfusion MRI in the diagnosis of flow-limiting obstructive CAD using fractional flow reserve measured at invasive coronary angiography as the reference standard [29].…”

Letter to the editor re: “Diagnostic performance of stress myocardial perfusion imaging for coronary artery disease: a systematic review and meta-analysis”—unfair study selection in meta-analysis

“…

Dear Editor, I was disappointed to realise that in the recent meta-analysis published online ahead of print in your journal, entitled "Diagnostic performance of stress myocardial perfusion imaging for coronary artery disease: a systematic review and meta-analysis" by de Jong et al [1], the single numerically most relevant prospective diagnostic study in the contrast stress-echo field, which I co-authored [2], comprising 400 patients and published in 2010 (in time for being included), was not cited and its data not included in the meta-analysis; this is a relevant mistake, first made by the authors in the data selection process and then by the reviewers in accepting such severely incomplete data: inevitably this makes the meta-analysis results and conclusions deeply flawed.All inclusion/exclusion criteria, clearly stated in the methods section, are fulfilled by our above-mentioned study, and it could not be otherwise, since that is one of the few prospective and multicentre studies in the contrast stress-echocardiography field, conducted on patients with a previous clinical indication to angiography, so that verification bias is not an issue. Data regarding stress myocardial perfusion accuracy were easily available in numerical table format and readily at hand in our study.

…”

“…Dear Editor, I was disappointed to realise that in the recent meta-analysis published online ahead of print in your journal, entitled "Diagnostic performance of stress myocardial perfusion imaging for coronary artery disease: a systematic review and meta-analysis" by de Jong et al [1], the single numerically most relevant prospective diagnostic study in the contrast stress-echo field, which I co-authored [2], comprising 400 patients and published in 2010 (in time for being included), was not cited and its data not included in the meta-analysis; this is a relevant mistake, first made by the authors in the data selection process and then by the reviewers in accepting such severely incomplete data: inevitably this makes the meta-analysis results and conclusions deeply flawed.…”