ResearchMeta-analysis of the diagnostic performance of stress perfusion cardiovascular magnetic resonance for detection of coronary artery disease

Aim: Evaluation of the diagnostic accuracy of stress perfusion cardiovascular magnetic resonance for the diagnosis of significant obstructive coronary artery disease (CAD) through meta-analysis of the available data. Methodology: Original articles in any language published before July 2009 were selected from available databases (MEDLINE, Cochrane Library and BioMedCentral) using the combined search terms of magnetic resonance, perfusion, and coronary angiography; with the exploded term coronary artery disease. Statistical analysis was only performed on studies that: (1) used a [greater than or equal to] 1.5 Tesla MR scanner; (2) employed invasive coronary angiography as the reference standard for diagnosing significant obstructive CAD, defined as a [greater than or equal to] 50% diameter stenosis; and (3) provided sufficient data to permit analysis. Results: From the 263 citations identified, 55 relevant original articles were selected. Only 35 fulfilled all of the inclusion criteria, and of these 26 presented data on patient-based analysis. The overall patient-based analysis demonstrated a sensitivity of 89% (95% CI: 88-91%), and a specificity of 80% (95% CI: 78-83%). Adenosine stress perfusion CMR had better sensitivity than with dipyridamole (90% (88-92%) versus 86% (80-90%), P = 0.022), and a tendency to a better specificity (81% (78-84%) versus 77% (71-82%), P = 0.065). Conclusion: Stress perfusion CMR is highly sensitive for detection of CAD but its specificity remains moderate. Introduction Perfusion cardiovascular magnetic resonance (CMR) is an emerging technique for the detection of coronary artery disease (CAD). The technique is attractive because of its non-invasive nature and safe characteristics, and might potentially play a major role in future diagnosis and risk stratification guidelines for patients with suspected CAD. Several small studies have evaluated the diagnostic performance of stress perfusion CMR and some of those have been included in a previous meta-analysis [1]. In the current study we provide a comprehensive and contemporary meta-analysis of its diagnostic accuracy compared with an invasive coronary angiography (CA) used as a reference standard. Methods Search strategy Using the combined medical subject headings (MeSH) of magnetic resonance, perfusion, and coronary angiography, with the exploded terms coronary artery disease; the MEDLINE, Cochrane Library and BioMedCentral databases were searched independently by two investigators (MH, GF) for all publications, in any language, before July 2009. In addition, the published reference lists of these articles were systematically searched. Study eligibility The search results were collated by the same two investigators (MH, GF), and duplicate or overlapping papers removed. Studies were eligible if: [1] stress perfusion CMR was used as a diagnostic test for significant obstructive CAD; [2] conventional invasive CA was used as the reference standard for diagnosing significant obstructive CAD, defined as a ≥50% diameter stenosis; and [3] the absolute numbers of true positive (TP), false positive * Correspondence: hamon-mi@chu-caen.fr 1 Department of Radiology, University Hospital of Caen, France Full list of author information is available at the end of the article © 2010 Hamon et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Hamon et al. Journal of Cardiovascular Magnetic Resonance 2010, 12:29 http://www.jcmr-online.com/content/12/1/29 Page 2 of 10 (FP), true negative (TN), and false negative (FN) were reported, or could be derived. Studies were excluded if they were performed with a 0.5 or 1 Tesla MR scanner, if they included less than 10 patients, and if only abstracts from scientific meetings were published as the data provided may either be not sufficiently detailed or finalized. Any disagreements on eligibility were resolved by discussion and consensus between the two investigators. Data extraction and quality assessment Data extraction was performed independently by the two investigators (MH, GF) for each study. The following fields were recorded: study population size; gender distribution; mean age and standard deviation; number of patients with documented CAD; prevalence of CAD; relative timing of the two imaging procedures; the degree of blinding in interpretation of test results (both to the patient's clinical context and the results of the other imaging modality); type and brand of MR machine used; the type of perfusion stressor (adenosine, nicorandil, dipyridamole), and the number of side effects; the dose and injection rate of Gadolinium administrated; and the modality of MR image analysis (visual, or semi-quantitative). Any discrepancies were resolved by discussion and consensus between the two investigators. Where available, data was recorded separately at the level of coronary territories and coronary arteries. The study quality conformed to the Quality Assessment of Studies of Diagnostic Accuracy included in Systematic Reviews guidelines [2]. In one study, for which patients were evaluated both with 1.5 and 3T CMR, we used 1.5 T data in the metaanalysis. For the studies where analysis was performed with both 50% and 70% coronary stenosis definitions, we included results with the 70% definition in the pooled reported sensitivity and specificity. Data synthesis and statistical analysis Data analysis was performed at the level of the patient, the coronary territory and the coronary artery. Sensitivity and specificity were calculated using the TP, TN, FP, and FN rates [3,4]. From these were calculated the likelihood ratios, which express how much the odds of significant obstructive CAD change in the presence of either an abnormal stress perfusion CMR (positive likelihood ratio: PLR = sensitivity/(1specificity)), or a normal stress perfusion CMR (negative likelihood ratio: NLR = (1sensitivity)/specificity). Finally, the ratio of the PLR to the NLR was used to calculate the diagnostic odds ratio (DOR), which estimates how much greater the odds of having significant obstructive CAD are for patients with a positive test result compared with a negative one. All these measures of diagnostic accuracy were calculated for each individual study and reported as point estimates with 95% confidence intervals. They were then combined using a random-effects model and each point estimate weighted by the inverse of the sum of its variance and the between-study variance. We also assessed between-study statistical heterogeneity using the Cochran Q chi-square tests (cut off for statistical significance P ≤ .10). Since diagnostic parameters are, by definition, interdependent, independent weighting may sometimes give spurious results and provide biased estimates; to overcome the interdependence problem, we computed the weighted symmetric summary receiver operating characteristic curve, with pertinent areas under the curve, using the Moses-Shapiro-Littenberg method [5-7]. All statistical calculations were performed with SPSS 14.0 (SPSS, Chicago, IL) and Meta-DiSc [8], and significance testing was at the two-tailed 0.05 level [9]. Results Database and literature searches retrieved 263 citations, amongst which 55 relevant publications were identified (Figure 1). Further scrutiny led 20 papers to be rejected either because of overlapping data, or exclusion criteria were met (employed 0.5 or 1 T CMR, or inclusion criteria were absent (impossible to find or calculate absolute figures from presented data). Therefore, 35 studies were finally included in the meta-analysis [10-44], all of which had been published between 2000 and 2009. Study and population characteristics are summarized in Table 1, and the results of the pooled analyses are summarized in Table 2. Dose of contrast Gadolinium administrated range from 0.025 to 0.15 mmol/kg, with an injection rate varying from 3 to 10 mL/s. Quality assessments for all included studies are shown in Table 3. The 35 papers eligible for the analyses comprised 2,456 patients, and of the 2,154 patients for whom gender and the age were speciFigure 1 Flow diagram of the reviewing process. 263 citations retrieved from database and literature searches 55 relevant publications identified 35 studies included in the metaanalysis 208 irrelevant citations excluded 20 papers rejected according to inclusion / exclusion criteria H am on e t a l. Jo ur na l o f C ar di ov as cu la r M ag ne tic R es on an ce 2 01 0, 1 2: 29 ht tp :// w w w .jc m ron lin e. co m /c on te nt /1 2/ 1/ 29 Pa ge 3 o f 1 0 Table 1: Characteristics of included studies Authors Year Brand Tesla Patients (n) Excluded (n) Male (%) Mean Age (SD) Prevalence (% per patient) Coronary Stenosis (%) Stressor* Side Effects ** (n) Data assessment Al Saadi, (10) 2000 Philips 1.5 40 6 100 ≥ 75 D 0 1/2 Quantitative Schwitter (11) 2001 GE 1.5 48 1 83 59(-) 79 ≥ 50 D 0 1/2 Quantitative Ibrahim, (12) 2002 Philips 1.5 25 0 76 63(13) 100 > 75 A 1/2 Quantitative Sensky (13) 2002 Siemens 1.5 30 0 90 62(-) 100 > 50 A 0 Visual Chiu, (14) 2003 Siemens 1.5 13 0 54 68(-) 92 > 50 A 0 Visual Doyle (15) 2003 Philips 1.5 229 45 0 59(11) 14 ≥ 70 D 1/2 Quantitative Ishida (16) 2003 GE 1.5 104 0 78 66(12) 74 > 70 D 0 Visual Nagel (17) 2003 Philips 1.5 90 6 81 63(8) 51 ≥ 75 A 2 1/2 Quantitative Bunce (18) 2004 Picker 1.5 35 0 77 56(12) 49 ≥ 50 A 0 1/2 Quantitative Giang (19) 2004 GE 1.5 94 14 69 58(-) 65 ≥ 50 A 0 1/2 Quantitative Kawase (20) 2004 Philips 1.5 50 0 58 66(12) 66 ≥ 70 N 0 Visual Paetsch (21) 2004 Philips 1.5 79 0 66 61(9) 67 > 50 A 0 Visual Plein (22) 2004 Philips 1.5 72 4 79 57(11) 82 ≥ 70 A 1 Visual Takase (23) 2004 GE 1.5 102 83 66(9) 74 > 50 D Visual Thiele (24) 2004 Philips 1.5 20 0 64(8) 90 ≥ 70 A 0 1/2 Quantitati