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

1532-429X-12-29 1532-429X Research Meta-analysis of the diagnostic performance of stress perfusion cardiovascular magnetic resonance for detection of coronary artery disease Hamon Michèle hamon-mi@chu-caen.fr Fau Georges georgesfau@hotmail.com Née Guillaume guillaume.nee@greyc.ensicaen.fr Ehtisham Javed jehtisham@nhs.net Morello Rémy morello-r@chu-caen.fr Hamon Martial hamon-m@chu-caen.fr

Department of Radiology, University Hospital of Caen, France

INSERM 919, Cyceron, Caen, France

Greyc Laboratory, CNRS UMR 6072, Caen, France

Department of Cardiology, University Hospital of Caen, France

Department of Statistics, University Hospital of Caen, France

INSERM 744, Institut Pasteur de Lille, France

Journal of Cardiovascular Magnetic Resonance 1532-429X 2010 12 1 29 http://www.jcmr-online.com/content/12/1/29 10.1186/1532-429X-12-29 20482819 18 9 2009 19 5 2010 19 5 2010 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.

Abstract

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 (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 meta-analysis. 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 34. 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/(1- specificity)), or a normal stress perfusion CMR (negative likelihood ratio: NLR = (1- sensitivity)/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 567. 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 1011121314151617181920212223242526272829303132333435363738394041424344, 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 specified, 1,481 were males (68.7%) and the mean age was 61.3 years.

Figure 1

Flow diagram of the reviewing process

Flow diagram of the reviewing process.

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

100

≥ 75

1/2 Quantitative

Schwitter (11)

2001

1.5

59(-)

≥ 50

1/2 Quantitative

Ibrahim, (12)

2002

Philips

1.5

63(13)

100

> 75

1/2 Quantitative

Sensky (13)

2002

Siemens

1.5

62(-)

100

> 50

Visual

Chiu, (14)

2003

Siemens

1.5

68(-)

> 50

Visual

Doyle (15)

2003

Philips

1.5

229

59(11)

≥ 70

1/2 Quantitative

Ishida (16)

2003

1.5

104

66(12)

> 70

Visual

Nagel (17)

2003

Philips

1.5

63(8)

≥ 75

1/2 Quantitative

Bunce (18)

2004

Picker

1.5

56(12)

≥ 50

1/2 Quantitative

Giang (19)

2004

1.5

58(-)

≥ 50

1/2 Quantitative

Kawase (20)

2004

Philips

1.5

66(12)

≥ 70

Visual

Paetsch (21)

2004

Philips

1.5

61(9)

> 50

Visual

Plein (22)

2004

Philips

1.5

57(11)

≥ 70

Visual

Takase (23)

2004

1.5

102

66(9)

> 50

Visual

Thiele (24)

2004

Philips

1.5

64(8)

≥ 70

1/2 Quantitative

Okuda (25)

2005

1.5

60(-)

≥ 75

Visual

Plein (26)

2005

Philips

1.5

58(-)

> 70

1/2 Quantitative

Sakuma (27)

2005

Siemens

1.5

65(9)

> 70

Visual

Cury (28)

2006

1.5

63(5)

≥ 70

Visual

Klem (29)

2006

Siemens

1.5

100

58(11)

>50/≥ 70

Visual

Pilz (30)

2006

1.5

176

62(12)

> 70

Visual

Rieber (31)

2006

Siemens

1.5

61(8)

> 50

1/2 Quantitative

Cheng (32)

2007

Siemens

1.5/3

64(8)

≥ 50

Visual

Costa (33)

2007

Siemens

1.5

65(11)

> 50/> 70

1/2 Quantitative

Greenwood (34)

2007

Philips

1.5

55(-)

≥ 70

Visual

Kühl (35)

2007

Philips

1.5

64(13)

100

≥ 50

1/2 Quantitative

Merkle (36)

2007

Philips

1.5

228

61(11)

> 50/> 70

Visual

Seeger (37)

2007

Siemens

1.5

65(9)

> 70

1/2 Quantitative

Gebker (38)

2008

Philips

101

62(8)

≥ 50

Visual

Meyer (39)

2008

Philips

59(10)

≥ 70

Visual

Pilz (40)

2008

1.5

66(12)

≥ 70

Visual

Klein (41)

2008

Philips

1.5

60(10)

≥ 50

Visual

Klem (42)

2008

Siemens

1.5

147

63(11)

≥ 70

Visual

Thomas (43)

2008

Philips

≥ 50

Visual

Burgstahler (44)

2008

Philips

1.5

68(12)

≥ 70

Visual

* Stressor: A (Adenosine); D (Dypirydamole); N (Nicorandil) ** n: significant side effects, which led to stop the MR exam.

Table 2

Pooled summary results

Studies

N studies

Sensitivity

Specificity

Positive Likelihood ratio

Negative likelihood ratio

Diagnostic odds ratio

Per Patient analysis (all)

2125 Patients

89% (88-91)

80% (78-83)

4.18 (3.31-5.27)

0.15 (0.11-0.20)

33.65 (22.09-51.27)

Adenosine stressor

1658 Patients

90% (88-92)

81% (78-84)

4.47 (3.39-5.88)

0.14 (0.11-0.18)

37.17 (25.16-54.91)

Dipyridamole stressor

417 Patients

86% (80-90)

77% (71-82)

2.97 (2.16-4.09)

0.20 (0.09-0.45)

17.03 (5.56 - 52.18)

Visual assessment

1624 Patients

91% (89-93)

79% (76-83)

4.08 (3.15-5.29)

0.13 (0.10-0.17)

36.79 (23.90-56.63)

Semi-quant. assessment

501 Patients

82%(77-87)

82% (77-86)

4.88 (2.62-9.09)

0.22 (0.13-0.37)

25.44 (8.90-72.70)

Per Territory analysis

2709 Territories

82% (79-84)

84% (82-85)

4.90(3.66-6.55)

0.23 (0.20-0.27)

23.23 (18.33-29.45)

Per Artery analysis

LAD

662 Arteries

83%(78-88)

83%(79-86)

4.37(2.96-6.44)

0.22 (0.16-0.31)

21.42 (10.94-41.94)

672 Arteries

76%(70-82)

87%(84-90)

5.74(3.94-8.35)

0.30 (0.23-0.38)

22.25 (14.09-35.10)

RCA

657 Arteries

78%(71-84)

87% (83-90)

5.58 (3.74-8.32)

0.29 (0.21-0.38)

23.07 (14.55-36.57)

Table 3

Quality assessment (QUADAS)

Study

Item 1

Item 2

Item 3

Item 4

Item 5

Item 6

Item 7

Item 8

Item 9

Item 10

Item 11

Item 12

Item 13

Item 14

Al Saadi, 2000 (10)

yes

unclear

yes

unclear

yes

Schwitter, 2001 (11)

yes

Yes

yes

Ibrahim, 2002 (12)

yes

unclear

yes

Yes

unclear

yes

Sensky, 2002 (13)

yes

unclear

yes

Yes

yes

Chiu, 2003 (14)

yes

Yes

yes

Doyle, 2003 (15)

yes

unclear

yes

Yes

yes

Ishida,2003 (16)

yes

Yes

yes

Nagel, 2003 (17)

yes

Yes

yes

Bunce, 2004 (18)

yes

Yes

yes

Giang, 2004 (19)

yes

Yes

yes

Kawase, 2004 (20)

yes

Yes

yes

Paetsch, 2004 (21)

yes

unclear

yes

Yes

yes

unclear

Plein, 2004 (22)

yes

Yes

yes

Takase, 2004 (23)

yes

Yes

yes

unclear

Thiele,2004 (24)

yes

Yes

yes

Okuda,2005 (25)

yes

Yes

yes

Plein, 2005 (26)

yes

Yes

yes

Sakuma,2005 (27)

yes

Yes

yes

Cury, 2006 (28)

yes

Yes

yes

Klem, 2006 (29)

yes

Yes

yes

Pliz, 2006 (30)

yes

unclear

yes

Yes

yes

Rieber, 2006 (31)

yes

Yes

yes

Cheng, 2007 (32)

yes

Yes

yes

Costa,2007 (33)

yes

Yes

yes

Greenwood, 2007 (34)

yes

Yes

yes

Kuhl, 2007 (35)

yes

Yes

yes

Merkle, 2007 (36)

yes

Yes

yes

Seeger, 2007 (37)

yes

Yes

yes

Gebker, 2008 (38)

yes

Yes

yes

Meyer, 2008 (39)

yes

Yes

yes

unclear

Pilz, 2008 (40)

yes

Yes

yes

Klein,2008 (41)

yes

Yes

yes

Klem, 2008 (42)

yes

Yes

yes

Thomas, 2008 (43)

yes

unclear

yes

Yes

yes

unclear

Burgstahler,2008 (44)

yes

unclear

yes

Yes

unclear

yes

Item 1: was the spectrum of patients representative of the patients who will receive the test in practice?; Item 2: were selection criteria clearly described?; Item 3: is the reference standard likely to correctly classify the target condition?; Item 4: is the time period between reference and standard and index test short enough to be reasonably sure that the target condition did not change between the two tests?; Item 5: did the whole sample or a random selection of the sample, receive verification using a reference standard of diagnosis?; Item 6: did patients receive the same reference standard regardless of the index test results?; Item 7: was the reference standard independent of the index test (i.e. the index test did not form part of the reference standard); Item 8: was the execution of the index test described in the sufficient detail to permit replication of the test; Item 9: was the execution of the reference standard described in the sufficient detail to permit its replication?; Item 10: were the index test results interpreted without knowledge of the results of the reference standard?; Item 11: were the reference standard results interpreted without knowledge of the results of the index test?; Item 12: were the same clinical data available when test results were interpreted as would be available when the test is used in practice?; Item 13: were uninterpretable/intermediate test results reported?; Item 14: were withdrawals from the study explained.

Diagnostic performance of stress perfusion CMR: Patient-based analysis

Overall per-patient analysis results pooled from 26 studies (2,125 patients) demonstrated a sensitivity of 89% (95% CI: 88-91%), a specificity of 80% (95% CI: 78-83%), a PLR of 4.18 (3.31-5.27), a NLR of 0.15 (95% CI: 0.11-0.20), a DOR of 33.65 (95% CI: 22.09-51.27), and an AUC of 0.92 (Figures 2, 3, 4, 5, 6). Statistical heterogeneity was observed for all relevant diagnostic performance measures. The per-patient prevalence of CAD was 57% (1,205 of 2,125 patients).

Figure 2

Forest plot of patient-level sensitivity of stress perfusion CMR, compared with coronary angiography

Forest plot of patient-level sensitivity of stress perfusion CMR, compared with coronary angiography..

Figure 3

Forest plot of patient-level specificity of stress perfusion CMR, compared with coronary angiography

Forest plot of patient-level specificity of stress perfusion CMR, compared with coronary angiography.

Figure 4

Forest plot of patient-level positive likelihood ratio of stress perfusion CMR, compared with coronary angiography

Forest plot of patient-level positive likelihood ratio of stress perfusion CMR, compared with coronary angiography.

Figure 5

Forest plot of patient-level negative likelihood ratio of stress perfusion CMR, compared with coronary angiography

Forest plot of patient-level negative likelihood ratio of stress perfusion CMR, compared with coronary angiography.

Figure 6

Plot of symmetric summary receiver operating curve characteristic of stress perfusion CMR, compared with coronary angiography

Plot of symmetric summary receiver operating curve characteristic of stress perfusion CMR, compared with coronary angiography. The receiver operator characteristic curve provides a graphical display of diagnostic accuracy by plotting 1-specificity in the horizontal axis and sensitivity in the vertical axis. The pertinent area under the curve (AUC) and the Q* statistic (the point where sensitivity and specificity are maximized), both with standard errors (SE), are also included.

With adenosine as the stressor (20 studies, 1,658 patients) the results were: a sensitivity of 90% (88-92%), a specificity of 81% (78-84%), a PLR of 4.47 (3.39-5.88), a NLR of 0.14 (0.11-0.18), a DOR of 37.17 (25.16-54.91), and an AUC of 0.93. Statistical heterogeneity was observed for all relevant diagnostic performance measures. With dipyridamole as the stressor (5 studies, 417 patients), the results were: a sensitivity of 86% (80-90%), a specificity of 77% (71-82%), a PLR of 2.97 (2.16-4.09), a NLR of 0.20 (0.09-0.45), a DOR of 17.03 (5.56-52.18), and an AUC of 0.84. Statistical heterogeneity was observed for all relevant diagnostic performance measures, except specificity and positive likelihood ratio. ROC curves for stress perfusion CMR performed with adenosine or dipyridamole are shown in Figure 7.

Figure 7

Plots of symmetric summary receiver operating curve characteristic of stress perfusion CMR, compared with coronary angiography for adenosine and dipyridamole stressors

Plots of symmetric summary receiver operating curve characteristic of stress perfusion CMR, compared with coronary angiography for adenosine and dipyridamole stressors.

A sensitivity analysis was carried out based on the equipment used (3 Tesla, and 1.5 Tesla MRI). For 3 Tesla (4 studies, 282 patients), results were: a sensitivity of 92% (87-95%), a specificity of 78% (69-85%), a PLR of 3.96 (2.78-5.63), a NLR of 0.12 (0.07-0.20), and a DOR of 35.74 (17.13-74.53). For 1.5 Tesla (23 studies, 1,904 patients), results were: a sensitivity 89% (87-91%), a specificity of 80% (78-83%), a PLR of 4.26 (3.26-5.55), a NLR of 0.15 (0.11-0.20), and a DOR of 34.25 (21.26-55.17).

Diagnostic performance of stress perfusion CMR: Coronary territory and coronary artery-based analysis

Per-territory results, pooled from 17 studies corresponding to 2,709 coronary territories, demonstrated a sensitivity of 82% (79-84%), a specificity of 84% (82-85%), a PLR of 4.90 (3.66-6.55), a NLR of 0.23 (0.20-0.27), and a DOR of 23.23 (18.33-29.45). At the territory level heterogeneity was significant for all relevant diagnostic performance measures except sensitivity, negative likelihood ratio and diagnostic odd ratios.

Per-artery analysis pooled 8 datasets and demonstrated for left anterior descending artery (LAD), circumflex artery (CX) and right coronary artery (RCA), respectively, sensitivities of 83%, 76% and 78% and specificities of 83%, 87%, and 87%. Statistical heterogeneity was observed for all the performance measurements except sensitivity and negative likelihood ratio for LAD and CX, and diagnostic odds ratio for CX.

Discussion

This meta-analysis showed stress perfusion CMR to have a high sensitivity (89%) and a moderate specificity (80%) at patient level for the diagnosis of significant obstructive CAD in patients with high prevalence of CAD (57%). We included twelve more studies (on stress perfusion CMR) than the previous meta-analysis by Nandalur et al. 1, which showed a similar diagnostic performance with a pooled sensitivity and specificity of respectively 90% and 81% from 14 perfusion studies. A high false positive rate could have driven the relatively low specificity, and may be due to perfusion defects caused by: 1 dark rim artefacts, the hypo-intensities along the endocardial border of the left ventricular myocardium seen during first-pass transit of a MR contrast medium, thought to be due to a combination of the gadolinium bolus, motion and resolution 45; 2 the presence of microvascular disease; and 3 spontaneous or therapeutic re-opening of a coronary artery supplying an area of myocardial infarction that has persistent microvascular obstruction 2832.

Alternatively, because CA detects luminal morphology rather than the functional significance of a stenosis, a false positive CMR results may in fact represent a 'false negative' angiogram in the context of angiographically 'invisible' small vessel disease capable of inducing subendocardial ischemia 40. This potential source of error could be minimised if the hemodynamic significance of an epicardial coronary artery stenosis were to be determined by the measurement of the fractional flow reserve (FFR) during CA. If validated, this may represent a better reference standard than CA alone. However, although three studies found there to be a good correlation between the performance of stress perfusion CMR and CA with FFR measurement 313335, sufficient data was not present to evaluate its accuracy in this study.

Another point to outline is that for some studies 111719, different decision thresholds to diagnose perfusion CMR as abnormal were appraised: for these studies, the reported sensitivity and specificity could be considered as optimistic because the end points was chosen retrospectively.

In addition, there was a large range of contrast doses used in the individual studies, with the dose of gadolinium administered in the included studies varying by 6-fold, with dose ranging from 0.025 to 0.15 mmole/kg. Although currently there is no consensus regarding the optimal dose and injection rates for perfusion CMR, two multicenter dose-ranging studies have evaluated the impact of contrast dose on the performance of perfusion CMR using a visual analysis 4647. In the first, Wolff et al. considered a low dose of 0.05 mmol/kg to be at least as efficacious as any higher dose, and hypothesized that higher doses preformed less well because of the increased likelihood and intensity of artefacts at these doses 46. However, in the MR-Impact study, Schwitter et al. found better results were obtained using 0.1 mmol/kg 47.

In this meta-analysis, 18 studies were based on stress perfusion CMR alone 101112131517192021242631323335373944, whilst the other 17 included a multi-component examination (cine and/or late gadolinium enhancement (LGE) and/or coronary angiography and/or stress tagging) 1416182223252728293034363840414243. In their studies, Plein 22, Cury 28 and Klem 29 evaluated the differences in accuracy based on the sequences evaluated and found that all studies increased accuracy when using a combined analysis. In his study, Klem reported increased specificity (moving from 58% to 87%) when using an algorithm interpretation (including perfusion, cine and LGE).

Having access to data from different sequences (cine, perfusion, and LGE) is especially useful when one component shows a borderline result or is affected by image artefacts. Most of the authors have argued that rest perfusion is an important component because, in combination with late enhancement CMR, it can help distinguish true defects from artefacts on the stress perfusion images.

The fact that the meta-analysis demonstrated a low NLR for stress perfusion CMR suggests that a negative test result may in fact be more clinically useful. This is in keeping with several reports, in different clinical settings, of improved prognosis associated with a normal adenosine stress perfusion CMR scan 484950. This meta-analysis also demonstrated adenosine to be superior to dipyridamole as the vasodilating stressor agent. Adenosine may also be safer, with minor side effects of flushing and headache being reported to occur more frequently that any severe adverse effects 51. Its shorter half life (< 10 s) is an added advantage. Moreover, adenosine has documented safety in the context of non-ST elevation acute coronary syndromes (in a study of 72 patients only one demonstrated intolerance), and in recent ST elevation myocardial infarction 142234.

From this analysis, visual assessment of stress perfusion CMR provided a higher sensitivity but a lower specificity than semi-quantitative assessment. Currently there is no consensus on the superiority of visual over semi-quantitative assessment, or on which method of semi-quantitative assessment should be used. However, the drawbacks of semi-quantitative assessment are that it is more time-consuming, hence not ideal for day-to-day clinical purposes, and the lack of any homogeneous post-processing protocols. Therefore, visual assessment is currently the method most often used in routine clinical practice.

Only 4 studies were performed using 3T CMR, which provides improved resolution 32383943. Enhanced sensitivity has been reported 32 and attributed to the higher signal-to-noise and contrast-to-noise ratios permitting improved detection of endocardial perfusion defects. Although most authors argue that the increased prevalence of dark rim artefacts at these higher field strengths (ranging from 8 up to 82%) does not hamper myocardial perfusion analysis 323943, Gebker disagrees and suggests they could limit specificity by increasing false positive rates 38. In this analysis, 3T CMR was also found to have a decreased specificity, indicating that higher false positive rates may be a real problem. Further studies will be necessary if this controversy is to be resolved.

The results of the per- territory-based analysis showed the anticipated decrease in sensitivity and increase in specificity seen when moving from the level of the patient to that of the coronary territory. Among the 8 studies that performed a coronary-artery level analysis, stress perfusion CMR had a higher sensitivity for detection of significant coronary disease in the LAD artery, compared with the CX and RCA. A possible explanation for this finding may have been the use of a surface radiofrequency coil, which led to lower signal intensities in the more distant inferior and lateral segments.

Study limitations

Although conventional CA is the established technique for diagnosing significant CAD in routine clinical practice, it remains an imperfect reference standard due to its inability to evaluate the hemodynamic significance of a stenosis.

Substantial inter-study heterogeneity in multiple performance characteristics were observed. Therefore, the pooled performance indices and their interpretation have to be treated with a degree of caution, even though the random-effects model used throughout the analysis should have compensated for this. The observed heterogeneity may have been due to variations in: (i) the image acquisition technique (MR scanner manufacturer, 1.5T or 3T field strengths, pulse sequence, number of slices, contrast dose and rate of infusion); (ii) the interpretation method (visual or semi-quantitative, post-processing techniques); (iii) the patient selection criteria (exclusion or inclusion of patients with prior myocardial infarction, patient populations with differing prevalence of CAD); and (iv) in the definition of significant obstructive CAD (50% or 70%). We noticed, as expected, that studies which performed analysis for 50% and for 70% coronary artery stenosis thresholds, reported an increased sensitivity and a decreased specificity when moving thresholds from 50% to 70% 293336.

These general limitations of stress perfusion CMR could be addressed in future multi-centre studies if standardized imaging protocols, post-processing techniques and patient selection criteria are employed.

Conclusion

Stress Perfusion CMR has a high sensitivity and moderate specificity for the diagnosis of significant obstructive CAD compared with CA in patients with a high prevalence of the disease.

Future technical developments that increase spatial and temporal resolution whilst reducing artefacts may further improve the diagnostic performance of stress perfusion CMR, and in particular improve its specificity 32. Currently, however, the low NLR makes stress perfusion CMR particularly accurate and useful in ruling out significant CAD.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

MiH conceived of the study, and participated in its design and coordination and drafted the manuscript. GF, MaH participated in its design and coordination and helped to draft the manuscript. GN, JE, helped to draft the manuscript. RM participated in the design of the study and performed the statistical analysis. All authors read and approved the final manuscript.

Diagnostic performance of stress cardiac magnetic resonance imaging in the detection of coronary artery disease Nandalur KR Dwamena BA Choudhri AF Nandalur MR Carlos RC J Am Coll Cardiol 2007 50 1343 53 10.1016/j.jacc.2007.06.030 17903634 The development of QUADAS: a tool for the quality assessment of studies of diagnostic accuracy included in systematic reviews Whiting P Rutjes AWS Reitsma JB Bossuyt PMM Kleijnen J BMC Med Res Methodol 2003 3 25 10.1186/1471-2288-3-25 305345 14606960 The diagnostic odds ratio: a single indicator of test performance Glas AS Lijmer JG Prins MH Bonsel GJ Bossuyt PM J Clin Epidemio 2003 56 1129 1135 10.1016/S0895-4356(03)00177-X Conducting systematic reviews of diagnostic studies: didactic guidelines Devillé WL Buntinx F Bouter LM Montori VM de Vet HC Windt van der DA Bezemer PD BMC Med Res Methodol 2002 2 9 10.1186/1471-2288-2-9 117243 12097142 Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations Moses LE Shapiro D Littenberg B Stat Med 1993 12 1293 1316 8210827 Properties of the summary receiver operating characteristic (SROC) curve for diagnostic test data Walter SD Stat Med 2002 21 1237 1256 10.1002/sim.1099 12111876 Exploring sources of heterogeneity in systematic reviews of diagnostic tests Lijmer JG Bossuyt PM Heisterkamp SH Stat Med 2002 21 1525 1537 10.1002/sim.1185 12111918 Meta-DiSc for Windows: A Software package for the Meta-analysis of Diagnostic Tests Zamora J Muriel A Abraira V XI Cochrane Colloquium. Barcelona 2003 http://www.hrc.es/investigacion/metadisc.html Evidence-based practice in radiology: step 3 and 4-appraise and apply systematic reviews and meta-analysis Halligan S Altman DG Radiology 2007 243 13 27 10.1148/radiol.2431051823 17392245 Noninvasive detection of myocardial ischemia from perfusion reserve based on cardiovascular magnetic resonance Al-Saadi N Nagel E Gross M Bornstedt A Schnackenburg B Klein C Klimek W Oswald H Fleck E Circulation 2000 101 1379 1383 10736280 Assessment of myocardial perfusion in coronary artery disease by magnetic resonance: a comparison with positron emission tomography and coronary angiography Schwitter J Nanz D Kneifel S Bertschinger K Büchi M Knüsel PR Marincek B Lüscher TF von Schulthess GK Circulation 2001 103 2230 2235 11342469 Assessment of coronary flow reserve: comparison between contrast-enhanced magnetic resonance imaging and positron emission tomography Ibrahim T Nekolla SG Schreiber K Odaka K Volz S Mehilli J Güthlin M Delius W Schwaiger M J Am Coll Cardiol 2002 39 864 870 10.1016/S0735-1097(01)01829-0 11869854 Magnetic resonance perfusion imaging in patients with coronary artery disease: a qualitative approach Sensky PR Samani NJ Reek C Cherryman GR Int J Cardiovasc Imaging 2002 18 373 383 10.1023/A:1016057821005 12194678 Combined first-pass perfusion and viability study at MR imaging in patients with non-ST segment-elevation acute coronary syndromes: feasibility study Chiu CW So NM Lam WW Chan KY Sanderson JE Radiology 2003 226 717 722 10.1148/radiol.2263011902 12601212 The impact of myocardial flow reserve on the detection of coronary artery disease by perfusion imaging methods: an NHLBI WISE study Doyle M Fuisz A Kortright E Biederman RW Walsh EG Martin ET Tauxe L Rogers WJ Merz CN Pepine C Sharaf B Pohost GM J Cardiovasc Magn Reson 2003 5 475 485 10.1081/JCMR-120022263 12882078 Noninfarcted myocardium: correlation between dynamic first-pass contrast-enhanced myocardial MR imaging and quantitative coronary angiography Ishida N Sakuma H Motoyasu M Okinaka T Isaka N Nakano T Takeda K Radiology 2003 229 209 216 10.1148/radiol.2291021118 12944596 Magnetic resonance perfusion measurements for the noninvasive detection of coronary artery disease Nagel E Klein C Paetsch I Hettwer S Schnackenburg B Wegscheider K Fleck E Circulation 2003 108 432 437 10.1161/01.CIR.0000080915.35024.A9 12860910 Combined coronary and perfusion cardiovascular magnetic resonance for the assessment of coronary artery stenosis Bunce NH Reyes E Keegan J Bunce C Davies SW Lorenz CH Pennell DJ J Cardiovasc Magn Reson 2004 6 527 539 10.1081/JCMR-120030580 15137337 Detection of coronary artery disease by magnetic resonance myocardial perfusion imaging with various contrast medium doses: first European multi-centre experience Giang TH Nanz D Coulden R Friedrich M Graves M Al-Saadi N Lüscher TF von Schulthess GK Schwitter J Eur Heart J 2004 25 1657 1665 10.1016/j.ehj.2004.06.037 15351166 Assessment of coronary artery disease with nicorandil stress magnetic resonance imaging Kawase Y Nishimoto M Hato K Okajima K Yoshika J Osaka City Med 2004 50 87 94 Comparison of dobutamine stress magnetic resonance, adenosine stress magnetic resonance, and adenosine stress magnetic resonance perfusion Paetsch I Jahnke C Wahl A Gebker R Neuss M Fleck E Nagel E Circulation 2004 110 835 842 10.1161/01.CIR.0000138927.00357.FB 15289384 Assessment of non-ST-segment elevation acute coronary syndromes with cardiac magnetic resonance imaging Plein S Greewood JP Ridgway JP Cranny G Ball SG Sivanathan MU J Am Coll Cardiol 2004 44 2173 2181 10.1016/j.jacc.2004.08.056 15582315 Whole-heart dipyridamole stress first-pass myocardial perfusion MRI for the detection of coronary artery disease Takase B Nagata M Kihara T Kameyawa A Noya K Matsui T Ohsuzu F Ishihara M Kurita A Jpn Heart J 2004 45 475 486 10.1536/jhj.45.475 15240967 Color-encoded semiautomatic analysis of multi-slice first-pass magnetic resonance perfusion: comparison to tetrofosmin single photon emission computed tomography perfusion and X-ray angiography Thiele H Plein S Breeuwer M Ridgway JP Higgins D Thorley PJ Schuler G Sivananthan MU Int J Cardiovasc Imaging 2004 20 371 384 10.1023/B:CAIM.0000041938.45383.a4 15765860 Evaluation of ischemic heart disease on a 1.5 Tesla scanner: combined first-pass perfusion and viability study Okuda S Tanimoto A Satoh T Hashimoto J Shinmoto H Higuchi N Nozaki A Kuribayashi S Radiat Med 2005 23 230 235 16012398 Coronary artery disease: myocardial perfusion MR imaging with sensitivity encoding versus conventional angiography Plein S Radjenovic A Ridgway JP Barmby D Greenwood JP Ball SG Sivananthan MU Radiology 2005 235 423 430 10.1148/radiol.2352040454 15858084 Diagnostic accuracy of stress first-pass contrast-enhanced myocardial perfusion MRI compared with stress myocardial perfusion scintigraphy Sakuma H Suzawa N Ichikawa Y Makino K Hirano T Kitagawa K Takeda K AJR Am J Roentgenol 2005 185 95 102 15972407 Diagnostic performance of stress perfusion and delayed-enhancement MR imaging in patients with coronary artery disease Cury RC Cattani CA Gabure LA Racy DJ de Gois JM Siebert U Lima SS Brady TJ Radiology 2006 240 39 45 10.1148/radiol.2401051161 16793971 Improved detection of coronary artery disease by stress perfusion cardiovascular magnetic resonance with the use of delayed enhancement infarction imaging Klem I Heitner JF Shah DJ Sketch MH Jr Behar V Weinsaft J Cawley P Parker M Elliott M Judd RM Kim RJ J Am Coll Cardiol 2006 47 1630 1638 10.1016/j.jacc.2005.10.074 16631001 Clinical implication of adenosine-stress cardiac magnetic resonance imaging as potential gatekeeper prior to invasive examination in patients with AHA/ACC class II indication for coronary angiography Pilz G Bernhardt P Klos M Ali E Wild M Hofling B Clin Res Cardiol 2006 95 531 538 10.1007/s00392-006-0422-7 16897145 Cardiac magnetic resonance perfusion imaging for the functional assessment of coronary artery disease: a comparison with coronary angiography and fractional flow reserve Rieber J Huber A Erhard I Mueller S Schweyer M Koenig A Schiele TM Theisen K Siebert U Schoenberg SO Reiser M Klauss V Eur Heart J 2006 27 1465 1471 10.1093/eurheartj/ehl039 16720685 Cardiovascular magnetic resonance perfusion imaging at 3-tesla for the detection of coronary artery disease: a comparison with 1.5-tesla Cheng AS Pegg TJ Karamitsos TD Searle N Jerosch-Herold M Choudhury RP Banning AP Neubauer S Robson MD Selvanayagam JB J Am Coll Cardiol 2007 49 2440 2249 10.1016/j.jacc.2007.03.028 17599608 Quantitative magnetic resonance perfusion imaging detects anatomic and physiologic coronary artery disease as measured by coronary angiography and fractional flow reserve Costa MA Shoemaker S Futamatsu H Klassen C Angiolillo DJ Nguyen M Siuciak A Gilmore P Zenni MM Guzman L Bass TA Wilke N J Am Coll Cardiol 2007 50 514 522 10.1016/j.jacc.2007.04.053 17678734 Safety and diagnostic accuracy of stress cardiac magnetic resonance imaging vs exercise tolerance testing early after acute ST elevation myocardial infarction Greenwood JP Younger JF Ridgway JP Sivananthan MU Ball SG Plein S Heart 2007 93 1363 1368 10.1136/hrt.2006.106427 17309909 Comparison of magnetic resonance perfusion imaging versus invasive fractional flow reserve for assessment of the hemodynamic significance of epicardial coronary artery stenosis Kühl HP Katoh M Buhr C Krombach GA Hoffmann R Rassaf T Neizel M Buecker A Kelm M Am J Cardiol 2007 99 1090 1095 10.1016/j.amjcard.2006.11.061 17437733 Assessment of myocardial perfusion for detection of coronary artery stenoses by steady-state, free-precession magnetic resonance first-pass imaging Merkle N Wöhrle J Grebe O Nusser T Kunze M Kestler HA Kochs M Hombach V Heart 2007 93 1381 1385 10.1136/hrt.2006.104232 17488772 MR stress perfusion for the detection of flow-limiting stenoses in symptomatic patients with known coronary artery disease and history of stent implantation Seeger A Doesch C Klumpp B Kramer U Fenchel M Hoevelborn T Gawaz M Claussen CD May AE Miller S Rofo 2007 179 1068 1073 17879175 Diagnostic performance of myocardial perfusion MR at 3 T in patients with coronary artery disease Gebker R Jahnke C Paetsch I Kelle S Schnackenburg B Fleck E Nagel E Radiology 2008 247 57 63 10.1148/radiol.2471070596 18305188 High-resolution myocardial stress perfusion at 3 T in patients with suspected coronary artery disease Meyer C Strach K Thomas D Litt H Nähle CP Tiemann K Schwenger U Schild HH Sommer T Eur Radiol 2008 18 226 233 10.1007/s00330-007-0746-3 17851665 Angiographic correlations of patients with small vessel disease diagnosed by adenosine-stress cardiac magnetic resonance imaging Pilz G Klos M Ali E Hoefling B Scheck R Bernhardt P J Cardiovasc Magn Reson 2008 10 8 10.1186/1532-429X-10-8 2267791 18275591 Combined magnetic resonance coronary artery imaging, myocardial perfusion and late gadolinium enhancement in patients with suspected coronary artery disease Klein C Gebker R Kokocinski T Dreysse S Schnackenburg B Fleck E Nagel E J Cardiovasc Magn Reson 2008 10 45 10.1186/1532-429X-10-45 2575198 18928521 Value of cardiovascular magnetic resonance stress perfusion testing for the detection of coronary artery disease in women Klem I Greulich S Heitner JF Kim H Vogelsberg H Kispert EM Ambati SR Bruch C Parker M Judd RM Kim RJ Sechtem U J Am Coll Cardiol Img 2008 1 436 45 Combined myocardial stress perfusion imaging and myocardial stress tagging for detection of coronary artery disease at 3 Tesla Thomas D Strach K Meyer C Naehle CP Schaare S Wasmann S Schild HH Sommer T J Cardiovasc Magn Reson 2008 10 59 10.1186/1532-429X-10-59 2615772 19094196 Adenosine stress first pass perfusion for the detection of coronary artery disease in patients with aortic stenosis: a feasibility study Burgstahler C Kunze M Gawaz MP Rasche V Wöhrle J Hombach V Merkle N Int J Cardiovasc Imaging 2008 24 195 200 10.1007/s10554-007-9236-6 17541724 On the dark rim artifact in dynamic contrast-enhanced MRI myocardial perfusion studies Di Bella EVR Parker DL Sinusas AJ Magn Reson Med 2005 54 1295 1299 10.1002/mrm.20666 2377407 16200553 Myocardial first-pass perfusion magnetic resonance imaging: a multicenter dose-ranging study Wolff SD Schwitter J Coulden R Friedrich MG Bluemke DA Biederman RW Martin ET Lansky AJ Kashanian F Foo TK Licato PE Comeau CR Circulation 2004 110 732 737 10.1161/01.CIR.0000138106.84335.62 15289374 MR-Impact: a comparison of perfusion-cardiac magnetic resonance with single-photon emission computed tomography for the detection of coronary artery disease in a multicentre, multivendor, randomized trial Schwitter J Wacker CM van Rossum AC Lombardi M Al-Saadi N Ahlstrom H Dill T Larsson HB Flamm SD Marquardt M Johansson L Eur Heart J 2008 29 480 489 10.1093/eurheartj/ehm617 18208849 Prognosis of negative adenosine stress magnetic resonance in patients presenting to an emergency department with chest pain Ingkanisorn WP Kwong RY Bohme NS Geller NL Rhoads KL Dyke CK Paterson DI Syed MA Aletras AH Arai AE J Am Coll Cardiol 2006 47 1427 1432 10.1016/j.jacc.2005.11.059 16580532 Prognostic value of cardiac magnetic resonance stress tests. Adenosine stress perfusion and dobutamine stress wall motion imaging Jahnke C Nagel E Gebker R Kokocinski T Kelle S Manka R Fleck E Paetsch I Circulation 2007 115 1769 1776 10.1161/CIRCULATIONAHA.106.652016 17353441 Prognostic value of normal adenosine-stress cardiac magnetic resonance imaging Pilz G Jeske A Klos M Ali E Hoefling B Scheck R Bernhardt P Am J Cardiol 2008 101 1408 1412 10.1016/j.amjcard.2008.01.019 18471450 Safety of adenosine stress magnetic resonance imaging using a mobile cardiac magnetic resonance system Bernhardt P Steffens M Kleinertz K Morell R Budde R Leischik R Krämer A Overhoff U Strohm O J Cardiovasc Magn Reson 2006 8 475 478 10.1080/10976640600575270 16755834