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Review
. 2017 Apr 1;38(13):991-998.
doi: 10.1093/eurheartj/ehw095.

Diagnostic performance of cardiac imaging methods to diagnose ischaemia-causing coronary artery disease when directly compared with fractional flow reserve as a reference standard: a meta-analysis

Ibrahim Danad  1   2 , Jackie Szymonifka  1   2 , Jos W R Twisk  3 , Bjarne L Norgaard  4 , Christopher K Zarins  5   6 , Paul Knaapen  7 , James K Min  1   2
Affiliations
Review

Diagnostic performance of cardiac imaging methods to diagnose ischaemia-causing coronary artery disease when directly compared with fractional flow reserve as a reference standard: a meta-analysis

Ibrahim Danad et al. Eur Heart J. .

Abstract

Aims: The aim of this study was to determine the diagnostic performance of single-photon emission computed tomography (SPECT), stress echocardiography (SE), invasive coronary angiography (ICA), coronary computed tomography angiography (CCTA), fractional flow reserve (FFR) derived from CCTA (FFRCT), and cardiac magnetic resonance (MRI) imaging when directly compared with an FFR reference standard.

Method and results: PubMed and Web of Knowledge were searched for investigations published between 1 January 2002 and 28 February 2015. Studies performing FFR in at least 75% of coronary vessels for the diagnosis of ischaemic coronary artery disease (CAD) were included. Twenty-three articles reporting on 3788 patients and 5323 vessels were identified. Meta-analysis was performed for pooled sensitivity, specificity, likelihood ratios (LR), diagnostic odds ratio, and summary receiver operating characteristic curves. In contrast to ICA, CCTA, and FFRCT reports, studies evaluating SPECT, SE, and MRI were largely retrospective, single-centre and with generally smaller study samples. On a per-patient basis, the sensitivity of CCTA (90%, 95% CI: 86-93), FFRCT (90%, 95% CI: 85-93), and MRI (90%, 95% CI: 75-97) were higher than for SPECT (70%, 95% CI: 59-80), SE (77%, 95% CI: 61-88), and ICA (69%, 95% CI: 65-75). The highest and lowest per-patient specificity was observed for MRI (94%, 95% CI: 79-99) and for CCTA (39%, 95% CI: 34-44), respectively. Similar specificities were noted for SPECT (78%, 95% CI: 68-87), SE (75%, 95% CI: 63-85), FFRCT (71%, 95% CI: 65-75%), and ICA (67%, 95% CI: 63-71). On a per-vessel basis, the highest sensitivity was for CCTA (pooled sensitivity, 91%: 88-93), MRI (91%: 84-95), and FFRCT (83%, 78-87), with lower sensitivities for ICA (71%, 69-74), and SPECT (57%: 49-64). Per-vessel specificity was highest for MRI (85%, 79-89), FFRCT (78%: 78-81), and SPECT (75%: 69-80), whereas ICA (66%: 64-68) and CCTA (58%: 55-61) yielded a lower specificity.

Conclusions: In this meta-analysis comparing cardiac imaging methods directly to FFR, MRI had the highest performance for diagnosis of ischaemia-causing CAD, with lower performance for SPECT and SE. Anatomic methods of CCTA and ICA yielded lower specificity, with functional assessment of coronary atherosclerosis by SE, SPECT, and FFRCT improving accuracy.

Keywords: Cardiac imaging; Diagnostic accuracy; Fractional flow reserve; Meta-analysis.

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Figures

Figure 1
Figure 1
Flow chart showing the process of literature search and selection algorithm. A total of 23 studies were selected. Of note, there are studies that investigated multiple imaging modalities. FFR, fractional flow reserve; CTP, computed tomography perfusion; PET, positron emission tomography; CT-TAG, CT-derived transluminal attenuation gradient; CCTA, coronary computed tomography angiography; FFRCT, computed fractional flow reserve derived from CCTA; ICA, invasive coronary angiography; SPECT, single-photon emission computed tomography; SE, stress echocardiography; MRI, magnetic resonance imaging.
Figure 2
Figure 2
Assessment of methodological quality of included studies using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) revised criteria. Stacked bars represent the number of studies with a low risk of bias (green), unclear risk of bias (yellow), or high risk of bias (red) with regard to patient selection, utilized reference standard, and imaging modality (index test).
Figure 3
Figure 3
SROC curves of the diagnostic accuracy of cardiac imaging compared with fractional flow reserve. Summary receiver operating characteristic (SROC) curve of the diagnostic accuracy of (A) per-patient and (B) per-vessel data of studies comparing CCTA, FFRCT, ICA, MRI, and SPECT to fractional flow reserve. Each study shows sensitivity and specificity of the different imaging modalities. Area under curve (AUC). The circles show the performance of the separate studies, while the diamond shapes reflect the pooled diagnostic performance of each imaging modality. Abbreviations as in Figure 1.
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Comment in

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