Noninvasive fractional flow reserve derived from coronary computed tomography angiography for identification of ischemic lesions: a systematic review and meta-analysis

Wen Wu, Dao-Rong Pan, Nicolas Foin, Si Pang, Peng Ye, Niels Holm, Xiao-Min Ren, Jie Luo, Aravinda Nanjundappa, Shao-Liang Chen, Wen Wu, Dao-Rong Pan, Nicolas Foin, Si Pang, Peng Ye, Niels Holm, Xiao-Min Ren, Jie Luo, Aravinda Nanjundappa, Shao-Liang Chen

Abstract

Detection of coronary ischemic lesions by fractional flow reserve (FFR) has been established as the gold standard. In recent years, novel computer based methods have emerged and they can provide simulation of FFR using coronary artery images acquired from coronary computed tomography angiography (FFRCT). This meta-analysis aimed to evaluate diagnostic performance of FFRCT using FFR as the reference standard. Databases of PubMed, Cochrane Library, EMBASE, Medion and Web of Science were searched. Seven studies met the inclusion criteria, including 833 stable patients (1377 vessels or lesions) with suspected or known coronary artery disease (CAD). The patient-based analysis showed pooled estimates of sensitivity, specificity and diagnostic odds ratio (DOR) for detection of ischemic lesions were 0.89 [95%confidence interval (CI), 0.85-0.93], 0.76 (95%CI, 0.64-0.84) and 26.21 (95%CI, 13.14-52.28). At a per-vessel or per-lesion level, the pooled estimates were as follows: sensitivity 0.84 (95%CI, 0.80-0.87), specificity 0.76 (95%CI, 0.67-0.83) and DOR 16.87 (95%CI, 9.41-30.25). Area under summary receiver operating curves was 0.90 (95%CI, 0.87-0.92) and 0.86 (95%CI, 0.83-0.89) at the two analysis levels, respectively. In conclusion, FFRCT technology achieves a moderate diagnostic performance for noninvasive identification of ischemic lesions in stable patients with suspected or known CAD in comparison to invasive FFR measurement.

Figures

Figure 1. Flow chart of search and…
Figure 1. Flow chart of search and selection of eligible studies.
Abbreviations: n, number of studies; FFRCT: fractional flow reserve derived from computed tomography.
Figure 2. Combined diagnostic performances of FFR…
Figure 2. Combined diagnostic performances of FFRCT at the per-patient level and at the per- vessel or per-lesion level.
Abbreviations: AUSROC, area under summary receiver operating curve; DOR, diagnostic odds ratio; ES, estimates; NLR, negative likelihood ratio; PLR, positive likelihood ratio; SROC, summary receiver operating curve.
Figure 3. Fagan’s Nomogram plot analysis to…
Figure 3. Fagan’s Nomogram plot analysis to evaluate the clinical utility of FFRCT for the detection of ischemic lesions using FFR as reference standard.
In each plot, a vertical axis on the left showed the fixed pre-test probability. Using the likelihood ratio in the middle axis, post-test probability (patient’s probability of having the disease after the index test result was known) was acquired. (a) With a pre-test probability of a positive FFR of 20%, the post-test probability of positive FFR, given positive and negative FFRCT results, were 48% and 3%. (b) With a pre-test probability of a positive FFR of 20% on a per-lesion basis, the post-test probability of FFR, given positive and negative FFRCT results, were 47% and 5%.
Figure 4. Deeks funnel plot for detecting…
Figure 4. Deeks funnel plot for detecting publication bias.
Abbreviations: ESS, effective sample size.

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