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Meta-Analysis
. 2017 May 17;12(5):e0176622.
doi: 10.1371/journal.pone.0176622. eCollection 2017.

Comparative accuracy of CT perfusion in diagnosing acute ischemic stroke: A systematic review of 27 trials

Jiantong Shen  1   2 , Xianglian Li  2 , Youping Li  1   2 , Bing Wu  3
Affiliations
Meta-Analysis

Comparative accuracy of CT perfusion in diagnosing acute ischemic stroke: A systematic review of 27 trials

Jiantong Shen et al. PLoS One. .

Abstract

Objective: To systematically evaluate and compare the diagnostic accuracy of CT perfusion (CTP), non-enhanced computed tomography (NCCT) and computed tomography angiography (CTA) in detecting acute ischemic stroke.

Methods: We searched seven databases and screened the reference lists of the included studies. The risk of bias in the study quality was assessed using QUADASII. We produced paired forest plots in RevMan to show the variation of the sensitivity and specificity estimates together with their 95% CI. We used a hierarchical summary ROC model to summarize the sensitivity and specificity of CTP in detecting ischemic stroke.

Results: We identified 27 studies with a total of 2168 patients. The pooled sensitivity of CTP for acute ischemic stroke was 82% (95% CI 75-88%), and the specificity was 96% (95% CI 89-99%). CTP was more sensitive than NCCT and had a similar accuracy with CTA. There were no statistically significant differences in the sensitivity and specificity between patients who underwent CTP within 6 hours of symptom onset and beyond 6 hours after symptom onset. No adverse events were reported in the included studies.

Conclusions: CTP is more accurate than NCCT and has similar accuracy to CTA in detecting acute ischemic stroke. However, the evidence is not strong. There is potential benefit of using CTP to select stroke patients for treatment, but more high-quality evidence is needed to confirm this result.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Study flow diagram.
Fig 2
Fig 2. Risk of bias and applicability concerns graph: Review authors’ judgments about each domain presented as percentages across included studies.
Fig 3
Fig 3. Risk of bias and applicability concerns summary.
Fig 4
Fig 4. Forest plot of CTP for detection of ischemic stroke.
The plot shows study-specific estimates of sensitivity and specificity (with 95% confidence intervals). The studies are ordered according to whether recruitment was prospective or not, and sensitivity. FN: false negative; FP: false positive; TN: true negative; TP: true positive.
Fig 5
Fig 5. Summary ROC Plot of CTP for detecting ischemic stroke.
The circle size represents the sample size of the corresponding study.
Fig 6
Fig 6. Forest plot of CTP and NCCT for detection of ischemic stroke.
Fig 7
Fig 7. Summary ROC Plot of CTP and NCCT for detecting ischemic stroke.
Each ellipse on the plot represents the study estimate of CTP. Each diamond represents the study estimate of NCCT. Red and black solid circles represent the summary sensitivity and specificity for NCCT and CTP respectively, and this summary point is surrounded by a 95% confidence region (dotted line). Red and black solid lines represent HSROC curve of NCCT and CTP respectively.
Fig 8
Fig 8. Forest plot of CTP and CTA for detection of ischemic stroke.
Fig 9
Fig 9. Summary ROC Plot of CTP and CTA for detecting ischemic stroke.
Each ellipse on the plot represents the study estimate of CTP. Each diamond represents the study estimate of CTA. Red and black solid circles represent the summary sensitivity and specificity for CTA and CTP respectively, and these summary points are surrounded by a 95% confidence region (dotted line). Red and black solid lines represent HSROC curve of CTA and CTP respectively.
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