Multidetector computed tomography angiography for assessment of in-stent restenosis: meta-analysis of diagnostic performance

doi:10.1186/1471-2342-8-14

BMC Medical Imaging
Volume 8

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Vanhoenacker PK
Decramer I
Bladt O
Sarno G
Van Hul E
Wijns W
Dwamena BA

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Decramer I
Bladt O
Sarno G
Van Hul E
Wijns W
Dwamena BA
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Research article

Multidetector computed tomography angiography for assessment of in-stent restenosis: meta-analysis of diagnostic performance

Piet K Vanhoenacker^*¹ , Isabel Decramer^*¹^,2 , Olivier Bladt¹ , Giovanna Sarno² , Erik Van Hul¹ , William Wijns² and Ben A Dwamena³

¹Department of Radiology and Imaging, OLV Ziekenhuis, Aalst, Belgium

²Cardiovascular Center Aalst, Aalst, Belgium

³Division of Nuclear Medicine, Department of Radiology, University of Michigan Health System, Ann Arbor, USA

author email corresponding author email* Contributed equally

BMC Medical Imaging 2008, 8:14doi:10.1186/1471-2342-8-14


Published:	31 July 2008

Abstract

Background

Multi-detector computed tomography angiography (MDCTA)of the coronary arteries after stenting has been evaluated in multiple studies.

The purpose of this study was to perform a structured review and meta-analysis of the diagnostic performance of MDCTA for the detection of in-stent restenosis in the coronary arteries.

Methods

A Pubmed and manual search of the literature on in-stent restenosis (ISR) detected on MDCTA compared with conventional coronary angiography (CA) was performed. Bivariate summary receiver operating curve (SROC) analysis, with calculation of summary estimates was done on a stent and patient basis. In addition, the influence of study characteristics on diagnostic performance and number of non-assessable segments (NAP) was investigated with logistic meta-regression.

Results

Fourteen studies were included. On a stent basis, Pooled sensitivity and specificity were 0.82(0.72–0.89) and 0.91 (0.83–0.96). Pooled negative likelihood ratio and positive likelihood ratio were 0.20 (0.13–0.32) and 9.34 (4.68–18.62) respectively. The exclusion of non-assessable stents and the strut thickness of the stents had an influence on the diagnostic performance. The proportion of non-assessable stents was influenced by the number of detectors, stent diameter, strut thickness and the use of an edge-enhancing kernel.

Conclusion

The sensitivity of MDTCA for the detection of in-stent stenosis is insufficient to use this test to select patients for further invasive testing as with this strategy around 20% of the patients with in-stent stenosis would be missed. Further improvement of scanner technology is needed before it can be recommended as a triage instrument in practice. In addition, the number of non-assessable stents is also high.