Coronary CT angiography-derived quantitative markers for predicting in-stent restenosis

Christian Tesche; Carlo N De Cecco; Rozemarijn Vliegenthart; Taylor M Duguay; Andrew C Stubenrauch; Russell D Rosenberg; Akos Varga-Szemes; Richard R Bayer 2nd; Junjie Yang; Ullrich Ebersberger; Moritz Baquet; David Jochheim; Ellen Hoffmann; Daniel H Steinberg; Salvatore A Chiaramida; U Joseph Schoepf

doi:10.1016/j.jcct.2016.07.005

Coronary CT angiography-derived quantitative markers for predicting in-stent restenosis

J Cardiovasc Comput Tomogr. 2016 Sep-Oct;10(5):377-83. doi: 10.1016/j.jcct.2016.07.005. Epub 2016 Jul 6.

Authors

Christian Tesche¹, Carlo N De Cecco², Rozemarijn Vliegenthart³, Taylor M Duguay⁴, Andrew C Stubenrauch⁴, Russell D Rosenberg⁵, Akos Varga-Szemes⁴, Richard R Bayer 2nd⁵, Junjie Yang⁶, Ullrich Ebersberger¹, Moritz Baquet⁷, David Jochheim⁷, Ellen Hoffmann⁸, Daniel H Steinberg⁹, Salvatore A Chiaramida⁹, U Joseph Schoepf¹⁰

Affiliations

¹ Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany.
² Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Radiological Sciences, Oncology and Pathology, University of Rome "Sapienza", Rome, Italy.
³ Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; University of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, The Netherlands.
⁴ Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.
⁵ Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA.
⁶ Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Cardiology, People's Liberation Army General Hospital, Beijing, China.
⁷ Department of Cardiology, Hospital of the Ludwig-Maximilians-University, Munich, Germany.
⁸ Department of Cardiology and Intensive Care Medicine, Heart Center Munich-Bogenhausen, Munich, Germany.
⁹ Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA.
¹⁰ Division of Cardiovascular Imaging, Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Division of Cardiology, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA. Electronic address: schoepf@musc.edu.

PMID: 27431607
DOI: 10.1016/j.jcct.2016.07.005

Abstract

Objective: To evaluate quantitative markers derived from coronary CT angiography (coronary CTA) performed prior to percutaneous coronary intervention (PCI) with stent placement for predicting in-stent restenosis (ISR) as defined by quantitative coronary angiography (QCA).

Materials and methods: We retrospectively analyzed the data of 74 patients (60 ± 12 years, 72% male) who had undergone dual-source coronary CTA within 3 months prior to a PCI procedure that included stent placement. Quantitative markers of the target vessel were derived from coronary CTA: Total plaque volume (TPV), calcified and non-calcified plaque volumes (CPV and NCPV), plaque burden (PB in %), remodeling index (RI), and lesion length (LL). Marker performance for predicting ISR, as defined by QCA at follow-up, was assessed.

Results: Twenty-one of 74 stented lesions showed ISR on follow-up (mean 616 ± 447 days). When comparing stent length and LL in patients with ISR, a trend towards less complete stent coverage of the target lesion was observed in cases with ISR (17/21 vs. 4/53 cases, p = 0.07). In multivariate analysis (corrected for dyslipidemia), the following markers showed predictive value for ISR (odds ratio [OR]): NCPV (OR 1.08, p = 0.045), LL (OR 1.38, p = 0.0024), and RI (OR 1.13, p = 0.0019). Sensitivity and specificity for ISR were: NCPV 65% and 80%, LL 74% and 74%, and RI 71% and 78%. At receiver-operating characteristics analysis, NCPV (0.72, p = 0.001), LL (0.77, p < 0.0001), and RI (0.79, p < 0.0001) showed discriminatory power for predicting ISR. A combination of these markers showed incremental predictive value (AUC 0.89, p < 0.0001) with sensitivity and specificity of 90% and 84%, respectively.

Conclusion: Coronary CTA-derived NCPV, LL, and RI portend predictive value for ISR with incremental predictive value when combining these parameters.

Keywords: Coronary artery disease; Coronary computed tomography angiography; In-stent restenosis; Quantitative coronary angiography.

MeSH terms

Aged
Area Under Curve
Computed Tomography Angiography*
Coronary Angiography / methods*
Coronary Artery Disease / diagnostic imaging
Coronary Artery Disease / therapy*
Coronary Restenosis / diagnostic imaging
Coronary Restenosis / etiology*
Coronary Vessels / diagnostic imaging*
Female
Humans
Logistic Models
Male
Middle Aged
Multivariate Analysis
Odds Ratio
Percutaneous Coronary Intervention / adverse effects*
Percutaneous Coronary Intervention / instrumentation*
Plaque, Atherosclerotic
Predictive Value of Tests
ROC Curve
Retrospective Studies
Risk Assessment
Risk Factors
Severity of Illness Index
Stents*
Treatment Outcome
Vascular Calcification / diagnostic imaging
Vascular Calcification / therapy*