Purpose: Coronary CTA is a reliable non-invasive risk stratification tool for patients with coronary artery disease. However, little is known about the prognostic implications of non-culprit plaques seen on coronary CTA in patients with ACS. In tis study, we sought ou to determine the prognostic value of non-culprit plaques on coronary CT angiography (CTA) in patients with acute coronary syndrome. Methods: Coronary CTA was performed in 169 ACS patients (mean 59±11 years, 129 males) during index admission. Overall residual coronary artery plaque burden was determined using a segment stenosis score for each patient: 0-20% stenosis: score 0, 20-50%: score 1, 50-70%: score 2, >70%: score 3, (maximal score of 48 per patient). Follow-up was performed for the occurrence of major adverse cardiac events (MACE) not related to the initially culprit lesion; cardiac death, recurrent non-fatal myocardial infarction or coronary revascularization after 90 days. Results: Follow-up was completed in 152 (90%) patients with a median follow-up time of 4.8 (IQR 2.6-6.6) years. MACE occurred in 36 (24%) patients, consisting of 6 cardiac deaths, 11 non-fatal myocardial infarctions and 19 coronary revascularisations. A total of 2432 segments were evaluated and 404 were considered non-diagnostic while 172 were censored because of treatment. The median segment stenosis score was higher in patients with MACE (12 [6-16] vs. 7 [3-11], p = 0.005). Non-culprit plaques with a >50% stenose were more often seen in patients with MACE than in those without (83% vs. 52%, p = 0.001). Dyslipidemia (hazard ratio [HR] 3.1 [95% CI 1.4 - 6.6], diabetes mellitus (HR 4.8 [2.3 - 10.3]) and TIMI risk score (HR 1.5 [1.2 - 1.9]) were univariable predictors of MACE, as well as the segment stenosis score (HR 1.09 [1.03 – 1.15]) and >50% stenosis of a non-culprit plaque (HR 3.7 [1.5 - 8.8]). After adjusting for clinical characteristics, >50% stenosis of a non-culprit plaque (HR 3.69 [1.41-9.68]) remained an independent predictor of MACE. Conclusions: Almost a quarter of ACS patients experienced a non-culprit related MACE during 5 years follow-up in this study. Coronary CTA detects non-culprit plaques in ACS patients and identifies those at risk of future non-culprit cardiac events with incremental value over clinical variables.

OBJECTIVE Echocardiography, radionuclide myocardial perfusion imaging (MPI), and coronary CT angiography (CTA) are the three main imaging techniques used in the emergency department for the diagnosis of acute coronary syndrome (ACS). The purpose of this article is to quantitatively examine existing evidence about the diagnostic performance of these imaging tests in this setting. CONCLUSION Our systematic search of the medical literature showed no significant difference between the modalities for the detection of ACS in the emergency department. There was a slight, positive trend favoring coronary CTA. Given the absence of large differences in diagnostic performance, practical aspects such as local practice, expertise, medical facilities, and individual patient characteristics may be more important.

Alexia Rossi, MD, PhD; Stella-Lida Papadopoulou, MD; Francesca Pugliese, MD, PhD; Brunella Russo, MD; Anoeshka S. Dharampal, MD; Admir Dedic, MD; Pieter H. Kitslaar, MSc; Alexander Broersen, PhD; W. Bob Meijboom, MD, PhD; Robert-Jan van Geuns, MD, PhD; Andrew Wragg, FRCP; Jurgen Ligthart, MSc; Carl Schultz, MD; Steffen E. Petersen, MD, DPhil; Koen Nieman, MD, PhD; Gabriel P. Krestin, MD, PhD; Pim J. de Feyter, MD, PhD

Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CTA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms devised to detect and quantify the coronary artery stenoses, and to segment the coronary artery lumen in CTA data. The objective of this evaluation framework is to demonstrate the feasibility of dedicated algorithms to: 1) (semi-)automatically detect and quantify stenosis on CTA, in comparison with quantitative coronary angiography (QCA) and CTA consensus reading, and 2) (semi-)automatically segment the coronary lumen on CTA, in comparison with expert's manual annotation. A database consisting of 48 multicenter multivendor cardiac CTA datasets with corresponding reference standards are described and made available. The algorithms from 11 research groups were quantitatively evaluated and compared. The results show that 1) some of the current stenosis detection/quantification algorithms can be used for triage or as a second-reader in clinical practice, and that 2) automatic lumen ha l-0 08 74 10 7, v er si on 1 segmentation is possible with a precision similar to that obtained by experts. The framework is open for new submissions through our website (http://coronary.bigr.nl/stenoses/). ha l-0 08 74 10 7, v er si on 1 Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in Computed Tomography Angiography H.A. Kirişlia,b,∗, M. Schaap, C.T. Metz, A.S. Dharampal, W.B. Meijboom, S.L. Papadopoulou, A. Dedic, K. Nieman, M.A. de Graaf, M.F.L. Meijs, M.J. Cramer, A. Broersen, S. Cetin, A. Eslami, L. Flórez-Valencia, K.L. Lor, B. Matuszewski, I. Melki, B. Mohr, I. Öksüz, R. Shahzad, C. Wang, P.H. Kitslaar, G. Unal, A. Katouzian, M. Orkisz, C.M. Chen, F. Precioso, L. Najman, S. Masood, D. Ünay, L. van Vliet, R. Moreno, R. Goldenberg, E. Vuçini, G.P. Krestin, W.J. Niessen, T. van Walsum Biomedical Imaging Group Rotterdam, Dept. of Radiology and Med. Informatics, Erasmus MC, Rotterdam, the Netherlands Div. of Image Processing, Dept. of Radiology, Leiden UMC, Leiden, the Netherlands Dept. of Radiology, Erasmus MC, Rotterdam, the Netherlands Dept. of Cardiology, Erasmus MC, Rotterdam, the Netherlands Dept. of Cardiology, UMC Utrecht, Utrecht, the Netherlands Dept. of Cardiology, Leiden UMC, Leiden, the Netherlands The Interuniversity Cardiology Institute of the Netherlands, Utrecht, the Netherlands Rcadia Medical Imaging, Häıfa, Israël Quantitative Imaging Group, Imaging Science and Technology, Faculty of Applied Sciences, Delft Univ. of Technology, Delft, the Netherlands VRVis Research Center for Virtual Reality and Visualization, Vienna, Austria Toshiba Medical Visualization Systems, Edinburgh, UK Faculty of Engineering and Natural Sciences, SabancıUniversity, Turkey Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan Université Paris-Est, Laboratoire d’Informatique Gaspard-Monge, Equipe A3SI, Noisy-le-Grand, France GE Healthcare, Buc, France Grupo Takina, Departamento de Ingenieŕıa de Sistemas, Pontificia Universidad Javeriana, Bogotá, Colombia ∗Corresponding author. Adress: P.O. Box 2040, 3000 CA Rotterdam, the Netherlands. Tel.: +31 10 7044246; fax: +31 10 7044722. Email address: h.kirisli@erasmusmc.nl (H.A. Kirişli) URL: www.bigr.nl/people/HortenseKirisli (H.A. Kirişli) Preprint submitted to Medical Image Analysis March 1, 2013 Revised manuscript Click here to view linked References ha l-0 08 74 10 7, v er si on 1 Université de Lyon, CREATIS; CNRS UMR 5220; INSERM U 1044; INSA-Lyon, Lyon, France Electrical and Electronics Engineering, Bahçeşehir University, Istanbul, Turkey Biomedical Engineering, Bahçeşehir University, Istanbul, Turkey Center for Medical Imaging Science and Visualization, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden Computer Aided Medical Procedures, Technical University of Munich, Munich, Germany Institute for Biomathematics and Biometry, Helmholtz Zentrum Munich, Germany Biomedical Engineering Department, Columbia University, New York, USA University Nice-Sophia Antipolis, Laboratory of Informatics, Signal and Systems (I3S), Nice Sophia Antipolis, France School of Computing Engineering and Physical Sciences, University of Central Lancashire, Preston, UK

Objective To determine the diagnostic accuracy of copeptin in patients with suspected acute coronary syndrome (ACS) and its correlation with obstructive coronary artery disease (CAD) on coronary CT angiography (CTA). Methods Copeptin was measured at arrival in 65 consecutive patients (56±10 years, 45 men) suspected of ACS and no indication for immediate invasive angiography. All patients underwent coronary CTA without disclosure of the results to the treating physician, and outcomes were classified as obstructive CAD (>50% stenosis) or no obstructive CAD (≤50%) in one or more vessel. Results The final diagnosis of ACS was established in 10 (15%) patients, 6 myocardial infarctions and 4 unstable angina pectoris. Coronary CTA detected obstructive CAD in all patients with ACS and in 10 (15%) patients with no ACS. Copeptin concentrations were higher in patients with ACS (median 7.42 pmol/l (IQR 3.71–18.72)) vs patients with no ACS (3.40 pmol/l (1.13–6.27), p=0.02). Copeptin was not higher in patients with obstructive CAD on coronary CTA (4.87 pmol/l (2.90–8.51) vs 3.60 pmol/l (1.21–6.23), p=0.20) compared with patients with no obstructive CAD. Conclusions Copeptin seems to be elevated in patients with ACS while there is no strong correlation with obstructive coronary disease on CTA.