Computed tomography-based high-risk coronary plaque score to predict acute coronary syndrome among patients with acute chest pain--Results from the ROMICAT II trial

Maros Ferencik; Thomas Mayrhofer; Stefan B Puchner; Michael T Lu; Pal Maurovich-Horvat; Ting Liu; Khristine Ghemigian; Pieter Kitslaar; Alexander Broersen; Fabian Bamberg; Quynh A Truong; Christopher L Schlett; Udo Hoffmann

doi:10.1016/j.jcct.2015.07.003

Computed tomography-based high-risk coronary plaque score to predict acute coronary syndrome among patients with acute chest pain--Results from the ROMICAT II trial

J Cardiovasc Comput Tomogr. 2015 Nov-Dec;9(6):538-45. doi: 10.1016/j.jcct.2015.07.003. Epub 2015 Jul 10.

Authors

Affiliations

¹ Knight Cardiovascular Institute, Oregon Health and Science University, Portland, OR, USA; Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Cardiac MR PET CT Program, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: ferencik@ohsu.edu.
² Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Cardiac MR PET CT Program, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
³ Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Cardiac MR PET CT Program, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria.
⁴ MTA-SE Lendület Cardiovascular Imaging Research Group, Heart and Vascular Centre, Semmelweis University, Budapest, Hungary.
⁵ Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Cardiac MR PET CT Program, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang, China.
⁶ Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands; Medis Medical Imaging Systems B.V, Leiden, The Netherlands.
⁷ Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands.
⁸ Department of Radiology, University of Tuebingen, Germany.
⁹ Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and Weill Cornell Medical College, New York, NY, USA.
¹⁰ Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.

Abstract

Background: Coronary computed tomography angiography (CTA) can be used to detect and quantitatively assess high-risk plaque features.

Objective: To validate the ROMICAT score, which was derived using semi-automated quantitative measurements of high-risk plaque features, for the prediction of ACS.

Material and methods: We performed quantitative plaque analysis in 260 patients who presented to the emergency department with suspected ACS in the ROMICAT II trial. The readers used a semi-automated software (QAngio, Medis medical imaging systems BV) to measure high-risk plaque features (volume of <60HU plaque, remodeling index, spotty calcium, plaque length) and diameter stenosis in all plaques. We calculated a ROMICAT score, which was derived from the ROMICAT I study and applied to the ROMICAT II trial. The primary outcome of the study was diagnosis of an ACS during the index hospitalization.

Results: Patient characteristics (age 57 ± 8 vs. 56 ± 8 years, cardiovascular risk factors) were not different between those with and without ACS (prevalence of ACS 7.8%). There were more men in the ACS group (84% vs. 59%, p = 0.005). When applying the ROMICAT score derived from the ROMICAT I trial to the patient population of the ROMICAT II trial, the ROMICAT score (OR 2.9, 95% CI 1.4-6.0, p = 0.003) was a predictor of ACS after adjusting for gender and ≥ 50% stenosis. The AUC of the model containing ROMICAT score, gender, and ≥ 50% stenosis was 0.91 (95% CI 0.86-0.96) and was better than with a model that included only gender and ≥ 50% stenosis (AUC 0.85, 95%CI 0.77-0.92; p = 0.002).

Conclusions: The ROMICAT score derived from semi-automated quantitative measurements of high-risk plaque features was an independent predictor of ACS during the index hospitalization and was incremental to gender and presence of ≥ 50% stenosis.

Keywords: Acute chest pain; Acute coronary syndrome; Coronary atherosclerotic plaque; Coronary computed tomography angiography; Risk score.

Publication types

Multicenter Study
Randomized Controlled Trial
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Acute Coronary Syndrome / diagnostic imaging*
Acute Coronary Syndrome / etiology
Aged
Angina Pectoris / diagnostic imaging*
Angina Pectoris / etiology
Area Under Curve
Automation
Coronary Angiography / methods*
Coronary Artery Disease / diagnostic imaging*
Coronary Artery Disease / etiology
Coronary Stenosis / diagnostic imaging*
Coronary Stenosis / etiology
Coronary Vessels / diagnostic imaging*
Female
Hospitalization
Humans
Male
Middle Aged
Observer Variation
Plaque, Atherosclerotic*
Predictive Value of Tests
Prognosis
ROC Curve
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results
Risk Assessment
Risk Factors
Severity of Illness Index
Software
Tomography, X-Ray Computed*
Vascular Calcification / diagnostic imaging

Abstract

Publication types

MeSH terms

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