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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.JC

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.

Authors+Show Affiliations

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.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, 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.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.MTA-SE Lendület Cardiovascular Imaging Research Group, Heart and Vascular Centre, Semmelweis University, Budapest, Hungary.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.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, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands; Medis Medical Imaging Systems B.V, Leiden, The Netherlands.Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, The Netherlands.Department of Radiology, University of Tuebingen, Germany.Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and Weill Cornell Medical College, New York, NY, USA.Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.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.

Pub Type(s)

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

Language

eng

PubMed ID

26229036

Citation

Ferencik, Maros, et al. "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." Journal of Cardiovascular Computed Tomography, vol. 9, no. 6, 2015, pp. 538-45.
Ferencik M, Mayrhofer T, Puchner SB, et al. 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;9(6):538-45.
Ferencik, M., Mayrhofer, T., Puchner, S. B., Lu, M. T., Maurovich-Horvat, P., Liu, T., Ghemigian, K., Kitslaar, P., Broersen, A., Bamberg, F., Truong, Q. A., Schlett, C. L., & Hoffmann, U. (2015). 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. Journal of Cardiovascular Computed Tomography, 9(6), 538-45. https://doi.org/10.1016/j.jcct.2015.07.003
Ferencik M, et al. 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. PubMed PMID: 26229036.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - 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. AU - Ferencik,Maros, AU - Mayrhofer,Thomas, AU - Puchner,Stefan B, AU - Lu,Michael T, AU - Maurovich-Horvat,Pal, AU - Liu,Ting, AU - Ghemigian,Khristine, AU - Kitslaar,Pieter, AU - Broersen,Alexander, AU - Bamberg,Fabian, AU - Truong,Quynh A, AU - Schlett,Christopher L, AU - Hoffmann,Udo, Y1 - 2015/07/10/ PY - 2015/03/26/received PY - 2015/04/16/revised PY - 2015/07/07/accepted PY - 2015/8/1/entrez PY - 2015/8/1/pubmed PY - 2016/9/30/medline KW - Acute chest pain KW - Acute coronary syndrome KW - Coronary atherosclerotic plaque KW - Coronary computed tomography angiography KW - Risk score SP - 538 EP - 45 JF - Journal of cardiovascular computed tomography JO - J Cardiovasc Comput Tomogr VL - 9 IS - 6 N2 - 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. SN - 1876-861X UR - https://www.unboundmedicine.com/medline/citation/26229036/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_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S1934-5925(15)00223-3 DB - PRIME DP - Unbound Medicine ER -