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
N1 - Funding Information:
This work was supported by grants from the National Heart, Lung, and Blood Institute ( U01HL092040 and U01HL092022 ). Dr. Ferencik received support from the American Heart Association ( 13FTF16450001 ). Dr. Hoffmann received research grant support from NIH ( U01HL092040 , U01HL092022 ), Siemens Medical Solutions and Heart Flow Inc. and consultant/advisory board support from Heart Flow Inc. Pieter Kitslaar is an employee of Medis medical imaging systems B.V. Dr. Truong received support from the NIH/NHLBI K23HL098370 and L30HL093896, St. Jude Medical, American College of Radiology Imaging Network, and Duke Clinical Research Institute.
Publisher Copyright:
© 2015 Society of Cardiovascular Computed Tomography.
PY - 2015/11/1
Y1 - 2015/11/1
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.
AB - 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.
KW - Acute chest pain
KW - Acute coronary syndrome
KW - Coronary atherosclerotic plaque
KW - Coronary computed tomography angiography
KW - Risk score
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U2 - 10.1016/j.jcct.2015.07.003
DO - 10.1016/j.jcct.2015.07.003
M3 - Article
C2 - 26229036
AN - SCOPUS:84949317646
SN - 1934-5925
VL - 9
SP - 538
EP - 545
JO - Journal of Cardiovascular Computed Tomography
JF - Journal of Cardiovascular Computed Tomography
IS - 6
ER -