Abstract
Aims: We aimed to investigate whether quantitative plaque features measured from coronary CT angiography (CCTA) predict ischemia by myocardial perfusion SPECT imaging (MPI). Methods and Results: Hundred and eighty-four consecutive patients (63% males) with suspected-coronary artery disease, undergoing hybrid CCTA, and attenuation corrected solid state 99mTc stress/rest MPI and single vessel ischemia were considered. Quantitative analysis of CCTA derived non-calcified plaque (NCP), low-density NCP [< 30 Hounsfield Units (HU)] (LDNCP), calcified and total plaque burdens (%, normalized to vessel volume), maximum diameter stenosis and contrast density difference (CD, maximum difference in HU/lumen area within lesion). Normal thresholds for plaque features were defined as 95th percentile thresholds, from 40% of vessels with non-ischemic MPI regions. These vessels were excluded from further analysis. Regional ischemia (≥ 2%) was quantified from MPI. All plaque features were higher in arteries corresponding to ischemia (P < 0.003 for all). In multi-variable analysis, abnormal NCP burden [odds ratio (OR) 2.6], LDNCP burden (OR 3.9), and CD (OR 2.7) were significantly associated with ischemia, whereas stenosis ≥ 50% was not (P = 0.14). In a subset of vessels with ≥ 50% stenosis, LDNCP burden (OR 4.3, P = 0.008) and CD (OR 3.7, P = 0.029) were associated with ischemia. In subsets of vessels with stenosis 30-69% and ≥ 70%, abnormal LDNCP burden (OR 6.4, P = 0.006) and CD (OR 7.3, P = 0.02) were associated with ischemia. Conclusions: Quantitative plaque features obtained from CCTA, LDNCP, and CD, are associated with ischemia by MPI independent of stenosis. LDNCP burden and CD are associated with ischemia in stenosis 30-69% and ≥ 70%, respectively.
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Diaz-Zamudio, M., Fuchs, T. A., Slomka, P., Otaki, Y., Arsanjani, R., Gransar, H., … Dey, D. (2017). Quantitative plaque features from coronary computed tomography angiography to identify regional ischemia by myocardial perfusion imaging. European Heart Journal Cardiovascular Imaging, 18(5), 499–507. https://doi.org/10.1093/ehjci/jew274
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