Quantitative plaque features from coronary computed tomography angiography to identify regional ischemia by myocardial perfusion imaging

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 (99m)Tc 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

Automated pericardial fat quantification from coronary magnetic resonance angiography: feasibility study

Pericardial fat volume (PFV) is emerging as an important parameter for cardiovascular risk stratification. We propose a hybrid approach for automated PFV quantification from water/fat-resolved whole-heart noncontrast coronary magnetic resonance angiography (MRA). Ten coronary MRA datasets were acquired. Image reconstruction and phase-based water-fat separation were conducted offline. Our proposed algorithm first roughly segments the heart region on the original image using a simplified atlas-based segmentation with four cases in the atlas. To get exact boundaries of pericardial fat, a three-dimensional graph-based segmentation is used to generate fat and nonfat components on the fat-only image. The algorithm then selects the components that represent pericardial fat. We validated the quantification results on the remaining six subjects and compared them with manual quantifications by an expert reader. The PFV quantified by our algorithm was 62.78±27.85 cm3, compared to 58.66±27.05 cm3 by the expert reader, which were not significantly different (p=0.47) and showed excellent correlation (R=0.89,p&lt;0.01). The mean absolute difference in PFV between the algorithm and the expert reader was 9.9±8.2 cm3. The mean value of the paired differences was -4.13 cm3 (95% confidence interval: -14.47 to 6.21). The mean Dice coefficient of pericardial fat voxels was 0.82±0.06. Our approach may potentially be applied in a clinical setting, allowing for accurate magnetic resonance imaging (MRI)-based PFV quantification without tedious manual tracing

Automated Quantitative Plaque Burden from Coronary CT Angiography Noninvasively Predicts Hemodynamic Significance by using Fractional Flow Reserve in Intermediate Coronary Lesions

PurposeTo evaluate the utility of multiple automated plaque measurements from coronary computed tomographic (CT) angiography in determining hemodynamic significance by using invasive fractional flow reserve (FFR) in patients with intermediate coronary stenosis.Materials and methodsThe study was approved by the institutional review board. All patients provided written informed consent. Fifty-six intermediate lesions (with 30%-69% diameter stenosis) in 56 consecutive patients (mean age, 62 years; range, 46-88 years), who subsequently underwent invasive coronary angiography with assessment of FFR (values ≤0.80 were considered hemodynamically significant) were analyzed at coronary CT angiography. Coronary CT angiography images were quantitatively analyzed with automated software to obtain the following measurements: volume and burden (plaque volume × 100 per vessel volume) of total, calcified, and noncalcified plaque; low-attenuation (&lt;30 HU) noncalcified plaque; diameter stenosis; remodeling index; contrast attenuation difference (maximum percent difference in attenuation per unit area with respect to the proximal reference cross section); and lesion length. Logistic regression adjusted for potential confounding factors, receiver operating characteristics, and integrated discrimination improvement were used for statistical analysis.ResultsFFR was 0.80 or less in 21 (38%) of the 56 lesions. Compared with nonischemic lesions, ischemic lesions had greater diameter stenosis (65% vs 52%, P = .02) and total (49% vs 37%, P = .0003), noncalcified (44% vs 33%, P = .0004), and low-attenuation noncalcified (9% vs 4%, P &lt; .0001) plaque burden. Calcified plaque and remodeling index were not significantly different. In multivariable analysis, only total, noncalcified, and low-attenuation noncalcified plaque burden were significant predictors of ischemia (P &lt; .015). For predicting ischemia, the area under the receiver operating characteristics curve was 0.83 for total plaque burden versus 0.68 for stenosis (P = .04).ConclusionCompared with stenosis grading, automatic quantification of total, noncalcified, and low-attenuation noncalcified plaque burden substantially improves determination of lesion-specific hemodynamic significance by FFR in patients with intermediate coronary lesions

Relationship Between Quantitative Adverse Plaque Features From Coronary Computed Tomography Angiography and Downstream Impaired Myocardial Flow Reserve by 13N-Ammonia Positron Emission Tomography

BackgroundWe investigated the relationship of quantitative plaque features from coronary computed tomography (CT) angiography and coronary vascular dysfunction by impaired myocardial flow reserve (MFR) by (13)N-Ammonia positron emission tomography (PET).Methods and resultsFifty-one patients (32 men, 62.4±9.5 years) underwent combined rest-stress (13)N-ammonia PET and CT angiography scans by hybrid PET/CT. Regional MFR was measured from PET. From CT angiography, 153 arteries were evaluated by semiautomated software, computing arterial noncalcified plaque (NCP), low-density NCP (NCP&lt;30 HU), calcified and total plaque volumes, and corresponding plaque burden (plaque volumex100%/vessel volume), stenosis, remodeling index, contrast density difference (maximum difference in luminal attenuation per unit area in the lesion), and plaque length. Quantitative stenosis, plaque burden, and myocardial mass were combined by boosted ensemble machine-learning algorithm into a composite risk score to predict impaired MFR (MFR≤2.0) by PET in each artery. Nineteen patients had impaired regional MFR in at least 1 territory (41/153 vessels). Patients with impaired regional MFR had higher arterial NCP (32.4% versus 17.2%), low-density NCP (7% versus 4%), and total plaque burden (37% versus 19.3%, P&lt;0.02). In multivariable analysis with 10-fold cross-validation, NCP burden was the most significant predictor of impaired MFR (odds ratio, 1.35; P=0.021 for all). For prediction of impaired MFR with 10-fold cross-validation, receiver operating characteristics area under the curve for the composite score was 0.83 (95% confidence interval, 0.79-0.91) greater than for quantitative stenosis (0.66, 95% confidence interval, 0.57-0.76, P=0.005).ConclusionsCompared with stenosis, arterial NCP burden and a composite score combining quantitative stenosis and plaque burden from CT angiography significantly improves identification of downstream regional vascular dysfunction