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Background: To compare computed tomography coronary angiography (CTCA) with intravascular ultrasound (IVUS) in quantitative and qualitative plaque assessment. Method(s): Patients who underwent IVUS and CTCA within 3 months for suspected coronary artery disease were retrospectively studied. Plaque volumes on CTCA were quantified manually and with automated-software and were compared to IVUS. High-risk plaque features were compared between CTCA and IVUS. Result(s): There were 769 slices in 32 vessels (27 patients). Manual plaque quantification on CTCA was comparable to IVUS per slice (mean difference of 0.06 +/- 0.07, p = 0.44; Bland-Altman 95% limits of agreement -2.19-2.08 mm3, bias of -0.06 mm3) and per vessel (3.1 mm3 +/- -2.85 mm3, p = 0.92). In contrast, there was significant difference between automated-software and IVUS per slice (2.3 +/- 0.09mm3, p < 0.001; 95% LoA -6.78 to 2.25 mm3, bias of -2.2 mm3) and per vessel (33.04 +/- 10.3 mm3, p < 0.01). The sensitivity, specificity, positive and negative predictive value of CTCA to detect plaques that had features of echo-attenuation on IVUS was 93.3%, 99.6%, 93.3% and 99.6% respectively. The association of >=2 high-risk plaque features on CTCA with echo attenuation (EA) plaque features on IVUS was excellent (86.7%, 99.6%, 92.9% and 99.2%). In comparison, the association of high-risk plaque features on CTCA and plaques with echo-lucency on IVUS was only modest. Conclusion(s): Plaque volume quantification by manual CTCA method is accurate when compared to IVUS. The presence of at least two high-risk plaque features on CTCA is associated with plaque features of echo attenuation on IVUS.Copyright © 2019

Background: To compare computed tomography coronary angiography (CTCA) with intravascular ultrasound (IVUS) in quantitative and qualitative plaque assessment. Method(s): Patients who underwent IVUS and CTCA within 3 months for suspected coronary artery disease were retrospectively studied. Plaque volumes on CTCA were quantified manually and with automated-software and were compared to IVUS. High-risk plaque features were compared between CTCA and IVUS. Result(s): There were 769 slices in 32 vessels (27 patients). Manual plaque quantification on CTCA was comparable to IVUS per slice (mean difference of 0.06 +/- 0.07, p = 0.44; Bland-Altman 95% limits of agreement -2.19-2.08 mm3, bias of -0.06 mm3) and per vessel (3.1 mm3 +/- -2.85 mm3, p = 0.92). In contrast, there was significant difference between automated-software and IVUS per slice (2.3 +/- 0.09mm3, p < 0.001; 95% LoA -6.78 to 2.25 mm3, bias of -2.2 mm3) and per vessel (33.04 +/- 10.3 mm3, p < 0.01). The sensitivity, specificity, positive and negative predictive value of CTCA to detect plaques that had features of echo-attenuation on IVUS was 93.3%, 99.6%, 93.3% and 99.6% respectively. The association of >=2 high-risk plaque features on CTCA with echo attenuation (EA) plaque features on IVUS was excellent (86.7%, 99.6%, 92.9% and 99.2%). In comparison, the association of high-risk plaque features on CTCA and plaques with echo-lucency on IVUS was only modest. Conclusion(s): Plaque volume quantification by manual CTCA method is accurate when compared to IVUS. The presence of at least two high-risk plaque features on CTCA is associated with plaque features of echo attenuation on IVUS.Copyright © 2019

Background and aims: There remains a substantial residual risk of ischaemic heart disease (IHD) despite optimal low-density lipoprotein cholesterol (LDLC) reduction. Part of this risk may be attributable to remnant cholesterol, which is carried in triglyceride-rich lipoproteins. We evaluated the relationship between remnant cholesterol and coronary atherosclerotic plaque burden assessed non-invasively by computed tomography coronary angiography (CTCA) in patients with suspected coronary artery disease (CAD). Methods and Results: This was a multicentre study of 587 patients who had a CTCA and fasting lipid profile within 3 months. Calculated remnant cholesterol was total cholesterol minus LDLC minus high-density lipoprotein cholesterol (HDLC). Significant coronary atherosclerotic burden was defined as CT-Leaman score >5 (CT-LeSc), an established predictor of cardiac events. Mean age was 61 +/- 12 years and mean pretest probability of CAD was 23.2 +/- 19.8%. LDLC levels were <1.8 mmol/L in 134 patients (23%), of whom 82% were statin-treated. Patients with CT-LeSc >5 had higher mean remnant cholesterol than those with CT-LeSc <=5 (0.76 +/- 0.36 mmol/L vs. 0.58 +/- 0.33 mmol/L, p = 0.01). On univariable analysis, remnant cholesterol (p = 0.01), LDLC (p = 0.002) and HDLC (p < 0.001) levels predicted CT-LeSc >5, whilst triglycerides (p = 0.79) had no association with CT-LeSc >5. On multivariable analysis in the subset of patients with optimal LDLC levels, remnant cholesterol levels remained predictive of CT-LeSc >5 (OR 3.87, 95% confidence interval 1.34-7.55, p = 0.004), adjusted for HDLC and traditional risk factors. Conclusion(s): Remnant cholesterol levels are associated with significant coronary atherosclerotic burden as assessed by CTCA, even in patients with optimal LDLC levels. Future studies examining whether lowering of remnant cholesterol can reduce residual IHD risk are warranted.Copyright © 2019 Elsevier B.V.

Background and aims: There remains a substantial residual risk of ischaemic heart disease (IHD) despite optimal low-density lipoprotein cholesterol (LDLC) reduction. Part of this risk may be attributable to remnant cholesterol, which is carried in triglyceride-rich lipoproteins. We evaluated the relationship between remnant cholesterol and coronary atherosclerotic plaque burden assessed non-invasively by computed tomography coronary angiography (CTCA) in patients with suspected coronary artery disease (CAD). Methods and Results: This was a multicentre study of 587 patients who had a CTCA and fasting lipid profile within 3 months. Calculated remnant cholesterol was total cholesterol minus LDLC minus high-density lipoprotein cholesterol (HDLC). Significant coronary atherosclerotic burden was defined as CT-Leaman score >5 (CT-LeSc), an established predictor of cardiac events. Mean age was 61 +/- 12 years and mean pretest probability of CAD was 23.2 +/- 19.8%. LDLC levels were <1.8 mmol/L in 134 patients (23%), of whom 82% were statin-treated. Patients with CT-LeSc >5 had higher mean remnant cholesterol than those with CT-LeSc <=5 (0.76 +/- 0.36 mmol/L vs. 0.58 +/- 0.33 mmol/L, p = 0.01). On univariable analysis, remnant cholesterol (p = 0.01), LDLC (p = 0.002) and HDLC (p < 0.001) levels predicted CT-LeSc >5, whilst triglycerides (p = 0.79) had no association with CT-LeSc >5. On multivariable analysis in the subset of patients with optimal LDLC levels, remnant cholesterol levels remained predictive of CT-LeSc >5 (OR 3.87, 95% confidence interval 1.34-7.55, p = 0.004), adjusted for HDLC and traditional risk factors. Conclusion(s): Remnant cholesterol levels are associated with significant coronary atherosclerotic burden as assessed by CTCA, even in patients with optimal LDLC levels. Future studies examining whether lowering of remnant cholesterol can reduce residual IHD risk are warranted.Copyright © 2019 Elsevier B.V.

Background: Computed tomography derived fractional flow reserve (CT-FFR) and computed tomography stress myocardial perfusion imaging (CTP) are emerging techniques to assess the haemodynamic significance of coronary stenoses. Computation of CT-FFR using analysis conditions derived from structural deformation of coronary lumen and aorta and reduced order modelling has been recently described to be feasible. Comparison of diagnostic performance with visually assessed CTP is not known. Purpose(s): To compare the diagnostic performance of CT-FFR and CTP in detecting haemodynamically significant stenosis (FFR <=0.8), using invasive FFR as a reference standard. Method(s): Forty-three patients (77 vessels) with suspected coronary artery disease from a single institution planned for elective coronary angiography with invasive FFR prospectively underwent 320-detector coronary CTA and CTP. Analyses were performed in separate core laboratories for CT-FFR and CTP blinded to FFR results. For CT-FFR, deformation of coronary cross-sectional lumen and aorta, computed from diastolic CTA images, was used to determine analysis conditions based on hierarchical Bayes modelling. CT-FFR was derived using a reduced order model with dedicated software on a standard desktop computer. Myocardial perfusion was assessed visually by consensus of two interpreters. Result(s): Invasive FFR was significant in 24 (31%) vessels. CT-FFR and CTP analyses were feasible in 100% and 88% of vessels respectively. Overall pervessel sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy for CT-FFR were 79%, 85%, 70%, 90%, 83% respectively and those of CTP were 50%, 91%, 75%, 77% and 77% respectively. Among the 12 false negative vessels in CTP, FFR range was 0.65-0.80. ROC curve analysis showed a significantly larger AUC for CT-FFR (0.89) compared with that for CTP (0.71; p=0.02). Conclusion(s): Based on this cohort of patients CT-FFR is superior to CTP in detectin

Aims To compare the diagnostic performance of a reduced-order computed tomography-derived fractional flow reserve (CT-FFR) technique derived from luminal deformation and static CT stress myocardial perfusion (CTP). Methods and results Forty-six patients (84 vessels) with suspected coronary artery disease from a single institution planned for elective coronary angiography prospectively underwent research indicated invasive fractional flow reserve (FFR) and 320-detector CT coronary angiography (CTA) and static CTP. Analyses were performed in separate blinded core laboratories for CT-FFR and CTP. CT-FFR was derived using a reduced-order model with dedicated software on a standard desktop computer. CTP was assessed visually and quantitatively by transmural perfusion ratio (TPR). Invasive FFR was significant in 33% (28/84) of vessels. Overall per-vessel sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for CT-FFR were 81%, 84%, 71%, 90%, and 83%, respectively, those of visual CTP were 54%, 92%, 79%, 77%, and 78%, respectively, and TPR were 64%, 48%, 42%, 70%, and 54%, respectively. Per-vessel receiver operator curve analysis demonstrated a significantly larger area under the curve (AUC) for CT-FFR (0.89) with that for visual CTP (0.72; P = 0.016), TPR (0.55; P < 0.0001), and CTA (0.76; P = 0.04). The addition of CT-FFR to CTA provided superior improvement in performance (AUC 0.93; P < 0.0001) compared with CTA alone, a combination of CTA with visual CTP (AUC 0.82; P = 0.007) and CTA with TPR (AUC 0.78; P = 0.0006). Conclusion Based on this selected cohort of patients, a reduced-order CT-FFR technique is superior to visual and quantitatively assessed static CTP in detecting haemodynamically significant coronary stenosis as assessed by invasive FFR. All rights reserved.Copyright © The Author(s) 2018.

Background: Visual assessment of diameter-stenosis on Computed Tomography Coronary Angiography (CTCA) lacks specificity to determine functional significance of coronary artery stenosis. Percent-aggregate plaque volume (%APV) and ASLA score, which incorporates Area of Stenosis, Lesion length, and area of myocardium subtended estimated by APPROACH score (Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease) have been described to predict lesion specific ischaemia in focal lesions with intermediate stenosis. Methods and Results: Included were 81 patients (mean age 64.7 +/- 9 years, 62% male; 94 vessels) who underwent 320- detector-row CTCA, invasive coronary angiography and fractional-flow-reserve (FFR). We examined vessels with wide range of diameter stenosis (mid to severe) and with multiple lesions. Invasive FFR of <=0.8 was considered functionally significant. The first 54 patients (62 vessels) formed the derivation cohort. ASLA score was the best predictor of FFR <= 0.8 (AUC 0.83, p < 0.001) compared to %APV (0.72), CT >50% (0.76), APPROACH score (0.79), area-stenosis (0.73), diameter-stenosis (0.74), minimum-luminal-diameter (0.74), minimal-luminal-area (0.72), and lesion-length (0.67). ASLA score and not %APV, provided incremental predictive value when added to CT > 50 [(NRI 0.71, p = 0.005) vs. (NRI 0.01, p = 0.96)]. In the validation cohort of 27 patients (32 vessels), the ASLA score (AUC 0.85) was again a better predictor of FFR <= 0.8 compared to %APV (0.71), CT > 50% (0.66) and other CT indices. The AUC of ASLA score was superior to CTCA>50% (p = 0.001). Conclusion(s): ASLA score is a novel predictor of functional significance of coronary stenosis and adds incremental predictive value to CT > 50 but %APV did not.Copyright © 2018 Elsevier B.V.

Background: Computed tomography derived fractional flow reserve (CT-FFR) and computed tomography stress myocardial perfusion imaging (CTP) are emerging techniques to assess the haemodynamic significance of coronary stenoses. Computation of CT-FFR using analysis conditions derived from structural deformation of coronary lumen and aorta and reduced order modelling has been recently described to be feasible. Comparison of diagnostic performance with visually assessed CTP is not known. Purpose(s): To compare the diagnostic performance of CT-FFR and CTP in detecting haemodynamically significant stenosis (FFR <=0.8), using invasive FFR as a reference standard. Method(s): Forty-three patients (77 vessels) with suspected coronary artery disease from a single institution planned for elective coronary angiography with invasive FFR prospectively underwent 320-detector coronary CTA and CTP. Analyses were performed in separate core laboratories for CT-FFR and CTP blinded to FFR results. For CT-FFR, deformation of coronary cross-sectional lumen and aorta, computed from diastolic CTA images, was used to determine analysis conditions based on hierarchical Bayes modelling. CT-FFR was derived using a reduced order model with dedicated software on a standard desktop computer. Myocardial perfusion was assessed visually by consensus of two interpreters. Result(s): Invasive FFR was significant in 24 (31%) vessels. CT-FFR and CTP analyses were feasible in 100% and 88% of vessels respectively. Overall pervessel sensitivity, specificity, positive predictive value, negative predictive value and diagnostic accuracy for CT-FFR were 79%, 85%, 70%, 90%, 83% respectively and those of CTP were 50%, 91%, 75%, 77% and 77% respectively. Among the 12 false negative vessels in CTP, FFR range was 0.65-0.80. ROC curve analysis showed a significantly larger AUC for CT-FFR (0.89) compared with that for CTP (0.71; p=0.02). Conclusion(s): Based on this cohort of patients CT-FFR is superior to CTP in detectin

Aims To compare the diagnostic performance of a reduced-order computed tomography-derived fractional flow reserve (CT-FFR) technique derived from luminal deformation and static CT stress myocardial perfusion (CTP). Methods and results Forty-six patients (84 vessels) with suspected coronary artery disease from a single institution planned for elective coronary angiography prospectively underwent research indicated invasive fractional flow reserve (FFR) and 320-detector CT coronary angiography (CTA) and static CTP. Analyses were performed in separate blinded core laboratories for CT-FFR and CTP. CT-FFR was derived using a reduced-order model with dedicated software on a standard desktop computer. CTP was assessed visually and quantitatively by transmural perfusion ratio (TPR). Invasive FFR was significant in 33% (28/84) of vessels. Overall per-vessel sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for CT-FFR were 81%, 84%, 71%, 90%, and 83%, respectively, those of visual CTP were 54%, 92%, 79%, 77%, and 78%, respectively, and TPR were 64%, 48%, 42%, 70%, and 54%, respectively. Per-vessel receiver operator curve analysis demonstrated a significantly larger area under the curve (AUC) for CT-FFR (0.89) with that for visual CTP (0.72; P = 0.016), TPR (0.55; P < 0.0001), and CTA (0.76; P = 0.04). The addition of CT-FFR to CTA provided superior improvement in performance (AUC 0.93; P < 0.0001) compared with CTA alone, a combination of CTA with visual CTP (AUC 0.82; P = 0.007) and CTA with TPR (AUC 0.78; P = 0.0006). Conclusion Based on this selected cohort of patients, a reduced-order CT-FFR technique is superior to visual and quantitatively assessed static CTP in detecting haemodynamically significant coronary stenosis as assessed by invasive FFR. All rights reserved.Copyright © The Author(s) 2018.

Epidemiological studies observed a higher prevalence of coronary atherosclerosis in South Asians when compared to Caucasians, but quantitative computed tomography differences in aggregate plaque volume (APV) and epicardial fat volume (EFV) between South Asians, Southeast or East Asians (SEEAs) and Caucasians remain unknown. We aimed to compare APV and EFV quantified on computed-tomographic-coronary-angiography (CTCA) between South Asian, SEEA and Caucasian populations residing in Australia. Age, gender and body-mass-index matched subjects from three ethnic groups who underwent clinically indicated 320-detector CTCA were retrospectively analysed. Percentage APV in the first 5 cm of the left anterior descending artery (LAD) and EFV were quantified using dedicated software (Vital Images, USA). One-hundred-and-fifty subjects (average age = 57.7 years, 56 % male, n = 50 in each ethnic group) were analysed. Mean LAD percentage APV was highest in South Asians (44.5 +/- 8.4 % vs. 37.5 +/- 6.5 % in SEEAs and 39.5 +/- 6.4 % in Caucasians, P = 0.00001). South Asian ethnicity predicted LAD APV above traditional risk factors on multivariate analysis (P = 0.000002). EFV was significantly higher in both South Asians (103.2 +/- 41.7 cm3 vs. 85.8 +/- 39.4 cm3, P = 0.035) and SEEAs (110.8 +/- 36.9 cm3 vs. 85.8 +/- 39.4 cm3, P = 0.001) when compared with Caucasians. In this cohort LAD percentage APV and EFV, as quantified on CTCA, differs between South Asians, SEEA and Caucasian populations, with higher LAD APV observed in South Asians and lower EFV in Caucasians. Atherosclerotic volume in LAD was best predicted by South Asian ethnicity above traditional risk factors and EFV. Further research is required to establish whether APV and EFV quantification can improve cardiac risk prediction in the South Asian population.Copyright © 2016, Springer Science+Business Media Dordrecht.

Objectives This study describes the feasibility and accuracy of a novel computed tomography (CT) fractional flow reserve (FFR) technique based on alternative boundary conditions. Background Techniques used to compute FFR based on images acquired from coronary computed tomography angiography (CTA) are described. Boundary conditions were typically determined by allometric scaling laws and assumptions regarding microvascular resistance. Alternatively, boundary conditions can be derived from the structural deformation of coronary lumen and aorta, although its accuracy remains unknown. Methods Forty-two patients (78 vessels) in a single institution prospectively underwent 320-detector coronary CTA and FFR. Deformation of coronary cross-sectional lumen and aorta, computed from coronary CTA images acquired over diastole, was used to determine the boundary conditions based on hierarchical Bayes modeling. CT-FFR was derived using a reduced order model performed using a standard desktop computer and dedicated software. First, 12 patients (20 vessels) formed the derivation cohort to determine optimal CT-FFR threshold with which to detect functional stenosis, defined as FFR of <=0.8, which was validated in the subsequent 30 patients (58 vessels). Results Derivation cohort results demonstrated optimal threshold for CT-FFR was 0.8 with 67% sensitivity and 91% specificity. In the validation cohort, CT-FFR was successfully computed in 56 of 58 vessels (97%). Compared with coronary CTA, CT-FFR at <=0.8 demonstrated a higher specificity (87% vs. 74%, respectively) and positive predictive value (74% vs. 60%, respectively), with comparable sensitivity (78% vs. 79%, respectively), negative predictive value (89% vs. 88%, respectively), and accuracy (area under the curve: 0.88 vs. 0.77, respectively; p = 0.22). Based on Bland-Altman analysis, mean intraobserver and interobserver variability values for CT-FFR were, respectively, -0.02 +/- 0.05 (95% limits of agreement: -0.12 to 0.08) and 0

Epidemiological studies observed a higher prevalence of coronary atherosclerosis in South Asians when compared to Caucasians, but quantitative computed tomography differences in aggregate plaque volume (APV) and epicardial fat volume (EFV) between South Asians, Southeast or East Asians (SEEAs) and Caucasians remain unknown. We aimed to compare APV and EFV quantified on computed-tomographic-coronary-angiography (CTCA) between South Asian, SEEA and Caucasian populations residing in Australia. Age, gender and body-mass-index matched subjects from three ethnic groups who underwent clinically indicated 320-detector CTCA were retrospectively analysed. Percentage APV in the first 5 cm of the left anterior descending artery (LAD) and EFV were quantified using dedicated software (Vital Images, USA). One-hundred-and-fifty subjects (average age = 57.7 years, 56 % male, n = 50 in each ethnic group) were analysed. Mean LAD percentage APV was highest in South Asians (44.5 +/- 8.4 % vs. 37.5 +/- 6.5 % in SEEAs and 39.5 +/- 6.4 % in Caucasians, P = 0.00001). South Asian ethnicity predicted LAD APV above traditional risk factors on multivariate analysis (P = 0.000002). EFV was significantly higher in both South Asians (103.2 +/- 41.7 cm3 vs. 85.8 +/- 39.4 cm3, P = 0.035) and SEEAs (110.8 +/- 36.9 cm3 vs. 85.8 +/- 39.4 cm3, P = 0.001) when compared with Caucasians. In this cohort LAD percentage APV and EFV, as quantified on CTCA, differs between South Asians, SEEA and Caucasian populations, with higher LAD APV observed in South Asians and lower EFV in Caucasians. Atherosclerotic volume in LAD was best predicted by South Asian ethnicity above traditional risk factors and EFV. Further research is required to establish whether APV and EFV quantification can improve cardiac risk prediction in the South Asian population.Copyright © 2016, Springer Science+Business Media Dordrecht.

Objectives This study describes the feasibility and accuracy of a novel computed tomography (CT) fractional flow reserve (FFR) technique based on alternative boundary conditions. Background Techniques used to compute FFR based on images acquired from coronary computed tomography angiography (CTA) are described. Boundary conditions were typically determined by allometric scaling laws and assumptions regarding microvascular resistance. Alternatively, boundary conditions can be derived from the structural deformation of coronary lumen and aorta, although its accuracy remains unknown. Methods Forty-two patients (78 vessels) in a single institution prospectively underwent 320-detector coronary CTA and FFR. Deformation of coronary cross-sectional lumen and aorta, computed from coronary CTA images acquired over diastole, was used to determine the boundary conditions based on hierarchical Bayes modeling. CT-FFR was derived using a reduced order model performed using a standard desktop computer and dedicated software. First, 12 patients (20 vessels) formed the derivation cohort to determine optimal CT-FFR threshold with which to detect functional stenosis, defined as FFR of <=0.8, which was validated in the subsequent 30 patients (58 vessels). Results Derivation cohort results demonstrated optimal threshold for CT-FFR was 0.8 with 67% sensitivity and 91% specificity. In the validation cohort, CT-FFR was successfully computed in 56 of 58 vessels (97%). Compared with coronary CTA, CT-FFR at <=0.8 demonstrated a higher specificity (87% vs. 74%, respectively) and positive predictive value (74% vs. 60%, respectively), with comparable sensitivity (78% vs. 79%, respectively), negative predictive value (89% vs. 88%, respectively), and accuracy (area under the curve: 0.88 vs. 0.77, respectively; p = 0.22). Based on Bland-Altman analysis, mean intraobserver and interobserver variability values for CT-FFR were, respectively, -0.02 +/- 0.05 (95% limits of agreement: -0.12 to 0.08) and 0

AIM: To assess the accuracy of Computed-Tomography-Coronary- Angiography (CTCA) derived quantitative plaque analysis using Intravascular-Ultrasound (IVUS) as reference standard. METHOD(S): Patients who underwent IVUS and CTCA within a 3-month period at MonashHEART between October-2008 and December-2013 were retrospectively studied. Core-lab analysis was performed on all IVUS and CTCA datasets. CT images were analyzed using SurePlaquesoftware. Luminal (LCSA), vessel-cross-sectional-area (VCSA) and plaque volume (PV), defined as (VCSA-LCSA)/VCSA were manually quantified on IVUS and CTCA at 0.5mm cross-sections on all interrogated vessels. Bland-Altman analysis was performed to assess the agreement of measurements between IVUS and CTCA. Data is expressed as mean +/- standard error of mean (SEM), and two-tailed p<0.05 was accepted as significant. RESULT(S): Thirty-two vessels (23 patients), including 513 cross-sections were analyzed (left-main n=9, left-anterior-descending n=16, left-circumflex n=4 and right-coronaryartery n=3). Un-interpretable-segments, segments without fiduciarypoints and seven patients with poor CT images were excluded. There was no significant mean difference in LCSA (0.08 +/- 0.08mm2, p=0.33), VSCA (0.06 +/- 0.12 mm2, p=0.65 or PV (0.03+/-0.06mm3, p=0.64) as quantified by IVUS and CTCA. The agreement between IVUS and CTCA for PV was better in non-calcified vessels (0.12 +/- 0.07mm3) compared to calcified vessels (0.19 +/- 0.9mm3). There was no significant difference in per-patient total-atheroma-volume measured on IVUS and CTCA (3.4 +/- 2.1mm3, p=0.12). CONCLUSION(S): Quantification of coronary-luminal-area and plaque volume using CTCA is highly accurate when compared with IVUS. Observed difference in plaque volumes was lower in non-calcified plaque. CTCA has the potential accurately monitor coronary plaque progression and regression non-invasively.

BACKGROUND: Epicardial fat is considered a local promoter of coronary atherosclerosis and is associated with burden of coronary plaque and acute-coronary- syndromes. We sought to verify the association between epicardial-fat-volume (EFV) and coronary-arterystenosis assessed by computed-tomography. METHOD(S): Patients with suspected coronary-artery-disease undergoing 320-detector-rowcomputed- tomography-coronary-angiography (CTCA) at MonashHeart (2009-2012) were assessed for EFV and coronary stenosis. Epicardial fat was manually traced and automatically quantified by software that detects fat as voxels with Hounsfield-unit between -200 and -50. Two, blinded experienced cardiologists qualitatively assessed coronary stenosis. Univariate and multivariate binary-logistic-regression was performed. Only univariate predictors with p<0.25 were included in the multivariate-analysis. Statistically significance was defined as p<0.05. RESULT(S): We examined 92 patients (61.7+/-12.1 years, 60% male). Mean EFV in all patients was 86.4+/-38.7 ml. The intra and interobserver variability was excellent; 2.7+/-1.8ml (p=0.19) and 0.87+/-3.0 ml (p=0.78) respectively. The mean duration for EFV quantification was between 5-10 minutes. Patients with coronary-stenosis (n=76) had higher EFV compared to patients with no coronary-stenosis (90.1+/-4.5 vs. 67.5+/-7.5, p=0.032). Furthermore, patients with significant (>50%) stenosis (n=25) had higher EFV than patients with no significant (n=67) stenosis (107.6+/-7.3ml vs. 78.1+/-4.4ml, p=0.001). On univariateanalysis, age (p=0.17), obesity (p=0.6), hypertension (p=0.32), hyperlipidaemia (p-0.08) and diabetes (p=0.1) were not associated with significant coronary-stenosis. On multivariate-analysis EFV was independently associated with significant coronary-stenosis (p=0.003). CONCLUSION(S): EFV is independently associated with significant coronary-artery-stenosis. If confirmed in larger studies with long term outcomes, quantification and reporting of

AIM: To assess the accuracy of Computed-Tomography-Coronary- Angiography (CTCA) derived quantitative plaque analysis using Intravascular-Ultrasound (IVUS) as reference standard. METHOD(S): Patients who underwent IVUS and CTCA within a 3-month period at MonashHEART between October-2008 and December-2013 were retrospectively studied. Core-lab analysis was performed on all IVUS and CTCA datasets. CT images were analyzed using SurePlaquesoftware. Luminal (LCSA), vessel-cross-sectional-area (VCSA) and plaque volume (PV), defined as (VCSA-LCSA)/VCSA were manually quantified on IVUS and CTCA at 0.5mm cross-sections on all interrogated vessels. Bland-Altman analysis was performed to assess the agreement of measurements between IVUS and CTCA. Data is expressed as mean +/- standard error of mean (SEM), and two-tailed p<0.05 was accepted as significant. RESULT(S): Thirty-two vessels (23 patients), including 513 cross-sections were analyzed (left-main n=9, left-anterior-descending n=16, left-circumflex n=4 and right-coronaryartery n=3). Un-interpretable-segments, segments without fiduciarypoints and seven patients with poor CT images were excluded. There was no significant mean difference in LCSA (0.08 +/- 0.08mm2, p=0.33), VSCA (0.06 +/- 0.12 mm2, p=0.65 or PV (0.03+/-0.06mm3, p=0.64) as quantified by IVUS and CTCA. The agreement between IVUS and CTCA for PV was better in non-calcified vessels (0.12 +/- 0.07mm3) compared to calcified vessels (0.19 +/- 0.9mm3). There was no significant difference in per-patient total-atheroma-volume measured on IVUS and CTCA (3.4 +/- 2.1mm3, p=0.12). CONCLUSION(S): Quantification of coronary-luminal-area and plaque volume using CTCA is highly accurate when compared with IVUS. Observed difference in plaque volumes was lower in non-calcified plaque. CTCA has the potential accurately monitor coronary plaque progression and regression non-invasively.

BACKGROUND: Epicardial fat is considered a local promoter of coronary atherosclerosis and is associated with burden of coronary plaque and acute-coronary- syndromes. We sought to verify the association between epicardial-fat-volume (EFV) and coronary-arterystenosis assessed by computed-tomography. METHOD(S): Patients with suspected coronary-artery-disease undergoing 320-detector-rowcomputed- tomography-coronary-angiography (CTCA) at MonashHeart (2009-2012) were assessed for EFV and coronary stenosis. Epicardial fat was manually traced and automatically quantified by software that detects fat as voxels with Hounsfield-unit between -200 and -50. Two, blinded experienced cardiologists qualitatively assessed coronary stenosis. Univariate and multivariate binary-logistic-regression was performed. Only univariate predictors with p<0.25 were included in the multivariate-analysis. Statistically significance was defined as p<0.05. RESULT(S): We examined 92 patients (61.7+/-12.1 years, 60% male). Mean EFV in all patients was 86.4+/-38.7 ml. The intra and interobserver variability was excellent; 2.7+/-1.8ml (p=0.19) and 0.87+/-3.0 ml (p=0.78) respectively. The mean duration for EFV quantification was between 5-10 minutes. Patients with coronary-stenosis (n=76) had higher EFV compared to patients with no coronary-stenosis (90.1+/-4.5 vs. 67.5+/-7.5, p=0.032). Furthermore, patients with significant (>50%) stenosis (n=25) had higher EFV than patients with no significant (n=67) stenosis (107.6+/-7.3ml vs. 78.1+/-4.4ml, p=0.001). On univariateanalysis, age (p=0.17), obesity (p=0.6), hypertension (p=0.32), hyperlipidaemia (p-0.08) and diabetes (p=0.1) were not associated with significant coronary-stenosis. On multivariate-analysis EFV was independently associated with significant coronary-stenosis (p=0.003). CONCLUSION(S): EFV is independently associated with significant coronary-artery-stenosis. If confirmed in larger studies with long term outcomes, quantification and reporting of