Machine learning combining clinical and CCTA data was found to predict 5-year ACM significantly better than existing clinical or CCTA metrics alone.

Ischemic MPS is associated with a high likelihood of subclinical atherosclerosis by CAC, but is rarely seen for CAC scores <100. In most patients, low CAC scores appear to obviate the need for subsequent noninvasive testing. Normal MPS patients, however, frequently have extensive atherosclerosis by CAC criteria. These findings imply a potential role for applying CAC screening after MPS among patients manifesting normal MPS.

Normal limits of ascending and descending aortic dimensions by noncontrast gated cardiac CT have been defined by age, gender, and BSA in a large, low-risk population of subjects undergoing CAC scanning.

Although ACS increases with %DS, most precursors of ACS cases and culprit lesions are nonobstructive. Plaque evaluation, including HRP, PB, and plaque composition, identifies high-risk patients above and beyond stenosis severity and aggregate plaque burden.

Over the past 2 decades, the frequency and severity of abnormal stress SPECT-MPI studies has progressively decreased. Notably, the frequency of abnormal SPECT-MPI is now very low among exercising patients without typical angina. These findings suggest the need for developing more cost-effective strategies for the initial work-up of patients who are presently at low risk for manifesting inducible myocardial ischemia during cardiac imaging procedures.

Background Pericardial fat volume (PFV) and thoracic fat volume (TFV) can be routinely measured from noncontrast CT (NCT) performed for calculating coronary calcium score (CCS) and may predict major adverse cardiovascular event (MACE) risk. Methods From a registry of 2751 asymptomatic patients without known CAD and 4-year follow-up for MACE (cardiac death, myocardial infarction, stroke, late revascularization) after NCT, we compared 58 patients with MACE (“EVENTS”) to 174 same-sex event-free controls matched by a propensity score to account for age, risk factors, and CCS. TFV was automatically calculated, and PFV was calculated with manual assistance in defining the pericardial contour, within which fat voxels were automatically identified. Independent relationships of PFV and TFV to MACE were evaluated using conditional multivariable logistic regression. Results EVENTS had higher mean PFV (101.8±49.2 cm3 vs. 84.9±37.7 cm3, p=0.007) and TFV (204.7±90.3 cm3 vs. 177±80.3 cm3, p=0.029) and higher frequencies of PFV>125 cm3 (33% vs. 14%, p=0.002) and TFV>250 cm3 (31% vs. 17%, p=0.025). After adjusting for Framingham Risk Score, CCS, and body-mass-index, PFV and TFV were significantly associated with MACE (odds ratio (OR) 1.74, 95%CI 1.03–2.95 for each doubling of PFV; OR 1.78, 95%CI 1.01–3.14 for TFV). Areas-under-the-curve from receiver operating characteristic analyses showed a trend of improved MACE prediction when PFV was added to FRS and CCS (0.73 vs 0.68, p=0.058). Addition of PFV, but not TFV, to FRS and CCS improved estimated specificity (0.72 vs 0.66, p=0.008) and overall accuracy (0.70 vs 0.65, p=0.009) in predicting MACE. Conclusion Asymptomatic patients who experience MACE exhibit greater PFV on pre-MACE NCT when compared to event-free controls with similar cardiovascular risk profiles. Our preliminary findings suggest that PFV may help improve prediction of MACE.

Objective We evaluated the association between atherosclerotic plaque characteristics (APCs) by coronary CT angiography (CT) and lesion ischemia by fractional flow reserve (FFR). Background FFR is the gold standard for determining lesion ischemia. While APCs by CT—including aggregate plaque volume % (%APV), positive remodeling (PR), low attenuation plaque (LAP) and spotty calcification (SC)—are associated with future coronary syndromes, their relationship to lesion ischemia is unclear. Methods 252 patients (17 centers, 5 countries) [mean age 63 years, 71% males] underwent CT, with FFR performed for 407 coronary lesions. CT was interpreted for < and >50% stenosis, with the latter considered obstructive. APCs by CT were defined as: (1) PR, lesion diameter/reference diameter >1.10; (2) LAP, any voxel <30 HU; and (3) SC, nodular calcified plaque <3 mm. Odds ratios (OR) and net reclassification improvement (NRI) of APCs for lesion ischemia, defined by FFR <0.8, were analyzed. Results By FFR, ischemia was present in 151 lesions (37%). %APV was associated with a 10% increased risk of ischemia per 5% additional APV. PR, LAP and SC were associated with ischemia, with a 3-5 times higher prevalence than in non-ischemic lesions. In multivariable analyses, a stepwise increased risk of ischemia was observed for 1 [OR 4.5, p<0.001)] and ≥2 (OR 13.2, p<0.001) APCs. These findings were APC-dependent, with PR (OR 5.4, p<0.001) and LAP (OR 2.2, p=0.028) associated with ischemia, but not SC. When examined by stenosis severity, PR remained a predictor of ischemia for all lesions, while %APV and LAP were associated with ischemia for only >50% but not for <50% stenosis. Conclusions %APV and APCs by CT improve identification of coronary lesions that cause ischemia. PR is associated with all ischemia-causing lesions, while %APV and LAP are only associated with ischemia-causing lesions >50%.

IMPORTANCE Pericoronary adipose tissue (PCAT) computed tomography (CT) attenuation measured from coronary CT angiography (CTA) may be a promising metric in identifying high-risk plaques. OBJECTIVE To determine whether high-risk plaque characteristics from coronary CTA are associated with PCAT CT attenuation in patients with a first acute coronary syndrome (ACS) and matched controls with stable coronary artery disease (CAD). DESIGN, SETTING, AND PARTICIPANTSThis retrospective, single-center case-control study (data were acquired at the University of Erlangen from 2009-2010) analyzed the CTA data sets of 19 patients who presented with ACS and 16 controls with stable CAD who were matched based on sex, age, and risk factors. Study observers were blinded to patients' clinical data. Semiautomated software was used to quantify and characterize plaques. The CT attenuation (Hounsfield unit [HU]) of PCAT was automatically measured around all lesions. MAIN OUTCOMES AND MEASURES To investigate the association between high-risk plaque characteristics from CTA and PCAT CT attenuation as a novel surrogate measure of coronary inflammation. RESULTS A total of 35 patients (mean [SD] age, 59.5 [11.3] years; 30 men [86%] and 5 women [14%]) were included in the analysis. Low-and intermediate-attenuation noncalcified plaque (NCP) burden were increased in culprit lesions (n = 19) compared with both nonculprit lesions (n = 55) in patients with ACS (12.6% vs 3.6%; P < .001; 38.4% vs 19.4%; P < .001) and the control group's highest-grade stenosis lesions (n = 16) (12.6% vs 5.6%; P = .002; 38.4% vs 22.1%; P < .001). Pericoronary adipose tissue attenuation was increased around culprit lesions (n = 19) compared with nonculprit lesions (n = 55) in patients with ACS (−69.1 HU vs −74.8 HU; P = .01) and highest-grade stenosis lesions in control patients (n = 16) (−69.1 HU vs −76.4 HU; P = .01). Pericoronary adipose tissue CT attenuation of all lesions in patients with ACS (n = 74) correlated more strongly with intermediate-attenuation (r = 0.393; P = .001) over low-attenuation (r = 0.221; P = .06) and high-attenuation NCP burden (r = −0.103; P = .38). In a multivariable analysis, low-and intermediate-attenuation NCP burden and PCAT CT attenuation were independently associated with the presence of culprit lesions (P < .05). CONCLUSIONS AND RELEVANCE Pericoronary CT attenuation was increased around culprit lesions compared with nonculprit lesions of patients with ACS and the lesions of matched controls. Combined quantitative high-risk plaque features and PCAT CT attenuation may allow for a more reliable identification of vulnerable plaques.