Journal of Cardiovascular Computed Tomography

2021

DOI: 10.1016/j.jcct.2020.11.002

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Society of Cardiovascular Computed Tomography / North American Society of Cardiovascular Imaging – Expert Consensus Document on Coronary CT Imaging of Atherosclerotic Plaque

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Cited by 156 publications

(86 citation statements)

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“…This includes the presence of high-risk plaque features such as NCP, LD-NCP and PR that qualitatively portend, by SCCT expert consensus, a future risk of cardiovascular events. 21 Importantly, AI identified a higher PAV of LD-NCP in younger individuals with non-obstructive atherosclerosis, a plaque type identified as highest risk by cardiac CT. 22 These data affirm prior findings that younger patients have high volumes of non-calcified atherosclerosis with a higher degree of LD-NCP, while older patients develop a higher degree of calcified plaque in both non-obstructive and obstructive lesions. 22 Lowenstern et al ’s subanalysis of the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) study also supports the finding that older patients have more calcified plaque.…”

Section: Discussionmentioning

confidence: 96%

Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence

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ObjectiveThe study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT).MethodsThis is a post-hoc analysis of data from 303 subjects enrolled in the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial who were referred for invasive coronary angiography and subsequently underwent coronary computed tomographic angiography (CCTA). In this study, a blinded core laboratory analysing quantitative coronary angiography images classified lesions as obstructive (≥50%) or non-obstructive (<50%) while AI software quantified APCs including plaque volume (PV), low-density non-calcified plaque (LD-NCP), non-calcified plaque (NCP), calcified plaque (CP), lesion length on a per-patient and per-lesion basis based on CCTA imaging. Plaque measurements were normalised for vessel volume and reported as % percent atheroma volume (%PAV) for all relevant plaque components. Data were subsequently stratified by age <65 and ≥65 years.ResultsThe cohort was 64.4±10.2 years and 29% women. Overall, patients >65 had more PV and CP than patients <65. On a lesion level, patients >65 had more CP than younger patients in both obstructive (29.2 mm3 vs 48.2 mm3; p<0.04) and non-obstructive lesions (22.1 mm3 vs 49.4 mm3; p<0.004) while younger patients had more %PAV (LD-NCP) (1.5% vs 0.7%; p<0.038). Younger patients had more PV, LD-NCP, NCP and lesion lengths in obstructive compared with non-obstructive lesions. There were no differences observed between lesion types in older patients.ConclusionAI-QCT identifies a unique APC signature that differs by age and degree of stenosis and provides a foundation for AI-guided age-based approaches to atherosclerosis identification, prevention and treatment.

“…This includes the presence of high-risk plaque features such as NCP, LD-NCP and PR that qualitatively portend, by SCCT expert consensus, a future risk of cardiovascular events. 21 Importantly, AI identified a higher PAV of LD-NCP in younger individuals with non-obstructive atherosclerosis, a plaque type identified as highest risk by cardiac CT. 22 These data affirm prior findings that younger patients have high volumes of non-calcified atherosclerosis with a higher degree of LD-NCP, while older patients develop a higher degree of calcified plaque in both non-obstructive and obstructive lesions. 22 Lowenstern et al ’s subanalysis of the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) study also supports the finding that older patients have more calcified plaque.…”

Section: Discussionmentioning

confidence: 96%

Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence

¹

,

³

et al. 2021

Self Cite

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ObjectiveThe study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT).MethodsThis is a post-hoc analysis of data from 303 subjects enrolled in the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial who were referred for invasive coronary angiography and subsequently underwent coronary computed tomographic angiography (CCTA). In this study, a blinded core laboratory analysing quantitative coronary angiography images classified lesions as obstructive (≥50%) or non-obstructive (<50%) while AI software quantified APCs including plaque volume (PV), low-density non-calcified plaque (LD-NCP), non-calcified plaque (NCP), calcified plaque (CP), lesion length on a per-patient and per-lesion basis based on CCTA imaging. Plaque measurements were normalised for vessel volume and reported as % percent atheroma volume (%PAV) for all relevant plaque components. Data were subsequently stratified by age <65 and ≥65 years.ResultsThe cohort was 64.4±10.2 years and 29% women. Overall, patients >65 had more PV and CP than patients <65. On a lesion level, patients >65 had more CP than younger patients in both obstructive (29.2 mm3 vs 48.2 mm3; p<0.04) and non-obstructive lesions (22.1 mm3 vs 49.4 mm3; p<0.004) while younger patients had more %PAV (LD-NCP) (1.5% vs 0.7%; p<0.038). Younger patients had more PV, LD-NCP, NCP and lesion lengths in obstructive compared with non-obstructive lesions. There were no differences observed between lesion types in older patients.ConclusionAI-QCT identifies a unique APC signature that differs by age and degree of stenosis and provides a foundation for AI-guided age-based approaches to atherosclerosis identification, prevention and treatment.

“…who were blinded to clinical and CT data. Plaque characteristics were defined in accordance with the Society of Cardiovascular CT. [ 13 ] Significant coronary artery stenosis was defined by a cross-sectional narrowing of >50%. The vascular remodeling index was calculated by dividing the cross-sectional lesion vessel area by the proximal reference vessel area.…”

Section: Methodsmentioning

confidence: 99%

Association between higher pericoronary adipose tissue attenuation measured by coronary computed tomography angiography and nonalcoholic fatty liver disease

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Non-alcoholic fatty liver disease (NAFLD) is a risk factor for cardiac mortality. Pericoronary adipose tissue (PCAT) attenuation, expressed by the fat attenuation index on coronary computed tomography angiography, reflects pericoronary inflammation. We aimed to investigate the association between PCAT attenuation and NAFLD. This is a single-center cohort study comprising of patients who underwent coronary computed tomography angiography for suspected stable coronary artery disease between January and December 2020. Patient characteristics and coronary computed tomography angiography findings were analyzed between patients with NAFLD (n = 78) and a propensity score-matched cohort of patients without NAFLD (n = 78). PCAT attenuation was assessed in Hounsfield units (HU) of proximal 40-mm segments of the left anterior descending artery (LAD) and right coronary artery. The mean PCAT attenuation in LAD and right coronary artery were significantly higher in patients with NAFLD than those without NAFLD. When patients were divided into 2 groups using the median LAD-PCAT attenuation of −72.5 HU, the high PCAT attenuation group had more males (82% vs 67%, P = .028) and NAFLD patients (63% vs 37%, P = .001) compared to the low PCAT attenuation group. No differences in age, body mass index, conventional cardiovascular risk factors, or the presence of high-risk plaque were observed between the 2 groups. In the multivariate logistic analysis, NAFLD was independently associated with high PCAT attenuation (odds ratio 2.912, 95% confidence interval 1.386 to 6.118, P = .005). NAFLD is associated with high PCAT attenuation on coronary computed tomography angiography. This finding suggests that pericoronary inflammation is involved in the increased cardiac mortality in NAFLD patients.

“…Lesions yielding >50% luminal stenosis were considered obstructive. Both multivessel disease and obstructive disease portend high cardiovascular event risk (35). Plaque composition was identified as noncalcified, mixed, or calcified, as described in a previous study (36).…”

Section: Methodsmentioning

confidence: 99%

Epicardial Adipose Tissue Volume As a Marker of Subclinical Coronary Atherosclerosis in Rheumatoid Arthritis

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Arthritis & Rheumatology

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Objective. To assess epicardial adipose tissue volume (EATV) and its link to coronary atherosclerosis and plaque morphology in patients with rheumatoid arthritis (RA) and in age-and sex-matched controls.Methods. Computed tomography angiography was used to evaluate EATV and coronary plaque in 139 RA patients and 139 non-RA controls. All models assessing the effect of EATV on plaque were adjusted for age, sex, hypertension, diabetes, dyslipidemia, smoking status, family history of coronary artery disease, and obesity (body mass index of ≥30 kg/m 2 ). Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated.Results. Mean ± SD log-transformed EATV was similar in patients with RA (4.69 ± 0.36) and controls (4.70 ± 0.42). EATV was higher in RA patients with atherosclerosis compared to those without atherosclerosis (P = 0.046). In stratified analyses, EATV was associated with the number of segments with plaque in RA patients (rate ratio 1.20 [95% CI 1.01-1.41] per 1-SD increment of log-unit increase in EATV) but not in controls (P for interaction = 0.089). Likewise, EATV (per 1-SD log-unit increase) was related to the presence of multivessel or obstructive disease (OR 1.63 [95% CI 1.04-2.61]), noncalcified plaque (OR 1.78 [95% CI 1.17-2.70]), and vulnerable plaque (OR 1.77 [95% CI 1.03-3.04]) in RA patients but not in controls (P for interaction ≤ 0.048 for each). Among RA patients, EATV was associated with the number of segments with plaque in those with RA for <10 years who did not develop any cardiovascular risk factors and who were not obese (P for interaction ≤ 0.017).Conclusion. Despite similar EATVs in RA patients and controls, EATVs were associated with greater plaque burden and presence of plaques with a noncalcified component and vulnerability features only in RA patients. EAT may be more pathogenic in RA and play a role in early-stage atherosclerosis. Its value as a biomarker of subclinical atherosclerosis and cardiovascular risk in RA warrants further studies.

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