Perivascular fat attenuation for predicting adverse cardiac events in stable patients undergoing invasive coronary angiography

Effect of Vessel Attenuation, VMI Level, and Reconstruction Kernel on Pericoronary Adipose Tissue Attenuation for EID CT and PCD CT: An Ex Vivo Porcine Heart Study

Background: Pericoronary adipose tissue (PCAT) attenuation and fat attenuation index (FAI) may serve as markers of inflammation and risk of adverse cardiac events. However, standardization of relevant CT acquisition and reconstruction parameters is lacking. Objective: To investigate the influence of vessel attenuation, virtual monoenergetic image (VMI) level, and reconstruction kernel on PCAT attenuation and FAI using energy-integrating detector (EID) and photon-counting detector (PCD) CT systems in an ex-vivo porcine heart model. Methods: A porcine heart's right coronary artery (RCA) was injected with saline or varying contrast media dilutions to achieve vessel attenuations ranging from 0 to 1000 HU. After each injection, the heart was scanned with EID CT at 120 kVp and PCD CT at 140 kVp, at constant CTDIvol (10 mGy). For EID CT, polychromatic images were reconstructed with Qr40 kernel. For PCD CT, VMI (40-80 keV at 10-keV increments) were reconstructed with Qr40, Bv40, and Bv56 kernels. ROIs were placed to measure RCA and PCAT attenuation. FAI was determined using software; histogram analysis was performed of voxel attenuations in the volumes of interest for FAI calculation. Results: Correlations were observed between attenuation in the RCA and adjacent PCAT (r=0.3-1.0), and between vessel attenuation and FAI (r=-0.9-1.0). For PCAT attenuation and FAI, these associations became progressively weaker for progressively sharper kernels. For increasing vessel attenuation for EID CT and for increasing VMI level for PCD CT, FAI histograms showed right shifts of the peak attenuation; the percentage of histogram voxels meeting the threshold range for inclusion in FAI calculation for EID CT was 8-29% and for PCD CT at VMI levels of 70-80 keV was 5-42%. For PCD CT, sharper kernels were associated with left shifts in peak attenuations and greater percentages of voxels within the threshold range for inclusion in FAI calculations. Conclusion: PCAT attenuation and FAI are influenced by vessel lumen attenuation, VMI level, and reconstruction kernel. A minority of pericoronary voxels contribute to FAI measurements for polychromatic EID CT and for PCD CT at high VMI levels. Clinical Impact: These findings may help standardize acquisition and reconstruction parameters for PCAT attenuation and FAI measurements.

Association Between Automated 3D Measurement of Coronary Luminal Narrowing and Risk of Future Myocardial Infarction

This study focuses on identifying anatomical markers with predictive capacity for long-term myocardial infarction (MI) in focal coronary artery disease (CAD). Eighty future culprit lesions (FCL) and 108 non-culprit lesions (NCL) from 80 patients underwent 3D quantitative coronary angiography. The minimum lumen area (MLA), minimum lumen ratio (MLR), and vessel fractional flow reserve (vFFR) were evaluated. MLR was defined as the ratio between MLA and the cross-sectional area at the proximal lesion edge, with lower values indicating more abrupt luminal narrowing. Significant differences were observed between FCL and NCL in MLR (0.41 vs. 0.53, p < 0.001). MLR correlated inversely with translesional vFFR (r =  - 0.26, p = 0.0004) and was the strongest predictor of MI at 5 years (AUC = 0.75). Lesions with MLR < 0.40 had a fourfold increased MI incidence at 5 years. MLR is a robust predictor of future adverse coronary events.

A cloud-based medical device for predicting cardiac risk in suspected coronary artery disease: a rapid review and conceptual economic model

Background

The CaRi-Heart® device estimates risk of 8-year cardiac death, using a prognostic model, which includes perivascular fat attenuation index, atherosclerotic plaque burden and clinical risk factors.

Objectives

To provide an Early Value Assessment of the potential of CaRi-Heart Risk to be an effective and cost-effective adjunctive investigation for assessment of cardiac risk, in people with stable chest pain/suspected coronary artery disease, undergoing computed tomography coronary angiography. This assessment includes conceptual modelling which explores the structure and evidence about parameters required for model development, but not development of a full executable cost-effectiveness model.

Data sources

Twenty-four databases, including MEDLINE, MEDLINE In-Process and EMBASE, were searched from inception to October 2022.

Methods

Review methods followed published guidelines. Study quality was assessed using Prediction model Risk Of Bias ASsessment Tool. Results were summarised by research question: prognostic performance; prevalence of risk categories; clinical effects; costs of CaRi-Heart. Exploratory searches were conducted to inform conceptual cost-effectiveness modelling.

Results

The only included study indicated that CaRi-Heart Risk may be predictive of 8 years cardiac death. The hazard ratio, per unit increase in CaRi-Heart Risk, adjusted for smoking, hypercholesterolaemia, hypertension, diabetes mellitus, Duke index, presence of high-risk plaque features and epicardial adipose tissue volume, was 1.04 (95% confidence interval 1.03 to 1.06) in the model validation cohort. Based on Prediction model Risk Of Bias ASsessment Tool, this study was rated as having high risk of bias and high concerns regarding its applicability to the decision problem specified for this Early Value Assessment. We did not identify any studies that reported information about the clinical effects or costs of using CaRi-Heart to assess cardiac risk. Exploratory searches, conducted to inform the conceptual cost-effectiveness modelling, indicated that there is a deficiency with respect to evidence about the effects of changing existing treatments or introducing new treatments, based on assessment of cardiac risk (by any method), or on measures of vascular inflammation (e.g. fat attenuation index). A de novo conceptual decision-analytic model that could be used to inform an early assessment of the cost effectiveness of CaRi-Heart is described. A combination of a short-term diagnostic model component and a long-term model component that evaluates the downstream consequences is anticipated to capture the diagnosis and the progression of coronary artery disease.

Limitations

The rapid review methods and pragmatic additional searches used to inform this Early Value Assessment mean that, although areas of potential uncertainty have been described, we cannot definitively state where there are evidence gaps.

Conclusions

The evidence about the clinical utility of CaRi-Heart Risk is underdeveloped and has considerable limitations, both in terms of risk of bias and applicability to United Kingdom clinical practice. There is some evidence that CaRi-Heart Risk may be predictive of 8-year risk of cardiac death, for patients undergoing computed tomography coronary angiography for suspected coronary artery disease. However, whether and to what extent CaRi-Heart represents an improvement relative to current standard of care remains uncertain. The evaluation of the CaRi-Heart device is ongoing and currently available data are insufficient to fully inform the cost-effectiveness modelling.

Future work

A large (n = 15,000) ongoing study, NCT05169333, the Oxford risk factors and non-invasive imaging study, with an estimated completion date of February 2030, may address some of the uncertainties identified in this Early Value Assessment.

Study registration

This study is registered as PROSPERO CRD42022366496.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135672) and is published in full in Health Technology Assessment; Vol. 28, No. 31. See the NIHR Funding and Awards website for further award information.

AI prediction of cardiovascular events using opportunistic epicardial adipose tissue assessments from CT calcium score

Background

Recent studies have used basic epicardial adipose tissue (EAT) assessments (e.g., volume and mean HU) to predict risk of atherosclerosis-related, major adverse cardiovascular events (MACE).

Objectives

Create novel, hand-crafted EAT features, "fat-omics", to capture the pathophysiology of EAT and improve MACE prediction.

Methods

We segmented EAT using a previously-validated deep learning method with optional manual correction. We extracted 148 radiomic features (morphological, spatial, and intensity) and used Cox elastic-net for feature reduction and prediction of MACE.

Results

Traditional fat features gave marginal prediction (EAT-volume/EAT-mean-HU/BMI gave C-index 0.53/0.55/0.57, respectively). Significant improvement was obtained with 15 fat-omics features (C-index=0.69, test set). High-risk features included volume-of-voxels-having-elevated-HU-[-50, -30-HU] and HU-negative-skewness, both of which assess high HU, which as been implicated in fat inflammation. Other high-risk features include kurtosis-of-EAT-thickness, reflecting the heterogeneity of thicknesses, and EAT-volume-in-the-top-25%-of-the-heart, emphasizing adipose near the proximal coronary arteries. Kaplan-Meyer plots of Cox-identified, high- and low-risk patients were well separated with the median of the fat-omics risk, while high-risk group having HR 2.4 times that of the low-risk group (P<0.001).

Conclusion

Preliminary findings indicate an opportunity to use more finely tuned, explainable assessments on EAT for improved cardiovascular risk prediction.

In vitro analysis of carotid lesions using a preliminary microwave sensor to detect vulnerable plaques: Correlation with histology, Duplex ultrasound examination, and computed tomography scanner: The Imaging and Microwave Phenotyping Assessment of Carotid stenosis Threat (IMPACT) study

Objective

Progress in best medical treatment have made identification of best candidates for carotid surgery more difficult. New diagnostic modalities could be helpful in this perspective. Microwaves (MWs) can quantify dielectric properties (complex relative permittivity) of biological tissues and MW technology has emerged as a promising field of research for distinguishing abnormal tissues from healthy ones. We here evaluated the ability of a dedicated MW sensor developed in our laboratory to identify vulnerable carotid lesions.

Methods

We included 50 carotid lesions in this study. The plaques were analyzed and classified preoperatively by ultrasound (US) examination, computed tomography angiography and tested postoperatively using a MW sensor. Histopathological analysis was used as a gold standard to separate vulnerable plaques (VPs) from nonvulnerable plaques (NVPs).

Results

VPs were more frequently types 2 or 3 plaques (on US examination), had a greater proportion of low (<60 Hounsfield unit) and moderate (60-130 Hounsfield unit) attenuation components (computed tomography angiography) and displayed higher dielectric constant values (MW) than NVPs, which had an opposite profile. NVPs were more frequently asymptomatic plaques compared with VPs (P = .035). Multivariate analysis showed that US examination and MW identified VPs with a sensitivity of 77% and a specificity of 76% (cutoff value, -0.045; area under the curve, 0.848; P < .0001).

Conclusions

We found that the presence of types 2 to 3 (on US examination) and high dielectric constant plaques in vitro was highly indicative of a VP based on histological analysis. Further studies are needed to determine the potential of MW to identify the most dangerous asymptomatic carotid lesions.

Cardiometabolic predictors of high-risk CCTA phenotype in a diverse patient population

Introduction

Low-attenuation non-calcified plaque (LAP) burden and vascular inflammation by pericoronary adipose tissue (PCAT) measured from coronary CT angiography (CCTA) have shown to be predictors of cardiovascular outcomes. We aimed to investigate the relationships of cardiometabolic risk factors including lipoprotein(a) and epicardial adipose tissue (EAT) with CCTA high-risk imaging biomarkers, LAP and vascular inflammation.

Methods

The patient population consisted of consecutive patients who underwent CCTA for stable chest pain and had a complete cardiometabolic panel including lipoprotein(a). Plaque, PCAT and EAT were measured from CT using semiautomated software. Elevated LAP burden and PCAT attenuation were defined as ≥4% and ≥70.5 HU, respectively. The primary clinical end-point was a composite of myocardial infarction, revascularization or cardiovascular death.

Results

A total of 364 consecutive patients were included (median age 56 years, 64% female); the majority of patients were of Hispanic (60%), and the rest were of non-Hispanic Black (21%), non-Hispanic White (6%) and non-Hispanic Asian (4%) race/ethnicity. The prevalence of elevated LAP burden and PCAT attenuation was 31 and 18%, respectively, while only 8% had obstructive stenosis. There were significant differences in plaque characteristics among different racial/ethnic groups (p<0.001). Lipoprotein(a) correlated with LAP burden in Hispanic patients. Patients with elevated LAP were older, more likely to be have diabetes, hypertension, hyperlipidemia and smoke with higher CAC and EAT volume (all P<0.05). Patients with elevated LAP were more likely to develop the primary clinical outcome (p<0.001) but those with elevated PCAT were not (p=0.797).

Conclusion

The prevalence of LAP and PCAT attenuation were 31 and 18%, respectively. Lipoprotein(a) levels correlated with LAP burden in Hispanic patients. Age, male sex, hypertension and hyperlipidemia increased the odds of elevated LAP, which showed prognostic significance.

Relationship between impaired myocardial blood flow by positron emission tomography and low-attenuation plaque burden and pericoronary adipose tissue attenuation from coronary computed tomography: From the prospective PACIFIC trial

BACKGROUND

Positron emission tomography (PET) is the clinical gold standard for quantifying myocardial blood flow (MBF). Pericoronary adipose tissue (PCAT) attenuation may detect vascular inflammation indirectly. We examined the relationship between MBF by PET and plaque burden and PCAT on coronary CT angiography (CCTA).

METHODS

This post hoc analysis of the PACIFIC trial included 208 patients with suspected coronary artery disease (CAD) who underwent [15O]H2O PET and CCTA. Low-attenuation plaque (LAP, < 30HU), non-calcified plaque (NCP), and PCAT attenuation were measured by CCTA.

RESULTS

In 582 vessels, 211 (36.3%) had impaired per-vessel hyperemic MBF (≤ 2.30 mL/min/g). In multivariable analysis, LAP burden was independently and consistently associated with impaired hyperemic MBF (P = 0.016); over NCP burden (P = 0.997). Addition of LAP burden improved predictive performance for impaired hyperemic MBF from a model with CAD severity and calcified plaque burden (P < 0.001). There was no correlation between PCAT attenuation and hyperemic MBF (r = - 0.11), and PCAT attenuation was not associated with impaired hyperemic MBF in univariable or multivariable analysis of all vessels (P > 0.1).

CONCLUSION

In patients with stable CAD, LAP burden was independently associated with impaired hyperemic MBF and a stronger predictor of impaired hyperemic MBF than NCP burden. There was no association between PCAT attenuation and hyperemic MBF.

The journal of cardiovascular computed tomography: A year in review: 2022

This review aims to summarize key articles published in the Journal of Cardiovascular Computed Tomography (JCCT) in 2022, focusing on those that had the most scientific and educational impact. The JCCT continues to expand; the number of submissions, published manuscripts, cited articles, article downloads, social media presence, and impact factor continues to grow. The articles selected by the Editorial Board of the JCCT in this review highlight the role of cardiovascular computed tomography (CCT) to detect subclinical atherosclerosis, assess the functional relevance of stenoses, and plan invasive coronary and valve procedures. A section is dedicated to CCT in infants and other patients with congenital heart disease, in women, and to the importance of training in CT. In addition, we highlight key consensus documents and guidelines published in JCCT last year. The Journal values the tremendous work by authors, reviewers, and editors to accomplish these contributions.

Evaluation of pericoronary adipose tissue attenuation on CT

Pericoronary adipose tissue (PCAT) is the fat deposit surrounding coronary arteries. Although PCAT is part of the larger epicardial adipose tissue (EAT) depot, it has different pathophysiological features and roles in the atherosclerosis process. While EAT evaluation has been studied for years, PCAT evaluation is a relatively new concept. PCAT, especially the mean attenuation derived from CT images may be used to evaluate the inflammatory status of coronary arteries non-invasively. The most commonly used measure, PCAT_MA, is the mean attenuation of adipose tissue of 3 mm thickness around the proximal right coronary artery with a length of 40 mm. PCAT_MA can be analyzed on a per-lesion, per-vessel or per-patient basis. Apart from PCAT_MA, other measures for PCAT have been studied, such as thickness, and volume. Studies have shown associations between PCAT_MA and anatomical and functional severity of coronary artery disease. PCAT_MA is associated with plaque components and high-risk plaque features, and can discriminate patients with flow obstructing stenosis and myocardial infarction. Whether PCAT_MA has value on an individual patient basis remains to be determined. Furthermore, CT imaging settings, such as kV levels and clinical factors such as age and sex affect PCAT_MA measurements, which complicate implementation in clinical practice. For PCAT_MA to be widely implemented, a standardized methodology is needed. This review gives an overview of reported PCAT methodologies used in current literature and the potential use cases in clinical practice.

The effect of patient and imaging characteristics on coronary CT angiography assessed pericoronary adipose tissue attenuation and gradient

BACKGROUND

Coronary CT angiography (CCTA) pericoronary adipose tissue (PCAT) markers are promising indicators of inflammation.

OBJECTIVE

To determine the effect of patient and imaging parameters on the associations between non-calcified plaque (NCP) and PCAT attenuation and gradient.

METHODS

This was a single-center, retrospective analysis of consecutive patients with stable chest pain who underwent CCTA and had zero calcium scores. CCTA images were evaluated for the presence of NCP, obstructive stenosis, segment stenosis and involvement score (SSS, SIS), and high-risk plaque (HRP). PCAT markers were assessed using semi-automated software. Uni- and multivariable regression models correcting for patient and imaging characteristics between plaque and PCAT markers were evaluated.

RESULTS

Overall, 1652 patients had zero calcium score (mean age: 51 years ​± ​11 [SD], 871 women); PCAT attenuation values ranged between -123 HU and -51 HU, and 649 patients had plaque. In univariable analysis, the presence of NCP, SSS, SIS, and HRP were associated with PCAT attenuation (2, 1, 1, 6 HU; respectively; p ​< ​.001 all); while obstructive stenosis was not (1 HU, p ​= ​.58). In multivariable analysis, none of the plaque markers were associated with PCAT attenuation (0 HU p ​= ​.93, 0 HU p ​= ​.39, 1 HU p ​= ​.18, 2 HU p ​= ​.10, 1 HU p ​= ​.71, respectively), while patient and imaging characteristics showed significant associations, such as: male sex (1 HU, p ​= ​.003), heart rate [1/min] (-0.2 HU, p ​< ​.001), 120 ​kVp (8 HU, p ​< ​.001) and pixel spacing [mm³] (32 HU, p ​< ​.001). Similar results were observed for PCAT gradient.

CONCLUSION

PCAT markers were significantly associated with NCP, however the associations did not persist following correction for patient and imaging characteristics.