Prognostic Value of RCA Pericoronary Adipose Tissue CT-Attenuation Beyond High-Risk Plaques, Plaque Volume, and Ischemia

Effect of colchicine on progression of known coronary atherosclerosis in patients with STable CoROnary artery disease CoMpared to placebo (EKSTROM) trial-rationale and design

BACKGROUND

Cardiovascular disease is the major cause of mortality in the United States. Despite lifestyle modification and traditional risk factor control residual inflammatory risk remains an untreated concern. Colchicine is an oral, medication that has been used for gout, mediterranean fever and pericarditis for decades. In recent trials, colchicine has been shown to reduce major adverse cardiovascular events, however the mechanism of benefit remains unclear. The objective of the randomized, double-blind, placebo controlled EKSTROM trial is to evaluate the effects of colchicine 0.5mg/day on atherosclerotic plaque.

METHODS

Eighty-four participants will be enrolled after obtaining informed consent and followed for 12 months. Eligible patients will be randomly assigned to colchicine 0.5mg/day or placebo in a 1:1 fashion as add-on to their standard of care. All participants will undergo coronary computed tomography angiography (CCTA) at baseline and at 12 months.

RESULTS

As of November 2023, the study is 100% enrolled with an expected end of study by the second quarter of 2024. The primary endpoint is change in low attenuation plaque volume as measured by CCTA. Secondary endpoints include change in volume of different plaque types (including total atheroma volume, noncalcified plaque volume, dense calcified plaque volume, remodeling index), change in inflammatory markers (IL-6, IL-1β, IL-18, hs-CRP), change in pericoronary adipose tissue attenuation, change in epicardial adipose tissue volume and attenuation and change in brachial flow mediated dilation.

CONCLUSION

EKSTROM is the first randomized study to assess the effects of colchicine on plaque progression, pericoronary and epicardial fat. EKSTROM will provide important information on the mechanistic effects of colchicine on the cardiovascular system.

TRIAL REGISTRATION

Registry: clinicaltrials.gov, Registration Number: NCT06342609 url: https://www.

CLINICALTRIALS

gov/study/NCT06342609?term=EKSTROM&rank=1.

Pericoronary adipose tissue for predicting long-term outcomes

AIMS

Pericoronary adipose tissue (PCAT) attenuation obtained by coronary computed tomography angiography (CCTA) has been associated with coronary inflammation and outcomes. Whether PCAT attenuation is predictive of major adverse cardiac events (MACE) during long-term follow-up is unknown.

METHODS AND RESULTS

Symptomatic patients with coronary artery disease (CAD) who underwent CCTA were included, and clinical outcomes were evaluated. PCAT was measured at all lesions for all three major coronary arteries using semi-automated software. A comparison between patients with and without MACE was made on both a per-lesion and a per-patient level. The predictive value of PCAT attenuation for MACE was assessed in Cox regression models. In 483 patients (63.3 ± 8.5 years, 54.9% men), 1561 lesions were analysed over a median follow-up duration of 9.5 years. The mean PCAT attenuation was not significantly different between patients with and without MACE. At a per-patient level, the adjusted hazard ratio (HR) and 95% confidence interval (CI) for MACE were 0.970 (95% CI: 0.933-1.008, P = 0.121) when the average of all lesions per patient was analysed, 0.992 (95% CI: 0.961-1.024, P = 0.622) when only the most obstructive lesion was evaluated, and 0.981 (95% CI: 0.946-1.016, P = 0.285) when only the lesion with the highest PCAT attenuation per individual was evaluated. Adjusted HRs for vessel-specific PCAT attenuation in the right coronary artery, left anterior descending artery, and left circumflex artery were 0.957 (95% CI: 0.830-1.104, P = 0.548), 0.989 (95% CI: 0.954-1.025, P = 0.550), and 0.739 (95% CI: 0.293-1.865, P = 0.522), respectively, in predicting long-term MACE.

CONCLUSION

In patients referred to CCTA for clinically suspected CAD, PCAT attenuation did not predict MACE during long-term follow-up.

Lipoprotein(a) and Long-Term Plaque Progression, Low-Density Plaque, and Pericoronary Inflammation

Importance

Lipoprotein(a) (Lp[a]) is a causal risk factor for cardiovascular disease; however, long-term effects on coronary atherosclerotic plaque phenotype, high-risk plaque formation, and pericoronary adipose tissue inflammation remain unknown.

Objective

To investigate the association of Lp(a) levels with long-term coronary artery plaque progression, high-risk plaque, and pericoronary adipose tissue inflammation.

Design, Setting, and Participants

This single-center prospective cohort study included 299 patients with suspected coronary artery disease (CAD) who underwent per-protocol repeated coronary computed tomography angiography (CCTA) imaging with an interscan interval of 10 years. Thirty-two patients were excluded because of coronary artery bypass grafting, resulting in a study population of 267 patients. Data for this study were collected from October 2008 to October 2022 and analyzed from March 2023 to March 2024.

Exposures

The median scan interval was 10.2 years. Lp(a) was measured at follow-up using an isoform-insensitive assay. CCTA scans were analyzed with a previously validated artificial intelligence-based algorithm (atherosclerosis imaging-quantitative computed tomography).

Main Outcome and Measures

The association between Lp(a) and change in percent plaque volumes was investigated in linear mixed-effects models adjusted for clinical risk factors. Secondary outcomes were presence of low-density plaque and presence of increased pericoronary adipose tissue attenuation at baseline and follow-up CCTA imaging.

Results

The 267 included patients had a mean age of 57.1 (SD, 7.3) years and 153 were male (57%). Patients with Lp(a) levels of 125 nmol/L or higher had twice as high percent atheroma volume (6.9% vs 3.0%; P = .01) compared with patients with Lp(a) levels less than 125 nmol/L. Adjusted for other risk factors, every doubling of Lp(a) resulted in an additional 0.32% (95% CI, 0.04-0.60) increment in percent atheroma volume during the 10 years of follow-up. Every doubling of Lp(a) resulted in an odds ratio of 1.23 (95% CI, 1.00-1.51) and 1.21 (95% CI, 1.01-1.45) for the presence of low-density plaque at baseline and follow-up, respectively. Patients with higher Lp(a) levels had increased pericoronary adipose tissue attenuation around both the right coronary artery and left anterior descending at baseline and follow-up.

Conclusions and Relevance

In this long-term prospective serial CCTA imaging study, higher Lp(a) levels were associated with increased progression of coronary plaque burden and increased presence of low-density noncalcified plaque and pericoronary adipose tissue inflammation. These data suggest an impact of elevated Lp(a) levels on coronary atherogenesis of high-risk, inflammatory, rupture-prone plaques over the long term.

Perivascular Fat: A Novel Risk Factor for Coronary Artery Disease

Perivascular adipose tissue (PVAT) interacts with the vascular wall and secretes bioactive factors which regulate vascular wall physiology. Vice versa, vascular wall inflammation affects the adjacent PVAT via paracrine signals, which induce cachexia-type morphological changes in perivascular fat. These changes can be quantified in pericoronary adipose tissue (PCAT), as an increase in PCAT attenuation in coronary computed tomography angiography images. Fat attenuation index (FAI), a novel imaging biomarker, measures PCAT attenuation around coronary artery segments and is associated with coronary artery disease presence, progression, and plaque instability. Beyond its diagnostic capacity, PCAT attenuation can also ameliorate cardiac risk stratification, thus representing an innovative prognostic biomarker of cardiovascular disease (CVD). However, technical, biological, and anatomical factors are weakly related to PCAT attenuation and cause variation in its measurement. Thus, to integrate FAI, a research tool, into clinical practice, a medical device has been designed to provide FAI values standardized for these factors. In this review, we discuss the interplay of PVAT with the vascular wall, the diagnostic and prognostic value of PCAT attenuation, and its integration as a CVD risk marker in clinical practice.

Polygenic Risk Is Associated With Long-Term Coronary Plaque Progression and High-Risk Plaque

BACKGROUND

The longitudinal relation between coronary artery disease (CAD) polygenic risk score (PRS) and long-term plaque progression and high-risk plaque (HRP) features is unknown.

OBJECTIVES

The goal of this study was to investigate the impact of CAD PRS on long-term coronary plaque progression and HRP.

METHODS

Patients underwent CAD PRS measurement and prospective serial coronary computed tomography angiography (CTA) imaging. Coronary CTA scans were analyzed with a previously validated artificial intelligence-based algorithm (atherosclerosis imaging-quantitative computed tomography imaging). The relationship between CAD PRS and change in percent atheroma volume (PAV), percent noncalcified plaque progression, and HRP prevalence was investigated in linear mixed-effect models adjusted for baseline plaque volume and conventional risk factors.

RESULTS

A total of 288 subjects (mean age 58 ± 7 years; 60% male) were included in this study with a median scan interval of 10.2 years. At baseline, patients with a high CAD PRS had a more than 5-fold higher PAV than those with a low CAD PRS (10.4% vs 1.9%; P < 0.001). Per 10 years of follow-up, a 1 SD increase in CAD PRS was associated with a 0.69% increase in PAV progression in the multivariable adjusted model. CAD PRS provided additional discriminatory benefit for above-median noncalcified plaque progression during follow-up when added to a model with conventional risk factors (AUC: 0.73 vs 0.69; P = 0.039). Patients with high CAD PRS had an OR of 2.85 (95% CI: 1.14-7.14; P = 0.026) and 6.16 (95% CI: 2.55-14.91; P < 0.001) for having HRP at baseline and follow-up compared with those with low CAD PRS.

CONCLUSIONS

Polygenic risk is strongly associated with future long-term plaque progression and HRP in patients suspected of having CAD.

Development and Validation of a Quantitative Coronary CT Angiography Model for Diagnosis of Vessel-Specific Coronary Ischemia

BACKGROUND

Noninvasive stress testing is commonly used for detection of coronary ischemia but possesses variable accuracy and may result in excessive health care costs.

OBJECTIVES

This study aimed to derive and validate an artificial intelligence-guided quantitative coronary computed tomography angiography (AI-QCT) model for the diagnosis of coronary ischemia that integrates atherosclerosis and vascular morphology measures (AI-QCTISCHEMIA) and to evaluate its prognostic utility for major adverse cardiovascular events (MACE).

METHODS

A post hoc analysis of the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) studies was performed. In both studies, symptomatic patients with suspected stable coronary artery disease had prospectively undergone coronary computed tomography angiography (CTA), myocardial perfusion imaging (MPI), SPECT, or PET, fractional flow reserve by CT (FFRCT), and invasive coronary angiography in conjunction with invasive FFR measurements. The AI-QCTISCHEMIA model was developed in the derivation cohort of the CREDENCE study, and its diagnostic performance for coronary ischemia (FFR ≤0.80) was evaluated in the CREDENCE validation cohort and PACIFIC-1. Its prognostic value was investigated in PACIFIC-1.

RESULTS

In CREDENCE validation (n = 305, age 64.4 ± 9.8 years, 210 [69%] male), the diagnostic performance by area under the receiver-operating characteristics curve (AUC) on per-patient level was 0.80 (95% CI: 0.75-0.85) for AI-QCTISCHEMIA, 0.69 (95% CI: 0.63-0.74; P < 0.001) for FFRCT, and 0.65 (95% CI: 0.59-0.71; P < 0.001) for MPI. In PACIFIC-1 (n = 208, age 58.1 ± 8.7 years, 132 [63%] male), the AUCs were 0.85 (95% CI: 0.79-0.91) for AI-QCTISCHEMIA, 0.78 (95% CI: 0.72-0.84; P = 0.037) for FFRCT, 0.89 (95% CI: 0.84-0.93; P = 0.262) for PET, and 0.72 (95% CI: 0.67-0.78; P < 0.001) for SPECT. Adjusted for clinical risk factors and coronary CTA-determined obstructive stenosis, a positive AI-QCTISCHEMIA test was associated with aHR: 7.6 (95% CI: 1.2-47.0; P = 0.030) for MACE.

CONCLUSIONS

This newly developed coronary CTA-based ischemia model using coronary atherosclerosis and vascular morphology characteristics accurately diagnoses coronary ischemia by invasive FFR and provides robust prognostic utility for MACE beyond presence of stenosis.

Relationship Analysis Between Pericoronary Fat Attenuation Index and Parameters of Single Plaque

OBJECTIVE

The aim of the study is to investigate the relationship between plaque parameters and pericoronary fat attenuation index (FAI).

METHODS

A retrospective collection was performed on 227 patients with coronary heart disease who underwent coronary computed tomography angiography examinations in our hospital from May 2021 to April 2023, with a total of 254 right coronary or left anterior descending coronary arteries exhibiting solitary plaques within the FAI measurement area. Based on whether the proximal coronary FAI value was ≥ -70.0 HU, patients and coronary arteries were divided into FAI-positive group (67 cases, 73 coronary arteries) and FAI-negative group (160 cases, 181 coronary arteries). Quantitative parameters of coronary solitary plaques were collected, including stenosis severity, plaque length, plaque volume, plaque composition ratios, minimal luminal area, and calcification score, as well as qualitative parameters such as plaque types and high-risk plaques. Differences in plaque parameters between the FAI-positive and FAI-negative groups were compared.

RESULTS

The proportion of positive remodeling in the FAI-positive group (73 coronary arteries) was higher than that in the FAI-negative group (181 coronary arteries) with statistical significance (89.0% vs 78.5%, P = 0.049). Multivariate analysis revealed that positive remodeling was a risk factor for abnormal FAI values in solitary plaques (odds ratio, 2.271, P = 0.049).

CONCLUSIONS

The FAI-positive group had a higher proportion of positive remodeling, and positive remodeling was an independent risk factor for positive FAI values.

Radiomics analysis of lesion-specific pericoronary adipose tissue to predict major adverse cardiovascular events in coronary artery disease

OBJECTIVE

To investigate the prognostic performance of radiomics analysis of lesion-specific pericoronary adipose tissue (PCAT) for major adverse cardiovascular events (MACE) with the guidance of CT derived fractional flow reserve (CT-FFR) in coronary artery disease (CAD).

MATERIALS AND METHODS

The study retrospectively analyzed 608 CAD patients who underwent coronary CT angiography. Lesion-specific PCAT was determined by the lowest CT-FFR value and 1691 radiomic features were extracted. MACE included cardiovascular death, nonfatal myocardial infarction, unplanned revascularization and hospitalization for unstable angina. Four models were generated, incorporating traditional risk factors (clinical model), radiomics score (Rad-score, radiomics model), traditional risk factors and Rad-score (clinical radiomics model) and all together (combined model). The model performances were evaluated and compared with Harrell concordance index (C-index), area under curve (AUC) of the receiver operator characteristic.

RESULTS

Lesion-specific Rad-score was associated with MACE (adjusted HR = 1.330, p = 0.009). The combined model yielded the highest C-index of 0.718, which was higher than clinical model (C-index = 0.639), radiomics model (C-index = 0.653) and clinical radiomics model (C-index = 0.698) (all p < 0.05). The clinical radiomics model had significant higher C-index than clinical model (p = 0.030). There were no significant differences in C-index between clinical or clinical radiomics model and radiomics model (p values were 0.796 and 0.147 respectively). The AUC increased from 0.674 for clinical model to 0.721 for radiomics model, 0.759 for clinical radiomics model and 0.773 for combined model.

CONCLUSION

Radiomics analysis of lesion-specific PCAT is useful in predicting MACE. Combination of lesion-specific Rad-score and CT-FFR shows incremental value over traditional risk factors.

The predictive value of lesion-specific pericoronary fat attenuation index for major adverse cardiovascular events in patients with type 2 diabetes

BACKGROUND

The purpose of this study was to explore the prognostic significance of the lesion-specific pericoronary fat attenuation index (FAI) in forecasting major adverse cardiovascular events (MACE) among patients with type 2 diabetes mellitus (T2DM).

METHODS

This study conducted a retrospective analysis of 304 patients diagnosed with T2DM who underwent coronary computed tomography angiography (CCTA) in our hospital from December 2011 to October 2021. All participants were followed for a period exceeding three years. Detailed clinical data and CCTA imaging features were carefully recorded, encompassing lesion-specific pericoronary FAI, FAI of the three prime coronary arteries, features of high-risk plaques, and the coronary artery calcium score (CACS). The MACE included in the study comprised cardiac death, acute coronary syndrome (which encompasses unstable angina pectoris and myocardial infarction), late-phase coronary revascularization procedures, and hospital admissions prompted by heart failure.

RESULTS

Within the three-year follow-up, 76 patients with T2DM suffered from MACE. The lesion-specific pericoronary FAI in patients who experienced MACE was notably higher compared to those without MACE (-84.87 ± 11.36 Hounsfield Units (HU) vs. -88.65 ± 11.89 HU, p = 0.016). Multivariate Cox regression analysis revealed that CACS ≥ 100 (hazard ratio [HR] = 4.071, 95% confidence interval [CI] 2.157-7.683, p < 0.001) and lesion-specific pericoronary FAI higher than - 83.5 HU (HR = 2.400, 95% CI 1.399-4.120, p = 0.001) were independently associated with heightened risk of MACE in patients with T2DM over a three-year period. Kaplan-Meier analysis showed that patients with higher lesion-specific pericoronary FAI were more likely to develop MACE (p = 0.0023). Additionally, lesions characterized by higher lesion-specific pericoronary FAI values were found to have a greater proportion of high-risk plaques (p = 0.015). Subgroup analysis indicated that lesion-specific pericoronary FAI higher than - 83.5 HU (HR = 2.017, 95% CI 1.143-3.559, p = 0.015) was independently correlated with MACE in patients with T2DM who have moderate to severe coronary calcification. Moreover, the combination of CACS ≥ 100 and lesion-specific pericoronary FAI>-83.5 HU significantly enhanced the predictive value of MACE in patients with T2DM within 3 years.

CONCLUSIONS

The elevated lesion-specific pericoronary FAI emerged as an independent prognostic factor for MACE in patients with T2DM, inclusive of those with moderate to severe coronary artery calcification. Incorporating lesion-specific pericoronary FAI with the CACS provided incremental predictive power for MACE in patients with T2DM.

Computed Tomography Angiography Characteristics of Thin-Cap Fibroatheroma in Patients With Diabetes

BACKGROUND

It was recently reported that thin-cap fibroatheroma (TCFA) detected by optical coherence tomography was an independent predictor of future cardiac events in patients with diabetes. However, the clinical usefulness of this finding is limited by the invasive nature of optical coherence tomography. Computed tomography angiography (CTA) characteristics of TCFA have not been systematically studied. The aim of this study was to investigate CTA characteristics of TCFA in patients with diabetes.

METHODS AND RESULTS

Patients with diabetes who underwent preintervention CTA and optical coherence tomography were included. Qualitative and quantitative analyses were performed for plaques on CTA. TCFA was assessed by optical coherence tomography. Among 366 plaques in 145 patients with diabetes, 111 plaques had TCFA. The prevalence of positive remodeling (74.8% versus 50.6%, P<0.001), low attenuation plaque (63.1% versus 33.7%, P<0.001), napkin-ring sign (32.4% versus 11.0%, P<0.001), and spotty calcification (55.0% versus 34.9%, P<0.001) was significantly higher in TCFA than in non-TCFA. Low-density noncalcified plaque volume (25.4 versus 15.7 mm3, P<0.001) and remodeling index (1.30 versus 1.20, P=0.002) were higher in TCFA than in non-TCFA. The presence of napkin-ring sign, spotty calcification, high low-density noncalcified plaque volume, and high remodeling index were independent predictors of TCFA. When all 4 predictors were present, the probability of TCFA increased to 82.4%.

CONCLUSIONS

The combined qualitative and quantitative plaque analysis of CTA may be helpful in identifying TCFA in patients with diabetes.

REGISTRATION INFORMATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT04523194.

Prognostic Value of Non-alcoholic Fatty Liver Disease and RCA Pericoronary Adipose Tissue CT Attenuation in Patients with Acute Chest Pain

RATIONALE AND OBJECTIVES

Pericoronary adipose tissue (PCAT) CT attenuation of right coronary artery (RCA) and non-alcoholic fatty liver disease (NAFLD) have prognostic value for major adverse cardiovascular events (MACE) in patients with coronary artery disease. However, the superior prognostic value between RCA PCAT CT attenuation and NAFLD remains unclear in patients with acute chest pain. This study is to evaluate the prognostic value of NAFLD for MACE, and further assess the incremental prognostic value of NAFLD over PCAT CT attenuation.

MATERIALS AND METHODS

Between January 2011 and December 2021, all consecutive emergency patients with acute chest pain referred for coronary CT angiography (CCTA) were retrospectively enrolled. MACE included unstable angina requiring hospitalization, coronary revascularization, non-fatal myocardial infarction, and all-cause death. Patients' baseline and CCTA characteristics, RCA PCAT CT attenuation, and the presence of NAFLD were used to evaluate risk factors of MACE using multivariable Cox regression analysis. The prognostic value of NAFLD compared to RCA PCAT CT attenuation was analyzed.

RESULTS

A total of 514 patients were enrolled (mean age, 58.36 ± 13.05 years; 310 men). During a median follow-up of 31 months, 60 patients (11.67%) experienced MACE. NAFLD (HR = 2.599, 95% CI: 1.207, 5.598, P = 0.015) and RCA PCAT CT attenuation (HR = 1.026, 95% CI: 1.001, 1.051, P = 0.038) were independent predictors of MACE. The global Chi-square analysis showed that NAFLD improved the risk of MACE more than that using clinical risk factors and CCTA metrics (59.51 vs 54.44, P = 0.024) or combined with RCA PCAT CT attenuation (63.75 vs 59.51, P = 0.040).

CONCLUSION

NAFLD and RCA PCAT CT attenuation were predictors of MACE. NAFLD had an incremental prognostic value beyond RCA PCAT CT attenuation for MACE in patients with acute chest pain. Adding CT-FFR into the risk prediction of patients with acute chest pain is worth considering.

Differentiation of acute coronary syndrome with radiomics of pericoronary adipose tissue

OBJECTIVE

To assess the potential values of radiomics signatures of pericoronary adipose tissue (PCAT) in identifying patients with acute coronary syndrome (ACS).

METHODS

In total, 149, 227, and 244 patients were clinically diagnosed with ACS, chronic coronary syndrome (CCS), and without coronary artery disease (CAD), respectively, and were retrospectively analysed and randomly divided into training and testing cohorts at a 2:1 ratio. From the PCATs of the proximal left anterior descending branch, left circumflex branch, and right coronary artery (RCA), the pericoronary fat attenuation index (FAI) value and radiomics signatures were calculated, among which features closely related to ACS were screened out. The ACS differentiation models AC1, AC2, AC3, AN1, AN2, and AN3 were constructed based on the FAI value of RCA and the final screened out first-order and texture features, respectively.

RESULTS

The FAI values were all higher in patients with ACS than in those with CCS and no CAD (all P < .05). For the identification of ACS and CCS, the area-under-the-curve (AUC) values of AC1, AC2, and AC3 were 0.92, 0.94, and 0.91 and 0.91, 0.86, and 0.88 in the training and testing cohorts, respectively. For the identification of ACS and no CAD, the AUC values of AN1, AN2, and AN3 were 0.95, 0.94, and 0.94 and 0.93, 0.87, and 0.89 in the training and testing cohorts, respectively.

CONCLUSIONS

Identification models constructed based on the radiomics signatures of PCAT are expected to be an effective tool for identifying patients with ACS.

ADVANCES IN KNOWLEDGE

The radiomics signatures of PCAT and FAI values are expected to differentiate between patients with ACS, CCS and those without CAD on imaging.

Evaluation of peri-plaque pericoronary adipose tissue attenuation in coronary atherosclerosis using a dual-layer spectral detector CT

Purpose

This study aimed to evaluate the differences between pericoronary adipose tissue (PCAT) attenuation at different measured locations in evaluating coronary atherosclerosis using spectral computed tomography (CT) and to explore valuable imaging indicators.

Methods

A total of 330 patients with suspicious coronary atherosclerosis were enrolled and underwent coronary CT angiography with dual-layer spectral detector CT (SDCT). Proximal and peri-plaque fat attenuation index (FAI) of stenosis coronary arteries were measured using both conventional images (CIs) and virtual monoenergetic images (VMIs) ranging from 40 keV to 100 keV. The slopes of the spectral attenuation curve (λ) of proximal and peri-plaque PCAT at three different monoenergetic intervals were calculated. Additionally, peri-plaque FAI on CI and virtual non-contrast images, and effective atomic number were measured manually.

Results

A total of 231 coronary arteries with plaques and lumen stenosis were finally enrolled. Peri-plaque FAICI and FAIVMI were significantly higher in severe stenosis than in mild and moderate stenosis (p < 0.05), while peri-plaque λ, proximal FAI, and proximal λ were not statistically different. Proximal FAI, peri-plaque FAI, and peri-plaque λ were significantly higher in low-density non-calcified plaque (LD-NCP) and non-calcified plaque (NCP) than in calcified plaque (p < 0.01). Peri-plaque FAI was the highest in the LD-NCP group, while proximal FAI was the highest in the NCP group. In severe stenosis and in LD-NCP, peri-plaque FAI was significantly higher than proximal FAI (p < 0.05). The manually measured parameters related to peri-plaque PCAT attenuation had a positive correlation with the results of peri-plaque FAI measured automatically.

Conclusion

Peri-plaque PCAT has more value in assessing coronary atherosclerosis than proximal PCAT. Peri-plaque PCAT attenuation is expected to be used as a standard biomarker for evaluating plaque vulnerability and hemodynamic characteristics.

AI-Guided Quantitative Plaque Staging Predicts Long-Term Cardiovascular Outcomes in Patients at Risk for Atherosclerotic CVD

BACKGROUND

The recent development of artificial intelligence-guided quantitative coronary computed tomography angiography analysis (AI-QCT) has enabled rapid analysis of atherosclerotic plaque burden and characteristics.

OBJECTIVES

This study set out to investigate the 10-year prognostic value of atherosclerotic burden derived from AI-QCT and to compare the spectrum of plaque to manually assessed coronary computed tomography angiography (CCTA), coronary artery calcium scoring (CACS), and clinical risk characteristics.

METHODS

This was a long-term follow-up study of 536 patients referred for suspected coronary artery disease. CCTA scans were analyzed with AI-QCT and plaque burden was classified with a plaque staging system (stage 0: 0% percentage atheroma volume [PAV]; stage 1: >0%-5% PAV; stage 2: >5%-15% PAV; stage 3: >15% PAV). The primary major adverse cardiac event (MACE) outcome was a composite of nonfatal myocardial infarction, nonfatal stroke, coronary revascularization, and all-cause mortality.

RESULTS

The mean age at baseline was 58.6 years and 297 patients (55%) were male. During a median follow-up of 10.3 years (IQR: 8.6-11.5 years), 114 patients (21%) experienced the primary outcome. Compared to stages 0 and 1, patients with stage 3 PAV and percentage of noncalcified plaque volume of >7.5% had a more than 3-fold (adjusted HR: 3.57; 95% CI 2.12-6.00; P < 0.001) and 4-fold (adjusted HR: 4.37; 95% CI: 2.51-7.62; P < 0.001) increased risk of MACE, respectively. Addition of AI-QCT improved a model with clinical risk factors and CACS at different time points during follow-up (10-year AUC: 0.82 [95% CI: 0.78-0.87] vs 0.73 [95% CI: 0.68-0.79]; P < 0.001; net reclassification improvement: 0.21 [95% CI: 0.09-0.38]). Furthermore, AI-QCT achieved an improved area under the curve compared to Coronary Artery Disease Reporting and Data System 2.0 (10-year AUC: 0.78; 95% CI: 0.73-0.83; P = 0.023) and manual QCT (10-year AUC: 0.78; 95% CI: 0.73-0.83; P = 0.040), although net reclassification improvement was modest (0.09 [95% CI: -0.02 to 0.29] and 0.04 [95% CI: -0.05 to 0.27], respectively).

CONCLUSIONS

Through 10-year follow-up, AI-QCT plaque staging showed important prognostic value for MACE and showed additional discriminatory value over clinical risk factors, CACS, and manual guideline-recommended CCTA assessment.

Lesion-specific pericoronary adipose tissue CT attenuation improves risk prediction of major adverse cardiovascular events in coronary artery disease

OBJECTIVES

To determine whether lesion-specific pericoronary adipose tissue CT attenuation (PCATa) is superior to PCATa around the proximal right coronary artery (PCATa-RCA) and left anterior descending artery (PCATa-LAD) for major adverse cardiovascular events (MACE) prediction in coronary artery disease (CAD).

METHODS

Six hundred and eight CAD patients who underwent coronary CTA from January 2014 to December 2018 were retrospectively included, with clinical risk factors, plaque features, lesion-specific PCATa, PCATa-RCA, and PCATa-LAD collected. MACE was defined as cardiovascular death, non-fatal myocardial infarction, unplanned revascularization, and hospitalization for unstable angina. Four models were established, encapsulating traditional factors (Model A), traditional factors and PCATa-RCA (Model B), traditional factors and PCATa-LAD (Model C), and traditional factors and lesion-specific PCATa (Model D). Prognostic performance was evaluated with C-statistic, area under receiver operator characteristic curve (AUC), and net reclassification index (NRI).

RESULTS

Lesion-specific PCATa was an independent predictor for MACE (adjusted hazard ratio = 1.108, P < .001). The C-statistic increased from 0.750 for model A to 0.762 for model B (P = .078), 0.773 for model C (P = .046), and 0.791 for model D (P = .005). The AUC increased from 0.770 for model A to 0.793 for model B (P = .027), 0.793 for model C (P = .387), and 0.820 for model D (P = .019). Compared with model A, the NRIs for models B, C, and D were 0.243 (-0.323 to 0.792, P = .392), 0.428 (-0.012 to 0.835, P = .048), and 0.708 (0.152-1.016, P = .001), respectively.

CONCLUSIONS

Lesion-specific PCATa improves risk prediction of MACE in CAD, which is better than PCATa-RCA and PCATa-LAD.

ADVANCES IN KNOWLEDGE

Lesion-specific PCATa was superior to PCATa-RCA and PCATa-LAD for MACE prediction.

Higher Noncalcified Plaque Volume Is Associated With Increased Plaque Vulnerability and Vascular Inflammation

BACKGROUND

Recently, it was reported that noncalcified plaque (NCP) volume was an independent predictor for cardiac events. Pericoronary adipose tissue (PCAT) attenuation is a marker of vascular inflammation and has been associated with increased cardiac mortality. The aim of this study was to evaluate the relationships between NCP volume, plaque vulnerability, and PCAT attenuation.

METHODS

Patients who underwent preintervention coronary computed tomography angiography and optical coherence tomography were enrolled. Plaque volume was measured by computed tomography angiography, plaque vulnerability by optical coherence tomography, and the level of coronary inflammation by PCAT attenuation. The plaques were divided into 2 groups of high or low NCP volume based on the median NCP volume.

RESULTS

Among 704 plaques in 454 patients, the group with high NCP volume had a higher prevalence of lipid-rich plaque (87.2% versus 75.9%; P<0.001), thin-cap fibroatheroma (38.1% versus 20.7%; P<0.001), macrophage (77.8% versus 63.4%; P<0.001), microvessel (58.2% versus 42.9%; P<0.001), and cholesterol crystal (42.0% versus 26.7%; P<0.001) than the group with low NCP plaque volume. The group with high NCP volume also had higher PCAT attenuation than the group with low NCP volume (-69.6±10.0 versus -73.5±10.6 Hounsfield unit; P<0.001). In multivariable analysis, NCP volume was significantly associated with thin-cap fibroatheroma and high PCAT attenuation. In the analysis of the combination of PCAT attenuation and NCP volume, the prevalence of thin-cap fibroatheroma was the highest in the high PCAT attenuation and high NCP volume group and the lowest in the low PCAT attenuation and low NCP volume group.

CONCLUSIONS

Higher NCP volume was associated with higher plaque vulnerability and vascular inflammation. The combination of PCAT attenuation and NCP volume may help identify plaque vulnerability noninvasively.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT04523194.

Prognostic value of CT-derived fractional flow reserve and fat attenuation index in patients with suspected coronary artery disease: a sex-disaggregated analyses

BACKGROUND

There are sex differences in many risk factors associated with coronary artery disease (CAD). CT-derived fractional flow reserve (CT-FFR) and fat attenuation index (FAI) have been shown to independently predict cardiovascular events. We aimed to examine the impact of sex on the prognostic value of CT-FFR and FAI in suspected CAD patients, and to examine the incremental prognostic value of FAI over CT-FFR in both sex.

METHODS

A total of 1334 consecutive suspected CAD subjects who underwent coronary computed tomographic angiography (CCTA) were retrospectively collected. We divided the patients into males and females and calculated CT-FFR and FAI data from CCTA images. Kaplan-Meier analysis was used to assess the risk of major adverse cardiovascular events (MACE) stratified by CT-FFR and FAI in both sex. Cox regression models were used to assess the incremental prognostic value of FAI by adding the variable to a model that included CT-FFR and clinical variables.

RESULTS

During a median follow-up of 2.08 years, 212 patients had MACE. CT-FFR ≤ 0.80 was significantly associated with MACE in both sex. FAI value of left anterior descending artery (FAI[LAD]) and FAI value of left circumflex (FAI[LCX]) ≥ 70.1 were significantly associated with MACE in females. FAI[LCX] added incremental prognostic value over clinical and CT-FFR variables in females, with hazard ratio (HR) 3.230 (1.982-5.265, P = 0.000), Harrel's C 0.669 (P < 0.001), net reclassification improvement (NRI) 0.161 (0.073-0.260, P < 0.001), and integrated discrimination index (IDI) 0.036 (0.008-0.090, P = 0.010). FAI[LAD] did not enhance risk prediction in females (Harrel's C 0.643, P = 0.054; NRI 0.041, P = 0.189; IDI 0.005, P = 0.259). The decision curve analysis demonstrated that the model including FAI[LCX] resulted in the highest net benefit.

CONCLUSIONS

In suspected CAD patients, the prognostic value of CT-FFR is not significantly biased by sex. The prognostic value of FAI[LAD] and FAI[LCX] were significantly associated with MACE in females, but not males. FAI[LCX], not FAI[LAD], added incremental prognostic value over CT-FFR and might enhance CT-FFR risk stratification in females.

Diagnostic Performance of Machine Learning-Derived Radiomics Signature of Pericoronary Adipose Tissue in Coronary Computed Tomography Angiography for Coronary Artery In-Stent Restenosis

RATIONALE AND OBJECTIVES

Coronary inflammation can alter the perivascular fat phenotype. Hence, we aimed to assess the diagnostic performance of radiomics features of pericoronary adipose tissue (PCAT) in coronary computed tomography angiography (CCTA) for in-stent restenosis (ISR) after percutaneous coronary intervention.

MATERIALS AND METHODS

In this study, 165 patients with 214 eligible vessels were included, and ISR was found in 79 vessels. After evaluating clinical and stent characteristics, peri-stent fat attenuation index, and PCAT volume, 1688 radiomics features were extracted from each peri-stent PCAT segmentation. The eligible vessels were randomly categorized into training and validation groups in a ratio of 7:3. After performing feature selection using Pearson's correlation, F test, and least absolute shrinkage and selection operator analysis, radiomics models and integrated models that combined selected clinical features and Radscore were established using five different machine learning algorithms (logistic regression, support vector machine, random forest, stochastic gradient descent, and XGBoost). Subgroup analysis was performed using the same method for patients with stent diameters of ≤ 3 mm.

RESULTS

Nine significant radiomics features were selected, and the areas under the curves (AUCs) for the radiomics model and the integrated model were 0.69 and 0.79, respectively, for the validation group. The AUCs of the subgroup radiomics model based on 15 selected radiomics features and the subgroup integrated model were 0.82 and 0.85, respectively, for the validation group, which showed better diagnostic performance.

CONCLUSION

CCTA-based radiomics signature of PCAT has the potential to identify coronary artery ISR without additional costs or radiation exposure.

Pericoronary adipose tissue attenuation is associated with non-calcified plaque burden in patients with chronic coronary syndromes

BACKGROUND

Pericoronary adipose tissue attenuation (PCAT) is a marker of inflammation of the pericoronary fat tissue, which can be assessed by coronary computed tomography angiography (CCTA). Its prognostic value was reported in previous studies. Nevertheless, the relationship between PCAT, plaque burden and coronary artery disease (CAD) severity, are not well defined.

AIM

We sought to evaluate the relationship between PCAT, CAD severity based on the CAD-RADS 2.0 score and plaque burden in patients with chronic coronary syndrome (CCS).

METHODS

Consecutive patients with a clinical indication for CCTA due to suspected or known CCS were included in our study. PCAT was measured in the proximal 4 ​cm of each of the right coronary artery (RCA), left anterior descending artery (LAD), and the left circumflex artery (LCX). The CAD-RADS 2.0 score was assessed in all patients and total, calcified, and non-calcified plaque burden was quantitatively measured.

RESULTS

868 patients (median age of 67.0 (IQR ​= ​58.0-75.0)yrs., 400 (46.1%) female) underwent CCTA between September 2020 and August 2022 due to CCS. Weak correlations were found between PCAT and the total plaque burden, as well as with the Agatston score, whereas no correlations were found between PCAT and CAD-RADS 2.0 score. Associations were also observed between the PCAT of the LAD, RCA and LCX with non-calcified plaque burden (Odds ratios of 1.22 (95%CI ​= ​1.15-1.29), 1.11 (95%CI ​= ​1.07-1.17) and 1.14 (95%CI ​= ​1.08-1.14), respectively, p ​< ​0.001 for all) which were independent of age, the Agatston score, and the CAD-RADS 2.0 score). In addition, higher PCAT were noticed with increasing number of plaques, exhibiting high-risk features per patient (p ​< ​0.05 by ANOVA for all).

CONCLUSION

PCAT exhibits significant associations with non-calcified plaque burden and plaques with high-risk features in patients undergoing CCTA for CCS. Thus, PCAT may identify high-risk patients who could benefit from more aggressive preventive therapy, which merits further investigation in future studies.

Deep Learning-based Post Hoc CT Denoising for the Coronary Perivascular Fat Attenuation Index

RATIONALE AND OBJECTIVES

Coronary inflammation related to high-risk hemorrhagic plaques can be captured by the perivascular fat attenuation index (FAI) using coronary computed tomography angiography (CCTA). Since the FAI is susceptible to image noise, we believe deep learning (DL)-based post hoc noise reduction can improve diagnostic capability. We aimed to assess the diagnostic performance of the FAI in DL-based denoised high-fidelity CCTA images compared with coronary plaque magnetic resonance imaging (MRI) delivered high-intensity hemorrhagic plaques (HIPs).

MATERIALS AND METHODS

We retrospectively reviewed 43 patients who underwent CCTA and coronary plaque MRI. We generated high-fidelity CCTA images by denoising the standard CCTA images using a residual dense network that supervised the denoising task by averaging three cardiac phases with nonrigid registration. We measured the FAIs as the mean CT value of all voxels (range of -190 to -30 HU) located within a radial distance from the outer proximal right coronary artery wall. The diagnostic reference standard was defined as HIPs (high-risk hemorrhagic plaques) using MRI. The diagnostic performance of the FAI in the original and denoised images was assessed using receiver operating characteristic curves.

RESULTS

Of 43 patients, 13 had HIPs. The denoised CCTA improved the area under the curve (0.89 [95% confidence interval (CI) 0.78-0.99]) of the FAI compared with that in the original image (0.77 [95% CI, 0.62-0.91], p = 0.008). The optimal cutoff value for predicting HIPs in denoised CCTA was -69 HU with 0.85 (11/13) sensitivity, 0.79 (25/30) specificity, and 0.80 (36/43) accuracy.

CONCLUSION

DL-based denoised high-fidelity CCTA improved the AUC and specificity of the FAI for predicting HIPs.

Development of a nomogram based on pericoronary adipose tissue histogram parameters to differentially diagnose acute coronary syndrome

PURPOSE

To develop a nomogram based on pericoronary adipose tissue (PCAT) histogram parameters to identify patients with acute coronary syndrome (ACS).

MATERIALS AND METHODS

This study retrospectively enrolled 114 and 383 eligible patients with ACS and stable coronary artery disease (CAD), respectively, and divided them into training and testing cohorts in a 7:3 ratio. A blinded radiologist obtained PCAT histogram parameters from the right coronary artery's proximal segment using fully automated software and compared clinical characteristics and PCAT histogram parameters between the two patient groups. The binary logistic regression included significant parameters (P < 0.05), and a nomogram was constructed.

RESULTS

In both the training and testing cohorts, the mean, 10th percentile, 90th percentile, median, and minimum values of PCAT were higher, and the interquartile range, skewness, and variance values of PCAT were lower in patients with ACS than in those with stable CAD (P ≤ 0.001). The mean (OR = 4.007), median (OR = 0.576), minimum (OR = 0.893), skewness (OR = 85,158.806) and variance (OR = 1.013) values of PCAT were independent risk factors for ACS and stable CAD in the training cohort. The nomogram was constructed using the five variables mentioned above with area under the curve values of 0.903 and 0.897, respectively, while the calibration and decision curves showed the nomogram's good clinical efficacy for the training and testing cohorts.

CONCLUSIONS

The constructed nomogram had good discrimination and accuracy and can be a noninvasive tool to intuitively and individually distinguish between ACS and stable CAD.

Characterization of plaque phenotypes exhibiting an elevated pericoronary adipose tissue attenuation: insights from the REASSURE-NIRS registry

Inflammation has been considered to promote atheroma instability. Coronary computed tomography angiography (CCTA) visualizes pericoronary adipose tissue (PCAT) attenuation, which reflects coronary artery inflammation. While PCAT attenuation has been reported to predict future coronary events, plaque phenotypes exhibiting high PCAT attenuation remains to be fully elucidated. The current study aims to characterize coronary atheroma with a greater vascular inflammation. We retrospectively analyzed culprit lesions in 69 CAD patients receiving PCI from the REASSURE-NIRS registry (NCT04864171). Culprit lesions were evaluated by both CCTA and near-infrared spectroscopy/intravascular ultrasound (NIRS/IVUS) imaging prior to PCI. PCAT attenuation at proximal RCA (PCATRCA) and NIRS/IVUS-derived plaque measures were compared in patients with PCATRCA attenuation ≥ and < -78.3 HU (median). Lesions with PCATRCA attenuation ≥ -78.3 HU exhibited a greater frequency of maxLCBI4mm ≥ 400 (66% vs. 26%, p < 0.01), plaque burden ≥ 70% (94% vs. 74%, p = 0.02) and spotty calcification (49% vs. 6%, p < 0.01). Whereas positive remodeling (63% vs. 41%, p = 0.07) did not differ between two groups. On multivariable analysis, maxLCBI4mm ≥ 400 (OR = 4.07; 95%CI 1.12-14.74, p = 0.03), plaque burden ≥ 70% (OR = 7.87; 95%CI 1.01-61.26, p = 0.04), and spotty calcification (OR = 14.33; 95%CI 2.37-86.73, p < 0.01) independently predicted high PCATRCA attenuation. Of note, while the presence of only one plaque feature did not necessarily elevate PCATRCA attenuation (p = 0.22), lesions harboring two or more features were significantly associated with higher PCATRCA attenuation. More vulnerable plaque phenotypes were observed in patients with high PCATRCA attenuation. Our findings suggest PCATRCA attenuation as the presence of profound disease substrate, which potentially benefits from anti-inflammatory agents.

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.

Computed tomography-based pericoronary adipose tissue attenuation in patients undergoing TAVR: a novel method for risk assessment

Objectives

This study aims to assess the attenuation of pericoronary adipose tissue (PCAT) surrounding the proximal right coronary artery (RCA) in patients with aortic stenosis (AS) and undergoing transcatheter aortic valve replacement (TAVR). RCA PCAT attenuation is a novel computed tomography (CT)-based marker for evaluating coronary inflammation. Coronary artery disease (CAD) in TAVR patients is common and usually evaluated prior to intervention. The most sensible screening method and consequential treatment approach are unclear and remain a matter of ceaseless discussion. Thus, interest remains for safe and low-demand predictive markers to identify patients at risk for adverse outcomes postaortic valve replacement.

Methods

This single-center retrospective study included patients receiving a standard planning CT scan prior to TAVR. Conventional CAD diagnostic tools, such as coronary artery calcium score and significant stenosis via invasive coronary angiography and coronary computed tomography angiography, were determined in addition to RCA PCAT attenuation using semiautomated software. These were assessed for their relationship with major adverse cardiovascular events (MACE) during a 24-month follow-up period.

Results

From a total of 62 patients (mean age: 82 ± 6.7 years), 15 (24.2%) patients experienced an event within the observation period, 10 of which were attributed to cardiovascular death. The mean RCA PCAT attenuation was higher in patients enduring MACE than that in those without an endpoint (-69.8 ± 7.5 vs. -74.6 ± 6.2, P = 0.02). Using a predefined cutoff of >-70.5 HU, 20 patients (32.3%) with high RCA PCAT attenuation were identified, nine (45%) of which met the endpoint within 2 years after TAVR. In a multivariate Cox regression model including conventional CAD diagnostic tools, RCA PCAT attenuation prevailed as the only marker with significant association with MACE (P = 0.02). After dichotomization of patients into high- and low-RCA PCAT attenuation groups, high attenuation was related to greater risk of MACE (hazard ration: 3.82, P = 0.011).

Conclusion

RCA PCAT attenuation appears to have predictive value also in a setting of concomitant AS in patients receiving TAVR. RCA PCAT attenuation was more reliable than conventional CAD diagnostic tools in identifying patients at risk for MACE .

Correlation of pericoronary adipose tissue CT attenuation values of plaques and periplaques with plaque characteristics

AIM

To investigate the relationship between different plaque characteristics and pericoronary adipose tissue (PCAT) computed tomography (CT) attenuation values for plaques and periplaques.

MATERIALS AND METHODS

The data from 188 eligible patients with stable coronary heart disease (280 lesions) who underwent coronary CT angiography between March 2021 and November 2021 were collected retrospectively. All PCAT CT attenuation values of plaques and periplaques (the area within 5 and 10 mm proximal and distal to the plaque) were calculated, and multiple linear regression was used to assess their correlation with different plaque characteristics.

RESULTS

PCAT CT attenuation of plaques and periplaques was higher in non-calcified plaques (-73.38 ± 10.41 HU, -76.77 ± 10.86 HU, 79.33 ± 11.13 HU, -75.67 ± 11.24 HU, -78.63 ± 12.09 HU) and mixed plaques (-76.83 ± 8.11 HU, -79 [-85, -68.5] HU, -78.55 ± 11 HU, -78.76 ± 9.9 HU, -78.79 ± 11.06 HU) than in calcified plaques (-86.96 ± 10 HU, -84 [-92, -76] HU, -84.14 ± 11.08 HU, -84.91 ± 11.41 HU, -84.59 ± 11.69 HU; all p<0.05) and higher in distal segment plaques than in proximal segment plaques (all p<0.05). Plaque PCAT CT attenuation was lower in plaques with minimal stenosis than in plaques with mild or moderate stenosis (p<0.05). The significant determinants of PCAT CT attenuation values of plaques and periplaques were non-calcified plaques, mixed plaques, and plaques located in the distal segment (all p<0.05).

CONCLUSIONS

PCAT CT attenuation values in both plaques and periplaques were related to plaque type and location.

The role of epicardial and pericoronary adipose tissue radiomics in identifying patients with non-ST-segment elevation myocardial infarction from unstable angina

OBJECTIVES

This study aimed to ascertain if the radiomics features of epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) based on coronary computed tomography angiography (CCTA) could identify non-ST-segment elevation myocardial infarction (NSTEMI) from unstable angina (UA).

MATERIALS AND METHODS

This retrospective case-control study included 108 patients with NSTEMI and 108 controls with UA. All patients were separated into training cohort (n = 116), internal validation cohort 1 (n = 50), and internal validation cohort 2 (n = 50) based on the time order of admission. The internal validation cohort 1 used the same scanner and scan parameters as the training cohort, while the internal validation cohort 2 used different canners and scan parameters than the training cohort. The EAT and PCAT radiomics features selected by maximum relevance minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) were adopted to build logistic regression models. Finally, we developed an EAT radiomics model, three vessel-based (right coronary artery [RCA], left anterior descending artery [LAD], and left circumflex artery [LCX]) PCAT radiomics models, and a combined model by combining the three PCAT radiomics models. Discrimination, calibration, and clinical application were employed to assess the performance of all models.

RESULTS

Eight radiomics features of EAT, sixteen of RCA-PCAT, fifteen of LAD-PCAT, and eighteen of LCX-PCAT were selected and used to construct radiomics models. The area under the curves (AUCs) of the EAT, RCA-PCAT, LAD-PCAT, LCX-PCAT and the combined models were 0.708 (95% CI: 0.614-0.802), 0.833 (95% CI:0.759-0.906), 0.720 (95% CI:0.628-0.813), 0.713 (95% CI:0.619-0.807), 0.889 (95% CI:0.832-0.946) in the training cohort, 0.693 (95% CI:0.546-0.840), 0.837 (95% CI: 0.729-0.945), 0.766 (95% CI: 0.625-0.907), 0.675 (95% CI: 0.521-0.829), 0.898 (95% CI: 0.802-0.993) in the internal validation cohort 1, and 0.691 (0.535-0.847), 0.822 (0.701-0.944), 0.760 (0.621-0.899), 0.674 (0.517-0.830), 0.866 (0.769-0.963) in the internal validation cohort 2, respectively.

CONCLUSION

Compared with the RCA-PCAT radiomics model, the EAT radiomics model had a limited ability to discriminate between NSTEMI and UA. The combination of the three vessel-based PCAT radiomics may have the potential to distinguish between NSTEMI and UA.

Computed tomography and nuclear medicine for the assessment of coronary inflammation: clinical applications and perspectives

There is increasing evidence that in patients with atherosclerotic cardiovascular disease (ASCVD) under optimal medical therapy, a persisting dysregulation of the lipid and glucose metabolism, associated with adipose tissue dysfunction and inflammation, predicts a substantial residual risk of disease progression and cardiovascular events. Despite the inflammatory nature of ASCVD, circulating biomarkers such as high-sensitivity C-reactive protein and interleukins may lack specificity for vascular inflammation. As known, dysfunctional epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) produce pro-inflammatory mediators and promote cellular tissue infiltration triggering further pro-inflammatory mechanisms. The consequent tissue modifications determine the attenuation of PCAT as assessed and measured by coronary computed tomography angiography (CCTA). Recently, relevant studies have demonstrated a correlation between EAT and PCAT and obstructive coronary artery disease, inflammatory plaque status and coronary flow reserve (CFR). In parallel, CFR is well recognized as a marker of coronary vasomotor function that incorporates the haemodynamic effects of epicardial, diffuse and small-vessel disease on myocardial tissue perfusion. An inverse relationship between EAT volume and coronary vascular function and the association of PCAT attenuation and impaired CFR have already been reported. Moreover, many studies demonstrated that 18F-FDG PET is able to detect PCAT inflammation in patients with coronary atherosclerosis. Importantly, the perivascular FAI (fat attenuation index) showed incremental value for the prediction of adverse clinical events beyond traditional risk factors and CCTA indices by providing a quantitative measure of coronary inflammation. As an indicator of increased cardiac mortality, it could guide early targeted primary prevention in a wide spectrum of patients. In this review, we summarize the current evidence regarding the clinical applications and perspectives of EAT and PCAT assessment performed by CCTA and the prognostic information derived by nuclear medicine.

Pericoronary Adipose Tissue as a Marker of Cardiovascular Risk: JACC Review Topic of the Week

Vascular inflammation is a key driver in atherosclerotic progression and plaque rupture. Recent evidence has shown that coronary computed tomography provides a noninvasive method of quantifying coronary inflammation by mapping changes in pericoronary adipose tissue (PCAT) radiodensity, which are associated with cardiovascular diseases. However, there are significant knowledge gaps in the performance and measurement of PCAT that complicate its interpretation. In this review the authors aim to summarize the role of PCAT in cardiac imaging and explore the clinical implications and applicability as a novel biomarker of cardiovascular risk, as well as to discuss its limitations and potential pitfalls.

Prediction of microvascular complications in diabetic patients without obstructive coronary stenosis based on peri-coronary adipose tissue attenuation model

OBJECTIVES

To investigate the predictive value of peri-coronary adipose tissue (PCAT) attenuation for microvascular complications in diabetic patients without significant stenosis and to develop a prediction model for early risk stratification.

METHODS

This study retrospectively included patients clinically identified for coronary computed tomography angiography (CCTA) and type 2 diabetes between January 2017 and December 2020. All patients were followed up for at least 1 year. The clinical data and CCTA-based imaging characteristics (including PCAT of major epicardial vessels, high-risk plaque features) were recorded. In the training cohort comprising of 579 patients, two models were developed: model 1 with the inclusion of clinical factors and model 2 incorporating clinical factors + RCA_PCAT using multivariable logistic regression analysis. An internal validation cohort comprising 249 patients and an independent external validation cohort of 269 patients were used to validate the proposed models.

RESULTS

Microvascular complications occurred in 69.1% (758/1097) of the current cohort during follow-up. In the training cohort, model 2 exhibited improved predictive power over model 1 based on clinical factors (AUC = 0.820 versus 0.781, p = 0.003) with lower prediction error (Brier score = 0.146 versus 0.164) compared to model 1. Model 2 accurately categorized 78.58% of patients with diabetic microvascular complications. Similar performance of model 2 in the internal validation cohort and the external validation cohort was further confirmed.

CONCLUSIONS

The model incorporating clinical factors and RCA_PCAT predicts the development of microvascular complications in diabetic patients without significant coronary stenosis.

KEY POINTS

• Hypertension, HbA1c, duration of diabetes, and RCA_PCAT were independent risk factors for microvascular complications. • The prediction model integrating RCA_PCAT exhibited improved predictive power over the model only based on clinical factors (AUC = 0.820 versus 0.781, p = 0.003) and showed lower prediction error (Brier score=0.146 versus 0.164).

Pericoronary Adipose Tissue Attenuation in Patients With Acute Coronary Syndrome Versus Stable Coronary Artery Disease

BACKGROUND

Pericoronary adipose tissue (PCAT) attenuation has been associated with coronary inflammation and can be evaluated with coronary computed tomography angiography. The aims of this study were to compare the PCAT attenuation across precursors of culprit and nonculprit lesions of patients with acute coronary syndrome versus stable coronary artery disease (CAD).

METHODS

In this case-control study, patients with suspected CAD who underwent coronary computed tomography angiography were included. Patients who developed an acute coronary syndrome within 2 years after the coronary computed tomography angiography scan were identified, and patients with stable CAD (defined as any coronary plaque ≥30% luminal diameter stenosis) were 1:2 propensity score matched for age, sex, and cardiac risk factors. The mean PCAT attenuation was analyzed at lesion level and compared between precursors of culprit lesions, nonculprit lesions, and stable coronary plaques.

RESULTS

In total, 198 patients (age 62±10 years, 65% male) were selected, including 66 patients who developed an acute coronary syndrome and 132 propensity matched patients with stable CAD. Overall, 765 coronary lesions were analyzed (culprit lesion precursors: n=66; nonculprit lesion precursors: n=207; and stable lesions: n=492). Culprit lesion precursors had larger total plaque volume, fibro-fatty plaque volume, and low-attenuation plaque volume compared to nonculprit and stable lesions. The mean PCAT attenuation was significantly higher across culprit lesion precursors compared to nonculprit and stable lesions (-63.8±9.7 Hounsfield units versus -68.8±10.6 Hounsfield units versus -69.6±10.6 Hounsfield units, respectively; P<0.001), whereas the mean PCAT attenuation around nonculprit and stable lesions was not significantly different (P=0.99).

CONCLUSIONS

The mean PCAT attenuation is significantly increased across culprit lesion precursors in patients with acute coronary syndrome, compared to nonculprit lesions of these patients and to lesions of patients with stable CAD, which may suggest a higher intensity of inflammation. PCAT attenuation on coronary computed tomography angiography may be a novel marker to identify high-risk plaques.

Advances in the Assessment of Coronary Artery Disease Activity with PET/CT and CTA

Non-invasive testing plays a pivotal role in the diagnosis, assessment of progression, response to therapy, and risk stratification of coronary artery disease. Although anatomical plaque imaging by computed tomography angiography (CTA) and ischemia detection with myocardial perfusion imaging studies are current standards of care, there is a growing body of evidence that imaging of the processes which drive atherosclerotic plaque progression and rupture has the potential to further enhance risk stratification. In particular, non-invasive imaging of coronary plaque inflammation and active calcification has shown promise in this regard. Positron emission tomography (PET) with newly-adopted radiotracers provides unique insights into atheroma activity acting as a powerful independent predictor of myocardial infarctions. Similarly, by providing a quantitative measure of coronary inflammation, the pericoronary adipose tissue density (PCAT) derived from standard coronary CTA enhances cardiac risk prediction and allows re-stratification over and above current state-of-the-art assessments. In this review, we shall discuss the recent advances in the non-invasive methods of assessment of disease activity by PET and CTA, highlighting how these methods could improve risk stratification and ultimately benefit patients with coronary artery disease.

Prognostic value of cardiac inflammation in ST-segment elevation myocardial infarction: A 18F-fluorodeoxyglucose PET/CT study

BACKGROUND

18F-fluorodeoxyglucose (FDG) imaging is used to detect cardiac inflammation and predict functional outcome in acute myocardial infarction (MI). However, data on the correlation of post-MI acute cardiac inflammation evaluated by 18F-FDG imaging and major adverse cardiac events (MACE) are limited. Therefore, we sought to explore the prognostic value of cardiac 18F-FDG imaging in patients with acute ST-segment elevation MI (STEMI).

METHODS

Thirty-six patients with STEMI underwent 18F-FDG positron emission tomography/computed tomography (PET/CT) 5 days after primary percutaneous coronary intervention. 18F-FDG activity in infarcted and remote regions, as well as peri-coronary adipose tissue (PCAT), were measured and expressed as the maximum standardized uptake value (SUVmax). Patients were followed to determine the occurrence of MACE.

RESULTS

The infarcted myocardium had a higher 18F-FDG intensity than the remote area. Moreover, the PCAT of culprit coronary arteries showed a higher 18F-FDG uptake than that of non-culprit arteries. Multivariate Cox regression analysis showed that increased SUVmax of PCAT [HR 5.198; 95% CI (1.058, 25.537), P = .042] was independently associated with a higher risk of MACE.

CONCLUSIONS

Enhanced PCAT activity after acute MI is related to the occurrence of MACE, and 18F-FDG PET/CT plays a promising role in providing prognostic information in patients with STEMI.

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

BACKGROUND

Inflammation surrounding the coronary arteries can be non-invasively assessed using pericoronary adipose tissue attenuation (PCAT). While PCAT holds promise for further risk stratification of patients with low coronary artery disease (CAD) prevalence, its value in higher risk populations remains unknown.

METHODS

CORE320 enrolled patients referred for invasive coronary angiography with known or suspected CAD. Coronary computed tomography angiography (CCTA) images were collected for 381 patients for whom clinical outcomes were assessed 5 years after enrollment. Using semi-automated image analysis software, PCAT was obtained and normalized for the right coronary (RCA), left anterior descending (LAD), and left circumflex arteries (LCx). The association between PCAT and major adverse cardiovascular events (MACE) during follow up was assessed using Cox regression models.

RESULTS

Thirty-seven patients were excluded due to technical failure. For the remaining 344 patients, median age was 62 (interquartile range, 55-68) with 59% having ≥1 coronary artery stenosis of ≥50% by quantitative coronary angiography. Mean attenuation values for PCAT in RCA, LAD, and LCx were -74.9, -74.2, and -71.2, respectively. Hazard ratios and 95% confidence intervals (CI) for normalized PCAT in the RCA, LAD, and LCx for MACE were 0.96 (CI: 0.75-1.22, p ​= ​0.71), 1.31 (95% CI: 0.96-1.78, p ​= ​0.09), and 0.98 (95% CI: 0.78-1.22, p ​= ​0.84), respectively. For death, stroke, or myocardial infarction only, hazard ratios were 0.68 (0.44-1.07), 0.85 (0.56-1.29), and 0.57 (0.41-0.80), respectively.

CONCLUSIONS

In patients referred for invasive coronary angiography with suspected CAD, PCAT did not predict MACE during long term follow up. Further studies are needed to understand the relationship of PCAT with CAD risk.

Pericoronary fat attenuation index-a new imaging biomarker and its diagnostic and prognostic utility: a systematic review and meta-analysis

Pericoronary fat attenuation index (FAI) on coronary computed tomography angiography imaging has been proposed as a novel marker of coronary vascular inflammation with prognostic value for major cardiovascular events. To date, there is no systematic review of the published literature and no meta-analysed data of previously published results. We performed a systematic review and meta-analysis according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. We systematically explored published literature in MEDLINE (PubMed) before 20 January 2022 for studies assessing FAI in both diagnostic and prognostic clinical settings in patients with or without cardiovascular disease. The primary outcome was the mean difference in FAI attenuation between stable and unstable coronary plaques. The secondary outcome was the hazard ratio (HR) of high FAI values for future cardiovascular events. We calculated I2 to test heterogeneity. We used random-effects modelling for the meta-analyses to assess the primary and secondary outcomes. This study is registered with PROSPERO (CRD42021229491). In total, 20 studies referred in a total of 7797 patients were included in this systematic review, while nine studies were used for the meta-analysis. FAI was significantly higher in unstable compared with stable plaques with a mean difference of 4.50 Hounsfield units [95% confidence interval (CI): 1.10-7.89, I2 = 88%] among 902 patients. Higher pericoronary FAI values offered incremental prognostic value for major adverse cardiovascular events (MACEs) in studies with prospective follow-up (HR = 3.29, 95% CI: 1.88-5.76, I2 = 75%) among 6335 patients. Pericoronary FAI seems to be a promising imaging biomarker that can be used for the detection of coronary inflammation, possibly to discriminate between stable and unstable plaques, and inform on the prognosis for future MACE. Further validation of these findings and exploration of the cost-effectiveness of the method before implementation in clinical practice are needed.

Vessel and sex differences in pericoronary adipose tissue attenuation obtained with coronary CT in individuals without coronary atherosclerosis

Pericoronary adipose tissue (PCAT) attenuation, derived from coronary computed tomography angiography (CCTA), is associated with coronary artery inflammation. Values for PCAT attenuation in men and women without atherosclerosis on CCTA are lacking. The aim of the current study was to assess the mean PCAT attenuation in individuals without coronary artery atherosclerosis on CCTA. Data on PCAT attenuation in men and women without coronary artery atherosclerosis on CCTA were included in this retrospective analysis. The PCAT attenuation was analyzed from the proximal part of the right coronary artery (RCA), the left anterior descending artery (LAD), and the left circumflex artery (LCx). For patient level analyses the mean PCAT attenuation was defined as the mean of the three coronary arteries. In 109 individuals (mean age 45 ± 13 years; 44% men), 320 coronary arteries were analyzed. The mean PCAT attenuation of the overall population was − 64.4 ± 8.0 HU. The mean PCAT attenuation was significantly lower in the LAD compared with the LCx and RCA (− 67.8 ± 7.8 HU vs − 62.6 ± 6.8 HU vs − 63.6 ± 7.9 HU, respectively, p < 0.001). In addition, the mean PCAT attenuation was significantly higher in men vs. women in all three coronary arteries (LAD: − 65.7 ± 7.6 HU vs − 69.4 ± 7.6 HU, p = 0.014; LCx: − 60.6 ± 7.4 HU vs − 64.3 ± 5.9 HU, p = 0.008; RCA: -61.7 ± 7.9 HU vs − 65.0 ± 7.7 HU, p = 0.029, respectively). The current study provides mean PCAT attenuation values, derived from individuals without CAD. Moreover, the mean PCAT attenuation is lower in women vs. men. Furthermore, the mean PCAT attenuation is significantly lower in the LAD vs LCx and RCA.

Association between high oxidized high-density lipoprotein levels and increased pericoronary inflammation determined by coronary computed tomography angiography

BACKGROUND

Impaired high-density lipoprotein (HDL) function is a risk factor for cardiac mortality. We aimed to investigate the association between oxidized HDL (oxHDL) and pericoronary adipose tissue (PCAT) attenuation, a novel imaging biomarker of pericoronary inflammation, by using coronary computed tomography angiography (CTA).

METHODS

A total of 287 outpatients with suspected coronary artery disease who had undergone both oxHDL measurement and coronary CTA were examined. PCAT attenuation values were assessed at the proximal 10-50 mm segments of the right coronary artery on coronary CTA. The presence of significant stenosis (luminal narrowing of >50 %) and high-risk plaque characteristics were also evaluated. Patients were then classified into tertiles according to their oxHDL level: low (n = 95), moderate (n = 96), and high (n = 96) groups.

RESULTS

PCAT attenuation in the high oxHDL group was significantly higher than that in other groups after adjusting for age and apolipoprotein-A-I. Multivariate linear regression analysis revealed that oxHDL was significantly associated with PCAT attenuation in the right coronary artery (β = 3.832, p < 0.001), whereas HDL cholesterol was not. Furthermore, subgroup analyses demonstrated that the association between oxHDL and PCAT attenuation remained significant in older patients (β = 6.367, p < 0.001) and in those with hypertension (β = 4.922, p < 0.011), dyslipidemia (β = 3.264, p = 0.010), diabetes mellitus (β = 4.284, p = 0.015), and significant stenosis (β = 3.075, p = 0.021).

CONCLUSIONS

High oxHDL levels were significantly associated with increased pericoronary inflammation, as assessed using coronary CTA. Our results may explain the association between impaired HDL function and the development of coronary atherosclerosis.

Added Value of CCTA-Derived Features to Predict MACEs in Stable Patients Undergoing Coronary Computed Tomography

Clinical evidence has emphasized the importance of coronary plaques’ characteristics, rather than lumen stenosis, for the outcome of cardiovascular events. Coronary computed tomographic angiography (CCTA) has a well-established role as a non-invasive tool for assessing plaques. The aim of this study was to compare clinical characteristics and CCTA-derived information of stable patients with non-severe plaques in predicting major adverse cardiac events (MACEs) during follow-up. We retrospectively selected 371 patients (64% male) who underwent CCTA in our center from March 2016 to January 2021 with Coronary Artery Disease—Reporting and Data System (CAD-RADS) 0 to 3. Of those, 198 patients (53% male) had CAD-RADS 0 to 1. Among them, 183 (49%) had normal pericoronary fat attenuation index (pFAI), while 15 (60% male) had pFAI ≥ 70.1 Hounsfield unit (HU). The remaining 173 patients (76% male) had CAD-RADS 2 to 3 and were divided into patients with at least one low attenuation plaque (LAP) and patients without LAPs (n-LAP). Compared to n-LAP, patients with LAPs had higher pFAI (p = 0.005) and had more plaques than patients with n-LAP. Presence of LAPs was significantly higher in elderly (p < 0.001), males (p < 0.001) and patients with traditional risk factors (hypertension p = 0.0001, hyperlipemia p = 0.0003, smoking p = 0.0003, diabetes p = <0.0001, familiarity p = 0.0007). Among patients with CAD-RADS 0 to 1, the ones with pFAI ≥ 70.1 HU were more often hyperlipidemic (p = 0.05) and smokers (p = 0.007). Follow-up (25,4 months, range: 17.6−39.2 months) demonstrated that LAP and pFAI ≥ 70.1 significantly and independently (p = 0.04) predisposed to outcomes (overall mortality and interventional procedures). There is an added value of CCTA-derived features in stratifying cardiovascular risk in low- to intermediate-risk patients with non-severe, non-calcified coronary plaques. This is of utmost clinical relevance as it is possible to identify a subset of patients with increased risk who need strengthening in therapeutic management and closer follow-up even in the absence of severe CAD. Further studies are needed to evaluate the effect of medical treatments on pericoronary inflammation and plaque composition.

Pericoronary Adipose Tissue Attenuation, Low-Attenuation Plaque Burden, and 5-Year Risk of Myocardial Infarction

BACKGROUND

Pericoronary adipose tissue (PCAT) attenuation and low-attenuation noncalcified plaque (LAP) burden can both predict outcomes.

OBJECTIVES

This study sought to assess the relative and additive values of PCAT attenuation and LAP to predict future risk of myocardial infarction.

METHODS

In a post hoc analysis of the multicenter SCOT-HEART (Scottish Computed Tomography of the Heart) trial, the authors investigated the relationships between the future risk of fatal or nonfatal myocardial infarction and PCAT attenuation measured from coronary computed tomography angiography (CTA) using multivariable Cox regression models including plaque burden, obstructive coronary disease, and cardiac risk score (incorporating age, sex, diabetes, smoking, hypertension, hyperlipidemia, and family history).

RESULTS

In 1,697 evaluable participants (age: 58 ± 10 years), there were 37 myocardial infarctions after a median follow-up of 4.7 years. Mean PCAT was -76 ± 8 HU and median LAP burden was 4.20% (IQR: 0%-6.86%). PCAT attenuation of the right coronary artery (RCA) was predictive of myocardial infarction (HR: 1.55; P = 0.017, per 1 SD increment) with an optimum threshold of -70.5 HU (HR: 2.45; P = 0.01). In multivariable analysis, adding PCAT-RCA of ≥-70.5 HU to an LAP burden of >4% (the optimum threshold for future myocardial infarction; HR: 4.87; P < 0.0001) led to improved prediction of future myocardial infarction (HR: 11.7; P < 0.0001). LAP burden showed higher area under the curve compared to PCAT attenuation for the prediction of myocardial infarction (AUC = 0.71 [95% CI: 0.62-0.80] vs AUC = 0.64 [95% CI: 0.54-0.74]; P < 0.001), with increased area under the curve when the 2 metrics are combined (AUC = 0.75 [95% CI: 0.65-0.85]; P = 0.037).

CONCLUSION

Coronary CTA-defined LAP burden and PCAT attenuation have marked and complementary predictive value for the risk of fatal or nonfatal myocardial infarction.

Non-contrast CT-based radiomic signature of pericoronary adipose tissue for screening non-calcified plaque

Objective. To develop two combined clinical-radiomics models of pericoronary adipose tissue (PCAT) for the presence and characterization of non-calcified plaques on non-contrast CT scan. Approach. Altogether, 431 patients undergoing Coronary Computed Tomography Angiography from March 2019 to June 2021 who had complete data were enrolled, including 173 patients with non-calcified plaques of the right coronary artery(RCA) and 258 with no abnormality. PCAT was segmented around the proximal RCA on non-contrast CT scan (calcium score acquisition). Two best models were established by screening features and classifiers respectively using FeAture Explorer software. Model 1 distinguished normal coronary arteries from those with non-calcified plaques, and model 2 distinguished vulnerable plaques in non-calcified plaques. Performance was assessed by the area under the receiver operating characteristic curve (AUC-ROC). Main results. 4 and 9 features were selected for the establishment of the radiomics model respectively through Model 1 and 2. In the test group, the AUC values, sensitivity, specificity and accuracy were 0.833%, 78.3%, 80.8%, 76.6% and 0.7467%, 75.0%, 77.8%, 73.5%, respectively. The combined model including radiomics features and independent clinical factors yielded an AUC, sensitivity, specificity and accuracy of 0.896%, 81.4%, 86.5%, 77.9% for model 1 and 0.752%, 75.0%, 77.8%, 73.5% for model 2. Significance. The combined clinical-radiomics models based on non-contrast CT images of PCAT had good diagnostic efficacy for non-calcified and vulnerable plaques.

High pericoronary adipose tissue attenuation on computed tomography angiography predicts cardiovascular events in patients with type 2 diabetes mellitus: post-hoc analysis from a prospective cohort study

Background

Pericoronary adipose tissue (PCAT) attenuation on coronary computed tomography angiography (CTA) is a non-invasive biomarker for pericoronary inflammation. We aimed to investigate the prognostic value of PCAT attenuation in patients with type 2 diabetes mellitus (T2DM).

Methods

We included 333 T2DM patients (mean age, 66 years; male patients, 211; mean body mass index, 25 kg/m²) who underwent clinically indicated coronary CTA and examined their CT findings, coronary artery calcium score, pericardial fat volume, stenosis (> 50% luminal narrowing), high-risk plaque features of low-attenuation plaque and/or positive remodelling and/or spotty calcification, and PCAT attenuation. We assessed PCAT attenuation in Hounsfield units (HU) of proximal 40-mm segments of the left anterior descending artery (LAD) and right coronary artery (RCA). Cardiovascular events were defined as cardiac death, hospitalisation for acute coronary syndrome, late coronary revascularisation, and hospitalisation for heart failure.

Results

During a median follow-up of 4.0 years, we observed 31 cardiovascular events. LAD-PCAT attenuation was significantly higher in patients with cardiovascular events than in those without (− 68.5 ± 6.5 HU vs − 70.8 ± 6.1 HU, p = 0.045), whereas RCA-PCAT attenuation was not (p = 0.089). High LAD-PCAT attenuation (> − 70.7 HU; median value) was significantly associated with cardiovascular events in a model that included adverse CTA findings, such as significant stenosis and/or high-risk plaque (hazard ratio; 2.69, 95% confidence interval; 1.17–0.20, p = 0.020). After adding LAD-PCAT attenuation to the adverse CTA findings, the C-statistic and global chi-square values increased significantly from 0.65 to 0.70 (p = 0.037) and 10.9–15.0 (p = 0.043), respectively.

Conclusions

In T2DM patients undergoing clinically indicated coronary CTA, high LAD-PCAT attenuation could significantly predict cardiovascular events. This suggests that assessing LAD-PCAT attenuation can help physicians identify high-risk T2DM patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12933-022-01478-9.

Physiological significance of pericoronary inflammation in epicardial functional stenosis and global coronary flow reserve

Both fractional flow reserve (FFR) and global coronary flow reserve (g-CFR) provide prognostic information in patients with stable coronary artery disease (CAD). Inflammation plays a vital role in impaired endothelial dysfunction and atherosclerotic progression, potentially predicting cardiovascular mortality. This study aimed to evaluate the physiological significance of pericoronary adipose tissue inflammation assessed by CT attenuation (PCATA) in epicardial functional stenosis severity and g-CFR in patients with CAD. A total of 131 CAD patients with a single de novo epicardial coronary stenosis who underwent coronary CT-angiography (CCTA), phase-contrast cine-magnetic resonance imaging (PC-CMR) and FFR measurement were studied. PCATA was assessed using the mean CT attenuation value. G-CFR was obtained by quantifying absolute coronary sinus flow (ml/min/g) by PC-CMR at rest and during maximum hyperemia. Median FFR, g-CFR, and PCATA values were 0.75, 2.59, and − 71.3, respectively. Serum creatinine, NT-proBNP, left ventricular end-diastolic volume, and PCATA were independently associated with g-CFR. PCATA showed a significant incremental predictive efficacy for impaired g-CFR (< 2.0) when added to the clinical risk model. PCATA was significantly associated with g-CFR, independent of FFR. Our results suggest the pathophysiological mechanisms linking perivascular inflammation with g-CFR in CAD patients.