Serial change of perivascular fat attenuation index after statin treatment: Insights from a coronary CT angiography follow-up study

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.

Prognostic value of serial coronary computed tomography angiography-derived perivascular fat-attenuation index and plaque volume in patients with suspected coronary artery disease

AIMS

To investigate the prognostic value of serial coronary computed tomography angiography (CCTA) derived plaque information, fractional flow reserve (CT-FFR), and perivascular fat-attenuation index (FAI) on major adverse cardiac events (MACE) in patients with suspected coronary artery disease.

MATERIALS AND METHODS

A total of 252 patients who underwent serial CCTA between January 2018 and December 2021 and were followed until June 2022. MACE were recorded. The analysis indexes included percent diameter stenosis (%DS), lesion length, plaque volume, CT-FFR, and FAI, with an emphasis on their changes between the baseline and follow-up CCTAs. Multivariate regression analysis were employed to identify independent risk factors for MACE.

RESULTS

After a median follow-up of 48-month, MACE occurred in 32 patients (12.7%). Patients with MACE displayed more severe stenosis, longer lesions, and larger plaque volumes in both baseline and follow-up CCTAs compared with no-MACE patients (all P<0.05). Patients with MACE displayed more severe stenosis, longer lesion, and larger plaque volume in both baseline and follow-up CCTAs compared with no-MACE patients. In addition, MACE patients also showed lower CT-FFR and higher △CT-FFR. Although FAI was significantly higher in MACE patients at baseline CCTA, FAI was notably increased in MACE patients, and decreased in the no-MACE patients (all P<0.05). Logistic regression analysis showed that ΔFAI, %DS, and plaque volume were independent predictors of MACE, with ΔFAI being the most significant (OR: 16.725, P<0.000). A multivariable model showed a significantly improved C-index of 0.903 (95% confidence interval: 0.836-0.970) for MACE prediction, when compared with single index alone.

CONCLUSIONS

Serial CCTA-derived ΔFAI, %DS, and plaque volume are crucial independent predictors of MACE in patients with suspected coronary artery disease, highlighting the importance of CCTA in patient risk stratification and prognostic assessment.

Perivascular fat attenuation index value and plaque volume increased in non-target lesions of coronary arteries after stenting

BACKGROUND

Progression of non-target lesions (NTLs) after stenting has been reported and is associated with the triggering of an inflammatory response. The perivascular fat attenuation index (FAI) may be used as a novel imaging biomarker for the direct quantification of coronary inflammation.

OBJECTIVES

To investigate whether FAI values can help identify changes in inflammation status in patients undergoing stent implantation, especially in NTLs.

METHODS

Patients who underwent pre- and post-stenting coronary computed tomography angiography (CCTA) examination between January 2015 and February 2021 were consecutively enrolled. The pre- and post-stenting FAIs of the full coronary arteries were compared in both the non- and stent-implanted coronary arteries. Moreover, local FAI values were measured and compared between the NTLs and target lesions in the stent implantations. We also compared changes in plaque type and volume in NTLs before and after stenting.

RESULTS

A total of 89 patients (mean age 61 years; male 59) were enrolled. The perivascular FAI values in the full coronary arteries decreased after stenting in both the non- and stent-implanted coronary arteries, similar to those in the target lesions. Conversely, the perivascular FAI values in the NTLs increased after stenting (p < 0.05). In addition, the plaque volumes significantly increased in the NTLs after stenting, regardless of whether they were non-calcified, mixed, or calcified (p < 0.05).

CONCLUSION

Perivascular FAI values and plaque volumes increased in the NTLs after stenting. Perivascular FAI can be a promising imaging biomarker for monitoring coronary inflammation after stenting and facilitate long-term monitoring in clinical settings.

CLINICAL RELEVANCE STATEMENT

Perivascular fat attenuation index, a non-invasive imaging biomarker, may help identify coronary arteries with high inflammation in non-target lesions and facilitate long-term monitoring, potentially providing an opportunity for more targeted treatment.

KEY POINTS

• Perivascular fat attenuation index (FAI) values and plaque volumes increased in the non-target lesions (NTLs) after stenting, suggesting potential focal inflammation progression after stenting. However, stenting along with anti-inflammatory treatment ameliorated inflammation in the full coronary arteries. • Perivascular FAI, a non-invasive imaging biomarker, may help identify coronary arteries with high inflammation in NTLs and facilitate long-term monitoring, potentially providing an opportunity for more targeted treatment.

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.

Advances in Clinical Imaging of Vascular Inflammation: A State-of-the-Art Review

Vascular inflammation is a major contributor to cardiovascular disease, particularly atherosclerotic disease, and early detection of vascular inflammation may be key to the ultimate reduction of residual cardiovascular morbidity and mortality. This review paper discusses the progress toward the clinical utility of noninvasive imaging techniques for assessing vascular inflammation, with a focus on coronary atherosclerosis. A discussion of multiple modalities is included: computed tomography (CT) imaging (the major focus of the review), cardiac magnetic resonance, ultrasound, and positron emission tomography imaging. The review covers recent progress in new technologies such as the novel CT biomarkers of coronary inflammation (eg, the perivascular fat attenuation index), new inflammation-specific tracers for positron emission tomography-CT imaging, and others. The strengths and limitations of each modality are explored, highlighting the potential for multi-modality imaging and the use of artificial intelligence image interpretation to improve both diagnostic and prognostic potential for common conditions such as coronary artery disease.

A case report of refractory multivessel coronary spasm associated with hypereosinophilic syndrome: one cell, one disease?

Background

Hypereosinophilic syndrome (HES) is characterized by moderate to severe eosinophilia, exclusion of neoplastic or secondary origins of eosinophilia, and systemic involvement with end-organ damage. Coronary arteries can be affected to cause vasospastic angina (VSA); however, the association of the two diseases is not well recognized.

Case summary

A 55-year-old woman who had a history of multiple allergic disease such as bronchial asthma and chronic sinusitis with nasal polyps was hospitalized due to attacks of chest pain at rest. During a spontaneous attack of chest pain, ECG revealed ST-segment elevation in the inferior leads and emergency coronary angiography showed focal spasms of the right and left anterior descending coronary arteries, both of which were relieved after intracoronary administration of nitroglycerine. She was diagnosed with VSA according to the Japanese Circulation Society guidelines. Despite conventional vasodilator therapies, her resting angina remained refractory. Laboratory findings were notable for moderate eosinophilia. A comprehensive evaluation to uncover the underlying cause of refractory VSA led to the diagnosis of HES, concomitant with eosinophilic pneumonia and eosinophilic chronic rhinosinusitis. Pericoronary inflammation by fat attenuation index (FAI) was increased in the proximal segment of the right coronary artery. Treatment was initiated with oral prednisolone at a starting dose of 30 mg/day. The response to treatment was rapid, with her symptoms disappearing and a regression of eosinophilia observed the following day.

Discussion

Hypereosinophilic syndrome manifests with refractory VSA, and eosinophil-suppressing corticosteroid therapy proves effective in improving both conditions along with reduction of the pericoronary inflammation by FAI.

Association between metformin treatment and coronary artery inflammation based on pericoronary adipose tissue attenuation in type 2 diabetes mellitus patients

Cardiovascular disease (CVD) is the leading cause of mortality in type 2 diabetes mellitus (T2DM) patients. The role of metformin in reducing cardiovascular events is well-established, but its effect on coronary artery inflammation in T2DM patients is still unclear. In this study, we evaluated 547 T2DM patients who underwent coronary computed tomography angiography (CCTA) at Wuhan Central Hospital. Using propensity score matching, we compared the attenuation of pericoronary adipose tissue (PCAT), an imaging marker of coronary artery inflammation, between patients treated with and without metformin. Multiple linear regression models were used to analyze the influence of metformin on PCAT attenuation. The results of the propensity-matched analysis showed that patients on metformin therapy had significantly lower PCAT attenuation, indicating reduced coronary inflammation. Specifically, the PCAT attenuation in the left anterior descending artery (LAD) and right coronary artery (RCA) was lower in the metformin group compared to the non-metformin group. Metformin use was independently associated with decreased LAD-PCAT attenuation in the multivariate regression analysis. The association of metformin with PCAT attenuation differed significantly in populations analyzed in subgroups of patients with obesity and chronic kidney disease. In conclusion, our study shows a preliminary signal that metformin therapy may be associated with decreased coronary artery inflammation in T2DM patients, as indicated by PCAT attenuation on CCTA. And this correlation may vary depending on the patient population. This initial finding suggests that PCAT attenuation could be potentially used as an imaging biomarker to monitor the anti-inflammatory effects of medication.

Assessing the Impact of Long-Term High-Dose Statin Treatment on Pericoronary Inflammation and Plaque Distribution-A Comprehensive Coronary CTA Follow-Up Study

Computed tomography angiography (CTA) has validated the use of pericoronary adipose tissue (PCAT) attenuation as a credible indicator of coronary inflammation, playing a crucial role in coronary artery disease (CAD). This study aimed to evaluate the long-term effects of high-dose statins on PCAT attenuation at coronary lesion sites and changes in plaque distribution. Our prospective observational study included 52 patients (mean age 60.43) with chest pain, a low-to-intermediate likelihood of CAD, who had documented atheromatous plaque through CTA, performed approximately 1 year and 3 years after inclusion. We utilized the advanced features of the CaRi-Heart® and syngo.via Frontier® systems to assess coronary plaques and changes in PCAT attenuation. The investigation of changes in plaque morphology revealed significant alterations. Notably, in mixed plaques, calcified portions increased (p < 0.0001), while non-calcified plaque volume (NCPV) decreased (p = 0.0209). PCAT attenuation generally decreased after one year and remained low, indicating reduced inflammation in the following arteries: left anterior descending artery (LAD) (p = 0.0142), left circumflex artery (LCX) (p = 0.0513), and right coronary artery (RCA) (p = 0.1249). The CaRi-Heart® risk also decreased significantly (p = 0.0041). Linear regression analysis demonstrated a correlation between increased PCAT attenuation and higher volumes of NCPV (p < 0.0001, r = 0.3032) and lipid-rich plaque volume (p < 0.0001, r = 0.3281). Our study provides evidence that high-dose statin therapy significantly reduces CAD risk factors, inflammation, and plaque vulnerability, as evidenced by the notable decrease in PCAT attenuation, a critical indicator of plaque progression.

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.

Enhancing Risk Stratification on Coronary Computed Tomography Angiography: The Role of Artificial Intelligence

PURPOSE

To describe and outline the role of artificial intelligence (AI) in assisting coronary computed tomography angiography (CCTA) in enhancing risk stratification.

METHODS

A comprehensive review of the literature was performed to identify published work investigating the utility of applying AI to CCTA.

FINDINGS

CCTA is an excellent diagnostic tool for the detection of atherosclerotic cardiovascular disease. The noninvasive nature and high diagnostic accuracy have made CCTA a viable alternative to invasive coronary angiography to detect luminal stenosis. However, it is now understood that stenosis is just one factor that predicts cardiac risk and other factors need to be considered. CCTA-derived plaque biomarkers have since emerged as established predictors of cardiac events to improve risk stratification. Despite awareness of these biomarkers, they are still yet to be incorporated into routine clinical practice. The major barriers to implementation include the specialized skills required for image evaluation and the time intensive nature of analysis. With the many recent advancements in the technology, AI presents itself as a promising solution. AI is attractive because it has the potential to rapidly automate technically challenging tasks with exceptional accuracy.

IMPLICATIONS

Developments in the field of AI are occurring at a rapid rate. There is already increasing evidence of the potential AI has to greatly improve the utility of CCTA by improving analysis time and extracting additional prognostic data from new plaque biomarkers. There are, however, technical and ethical challenges that need to be considered before implementing such technology into routine clinical practice.

Preventative Imaging with Coronary Computed Tomography Angiography

PURPOSE OF REVIEW

Coronary computed tomography angiography (CCTA) is the diagnostic modality of choice for patients with stable chest pain. In this review, we scrutinize the evidence on the use of CCTA for the screening of asymptomatic patients.

RECENT FINDINGS

Clinical evidence suggests that CCTA imaging enhances cardiovascular risk stratification and prompts the timely initiation of preventive treatment leading to reduced risk of major adverse coronary events. Visualization of coronary plaques by CCTA also helps patients to comply with preventive medications. The presence of non-obstructive plaques and total plaque burden are prognostic for cardiovascular events. High-risk plaque features and pericoronary fat attenuation index, enrich the prognostic output of CCTA on top of anatomical information by capturing information on plaque vulnerability and coronary inflammatory burden. Timely detection of atherosclerotic disease or coronary inflammation by CCTA can assist in the deployment of targeted preventive strategies and novel therapeutics to prevent cardiovascular disease.

Perivascular adipose tissue as a source of therapeutic targets and clinical biomarkers

Obesity is a modifiable cardiovascular risk factor, but adipose tissue (AT) depots in humans are anatomically, histologically, and functionally heterogeneous. For example, visceral AT is a pro-atherogenic secretory AT depot, while subcutaneous AT represents a more classical energy storage depot. Perivascular adipose tissue (PVAT) regulates vascular biology via paracrine cross-talk signals. In this position paper, the state-of-the-art knowledge of various AT depots is reviewed providing a consensus definition of PVAT around the coronary arteries, as the AT surrounding the artery up to a distance from its outer wall equal to the luminal diameter of the artery. Special focus is given to the interactions between PVAT and the vascular wall that render PVAT a potential therapeutic target in cardiovascular diseases. This Clinical Consensus Statement also discusses the role of PVAT as a clinically relevant source of diagnostic and prognostic biomarkers of vascular function, which may guide precision medicine in atherosclerosis, hypertension, heart failure, and other cardiovascular diseases. In this article, its role as a 'biosensor' of vascular inflammation is highlighted with description of recent imaging technologies that visualize PVAT in clinical practice, allowing non-invasive quantification of coronary inflammation and the related residual cardiovascular inflammatory risk, guiding deployment of therapeutic interventions. Finally, the current and future clinical applicability of artificial intelligence and machine learning technologies is reviewed that integrate PVAT information into prognostic models to provide clinically meaningful information in primary and secondary prevention.

Diagnostic Ability of Perivascular Fat Attenuation Index in Predicting Atherosclerotic Plaque Formation Proximal to Myocardial Bridging of the Left Anterior Descending Artery within 3 Years

RATIONALE AND OBJECTIVES

This study was designed to investigate the association between the perivascular fat attenuation index (FAI) and atherosclerotic plaque formation proximal to myocardial bridging (MB) of the left anterior descending artery (LAD) within 3 years.

MATERIALS AND METHODS

LAD-MB patients who underwent coronary computed tomography angiography at least twice between January 2016 and December 2022 were retrospectively included in this study. In total, 99 LAD-MB patients were included in the study. Based on the formation of atherosclerotic plaques proximal to LAD-MB during follow-up, the patients were classified into two groups: LAD-MB with plaque formation and LAD-MB without plaque formation within 3 years. The anatomical features, clinical factors, and proximal perivascular FAI of LAD-MB were measured and recorded. The association of the previously mentioned factors with the presence of atherosclerotic plaque proximal to LAD-MB was determined.

RESULTS

The results showed that MB length, MB stenosis, and the perivascular FAI were significant predictors of the formation of atherosclerotic plaques proximal to LAD-MB. The area under the curve of the combined predictive model incorporating MB length, MB stenosis, and the perivascular FAI was 0.901(95% confidence interval: 0.824-0.952), with higher diagnostic performance than any other single parameter (all P < 0.05). Moreover, dynamic changes in the perivascular FAI of the vascular segments proximal to LAD-MB were higher in high-risk plaques than in non-high-risk plaques (P = 0.003).

CONCLUSION

The combined use of the perivascular FAI, MB length, and MB stenosis may enable prediction of the probability of atherosclerotic plaque formation proximal to LAD-MB within 3 years. Dynamic changes in perivascular FAI were associated with the vulnerability of plaques proximal to LAD-MB.

Pericoronary adipose tissue density is increased in patients with recent spontaneous coronary dissection

OBJECTIVE

Inflammatory activity is one of the potential mechanisms of spontaneous coronary artery dissection (SCAD). Recently, the pericoronary adipose tissue attenuation (PCAT) derived from CT angiography (CTA) has been established as a method for measuring vascular inflammation. We aimed to characterise the pancoronary and vessel-specific PCAT in patients with and without recent SCAD.

METHODS

The study comprised patients with SCAD referred to a tertiary centre between 2017 and 2022 who underwent CTA and were compared with individuals with no prior SCAD. PCAT was analysed on end-diastolic CTA reconstructions along proximal 40 mm of all major coronary vessels as well as the SCAD-related vessel. We analysed 48 patients with recent SCAD (median 6.1 (IQR 3.5-14.9) months since SCAD, 95.8% female) and 48 patients in the group without SCAD.

RESULTS

Pancoronary PCAT was higher in patients with SCAD compared with those without SCAD (-80.6±7.9 vs -85.3 HU±6.1, p=0.002). Vessel-specific PCAT in patients with SCAD compared with patients without SCAD was higher for both the RCA (-80.9±9.5 vs -87.1±6.9 HU, p=0.001) and the LCA (-80.3±7.8 vs -83.4±7.2 HU, p=0.04). In patients with SCAD, PCAT of the SCAD-related vessel was not significantly different from averaged PCAT of unaffected vessels (-81.2±9.2 vs -80.6±7.6, p=0.74). There was no association between PCAT and the interval from SCAD to CTA.

CONCLUSIONS

Patients with recent SCAD have higher PCAT compared with patients without SCAD, suggesting an increased perivascular inflammatory activity. This association is not restricted to the dissected vessel.

Radiomics features of pericoronary adipose tissue improve CT-FFR performance in predicting hemodynamically significant coronary artery stenosis

OBJECTIVES

To evaluate the value of radiomics-based model of pericoronary adipose tissue (PCAT) combined with CT fractional flow reserve (CT-FFR) in predicting hemodynamically significant coronary stenosis.

METHODS

Patients with suspected or known coronary artery disease, who had coronary computed tomography angiography (CCTA), invasive coronary angiography (ICA), and FFR within 1 month, were retrospectively included. Radiomics features of lesion-based PCAT were extracted. The lesion-specific CT-FFR values, CCTA-derived diameter stenosis, lesion length, and PCAT attenuation were also measured. FFR values were used as the reference standard to assess the diagnostic performance of radiomics model, CT-FFR, and combined model for detection of flow-limiting stenosis.

RESULTS

A total of 146 patients with 180 lesions were included in the study. All lesions were divided into training and validation cohorts at a ratio of 2:1. CT-FFR model exhibited the highest area under the curve (AUC) (0.803 for training, 0.791 for validation) in predicting hemodynamically significant stenosis, followed by radiomics model (0.776 for training, 0.744 for validation). However, no statistically significant difference was found between the AUCs of the above two models (p > 0.05). When CT-FFR was combined with radiomics model, the AUC reached 0.900 for training cohort and 0.875 for validation cohort, which were significantly higher than that of CT-FFR and radiomics model alone (both p < 0.05).

CONCLUSION

The diagnostic performance of PCAT radiomics model was comparable to that of CT-FFR for identification of ischemic coronary stenosis. Adding PCAT radiomics model to CT-FFR showed incremental value in discriminating flow-limiting from non-flow-limiting lesions.

KEY POINTS

• Radiomics analysis of lesion-based PCAT is potentially an alternative method to identify hemodynamic significance of coronary artery stenosis. • Adding radiomics model of PCAT to CT-FFR improved diagnostic performance for the detection of flow-limiting coronary stenosis. • Radiomics features + CT-FFR is a promising noninvasive method for comprehensive evaluation of hemodynamic significance of coronary artery stenosis.

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).

Diagnosis of coronary artery disease in patients with type 2 diabetes mellitus based on computed tomography and pericoronary adipose tissue radiomics: a retrospective cross-sectional study

BACKGROUND

Patients with type 2 diabetes mellitus (T2DM) are highly susceptible to cardiovascular disease, and coronary artery disease (CAD) is their leading cause of death. We aimed to assess whether computed tomography (CT) based imaging parameters and radiomic features of pericoronary adipose tissue (PCAT) can improve the diagnostic efficacy of whether patients with T2DM have developed CAD.

METHODS

We retrospectively recruited 229 patients with T2DM but no CAD history (146 were diagnosed with CAD at this visit and 83 were not). We collected clinical information and extracted imaging manifestations from CT images and 93 radiomic features of PCAT from all patients. All patients were randomly divided into training and test groups at a ratio of 7:3. Four models were constructed, encapsulating clinical factors (Model 1), clinical factors and imaging indices (Model 2), clinical factors and Radscore (Model 3), and all together (Model 4), to identify patients with CAD. Receiver operating characteristic curves and decision curve analysis were plotted to evaluate the model performance and pairwise model comparisons were performed via the DeLong test to demonstrate the additive value of different factors.

RESULTS

In the test set, the areas under the curve (AUCs) of Model 2 and Model 4 were 0.930 and 0.929, respectively, with higher recognition effectiveness compared to the other two models (each p < 0.001). Of these models, Model 2 had higher diagnostic efficacy for CAD than Model 1 (p < 0.001, 95% CI [0.129-0.350]). However, Model 4 did not improve the effectiveness of the identification of CAD compared to Model 2 (p = 0.776); similarly, the AUC did not significantly differ between Model 3 (AUC = 0.693) and Model 1 (AUC = 0.691, p = 0.382). Overall, Model 2 was rated better for the diagnosis of CAD in patients with T2DM.

CONCLUSIONS

A comprehensive diagnostic model combining patient clinical risk factors with CT-based imaging parameters has superior efficacy in diagnosing the occurrence of CAD in patients with T2DM.

Current Concepts and Future Applications of Non-Invasive Functional and Anatomical Evaluation of Coronary Artery Disease

Over the last decades, significant advances have been achieved in the treatment of coronary artery disease (CAD). Proper non-invasive diagnosis and appropriate management based on functional information and the extension of ischemia or viability remain the cornerstone in the fight against adverse CAD events. Stress echocardiography and single photon emission computed tomography are often used for the evaluation of ischemia. Advancements in non-invasive imaging modalities such as computed tomography (CT) coronary angiography and cardiac magnetic resonance imaging (MRI) have not only allowed non-invasive imaging of coronary artery lumen but also provide additional functional information. Other characteristics regarding the plaque morphology can be further evaluated with the latest modalities achieving a morpho-functional evaluation of CAD. Advances in the utilization of positron emission tomography (PET), as well as software advancements especially regarding cardiac CT, may provide additional prognostic information to a more evidence-based treatment decision. Since the armamentarium on non-invasive imaging modalities has evolved, the knowledge of the capabilities and limitations of each imaging modality should be evaluated in a case-by-case basis to achieve the best diagnosis and treatment decision. In this review article, we present the most recent advances in the noninvasive anatomical and functional evaluation of CAD.

Multi-modality cardiac imaging in the management of diabetic heart disease

Diabetic heart disease is a major healthcare problem. Patients with diabetes show an excess of death from cardiovascular causes, twice as high as the general population and those with diabetes type 1 and longer duration of the disease present with more severe cardiovascular complications. Premature coronary artery disease and heart failure are leading causes of morbidity and reduced life expectancy. Multimodality cardiac imaging, including echocardiography, cardiac computed tomography, nuclear medicine, and cardiac magnetic resonance play crucial role in the diagnosis and management of different pathologies included in the definition of diabetic heart disease. In this review we summarise the utility of multi-modality cardiac imaging in characterising ischaemic and non-ischaemic causes of diabetic heart disease and give an overview of the current clinical practice. We also describe emerging imaging techniques enabling early detection of coronary artery inflammation and the non-invasive characterisation of the atherosclerotic plaque disease. Furthermore, we discuss the role of MRI-derived techniques in studying altered myocardial metabolism linking diabetes with the development of diabetic cardiomyopathy. Finally, we discuss recent data regarding the use of artificial intelligence applied to large imaging databases and how those efforts can be utilised in the future in screening of patients with diabetes for early signs of disease.

Clinical utility of coronary artery computed tomography angiography- What we know and What's new?

Coronary computed tomography (CT) angiography (CCTA) is increasingly recognized for diagnosing obstructive coronary artery disease (CAD) among patients presenting with chest pain. In this review, we summarize the utility of CCTA to determine luminal stenosis and identifying coronary plaques with high-risk features. We review different scoring systems that can quantify total plaque burden including how artificial intelligence can facilitate more detailed plaque assessment. We discuss how CCTA can also be used to detect the hemodynamic significance of CAD lesions (fractional flow reserve CT and CT perfusion) and also local factors outside the vessel wall that may predispose to plaque rupture (fat attenuation index and wall shear stress). We conclude with technological advances in imaging acquisition using photon counting CT and post-image processing techniques especially those that can mitigate blooming artifacts.

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.

The correlation of pericoronary adipose tissue with coronary artery disease and left ventricular function

OBJECTIVE

We sought to investigate the correlation of pericoronary adipose tissue with coronary artery disease and left ventricular (LV) function.

METHODS

Participants with clinically suspected coronary artery disease were enrolled. All participants underwent coronary computed tomography angiography (CCTA) and echocardiography followed by invasive coronary angiography (ICA) within 6 months. Pericoronary adipose tissue (PCAT) was extracted to analyze the correlation with the Gensini score and LV function parameters, including IVS, LVPW, LVEDD, LVESD, LVEDV, LVESV, FS, LVEF, LVM, and LVMI. The correlation between PCAT and the Gensini score was assessed using Spearman's correlation analysis, and that between the PCAT volume or FAI and LV function parameters was determined using partial correlation analysis.

RESULTS

One hundred and fifty-nine participants (mean age, 64.55 ± 10.64 years; men, 65.4% [104/159]) were included in the final analysis. Risk factors for coronary artery disease, such as hypertension, diabetes, dyslipidemia, and a history of smoking or drinking, had no significant association with PCAT (P > 0.05), and there was also no correlation between PCAT and the Gensini score. However, the LAD-FAI was positively correlated with the IVS (r = 0.203, P = 0.013), LVPW (r = 0.218, P = 0.008), LVEDD (r = 0.317, P < 0.001), LVESD (r = 0.298, P < 0.001), LVEDV (r = 0.317, P < 0.001), LVESV (r = 0.301, P < 0.001), LVM (r = 0.371, P < 0.001), and LVMI (r = 0.304, P < 0.001). Also, the LCX-FAI was positively correlated with the LVEDD (r = 0.199, P = 0.015), LVESD (r = 0.190, P = 0.021), LVEDV (r = 0.203, P = 0.013), LVESV (r = 0.197, P = 0.016), LVM (r = 0.220, P = 0.007), and LVMI (r = 0.172, P = 0.036), and the RCA-FAI was positively correlated with the LVEDD (r = 0.258, P = 0.002), LVESD (r = 0.238, P = 0.004), LVEDV (r = 0.266, P = 0.001), LVESV (r = 0.249, P = 0.002), LVM (r = 0.237, P = 0.004), and LVMI (r = 0.218, P = 0.008), respectively. Finally, the total volume was positively correlated with FS (r = 0.167, P = 0.042).

CONCLUSION

The FAI was positively correlated with the LV function but was not associated with the severity of coronary artery disease.

Non-Invasive Modalities in the Assessment of Vulnerable Coronary Atherosclerotic Plaques

Coronary atherosclerosis is a complex, multistep process that may lead to critical complications upon progression, revolving around plaque disruption through either rupture or erosion. Several high-risk features are associated with plaque vulnerability and may add incremental prognostic information. Although invasive imaging modalities such as optical coherence tomography or intravascular ultrasound are considered to be the gold standard in the assessment of vulnerable coronary atherosclerotic plaques (VCAPs), contemporary evidence suggests a potential role for non-invasive methods in this context. Biomarkers associated with deleterious pathophysiologic pathways, including inflammation and extracellular matrix degradation, have been correlated with VCAP characteristics and adverse prognosis. However, coronary computed tomography (CT) angiography has been the most extensively investigated technique, significantly correlating with invasive method-derived VCAP features. The estimation of perivascular fat attenuation as well as radiomic-based approaches represent additional concepts that may add incremental information. Cardiac magnetic resonance imaging (MRI) has also been evaluated in clinical studies, with promising results through the various image sequences that have been tested. As far as nuclear cardiology is concerned, the implementation of positron emission tomography in the VCAP assessment currently faces several limitations with the myocardial uptake of the radiotracer in cases of fluorodeoxyglucose use, as well as with motion correction. Moreover, the search for the ideal radiotracer and the most adequate combination (CT or MRI) is still ongoing. With a look to the future, the possible combination of imaging and circulating inflammatory and extracellular matrix degradation biomarkers in diagnostic and prognostic algorithms may represent the essential next step for the assessment of high-risk individuals.

Association between High Pericoronary Adipose Tissue Computed Tomography Attenuation and Impaired Flow-Mediated Dilation of the Brachial Artery

AIMS

Pericoronary adipose tissue (PCAT) attenuation on coronary computed tomography angiography (CTA) is a noninvasive biomarker for pericoronary inflammation and is associated with cardiac mortality. We aimed to investigate the association between PCAT attenuation and endothelial dysfunction assessed using flow-mediated dilation (FMD).

METHODS

A total of 119 outpatients who underwent both coronary CTA and FMD measurements were examined. PCAT attenuation values were assessed at the proximal 40-mm segments of all three major coronary arteries on coronary CTA. Endothelial function was assessed using FMD. Patients were then classified into two groups: those with endothelial dysfunction (FMD ＜4%, n=44) and those without endothelial dysfunction (FMD ≥ 4%, n=75).

RESULTS

In all three coronary arteries, PCAT attenuation was significantly higher in patients with endothelial dysfunction than in those without endothelial dysfunction. Multivariate logistic regression analysis revealed that PCAT attenuation in the right coronary artery (odds ratio [OR]=1.543; 95% confidence interval [CI]=1.004-2.369,p=0.048) and left anterior descending artery (OR=1.525, 95% CI=1.004-2.369, p=0.049) was an independent predictor of endothelial dysfunction. Subgroup analysis of patients with adverse CTA findings (significant stenosis and/or high-risk plaque) and those with coronary artery calcium score ＞100 showed that high PCAT attenuation in all three coronary arteries was a significant predictor of endothelial dysfunction.

CONCLUSION

High PCAT attenuation was significantly associated with FMD-assessed endothelial dysfunction in patients with suspected coronary artery disease. Our results suggest that endothelial dysfunction is one of the pathophysiological mechanisms linking pericoronary inflammation to cardiac mortality.

A preliminary coronary computed tomography angiography-based study of perivascular fat attenuation index: relation with epicardial adipose tissue and its distribution over the entire coronary vasculature

OBJECTIVES

To investigate the perivascular fat attenuation index (FAI) in association with epicardial adipose tissue (EAT) parameters and its distribution over the entire coronary vasculature in patients with known or suspected coronary artery disease (CAD).

METHODS

Patients with known or suspected CAD who underwent coronary computed tomography angiography from January 1, 2019, to June 1, 2019, were retrospectively included. The perivascular FAI was quantified on four main epicardial coronary arteries and seven coronary segments. Moreover, EAT density and volume were measured.

RESULTS

We included 192 consecutive patients (55 without coronary plaque [mean age 46.4 ± 13.2 years, 69.1% male] and 137 with coronary plaque [mean age 57.9 ± 13.0 years, 84.7% male]). EAT density was lower than perivascular FAI in both groups, but they exhibited substantial correlation (- 83.33 ± 4.54 vs. - 78.22 ± 6.52 HU, p < 0.001; r = 0.667 in plaque- patients and - 83.11 ± 4.48 vs. - 77.81 ± 5.63 HU, p < 0.001; r = 0.778 in plaque+ patients). The left main coronary artery had the highest perivascular FAI, followed by the left circumflex artery. The perivascular FAI in proximal segments was significantly higher compared to that in distal segments (all p < 0.05). Furthermore, the presence of plaque did not alter perivascular FAI on the patient or segmental level.

CONCLUSION

The perivascular FAI was significantly higher than EAT density and correlated substantially with EAT density. The perivascular FAI distribution over the entire coronary tree varied and prompted for vessel-specific or segment-specific thresholds to determine abnormal perivascular FAI in practice.

KEY POINTS

• The perivascular FAI correlated well with EAT density and had higher values than EAT density. • The distributions of perivascular FAI differ between coronary vessels or segments; considering segment and vessel confounding factors while conducting a perivascular FAI study is necessary. • No significant difference of perivascular FAI was observed between patients without and with coronary plaque, nor between coronary segments without plaque and those with plaque.

Cardiovascular risk stratification by coronary computed tomography angiography imaging: current state-of-the-art

Current cardiovascular risk stratification by use of clinical risk score systems or plasma biomarkers is good but less than satisfactory in identifying patients at residual risk for coronary events. Recent clinical evidence puts now further emphasis on the role of coronary anatomy assessment by coronary computed tomography angiography (CCTA) for the management of patients with stable ischaemic heart disease. Available computed tomography (CT) technology allows the quantification of plaque burden, identification of high-risk plaques, or the functional assessment of coronary lesions for ischaemia detection and revascularization for refractory angina symptoms. The current CT armamentum is also further enhanced by perivascular Fat Attenuation Index (FAI), a non-invasive metric of coronary inflammation, which allows for the first time the direct quantification of the residual vascular inflammatory burden. Machine learning and radiomic features' extraction and spectral CT for tissue characterization are also expected to maximize the diagnostic and prognostic yield of CCTA. The combination of anatomical, functional, and biological information on coronary circulation by CCTA offers a unique toolkit for the risk stratification of patients, and patient selection for targeted aggressive prevention strategies. We hereby provide a review of the current state-of-the art in the field and discuss how integrating the full capacities of CCTA into clinical care pathways opens new opportunities for the tailored management of coronary artery disease.

Clinical applications of cardiac computed tomography: a consensus paper of the European Association of Cardiovascular Imaging-part II

Cardiac computed tomography (CT) was initially developed as a non-invasive diagnostic tool to detect and quantify coronary stenosis. Thanks to the rapid technological development, cardiac CT has become a comprehensive imaging modality which offers anatomical and functional information to guide patient management. This is the second of two complementary documents endorsed by the European Association of Cardiovascular Imaging aiming to give updated indications on the appropriate use of cardiac CT in different clinical scenarios. In this article, emerging CT technologies and biomarkers, such as CT-derived fractional flow reserve, perfusion imaging, and pericoronary adipose tissue attenuation, are described. In addition, the role of cardiac CT in the evaluation of atherosclerotic plaque, cardiomyopathies, structural heart disease, and congenital heart disease is revised.

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.

Long-term prognostic value of the serial changes of CT-derived fractional flow reserve and perivascular fat attenuation index

BACKGROUND

To investigate the serial changes of computed tomography (CT) fractional flow reserve (CT-FFR) and fat attenuation index (FAI), and explore their relationships with long-term clinical outcomes.

METHODS

Consecutive symptomatic patients with an intermediate pretest probability of coronary artery disease 1-4 were prospectively enrolled if coronary CT angiography (CCTA) revealed at least 1 lesion with 30-70% stenosis on major epicardial arteries. Follow-up CCTA was performed at 1 to 1.5-year intervals. All patients were further followed up after the second CCTA until September 2019. The Coronary Artery Disease - Reporting and Data System (CAD-RADS) grade, high-risk plaque features, lesion-specific CT-FFR, and FAI were measured for prognosis analysis.

RESULTS

A total of 263 patients were included in the analysis, and 38 major adverse cardiac events (MACEs) occurred. In the MACE group, the lesion-specific CT-FFR decreased significantly at the follow-up CCTA [0.80 (0.74-0.90) versus 0.85 (0.76-0.93); P=0.01], whereas the FAI did not notably increase (-70.4±8.9 versus -71.3±7.1 HU; P=0.436). In the non-MACE group, lesion-specific CT-FFR increased markedly [0.91 (0.84-0.95) versus 0.90 (0.82-0.94); P<0.001], while the FAI decreased substantially (-74.0±10.8 versus -72.4±11.5 HU; P=0.004). Decreased CT-FFR (adjusted overall hazard ratio =2.455; P=0.023) and increased FAI (adjusted hazard ratio =2.956; P=0.002) were the strongest independent predictors of MACEs. Serial changes of CT-FFR and FAI provided incremental prognostic value (Concordance statistic =0.716; P=0.003; over conventional clinical and imaging parameters (Concordance statistic =0.762; P=0.004).

CONCLUSIONS

Decreased CT-FFR and increased FAI at follow-up CCTA were the 2 strongest predictors of MACEs. Serial changes of CT-FFR and FAI provided incremental prognostic value over conventional clinical and imaging parameters for risk stratification. In addition, decreased CT-FFR provided incremental predictive value for MACEs from 15 months after second CCTA, while increased FAI added prognostic value from the second CCTA onwards.

Lipoprotein(a) is associated with coronary atheroma progression: analysis from a serial coronary computed tomography angiography study

BACKGROUND

Lipoprotein(a) [Lp(a)] has been closely related to coronary atherosclerosis and might affect perivascular inflammation due to its proinflammatory properties. However, there are limited data about Lp(a) and related perivascular inflammation on coronary atheroma progression. Therefore, this study aimed to investigate the associations between Lp(a) and the perivascular fat attenuation index (FAI) with coronary atheroma progression detected by coronary computed tomography angiography (CCTA).

METHODS

Patients who underwent serial CCTA examinations without a history of revascularization and with available data for Lp(a) within one month before or after baseline and follow-up CCTA imaging scans were considered to be included. CCTA quantitative analyses were performed to obtain the total plaque volume (TPV) and the perivascular FAI. Coronary plaque progression (PP) was defined as a ≥ 10% increase in the change of the TPV at the patient level or the presence of new-onset coronary atheroma lesions. The associations between Lp(a) or the perivascular FAI with PP were examined by multivariate logistic regression.

RESULTS

A total of 116 patients were ultimately enrolled in the present study with a mean CCTA interscan interval of 30.80 ± 13.50 months. Among the 116 patients (mean age: 53.49 ± 10.21 years, males: 83.6%), 32 patients presented PP during the follow-up interval. Lp(a) levels were significantly higher among PP patients than those among non-PP patients at both baseline [15.80 (9.09-33.60) mg/dLvs. 10.50 (4.75-19.71) mg/dL,P = 0.029] and follow-up [20.60 (10.45-34.55) mg/dLvs. 8.77 (5.00-18.78) mg/dL,P = 0.004]. However, there were no differences in the perivascular FAI between PP group and non-PP group at either baseline or follow-up. Multivariate logistic regression analysis showed that elevated baseline Lp(a) level (OR = 1.031, 95% CI: 1.005-1.058,P = 0.019) was an independent risk factor for PP after adjustment for other conventional variables.

CONCLUSIONS

Lp(a) was independently associated with coronary atheroma progression beyond low-density lipoprotein cholesterol and other conventional risk factors. Further studies are warranted to identify the inflammation effect exhibited as the perivascular FAI on coronary atheroma progression.

Standardized measurement of coronary inflammation using cardiovascular computed tomography: integration in clinical care as a prognostic medical device

AIMS

Coronary computed tomography angiography (CCTA) is a first-line modality in the investigation of suspected coronary artery disease (CAD). Mapping of perivascular fat attenuation index (FAI) on routine CCTA enables the non-invasive detection of coronary artery inflammation by quantifying spatial changes in perivascular fat composition. We now report the performance of a new medical device, CaRi-Heart®, which integrates standardized FAI mapping together with clinical risk factors and plaque metrics to provide individualized cardiovascular risk prediction.

METHODS AND RESULTS

The study included 3912 consecutive patients undergoing CCTA as part of clinical care in the USA (n = 2040) and Europe (n = 1872). These cohorts were used to generate age-specific nomograms and percentile curves as reference maps for the standardized interpretation of FAI. The first output of CaRi-Heart® is the FAI-Score of each coronary artery, which provides a measure of coronary inflammation adjusted for technical, biological, and anatomical characteristics. FAI-Score is then incorporated into a risk prediction algorithm together with clinical risk factors and CCTA-derived coronary plaque metrics to generate the CaRi-Heart® Risk that predicts the likelihood of a fatal cardiac event at 8 years. CaRi-Heart® Risk was trained in the US population and its performance was validated externally in the European population. It improved risk discrimination over a clinical risk factor-based model [Δ(C-statistic) of 0.085, P = 0.01 in the US Cohort and 0.149, P < 0.001 in the European cohort] and had a consistent net clinical benefit on decision curve analysis above a baseline traditional risk factor-based model across the spectrum of cardiac risk.

CONCLUSION

Mapping of perivascular FAI on CCTA enables the non-invasive detection of coronary artery inflammation by quantifying spatial changes in perivascular fat composition. We now report the performance of a new medical device, CaRi-Heart®, which allows standardized measurement of coronary inflammation by calculating the FAI-Score of each coronary artery. The CaRi-Heart® device provides a reliable prediction of the patient's absolute risk for a fatal cardiac event by incorporating traditional cardiovascular risk factors along with comprehensive CCTA coronary plaque and perivascular adipose tissue phenotyping. This integration advances the prognostic utility of CCTA for individual patients and paves the way for its use as a dual diagnostic and prognostic tool among patients referred for CCTA.

Perivascular fat imaging by computed tomography (CT): a virtual guide

Imaging in medicine has been revolutionised by technological, computational and research advances over the past decades. Computed tomography (CT), in particular, has seen rapid evolution especially in the field of cardiovascular non-invasive imaging. It is being recognised as the first-line tool for the assessment of stable and unstable disease with diagnostic, prognostic and re-stratification potential. Vascular inflammation is a key component of the atherosclerotic process and has been shown to induce molecular, transcriptional and structural changes to perivascular adipose tissue (PVAT). Being a diverse structure itself, PVAT surrounds the human vessels and is characterised by a highly rich secretome, including, amongst others, adipokines, cytokines, gaseous messengers and miRNAs It is implicated in a bidirectional interplay with the adjacent vascular wall, affecting and being affected by aspects of its biology, mainly inflammation. In this review, we discuss the current status of cardiac CT in imaging vascular inflammation through PVAT phenotyping. LINKED ARTICLES: This article is part of a themed issue on Molecular imaging - visual themed issue. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v178.21/issuetoc.

Association between higher pericoronary adipose tissue attenuation measured by coronary computed tomography angiography and nonalcoholic fatty liver disease: A matched case-control study

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

Association between carotid artery perivascular fat density and cerebral small vessel disease

Studies aiming to identify the significance of the carotid artery perivascular fat density are limited. The present study investigated the distribution pattern of pericarotid fat and its association with imaging markers of cerebral small vessel disease (CSVD). In total, 572 subjects who underwent both neck computed tomography angiography and cranial magnetic resonance imaging were analyzed. The pericarotid fat density near the origin of the internal carotid artery (ICA) and imaging markers of CSVD, such as lacunes, white matter hyperintensities (WMHs) and dilated perivascular spaces (PVSs), were assessed. We found that an increased pericarotid fat density was associated with the presence of lacunes and a higher WMH grade in all subjects, but in the patients with acute ischemic stroke, there was a difference only among the WMH grades. There was no significant difference in the pericarotid fat density in different grades of PVSs. The patients with acute ischemic stroke had a significantly higher mean pericarotid fat density than those without stroke. In conclusion, our study provides evidence suggesting that an increased pericarotid fat density is associated with the presence and degree of WMHs and lacunes. Our findings suggested that features that appear to extend beyond the vessel lumen of the ICA may be linked to CSVD.

The Emerging Role of CT-Based Imaging in Adipose Tissue and Coronary Inflammation

A large body of evidence arising from recent randomized clinical trials demonstrate the association of vascular inflammatory mediators with coronary artery disease (CAD). Vascular inflammation localized in the coronary arteries leads to an increased risk of CAD-related events, and produces unique biological alterations to local cardiac adipose tissue depots. Coronary computed tomography angiography (CTA) provides a means of mapping inflammatory changes to both epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT) as independent markers of coronary risk. Radiodensity or attenuation of PCAT on coronary CTA, notably, provides indirect quantification of coronary inflammation and is emerging as a promising non-invasive imaging implement. An increasing number of observational studies have shown robust associations between PCAT attenuation and major coronary events, including acute coronary syndrome, and 'vulnerable' atherosclerotic plaque phenotypes that are associated with an increased risk of the said events. This review outlines the biological characteristics of both EAT and PCAT and provides an overview of the current literature on PCAT attenuation as a surrogate marker of coronary inflammation.

Imaging of the Pericoronary Adipose Tissue (PCAT) Using Cardiac Computed Tomography: Modern Clinical Implications

Modern coronary computed tomography angiography (CTA) is the gold standard to visualize the epicardial adipose tissue (EAT) and pericoronary adipose tissue (PCAT). The EAT is a metabolic active fat depot enclosed by the visceral pericardium and surrounds the coronary arteries. In disease states with increased EAT volume and dysfunctional adipocytes, EAT secretes an increased amount of adipocytokines and the resulting imbalance of proinflammatory and anti-inflammatory mediators potentially causes atherogenic effects on the coronary vessel wall in a paracrine way ("outside-to-inside" signaling). These EAT-induced atherogenic effects are reported to increase the risk for the development of coronary artery disease, myocardial ischemia, high-risk plaque features, and future major adverse cardiac events. Coronary inflammation plays a key role in the development and progression of coronary artery disease; however, its noninvasive detection remains challenging. In future, this clinical dilemma might be changed by the CTA-derived analysis of the PCAT. On the basis of the concept of an "inside-to-outside" signaling between the inflamed coronary vessel wall and the surrounding PCAT recent evidence demonstrates that PCAT computed tomography attenuation especially around the right coronary artery derived from routine CTA is a promising imaging biomarker and "sensor" to noninvasively detect coronary inflammation. This review summarizes the biological and technical principles of CTA-derived PCAT analysis and highlights its clinical implications to improve modern cardiovascular prevention strategies.

Assessing Cardiovascular Risk by Using the Fat Attenuation Index in Coronary CT Angiography

Coronary CT angiography (CCTA) has evolved into a first-line diagnostic test for the investigation of chest pain. Despite advances toward standardizing the reporting of CCTA through the Coronary Artery Disease Reporting and Data System (or CAD-RADS) tool, the prognostic value of CCTA in the earliest stages of atherosclerosis remains limited. Translational work on the bidirectional interplay between the coronary arteries and the perivascular adipose tissue (PVAT) has highlighted PVAT as an in vivo molecular sensor of coronary inflammation. Coronary inflammation is dynamically associated with phenotypic changes in its adjacent PVAT, which can now be detected as perivascular attenuation gradients at CCTA. These gradients are captured and quantified through the fat attenuation index (FAI), a CCTA-based biomarker of coronary inflammation. FAI carries significant prognostic value in both primary and secondary prevention (patients with and without established coronary artery disease) and offers a significant improvement in cardiac risk discrimination beyond traditional risk factors, such as coronary calcium, high-risk plaque features, or the extent of coronary atherosclerosis. Thanks to its dynamic nature, FAI may be used as a marker of disease activity, with observational studies further suggesting that it tracks the response to anti-inflammatory interventions. Finally, radiotranscriptomic studies have revealed complementary radiomic patterns of PVAT, which detect more permanent adverse fibrotic and vascular PVAT remodeling, further expanding the value of PVAT phenotyping as an important readout in modern CCTA analysis. © RSNA, 2021.