assessment of coronary remodeling in stenotic and nonstenotic coronary atherosclerotic lesions by multidetector spiral computed tomography

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.

High-risk coronary plaque of sudden cardiac death victims: postmortem CT angiographic features and histopathologic findings

High-risk coronary plaques (HRP) are characterized in clinical radiological imaging by the presence of low plaque attenuation, a napkin-ring sign (NRS), spotty calcifications (SC) and a positive remodeling index (RI). To evaluate if these signs are detectable in postmortem imaging by a multi-phase postmortem CT angiography (MPMCTA), a retrospective study of a series of autopsy well-documented coronary plaques related to sudden cardiac death (SCD) was performed. Then correlations between histological and radiological findings were described. Fourty SCD cases due to acute coronary syndrome based on clinical history and confirmed at autopsy were selected (28 men and 12 women, age 53.3 ± 10.9). The culprit lesion was mainly situated in the proximal segments of coronary arteries, in the right coronary artery in 23 cases (57.5%), the left anterior descending artery in 13 cases (32.5%), the circumflex artery in 3 cases (7.5%) and in one case in the left main stem. MPMCTA showed a positive RI (≥ 1.1) in 75% of cases with a mean RI 1.39 ± 0.71. RI values were lower in cases with fibrotic plaques. NRS was observed in 40% of cases, low attenuation plaque in 46.3%, and SC in 48.7% of cases. There were significant correlations of the radiological presence of NRS for fibrolipid composition of the plaque (p-value 0.007), severe intraplaque inflammation (p-value 0.017), severe adventitial inflammation (p-value 0.021) and an increased vasa vasorum (p-value 0.012). A significant correlation (p-value 0.002) was observed between the presence of SC at radiological examination and the presence of punctuate/fragmented calcification at histology. In addition, in 58.3% of cases, plaque enhancement was observed, which correlated with plaque inflammation and the fibrolipid composition of the plaque. The coronary artery calcium score was 314 (± 455). There was a poor agreement between stenosis of the lumen at histology versus radiology. Our study shows that the various radiological signs of HRP can be detected in all plaques by MPMCTA, but individually only to a variable extent; plaque enhancement appeared as a new sign of vulnerability. In the postmortem approach, these radiological markers of HRP, should always be applied in combination, which can be useful for developing a predictive model for diagnosing coronary SCD.

Imaging biomarkers in cardiac CT: moving beyond simple coronary anatomical assessment

Cardiac computed tomography angiography (CCTA) is considered the standard non-invasive tool to rule-out obstructive coronary artery disease (CAD). Moreover, several imaging biomarkers have been developed on cardiac-CT imaging to assess global CAD severity and atherosclerotic burden, including coronary calcium scoring, the segment involvement score, segment stenosis score and the Leaman-score. Myocardial perfusion imaging enables the diagnosis of myocardial ischemia and microvascular damage, and the CT-based fractional flow reserve quantification allows to evaluate non-invasively hemodynamic impact of the coronary stenosis. The texture and density of the epicardial and perivascular adipose tissue, the hypodense plaque burden, the radiomic phenotyping of coronary plaques or the fat radiomic profile are novel CT imaging features emerging as biomarkers of inflammation and plaque instability, which may implement the risk stratification strategies. The ability to perform myocardial tissue characterization by extracellular volume fraction and radiomic features appears promising in predicting arrhythmogenic risk and cardiovascular events. New imaging biomarkers are expanding the potential of cardiac CT for phenotyping the individual profile of CAD involvement and opening new frontiers for the practice of more personalized medicine.

No evidence of coronary plaque stabilization by allopurinol in patients with acute coronary syndrome

BACKGROUND

Allopurinol, a xanthine inhibitor that lowers uric acid concentration, has been proven to reduce inflammation and oxidative stress in patients with cardiovascular disease. However, it is unknown whether these beneficial effects translate into favorable plaque modification in acute coronary syndromes (ACS). This study aimed to investigate whether allopurinol could improve coronary plaque stabilization using coronary computed tomography angiography (CCTA).

METHODS

This was a prospective, single-center, randomized, double-blind clinical trial began in March 2019. A total of 162 ACS patients aged 18-80 years with a blood level of high-sensitivity C-reactive protein (hsCRP) ​> ​2 ​mg/L were included. The subjects were randomly assigned in a 1:1 ratio to receive either allopurinol sustained-release capsules (at a dose of 0.25 ​g once daily) or placebo for 12 months. The plaque analysis was performed at CCTA. The primary efficacy endpoint was the change in low-attenuation plaque volume (LAPV) from baseline to the 12-month follow-up.

RESULTS

Among 162 patients, 54 in allopurinol group and 51 in placebo group completed the study. The median follow-up duration was 14 months in both groups. Compared with placebo, allopurinol therapy did not significantly alter LAPV (-13.4 ​± ​3.7 ​% vs. -17.8 ​± ​3.6 ​%, p ​= ​0.390), intermediate attenuation plaque volume (-16.1 ​± ​3.0 ​% vs. -16.2 ​± ​2.9 ​%, p ​= ​0.992), dense calcified plaque volume (12.2 ​± ​13.7 ​% vs. 9.7 ​± ​13.0 ​%, p ​= ​0.894), total atheroma volume (-15.2 ​± ​3.2 ​% vs. -16.4 ​± ​3.1 ​%, p ​= ​0.785), remodeling index (2.0 ​± ​3.9 ​% vs. 5.4 ​± ​3.8 ​%, p ​= ​0.536) or hsCRP levels (-73.6 [-91.6-17.9] % vs. -81.2 [-95.4-47.7] %, p ​= ​0.286).

CONCLUSIONS

Our findings suggest that allopurinol does not improve atherosclerotic plaque stability or inflammation in ACS.

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.

CT Coronary Angiography: Technical Approach and Atherosclerotic Plaque Characterization

Coronary computed tomography angiography (CCTA) currently represents a robust imaging technique for the detection, quantification and characterization of coronary atherosclerosis. However, CCTA remains a challenging task requiring both high spatial and temporal resolution to provide motion-free images of the coronary arteries. Several CCTA features, such as low attenuation, positive remodeling, spotty calcification, napkin-ring and high pericoronary fat attenuation index have been proved as associated to high-risk plaques. This review aims to explore the role of CCTA in the characterization of high-risk atherosclerotic plaque and the recent advancements in CCTA technologies with a focus on radiomics plaque analysis.

Coronary Atherosclerosis Phenotypes in Focal and Diffuse Disease

BACKGROUND

The interplay between coronary hemodynamics and plaque characteristics remains poorly understood.

OBJECTIVES

The aim of this study was to compare atherosclerotic plaque phenotypes between focal and diffuse coronary artery disease (CAD) defined by coronary hemodynamics.

METHODS

This multicenter, prospective, single-arm study was conducted in 5 countries. Patients with functionally significant lesions based on an invasive fractional flow reserve ≤0.80 were included. Plaque analysis was performed by using coronary computed tomography angiography and optical coherence tomography. CAD patterns were assessed using motorized fractional flow reserve pullbacks and quantified by pullback pressure gradient (PPG). Focal and diffuse CAD was defined according to the median PPG value.

RESULTS

A total of 117 patients (120 vessels) were included. The median PPG was 0.66 (IQR: 0.54-0.75). According to coronary computed tomography angiography analysis, plaque burden was higher in patients with focal CAD (87% ± 8% focal vs 82% ± 10% diffuse; P = 0.003). Calcifications were significantly more prevalent in patients with diffuse CAD (Agatston score per vessel: 51 [IQR: 11-204] focal vs 158 [IQR: 52-341] diffuse; P = 0.024). According to optical coherence tomography analysis, patients with focal CAD had a significantly higher prevalence of circumferential lipid-rich plaque (37% focal vs 4% diffuse; P = 0.001) and thin-cap fibroatheroma (TCFA) (47% focal vs 10% diffuse; P = 0.002). Focal disease defined by PPG predicted the presence of TCFA with an area under the curve of 0.73 (95% CI: 0.58-0.87).

CONCLUSIONS

Atherosclerotic plaque phenotypes associate with intracoronary hemodynamics. Focal CAD had a higher plaque burden and was predominantly lipid-rich with a high prevalence of TCFA, whereas calcifications were more prevalent in diffuse CAD. (Precise Percutaneous Coronary Intervention Plan [P3]; NCT03782688).

Cardiac Computed Tomography Angiography in CAD Risk Stratification and Revascularization Planning

PURPOSE OF REVIEW

Functional stress testing is frequently used to assess for coronary artery disease (CAD) in symptomatic, stable patients with low to intermediate pretest probability. However, patients with highly vulnerable plaque may have preserved luminal patency and, consequently, a falsely negative stress test. Cardiac computed tomography angiography (CCTA) has emerged at the forefront of primary prevention screening and has excellent agency in ruling out obstructive CAD with high negative predictive value while simultaneously characterizing nonobstructive plaque for high-risk features, which invariably alters risk-stratification and pre-procedural decision making.

RECENT FINDINGS

We review the literature detailing the utility of CCTA in its ability to risk-stratify patients with CAD based on calcium scoring as well as high-risk phenotypic features and to qualify the functional significance of stenotic lesions.

SUMMARY

Calcium scores ≥ 100 should prompt consideration of statin and aspirin therapy. Spotty calcifications < 3 mm, increased non-calcified plaque > 4 mm3 per mm of the vessel wall, low attenuation < 30 HU soft plaque and necrotic core with a rim of higher attenuation < 130 HU, and a positive remodeling index ratio > 1.1 all confer additive risk for acute plaque rupture when present. Elevations in the perivascular fat attenuation index > -70.1 HU are a strong predictor of all-cause mortality and can further the risk stratification of patients in the setting of a non-to-minimal plaque burden. Lastly, a CT-derived fractional flow reserve (FFRCT) < 0.75 or values from 0.76 to 0.80 in conjunction with additional risk factors is suggestive of flow-limiting disease that would benefit from invasive testing. The wealth of information available through CCTA can allow clinicians to risk-stratify patients at elevated risk for an acute ischemic event and engage in advanced revascularization planning.

Investigating the Association between Coronary Artery Disease and the Liver Fibrosis-4 Index in Patients Who Underwent Coronary Computed Tomography Angiography: A Cross-Sectional Study

Liver fibrosis scores, indicative of hepatic scarring, have recently been linked to coronary artery disease (CAD). We investigated the association between CAD and the fibrosis-4 index (FIB-4I) in patients who underwent coronary computed tomography angiography (CCTA). This study included 1244 patients who were clinically suspected of having CAD. The presence or absence of CAD was the primary endpoint. FIB-4I was higher in the CAD group than in the non-CAD group (1.95 ± 1.21 versus [vs.] 1.65 ± 1.22, p < 0.001). FIB-4I was also higher in the hypertension (HTN) group than in the non-HTN group (1.90 ± 1.32 vs. 1.60 ± 0.98, p < 0.001). In all patients, high FIB-4I (≥2.67) was a predictor of presence of CAD (odds ratio [OR]: 1.92, 95% confidence interval [CI]: 1.30-2.83, p = 0.001), and low FIB-4I (≤1.29) was proven to be a predictor of absence of CAD (OR: 0.65, 95% CI: 0.48-0.88, p = 0.006). In the HTN group, high and low FIB-4I levels, were found to be predictors for CAD (OR: 2.01, 95% CI: 1.26-3.21, p < 0.001 and OR: 0.65, 95% CI: 0.45-0.94, p < 0.022, respectively), in particular. FIB-4I may serve as a diagnostic indicator of the presence or absence of CAD in hypertensive patients undergoing CCTA.

Predictive value of DEEPVESSEL-fractional flow reserve and quantitative plaque analysis based on coronary CT angiography for major adverse cardiac events

AIM

To investigate the predictive value of the combination of DEEPVESSEL-fractional flow reserve (DVFFR) and quantitative plaque analysis using coronary computed tomographic angiography (CCTA) for major adverse cardiac events (MACE).

METHOD

In this retrospective study, data from 69 vessels from 58 consecutive patients were collected. These patients who underwent coronary angiography (CAG) with DVFFR were divided into MACE-positive and MACE-negative groups. DVFFR measurements were obtained from CCTA images acquired before CAG, and an FFR or DVFFR value ≤ 0.80 was considered haemodynamically significant. CCTA images were analysed quantitatively using automated software to obtain the following indices: total plaque volume (TPV) and burden (TPB), calcified plaque volume (CPV) and burden (CPB), non-calcified plaque volume (NCPV) and burden (NCPB), low-attenuation plaque (LAP), minimum lumen area (MLA), stenosis grade (SG) and lesion length (LL). Univariate and multivariate logistic regression, correlation, and receiver operating characteristic (ROC) analyses were used for statistical analysis.

RESULTS

DVFFR was highly correlated with invasive FFR (R=0.728), and the Bland-Altman plot showed good agreement between DVFFR and FFR (95% CI: -0.109-0.087) on a per-vessel level. DVFFR showed a high diagnostic performance in identifying abnormal haemodynamic vessels, with an area under the ROC curve (AUC) of 0.984. In multivariate analysis, the following biomarkers were predictors of MACE: DVFFR ≤ 0.8, SG, TPB, NCPB, and LL values. The combination of the above independent risk factors yielded the most valuable prediction for MACE (AUC:0.888).

CONCLUSIONS

DVFFR was highly correlated with FFR with satisfactory diagnostic accuracy. DVFFR, together with plaque analysis indices, yielded valuable predictions for MACE.

Prognostic Utility of Coronary Computed Tomography Angiography-derived Plaque Information on Long-term Outcome in Patients With and Without Diabetes Mellitus

PURPOSE

To investigate the long-term prognostic value of coronary computed tomography angiography (cCTA)-derived plaque information on major adverse cardiac events (MACE) in patients with and without diabetes mellitus.

MATERIALS AND METHODS

In all, 64 patients with diabetes (63.3±10.1 y, 66% male) and suspected coronary artery disease who underwent cCTA were matched with 297 patients without diabetes according to age, sex, cardiovascular risk factors, and statin and antithrombotic therapy. MACE were recorded. cCTA-derived risk scores and plaque measures were assessed. The discriminatory power to identify MACE was evaluated using multivariable regression analysis and concordance indices.

RESULTS

After a median follow-up of 5.4 years, MACE occurred in 31 patients (8.6%). In patients with diabetes, cCTA risk scores and plaque measures were significantly higher compared with nondiabetic patients (all P <0.05). The following plaque measures were predictors of MACE using multivariable Cox regression analysis (hazard ratio [HR]) in patients with diabetes: segment stenosis score (HR=1.20, P <0.001), low-attenuation plaque (HR=3.47, P =0.05), and in nondiabetic patients: segment stenosis score (HR=1.92, P <0.001), Agatston score (HR=1.0009, P =0.04), and low-attenuation plaque (HR=4.15, P =0.04). A multivariable model showed a significantly improved C-index of 0.96 (95% confidence interval: 0.94-0.0.97) for MACE prediction, when compared with single measures alone.

CONCLUSION

Diabetes is associated with a significantly higher extent of coronary artery disease and plaque features, which have independent predictive values for MACE. cCTA-derived plaque information portends improved risk stratification of patients with diabetes beyond the assessment of obstructive stenosis on cCTA alone with subsequent impact on individualized treatment decision-making.

Association of epicardial adipose tissue with coronary CT angiography plaque parameters on cardiovascular outcome in patients with and without diabetes mellitus

BACKGROUND AND AIMS

We aimed to evaluate the association of epicardial adipose tissue (EAT) with coronary CT angiography (CCTA) plaque parameters on cardiovascular outcome in patients with and without diabetes mellitus.

METHODS

Data of 353 patients (62.9 ± 10.4 years, 62% male), who underwent CCTA as part of their clinical workup for the evaluation of suspected or known CAD, were retrospectively analyzed. EAT volume and plaque parameters from CCTA were compared in patients with diabetes (n = 63) and without diabetes (n = 290). Follow-up was performed to record adverse cardiovascular events. The predictive value to detect adverse cardiovascular events was assessed using concordance indices (CIs) and multivariable Cox proportional hazards analysis.

RESULTS

In total, 33 events occurred after a median follow-up of 5.1 years. In patients with diabetes, EAT volume and plaque parameters were significantly higher than in patients without diabetes (all p < 0.05). A multivariable model demonstrated an incrementally improved C-index of 0.84 (95%CI 0.80-0.88) over the Framingham risk score and single measures alone. In multivariable Cox regression analysis EAT volume (Hazard ratio[HR] 1.21, p = 0.022), obstructive CAD (HR 1.18, p = 0.042), and ≥2 high-risk plaque features (HR 2.13, p = 0.031) were associated with events in patients with diabetes and obstructive CAD (HR 1.88, p = 0.017), and Agatston calcium score (HR 1.009, p = 0.039) in patients without diabetes.

CONCLUSIONS

EAT, as a biomarker of inflammation, and plaque parameters, as an extent of atherosclerotic CAD, are higher in patients with diabetes and are associated with increased adverse cardiovascular outcomes. These parameters may help identify patients at high risk with need for more aggressive therapeutic and preventive care.

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.

The role of cardiac computed tomography in predicting adverse coronary events

Cardiac computed tomography (CCT) is now considered a first-line diagnostic test for suspected coronary artery disease (CAD) providing a non-invasive, qualitative, and quantitative assessment of the coronary arteries and pericoronary regions. CCT assesses vascular calcification and coronary lumen narrowing, measures total plaque burden, identifies plaque composition and high-risk plaque features and can even assist with hemodynamic evaluation of coronary lesions. Recent research focuses on computing coronary endothelial shear stress, a potent modulator in the development and progression of atherosclerosis, as well as differentiating an inflammatory from a non-inflammatory pericoronary artery environment using the simple measurement of pericoronary fat attenuation index. In the present review, we discuss the role of the above in the diagnosis of coronary atherosclerosis and the prediction of adverse cardiovascular events. Additionally, we review the current limitations of cardiac computed tomography as an imaging modality and highlight how rapid technological advancements can boost its capacity in predicting cardiovascular risk and guiding clinical decision-making.

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.

Quantitative assessment of atherosclerotic plaque, recent progress and current limitations

An important advantage of computed tomography coronary angiography (CCTA) is its ability to visualize the presence and severity of atherosclerotic plaque, rather than just assessing coronary artery stenoses. Until recently, assessment of plaque subtypes on CCTA relied on visual assessment of the extent of calcified/non-calcified plaque, or visually identifying high-risk plaque characteristics. Recent software developments facilitate the quantitative assessment of plaque volume or burden on CCTA, and the identification of subtypes of plaque based on their attenuation density. These techniques have shown promise in single and multicenter studies, demonstrating that the amount and type of plaque are associated with subsequent cardiac events. However, there are a number of limitations to the application of these techniques, including the limitations imposed by the spatial resolution of current CT scanners, challenges from variations between reconstruction algorithms, and the additional time to perform these assessments. At present, these are a valuable research technique, but not yet part of routine clinical practice. Future advances that improve CT resolution, standardize acquisition techniques and reconstruction algorithms and automate image analysis will improve the clinical utility of these techniques. This review will discuss the technical aspects of quantitative plaque analysis and present pro and con arguments for the routine use of quantitative plaque analysis on CCTA.

Quantitative plaque assessment by coronary computed tomography angiography: An up-to-date review

Coronary computed tomography angiography has an emerging role in the diagnostic workup of coronary artery disease. Due to its high sensitivity and negative predictive value, coronary computed tomography angiography can rule out obstructive coronary artery diseases and substitute invasive coronary angiography in many cases. In addition, coronary computed tomography angiography provides a unique information beyond stenosis grading as it can visualize atherosclerosis and quantify its extent. Qualitative and quantitative plaque assessment provides an incremental value in the prediction of future major adverse cardiac events. Moreover, determining adverse plaque features has a potential to identify advanced atherosclerosis and patients at increased risk of acute coronary syndrome. Nevertheless, challenges may emerge with the process of quantifying coronary plaques due to limited reproducibility, lack of automated, standardized and validated techniques. Therefore, reliable quantified data are scarce due to the various computed tomography scanners and software platforms and investigations with small sample sizes. Radiomics and machine learning-based image processing methods are relatively new in the field of cardiovascular plaque imaging. These techniques hold the promise to improve diagnostic performance, reproducibility and prognostic value of computed tomography based plaque assessment.

Association Between Major Adverse Cardiovascular Events and the Ratio of Subcutaneous Fat Area to Visceral Fat Area in Patients Who Have Undergone Multidetector Row Computed Tomography

Background: Obesity is a critical cardiovascular risk factor that has been defined in terms of body mass index (BMI), abdominal circumference (AC), and fat area. In this study, we examined which markers of obesity are most closely associated with major adverse cardiovascular events (MACE).

Methods and Results: This prospective cohort study enrolled 529 consecutive patients who initially underwent coronary computed tomography angiography for screening of coronary atherosclerosis at Fukuoka University Hospital (FU-CCTA Registry) and either were clinically suspected of having coronary artery disease (CAD) or had at least 1 cardiovascular risk factor with a follow-up of up to 5 years. Measurements of subcutaneous fat area (SFA), visceral fat area (VFA), and AC were quantified using multidetector row computed tomography. The primary endpoint was MACE. SFA and the SFA to VFA ratio (SFA/VFA) were significantly lower in the MACE than non-MACE group. SFA, AC, BMI, and SFA/VFA were each independently associated with MACE. Receiver operating characteristic curve analysis revealed a greater area under the curve for SFA/VFA than for the other parameters. The cut-off level of SFA/VFA with the greatest sensitivity and specificity for the diagnosis of MACE was 1.45 (sensitivity 0.849, specificity 0.472).

Conclusions: Our results suggest that SFA/VFA may be a marker for evaluating the presence of MACE.

Computed Tomography Coronary Plaque Characteristics Predict Ischemia Detected by Invasive Fractional Flow Reserve

PURPOSE

Coronary computed tomography angiography (CCTA) plaque quantification has been proposed to be of incremental value in the prediction of ischemia, although prior studies have shown conflicting results. We aimed to determine whether CCTA plaque features assessed on a commercial vendor platform predict invasive fractional flow reserve (FFR)/instantaneous wave-free ratio (IFR).

METHODS

Consecutive patients who underwent CCTA for evaluation of suspected stable coronary artery disease followed by invasive coronary physiology testing within 60 days at a single academic center were identified retrospectively. Semiautomated plaque quantification of the vessel proximal to the location of FFR/IFR measurement was carried out in TeraRecon, along with simple visual assessment for high-risk plaque features of positive remodeling, spotty calcification, low-attenuation plaque (LAP), and lesion length. Ischemia was defined by FFR ≤0.80 or IFR ≤0.89.

RESULTS

A total of 134 patients (62% male, mean age 62±10 y) were included in this study. On univariate logistic regression, the following visual plaque analysis parameters were predictive of ischemia: positive remodeling (odds ratio [OR] with 95% confidence interval [CI]: 4.96; 2.25-10.95; P<0.001), lesion length (OR for every 1 mm with 95% CI: 1.24; 1.14-1.34; P<0.001), spotty calcification (OR with 95% CI: 6.67; 1.67-26.64; P=0.007), and LAP (OR with 95% CI: 30; 3.78-246; P=0.001). None of the semiautomated plaque quantification parameters, such as noncalcified plaque volume or LAP volume, were predictive of ischemia. On stepwise multivariable logistic regression, lesion length (OR with 95% CI: 1.25; 1.14-1.37; P<0.0001) and LAP (OR with 95% CI: 43; 4.4-438; P=0.001) were significant predictors of ischemia, improving the area under the curve of CCTA from 0.53 to 0.87.

CONCLUSIONS

Simple visual plaque assessment for high-risk plaque features improved the performance of CCTA to predict ischemia. Semiautomated plaque quantification performed on a commercial vendor platform was not predictive of ischemia.

Coronary Computed Tomography Angiography Assessment of High-Risk Plaques in Predicting Acute Coronary Syndrome

Coronary computed tomography angiography (CCTA) is a comprehensive, non-invasive and cost-effective imaging assessment approach, which can provide the ability to identify the characteristics and morphology of high-risk atherosclerotic plaques associated with acute coronary syndrome (ACS). The development of CCTA and latest advances in emerging technologies, such as computational fluid dynamics (CFD), have made it possible not only to identify the morphological characteristics of high-risk plaques non-invasively, but also to assess the hemodynamic parameters, the environment surrounding coronaries and so on, which may help to predict the risk of ACS. In this review, we present how CCTA was used to characterize the composition and morphology of high-risk plaques prone to ACS and the current role of CCTA, including emerging CCTA technologies, advanced analysis, and characterization techniques in prognosticating the occurrence of ACS.

Measurement of Plaque Characteristics Using Coronary Computed Tomography Angiography: Achieving High Interobserver Performance

Background

Coronary computed tomography angiography (CCTA) is used to assess plaque characteristics, remodelling, and progression and regression. Few papers address standard operating procedures that ensure achievement of high interobserver reproducibility. Moreover, assessment of coronary artery bypass grafts has not been reported.

Methods

A training set of images was created of native coronary segments, spanning the full range of atheromatous disease from normal to severe, excluding totally occluded segments, and including segments with or without calcification (n = 24) and completely normal-appearing bypass grafts (n = 16). Three observers used a validated software program during a training phase to establish standard operating procedures and then to achieve high intraobserver performance based on Pearson’s correlation coefficient. Subsequently, interobserver variability for the laboratory as a whole was determined with a focus on measures of plaque volume, low- attenuation plaque (LAP), mixed plaque (MP), and calcified plaque (CP).

Results

We found no substantive differences in analytical issues between grafts and native vessels and emphasize the aggregated data. The range of mean total plaque percent was approximately 55% of total vessel volume with maximal interobserver mean absolute differences of 2% or less. Percent of LAP, MP, and CP demonstrated interobserver standard errors of 1% to 2% and interobserver mean absolute differences of 0% to 1%. Pearson’s correlations were all highly significant and ranged from 0.969 to 0.999.

Conclusions

CCTA provides a rich diversity of measures of atherosclerosis in coronary and bypass segments that are highly reproducible with experience and adherence to standard operating procedures.

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

Coronary computed tomographic angiography (CCTA) provides a wealth of clinically meaningful information beyond anatomic stenosis alone, including the presence or absence of nonobstructive atherosclerosis and high-risk plaque features as precursors for incident coronary events. There is, however, no uniform agreement on how to identify and quantify these features or their use in evidence-based clinical decision-making. This statement from the Society of Cardiovascular Computed Tomography and North American Society of Cardiovascular Imaging addresses this gap and provides a comprehensive review of the available evidence on imaging of coronary atherosclerosis. In this statement, we provide standardized definitions for high-risk plaque (HRP) features and distill the evidence on the effectiveness of risk stratification into usable practice points. This statement outlines how this information should be communicated to referring physicians and patients by identifying critical elements to include in a structured CCTA report - the presence and severity of atherosclerotic plaque (descriptive statements, CAD-RADS™ categories), the segment involvement score, HRP features (e.g., low attenuation plaque, positive remodeling), and the coronary artery calcium score (when performed). Rigorous documentation of atherosclerosis on CCTA provides a vital opportunity to make recommendations for preventive care and to initiate and guide an effective care strategy for at-risk patients.

Relationship between changes in pericoronary adipose tissue attenuation and coronary plaque burden quantified from coronary computed tomography angiography

AIMS

Increased attenuation of pericoronary adipose tissue (PCAT) around the proximal right coronary artery (RCA) from coronary computed tomography angiography (CTA) has been shown to be associated with coronary inflammation and improved prediction of cardiac death over plaque features. Our aim was to investigate whether PCAT CT attenuation is related to progression of coronary plaque burden.

METHODS AND RESULTS

We analysed CTA studies of 111 stable patients (age 59.2 ± 9.8 years, 77% male) who underwent sequential CTA (3.4 ± 1.6 years between scans) with identical acquisition protocols. Total plaque (TP), calcified plaque (CP), non-calcified plaque (NCP), and low-density non-calcified plaque (LD-NCP) volumes and corresponding burden (plaque volume × 100%/vessel volume) were quantified using semi-automated software. PCAT CT attenuation (HU) was measured around the proximal RCA, the most standardized method for PCAT analysis. Patients with an increase in NCP burden (n = 51) showed an increase in PCAT attenuation, whereas patients with a decrease in NCP burden (n = 60) showed a decrease {4.4 [95% confidence interval (CI) 2.6-6.2] vs. -2.78 (95% CI -4.6 to -1.0) HU, P < 0.0001}. Changes in PCAT attenuation correlated with changes in the burden of NCP (r = 0.55, P < 0.001) and LD-NCP (r = 0.24, P = 0.01); but not CP burden (P = 0.3). Increased baseline PCAT attenuation ≥-75 HU was independently associated with increase in NCP (odds ratio 3.07, 95% CI 1.4-7.0; P < 0.008) and TP burden on follow-up CTA.

CONCLUSION

PCAT attenuation measured from routine CTA is related to the progression of NCP and TP burden. This imaging biomarker may help to identify patients at increased risk of high-risk plaque progression and allow monitoring of beneficial changes from medical therapy.

Presence and severity of coronary artery disease in patients who achieved intensive blood pressure reduction at the time of coronary computed tomography angiography

Blood pressure (BP)-lowering treatment should be aimed at achieving intensive BP control. Coronary computed tomography angiography (CCTA) has become more widely available and enables the accurate noninvasive assessment of coronary artery stenosis for screening. The presence and severity of coronary artery disease (CAD) in patients who achieved intensive BP control at the time of CCTA were compared to those in patients without hypertension (HTN). Nine hundred eighty-five consecutive subjects who were clinically suspected of having CAD or who had at least one cardiac risk factor underwent CCTA. The patients were divided into four groups: patients without HTN (non-HTN group), hypertensive patients who underwent intensive BP lowering (intensive group, <130/80 mmHg), patients who underwent standard BP lowering (standard group, 130-139/80-89 mmHg) and patients with uncontrolled BP (uncontrolled group, >140/90 mmHg). Interestingly, %CAD in the Intensive group was significantly higher than that in patients without HTN. The Intensive group was older and had a higher body mass index, more significantly stenosed coronary vessels, lower levels of high-density lipoprotein cholesterol in the blood, and higher rates of dyslipidemia, diabetes, and anti-dyslipidemia and anti-diabetic medication use than the non-HTN group. The presence of CAD in the Intensive group was independently associated with age, male and smoking, whereas the presence of CAD in the non-HTN group was associated with age, male and family history. Finally, predictors of the number of VDs in the non-HTN and intensive BP-lowering groups were age, male, DL, and intensive BP lowering. In conclusion, these results suggest that hypertensive patients need more rigorous management of other coronary risk factors, despite receiving intensive BP-lowering treatment.

Improved long-term prognostic value of coronary CT angiography-derived plaque measures and clinical parameters on adverse cardiac outcome using machine learning

OBJECTIVES

To evaluate the long-term prognostic value of coronary CT angiography (cCTA)-derived plaque measures and clinical parameters on major adverse cardiac events (MACE) using machine learning (ML).

METHODS

Datasets of 361 patients (61.9 ± 10.3 years, 65% male) with suspected coronary artery disease (CAD) who underwent cCTA were retrospectively analyzed. MACE was recorded. cCTA-derived adverse plaque features and conventional CT risk scores together with cardiovascular risk factors were provided to a ML model to predict MACE. A boosted ensemble algorithm (RUSBoost) utilizing decision trees as weak learners with repeated nested cross-validation to train and validate the model was used. Performance of the ML model was calculated using the area under the curve (AUC).

RESULTS

MACE was observed in 31 patients (8.6%) after a median follow-up of 5.4 years. Discriminatory power was significantly higher for the ML model (AUC 0.96 [95%CI 0.93-0.98]) compared with conventional CT risk scores including Agatston calcium score (AUC 0.84 [95%CI 0.80-0.87]), segment involvement score (AUC 0.88 [95%CI 0.84-0.91]), and segment stenosis score (AUC 0.89 [95%CI 0.86-0.92], all p < 0.05). Similar results were shown for adverse plaque measures (AUCs 0.72-0.82, all p < 0.05) and clinical parameters including the Framingham risk score (AUCs 0.71-0.76, all p < 0.05). The ML model yielded significantly higher diagnostic performance compared with logistic regression analysis (AUC 0.96 vs. 0.92, p = 0.024).

CONCLUSION

Integration of a ML model improves the long-term prediction of MACE when compared with conventional CT risk scores, adverse plaque measures, and clinical information. ML algorithms may improve the integration of patient's information to enhance risk stratification.

KEY POINTS

• A machine learning (ML) model portends high discriminatory power to predict major adverse cardiac events (MACE). • ML-based risk stratification shows superior diagnostic performance for MACE prediction over coronary CT angiography (cCTA)-derived risk scores or clinical parameters alone. • A ML model outperforms conventional logistic regression analysis for the prediction of MACE.

Associations between the psoas major muscle index and the presence and severity of coronary artery disease

The associations between the presence and severity of coronary artery disease (CAD) and measurements of the psoas major muscle (PMM) as assessed by multidetector row coronary computed tomography angiography (MDCT) are not known.We enrolled 793 patients who were clinically suspected to have CAD or had at least one cardiac risk factor and had undergone MDCT. The number of significantly stenosed coronary vessels (VD) and measurements of the PMM index (PMMI) were determined using MDCT.PMMI in the CAD group was significantly lower than that in the non-CAD group in males, but not females. In addition, the levels of PMMI tended to increase as the number of VD decreased in males. When male patients were divided into 2 groups according to median value of age, that is, relatively younger (53.4 ± 9.2 years) and older (72.6 ± 5.7 years) groups, the presence of CAD was independently associated with PMMI in the younger group by a multiple logistic regression analysis. The cut-off level of PMMI that gave the greatest sensitivity and specificity for the diagnosis of CAD in younger males was 8.3 cm/m (sensitivity 0.441, specificity 0.752).In conclusion, PMMI may be an imaging marker for evaluating the presence and/or severity of CAD in males, and particularly in the non-elderly.

Vulnerable Plaques Producing an Acute Coronary Syndrome Exhibit a Different CT Phenotype than Those That Remain Silent

Background: All plaques that trigger acute coronary syndromes (ACS) present various characteristics of vulnerability. However, not all vulnerable plaques (VP) lead to an ACS. This raises the question as to which of the established CT vulnerability features hold the highest probability of developing ACS.

Aim: To identify the distinct phenotype of VP that exposes the unstable atheromatous plaque to a higher risk of rupture.

Material and Methods: In total, 20 patients in whom cardiac computed tomographic angiography (CCTA) identified the presence of a vulnerable plaque and who developed an ACS within 6 months after CCTA examination were enrolled in the study, and compared to 20 age- and gender-matched subjects with VPs who did not develop an ACS. All included patients presented VPs at baseline, defined as the presence of minimum 50% degree of stenosis and at least one CT marker of vulnerability (low attenuation plaques [LAP], napkin-ring sign [NRS], positive remodeling [PR], spotty calcifications [SCs]).

Results: The two groups were not different in regards to age, gender, cardiovascular risk factors, and comorbidities. Patients who developed an ACS at six months presented higher volumes of lipid-rich (p = 0.01) and calcified plaques (p = 0.01), while subjects in the control group presented plaques with a larger fibrotic content (p = 0.0005). The most frequent vulnerability markers within VPs that had triggered ACS were LAPs (p <0.0001) and PR (p <0.0001). Multivariate analysis identified LAP as the strongest independent predictor of ACS at 6 months in our study population (OR 8.18 [1.23-95.08], p = 0.04).

Conclusions: VPs producing an ACS exhibit a different phenotype compared to VPs that remain silent. The CCTA profile of VPs producing an ACS includes the presence of low attenuation, positive remodeling, and lipid-rich atheroma. The presence of these features in VPs identifies very high-risk patients, who can benefit from adapted therapeutic strategies in order to prevent an ACS.

From CT to artificial intelligence for complex assessment of plaque-associated risk

The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust information on the overall coronary circulation and luminal stenosis, also providing the ability to assess the composition, morphology, and vulnerability of atherosclerotic plaques. In addition, the perivascular adipose tissue (PVAT) has recently emerged as a marker of increased cardiovascular risk. The addition of PVAT quantification to standard CCTA imaging may provide the ability to extract information on local inflammation, for an individualized approach in coronary risk stratification. The development of image post-processing tools over the past several years allowed CCTA to provide a significant amount of data that can be incorporated into machine learning (ML) applications. ML algorithms that use radiomic features extracted from CCTA are still at an early stage. However, the recent development of artificial intelligence will probably bring major changes in the way we integrate clinical, biological, and imaging information, for a complex risk stratification and individualized therapeutic decision making in patients with CAD. This review aims to present the current evidence on the complex role of CCTA in the detection and quantification of vulnerable plaques and the associated coronary inflammation, also describing the most recent developments in the radiomics-based machine learning approach for complex assessment of plaque-associated risk.

[Prognosis of patients with vulnerable plaques indicated by coronary CT angiography]

OBJECTIVE

To investigate the prognosis of patients with vulnerable plaque indicated by coronary CT angiography (CCTA).

METHODS

Totally 1963 patients underwent CCTA from February 2nd 2015 to September 13th 2015, and 2728 coronary borderline lesions (stenosis of 50%-70%) were detected. Among them 804 patients had vulnerable plaques and 1159 patients had stable plaques. The primary endpoint was major cardiac adverse events (MACE), including cardiac death, acute myocardial infarction and target lesion revascularization.

RESULTS

Patients were followed up for a mean follow-up of 27.4±2.3 months. The incidence of MACE in the vulnerable plaque group was significantly higher than that in the stable plaque group (10.8%vs 2.3%, P &lt; 0.01). After adjusting for age, gender, smoking, hypertension, diabetes, hyperlipidemia, the MACE hazard ratio (HR) in the vulnerable plaque group was 5.022 (95% CI:3.254-7.751, P &lt; 0.01).Subgroup analysis showed that in the vulnerable plaque group, the incidence of MACE in patients taking antiplatelet and statin ≤3 months and those taking antiplatelet and statin &gt; 3 months was 17.0%and 5.8%, respectively (HR=3.149, 95% CI:1.987-4.992, P &lt; 0.01); but the difference did not seen in stable plaque group (HR=1.721, 95% CI:0.798-3.712, P&gt;0.05).

CONCLUSIONS

This study confirmed the risk of MACE in patients with vulnerable plaque detected by CCTA and the drug treatment may reduce the risk for patients with vulnerable plaque.

Noncalcified plaque burden quantified from coronary computed tomography angiography improves prediction of side branch occlusion after main vessel stenting in bifurcation lesions: results from the CT-PRECISION registry

OBJECTIVES

To assess the incremental value of quantitative plaque features measured from computed tomography angiography (CTA) for predicting side branch (SB) occlusion in coronary bifurcation intervention.

METHODS

We included 340 patients with 377 bifurcation lesions in the post hoc analysis of the CT-PRECISION registry. Each bifurcation was divided into three segments: the proximal main vessel (MV), the distal MV, and the SB. Segments with evidence of coronary plaque were analyzed using semi-automated software allowing for quantitative analysis of coronary plaque morphology and stenosis. Coronary plaque measurements included calcified and noncalcified plaque volumes, and corresponding burdens (respective plaque volumes × 100%/vessel volume), remodeling index, and stenosis.

RESULTS

SB occlusion occurred in 28 of 377 bifurcation lesions (7.5%). The presence of visually identified plaque in the SB segment, but not in the proximal and distal MV segments, was the only qualitative parameter that predicted SB occlusion with an area under the curve (AUC) of 0.792. Among quantitative plaque parameters calculated for the SB segment, the addition of noncalcified plaque burden (AUC 0.840, p = 0.003) and low-density plaque burden (AUC 0.836, p = 0.012) yielded significant improvements in predicting SB occlusion. Using receiver operating characteristic curve analysis, optimal cut-offs for noncalcified plaque burden and low-density plaque burden were > 33.6% (86% sensitivity and 78% specificity) and > 0.9% (89% sensitivity and 73% specificity), respectively.

CONCLUSIONS

CTA-derived noncalcified plaque burden, when added to the visually identified SB plaque, significantly improves the prediction of SB occlusion in coronary bifurcation intervention.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03709836 registered on October 17, 2018.

Relationships between myocardial perfusion abnormalities and integrated indices of atherosclerotic burden: clinical impact of combined anatomic-functional evaluation

Aim to evaluate the relationships between functional and anatomical information obtained by myocardial perfusion imaging (MPI) and coronary computed tomography angiography (CCTA) in a series of consecutive patients at intermediate probability of coronary artery disease (CAD). Material and Methods — The study group comprised 139 patients (83 men, age of 61.6±7.5 years) who underwent CCTA and single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI). Based on CCTA results patients were divided into three groups: 1) with the absence of coronary atherosclerosis on CCTA; 2) with non-obstructive CAD (<50%); 3) with obstructive (≥50%) CAD. The Segment Involvement Score, Segment Stenosis Score (SSS) and CTA Risk Score were calculated as measures of global atherosclerosis burden. MPI studies were considered abnormal in the presence of SSS≥4. Results — Abnormal myocardial perfusion was detected in 60% of cases in group 1 and 2; in 75% of cases in group 3. The overall frequencies of normal and abnormal MPI studies differed significantly only in obstructive CAD patients and did not differ in group 1 and 2. There were no significant correlations between calcium score, atherosclerotic lesion length, positive remodelling index and MPI results in patients with non-obstructive as well as in patients with obstructive CAD. In group of patients with obstructive CAD Segment Stenosis Score correlated wekly with SSS (r=0.39, p=0.001) and SDS (r=0.28; p=0.012); the CTA Risk Score showed correlationes with SSS (r=0.38, p=0.002) and SDS (r=0.30, p=0.020). Conclusion — Myocardial perfusion abnormalities may develop even in the absence of critical coronary artery lesions. The extent of myocardial ischemia correlates with measures of global CAD burden only in patients with obstructive CAD.

Comparison of Machine Learning Computed Tomography-Based Fractional Flow Reserve and Coronary CT Angiography-Derived Plaque Characteristics with Invasive Resting Full-Cycle Ratio

Background: The aim is to compare the machine learning-based coronary-computed tomography fractional flow reserve (CT-FFR_ML) and coronary-computed tomographic morphological plaque characteristics with the resting full-cycle ratio (RFR^TM) as a novel invasive resting pressure-wire index for detecting hemodynamically significant coronary artery stenosis. Methods: In our single center study, patients with coronary artery disease (CAD) who had a clinically indicated coronary computed tomography angiography (cCTA) and subsequent invasive coronary angiography (ICA) with pressure wire-measurement were included. On-site prototype CT-FFR_ML software and on-site CT-plaque software were used to calculate the hemodynamic relevance of coronary stenosis. Results: We enrolled 33 patients (70% male, mean age 68 ± 12 years). On a per-lesion basis, the area under the receiver operating characteristic curve (AUC) of CT-FFR_ML (0.90) was higher than the AUCs of the morphological plaque characteristics length/minimal luminal diameter⁴ (LL/MLD⁴; 0.80), minimal luminal diameter (MLD; 0.77), remodeling index (RI; 0.76), degree of luminal diameter stenosis (0.75), and minimal luminal area (MLA; 0.75). Conclusion: CT-FFR_ML and morphological plaque characteristics show a significant correlation to detected hemodynamically significant coronary stenosis. Whole CT-FFR_ML had the best discriminatory power, using RFR^TM as the reference standard.

Pericoronary adipose tissue and quantitative global non-calcified plaque characteristics from CT angiography do not differ in matched South Asian, East Asian and European-origin Caucasian patients with stable chest pain

PURPOSE

South Asian (SA) have been observed to have higher cardiovascular mortality rates compared to East Asians (EA) and Caucasians. Pericoronary adipose tissue (PCAT) attenuation around the right coronary artery (RCA) from coronary CT angiography (CTA) has been associated with coronary inflammation and cardiac death. We aimed to investigate i) the relationship between plaque characteristics and PCAT attenuation and ii) to assess gender and ethnic differences in PCAT attenuation using a matched cohort of SA, EA and Caucasians.

METHOD

Three-hundred symptomatic patients who underwent CTA were matched for age, gender, BMI and diabetes (100 in each ethnic group). Semi-automated software was used to quantify the total volumes and burden of non-calcified plaque (NCP), low-density non-calcified plaque (LD-NCP) and calcified plaque (CP) in blinded core-lab analysis. PCAT CT attenuation was measured around the RCA (10-50 mm from RCA ostium), the most standardized model for PCAT analysis.

RESULTS

The total volumes and burden of NCP, LD-NCP and CP were comparable in the ethnic groups (each p > 0.05). PCAT attenuation was higher in patients with coronary plaque. PCAT attenuation correlated with the total volumes and burden of NCP, LD-NCP and CP (r>0.17; p < 0.003). Within the RCA this correlation persisted only for NCP features (r>0.39;p < 0.001). Males showed higher PCAT attenuation (p < 0.001). PCAT attenuation was similar between Caucasian, EA and SA (p = 0.32).

CONCLUSIONS

PCAT CT attenuation correlated most with its surrounded NCP features further highlighting its role as surrogate measure of coronary inflammation. As coronary plaque burden and RCA PCAT attenuation did not differ between ethnic groups, causes of increased cardiac mortality in South Asians needs further investigations.

Prognostic value of normal and non-obstructive coronary artery disease based on CT angiography findings. A 12 month follow up study

Introduction: The advent of multi-slice computed tomography (CT) technology has provided a new promising tool for non-invasive assessment of the coronary arteries. However, as the prognostic outcome of patients with normal or non-significant finding on computed tomography coronary angiography (CTCA) is not well-known, this study was aimed to determine the prognostic value of CTCA in patients with either normal or non-significant CTCA findings.

Methods: This retrospective cohort study was performed on patients who were referred for CTCA to the hospital. 527 patients with known or suspected coronary artery disease (CAD), who had undergone CTCA within one year were enrolled. Among them, data of 465 patients who had normal (no stenosis, n=362) or non-significant CTCA findings (stenosis <50% of luminal narrowing, n=103) were analyzed and prevalence of cardiac risk factors and major adverse cardiac events (MACE) were compared between these groups. In addition, a correlation between these factors and the number of involved coronary arteries was also determined.

Results: After a mean follow-up duration of 13.11±4.63 months, all cases were alive except for three patients who died by non-cardiac events. Prevalence of MACE was 0% and 3% in normal CTCA group and non-significant groups, respectively. There was no correlation found between the number of involved coronary arteries and the prevalence of MACE (P = 0.57).

Conclusion: A normal CTCA could be associated with extremely low risk of MACE over the first year after the initial imaging, whereas non-significant obstruction in coronary arteries may be associated with a slightly higher risk of MACE.

Impact of Coronary Computerized Tomography Angiography-Derived Plaque Quantification and Machine-Learning Computerized Tomography Fractional Flow Reserve on Adverse Cardiac Outcome

This study investigated the impact of coronary CT angiography (cCTA)-derived plaque markers and machine-learning-based CT-derived fractional flow reserve (CT-FFR) to identify adverse cardiac outcome. Data of 82 patients (60 ± 11 years, 62% men) who underwent cCTA and invasive coronary angiography (ICA) were analyzed in this single-center retrospective, institutional review board-approved, HIPAA-compliant study. Follow-up was performed to record major adverse cardiac events (MACE). Plaque quantification of lesions responsible for MACE and control lesions was retrospectively performed semiautomatically from cCTA together with machine-learning based CT-FFR. The discriminatory value of plaque markers and CT-FFR to predict MACE was evaluated. After a median follow-up of 18.5 months (interquartile range 11.5 to 26.6 months), MACE was observed in 18 patients (21%). In a multivariate analysis the following markers were predictors of MACE (odds ratio [OR]): lesion length (OR 1.16, p = 0.018), low-attenuation plaque (<30 HU) (OR 4.59, p = 0.003), Napkin ring sign (OR 2.71, p = 0.034), stenosis ≥50% (OR 3.83, p 0.042), and CT-FFR ≤0.80 (OR 7.78, p = 0.001). Receiver operating characteristics analysis including stenosis ≥50%, plaque markers and CT-FFR ≤0.80 (Area under the curve 0.94) showed incremental discriminatory power over stenosis ≥50% alone (Area under the curve 0.60, p <0.0001) for the prediction of MACE. cCTA-derived plaque markers and machine-learning CT-FFR demonstrate predictive value to identify MACE. In conclusion, combining plaque markers with machine-learning CT-FFR shows incremental discriminatory power over cCTA stenosis grading alone.

Impact of Coronary Plaque Vulnerability on Acute Cardiovascular Events – Design of a CT-based 2-year Follow-up Study

With coronary artery disease (CAD) projected to remain the leading cause of global mortality, prevention strategies seem to be the only effective approach able to reduce the burden and improve mortality and morbidity. At this moment, diagnostic strategies focus mainly on symptomatic patients, ignoring the occurrence of major cardiovascular events as the only manifestation of CAD. As two thirds of fatal myocardial infarction are resulting from plaque rupture, an approach based on the “vulnerable plaque” concept is mandatory in order to improve patient diagnosis, treatment, and, by default, prognosis. Given that the main studies focus on a plaque-centered approach, this is a prospective observational study that will perform a complex assessment of the features that characterize unstable coronary lesions, in terms of both local assessment via specific coronary computed tomography angiography markers of coronary plaque vulnerability and systemic approach based on serological markers of systemic inflammation in patients proved to be “vulnerable” by developing acute cardiovascular events.

Scoring of Coronary Artery Disease Characteristics on Coronary CT Angiograms by Using Machine Learning

Background Coronary CT angiography contains prognostic information but the best method to extract these data remains unknown. Purpose To use machine learning to develop a model of vessel features to discriminate between patients with and without subsequent death or cardiovascular events. Performance was compared with that of conventional scores. Materials and Methods Coronary CT angiography was analyzed by radiologists into four features for each of 16 coronary segments. Four machine learning model types were explored. Five conventional vessel scores were computed for comparison including the Coronary Artery Disease Reporting and Data System (CAD-RADS) score. The National Death Index was retrospectively queried from January 2004 through December 2015. Outcomes were all-cause mortality, coronary heart disease deaths, and coronary deaths or nonfatal myocardial infarctions. Score performance was assessed by using area under the receiver operating characteristic curve (AUC). Results Between February 2004 and November 2009, 6892 patients (4452 men [mean age ± standard deviation, 51 years ± 11] and 2440 women [mean age, 57 years ± 12]) underwent coronary CT angiography (median follow-up, 9.0 years; interquartile range, 8.2-9.8 years). There were 380 deaths of all causes, 70 patients died of coronary artery disease, and 43 patients reported nonfatal myocardial infarctions. For all-cause mortality, the AUC was 0.77 (95% confidence interval: 0.76, 0.77) for machine learning (k-nearest neighbors) versus 0.72 (95% confidence interval: 0.72, 0.72) for CAD-RADS (P < .001). For coronary artery heart disease deaths, AUC was 0.85 (95% confidence interval: 0.84, 0.85) for machine learning versus 0.79 (95% confidence interval: 0.78, 0.80) for CAD-RADS (P < .001). When deciding whether to start statins, if the choice is made to tolerate treating 45 patients to be sure to include one patient who will later die of coronary disease, the use of the machine learning score ensures that 93% of patients with events will be administered the drug; if CAD-RADS is used, only 69% will be treated. Conclusion Compared with Coronary Artery Disease Reporting and Data System and other scores, machine learning methods better discriminated patients who subsequently experienced an adverse event from those who did not. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Schoepf and Tesche in this issue.

Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia

OBJECTIVES

We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)-derived plaque markers combined with deep machine learning-based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FFR as the reference standard.

METHODS

Eighty-four patients (61 ± 10 years, 65% male) who had undergone cCTA followed by invasive FFR were included in this single-center retrospective, IRB-approved, HIPAA-compliant study. Various plaque markers were derived from cCTA using a semi-automatic software prototype and deep machine learning-based CT-FFR. The discriminatory value of plaque markers and CT-FFR to identify lesion-specific ischemia on a per-vessel basis was evaluated using invasive FFR as the reference standard.

RESULTS

One hundred three lesion-containing vessels were investigated. 32/103 lesions were hemodynamically significant by invasive FFR. In a multivariate analysis (adjusted for Framingham risk score), the following markers showed predictive value for lesion-specific ischemia (odds ratio [OR]): lesion length (OR 1.15, p = 0.037), non-calcified plaque volume (OR 1.02, p = 0.007), napkin-ring sign (OR 5.97, p = 0.014), and CT-FFR (OR 0.81, p < 0.0001). A receiver operating characteristics analysis showed the benefit of identifying plaque markers over cCTA stenosis grading alone, with AUCs increasing from 0.61 with ≥ 50% stenosis to 0.83 with addition of plaque markers to detect lesion-specific ischemia. Further incremental benefit was realized with the addition of CT-FFR (AUC 0.93).

CONCLUSION

Coronary CTA-derived plaque markers portend predictive value to identify lesion-specific ischemia when compared to cCTA stenosis grading alone. The addition of CT-FFR to plaque markers shows incremental discriminatory power.

KEY POINTS

• Coronary CT angiography (cCTA)-derived quantitative plaque markers of atherosclerosis portend high discriminatory power to identify lesion-specific ischemia. • Coronary CT angiography-derived fractional flow reserve (CT-FFR) shows superior diagnostic performance over cCTA alone in detecting lesion-specific ischemia. • A combination of plaque markers with CT-FFR provides incremental discriminatory value for detecting flow-limiting stenosis.

Quantitative global plaque characteristics from coronary computed tomography angiography for the prediction of future cardiac mortality during long-term follow-up

Aims

Adverse plaque characteristics determined by coronary computed tomography angiography (CTA) have been associated with future cardiac events. Our aim was to investigate whether quantitative global per-patient plaque characteristics from coronary CTA can predict subsequent cardiac death during long-term follow-up.

Methods and results

Out of 2748 patients without prior history of coronary artery disease undergoing CTA with dual-source CT, 32 patients suffered cardiac death (mean follow-up of 5 ± 2 years). These patients were matched to 32 controls by age, gender, risk factors, and symptoms (total 64 patients, 59% male, age 69 ± 10 years). Coronary CTA data sets were analysed by semi-automated software to quantify plaque characteristics over the entire coronary tree, including total plaque volume, volumes of non-calcified plaque (NCP), low-density non-calcified plaque (LD-NCP, attenuation <30 Hounsfield units), calcified plaque (CP), and corresponding burden (plaque volume × 100%/vessel volume), as well as stenosis and contrast density difference (CDD, maximum percent difference in luminal attenuation/cross-sectional area compared to proximal cross-section). In patients who died from cardiac cause, NCP, LD-NCP, CP and total plaque volumes, quantitative stenosis, and CDD were significantly increased compared to controls (P < 0.025 for all). NCP > 146 mm³ [hazards ratio (HR) 2.24; 1.09-4.58; P = 0.027], LD-NCP > 10.6 mm³ (HR 2.26; 1.11-4.63; P = 0.025), total plaque volume > 179 mm³ (HR 2.30; 1.12-4.71; P = 0.022), and CDD > 35% in any vessel (HR 2.85;1.4-5.9; P = 0.005) were associated with increased risk of future cardiac death, when adjusted for segment involvement score.

Conclusion

Among quantitative global plaque characteristics, total, non-calcified, and low-density plaque volumes as well as CDD predict cardiac death in long-term follow-up.

Cardiac CT: Technological Advances in Hardware, Software, and Machine Learning Applications

Purpose of Review

Multidetector row computed tomography (CT) allows noninvasive imaging of the heart and coronary arteries. The purpose of this review is to briefly summarize recent advances in CT hardware and software technology, and machine learning applications for cardiovascular imaging.

Recent Findings

In the last decades, there have been significant improvements in CT hardware focusing on faster gantry rotation resulting in improved temporal resolution. Concurrent hardware improvements include improved spatial resolution and higher coverage of the patient, enabling faster acquisition. Advances in cardiac CT software include methods for measurement of noninvasive FFR, coronary plaque characterization, and adipose tissue characteristics around the heart. Machine learning approaches using cardiac CT have been shown to improve both risk of prognosis and lesion-specific ischemia.

Summary

Recent advances in CT hardware and software have expanded the clinical utility of CT for cardiovascular imaging. In the next decades, continued advances can be anticipated in these areas, and in machine learning applications in cardiac CT, as they are incorporated into clinical routine for image acquisition, image analysis, and prediction of patient outcomes.

Improvement in LDL is associated with decrease in non-calcified plaque volume on coronary CTA as measured by automated quantitative software

BACKGROUND

Computed tomography coronary angiography (CTA) can be used for assessment of plaque characteristics; however, quantitative assessment of changes in plaque composition in response to LDL lowering has not been performed with CTA. We sought to assess the association between LDL reduction and changes in plaque composition with quantitative CTA.

METHODS

Quantification of total, calcified, non-calcified and low-density non-calcified plaque volumes (TPV, CPV, NCPV and LD-NCPV) was performed using semi-automated software in 234 vessels from 116 consecutive patients (89 men, 60 ± 10 years) with baseline LDL>70 mg/dl. Significant reduction in LDL was defined as a decrease by >10% of baseline LDL. Changes (Δ) in plaque volumes between the second and baseline study were compared between patients with LDL reduction (n = 63) and those with no decrease in LDL (n = 53).

RESULTS

Median LDL at baseline was 98 mg/dl [interquartile range (IQR) 83-119 mg/dl] and median ΔLDL was -14 mg/dl (IQR -38 to 3 mg/dl). Mean interval between sequential CTA was 3.5 ± 1.6 years. TPV, NCPV, and LD-NCPV decreased in patients with a reduction in LDL compared to baseline; whereas, patients without reduction in LDL experienced an increase in TPV, NCPV and LD-NCPV. After adjusting for age, statin use, diabetes, baseline LDL and baseline TPV, reduction in LDL was associated with a decrease in TPV (P = 0.005), NCPV (P = 0.002) and LD-NCPV (P = 0.011) compared to patients without a reduction in LDL.

CONCLUSION

Reduction in LDL was associated with beneficial changes in the amount and composition of noncalcified plaque as measured using semi-automated quantitative software by CTA.