Automated three-dimensional quantification of noncalcified coronary plaque from coronary CT angiography: comparison with intravascular US

Longitudinal assessment of coronary plaque regression related to sodium-glucose cotransporter-2 inhibitor using coronary computed tomography angiography

BACKGROUND

Sodium-Glucose Cotransporter-2 Inhibitor (SGLT2i) is a novel oral drug for treating type 2 diabetes mellitus (T2DM) with demonstrated cardiovascular benefits. Previous studies in apolipoprotein E knockout mice have shown that SGLT2i is associated with attenuated progression of atherosclerosis. However, whether this effect extends to T2DM patients with coronary atherosclerosis in real-world settings remains unknown.

METHODS

In this longitudinal cohort study using coronary computed tomography angiography (CCTA), T2DM patients who underwent ≥ 2 CCTA examinations at our center between 2019 and 2022 were screened. Eligible patients had multiple study plaques, defined as non-obstructive stenosis at baseline and not intervened during serial CCTAs. Exclusion criteria included a CCTA time interval < 12 months, prior SGLT2i treatment, or initiation/discontinuation of SGLT2i during serial CCTAs. Plaque volume (PV) and percent atheroma volume (PAV) were measured for each study plaque using CCTA plaque analysis software. Patients and plaques were categorized based on SGLT2i therapy and compared using a 1:1 propensity score matching (PSM) analysis.

RESULTS

The study included 236 patients (mean age 60.5 ± 9.5 years; 69.1% male) with 435 study plaques (diameter stenosis ≥ 50%, 31.7%). Following SGLT2i treatment for a median duration of 14.6 (interquartile range: 13.0, 20.0) months, overall, non-calcified, and low-attenuation PV and PAV were significantly decreased, while calcified PV and PAV were increased (all p < 0.001). Meanwhile, reductions in overall PV, non-calcified PV, overall PAV, and non-calcified PAV were significantly greater in SGLT2i-treated compared to non-SGLT2i-treated plaques (all p < 0.001). PSM analysis showed that SGLT2i treatment was associated with higher reductions in overall PV (- 11.77 mm3 vs. 4.33 mm3, p = 0.005), non-calcified PV (- 16.96 mm3 vs. - 1.81 mm3, p = 0.017), overall PAV (- 2.83% vs. 3.36%, p < 0.001), and non-calcified PAV (- 4.60% vs. 0.70%, p = 0.003). These findings remained consistent when assessing annual changes in overall and compositional PV and PAV. Multivariate regression models demonstrated that SGLT2i therapy was associated with attenuated progression of overall or non-calcified PV or PAV, even after adjusting for cardiovascular risk factors, medications, and baseline overall or non-calcified PV or PAV, respectively (all p < 0.05). The effect of SGLT2i on attenuating non-calcified plaque progression was consistent across subgroups (all p for interaction > 0.05).

CONCLUSIONS

In this longitudinal CCTA cohort of T2DM patients, SGLT2i therapy markedly regressed coronary overall PV and PAV, mainly result from a significant reduction in non-calcified plaque.

Non-calcified plaque-based coronary stenosis grading in contrast enhanced CT

BACKGROUND

The high mortality rate associated with coronary heart disease has led to state-of-the-art non-invasive methods for cardiac diagnosis including computed tomography and magnetic resonance imaging. However, stenosis computation and clinical assessment of non-calcified plaques has been very challenging due to their ambiguous intensity response in CT i.e. a significant overlap with surrounding muscle tissues and blood. Accordingly, this research presents an approach for computation of coronary stenosis by investigating cross-sectional lumen behaviour along the length of 3D coronary segments.

METHODS

Non-calcified plaques are characterized by comparatively lower-intensity values with respect to the surrounding. Accordingly, segment-wise orthogonal volume was reconstructed in 3D space using the segmented coronary tree. Subsequently, the cross sectional volumetric data was investigated using proposed CNN-based plaque quantification model and subsequent stenosis grading in clinical context was performed. In the last step, plaque-affected orthogonal volume was further investigated by comparing vessel-wall thickness and lumen area obstruction w.r.t. expert-based annotations to validate the stenosis grading performance of model.

RESULTS

The experimental data consists of clinical CT images obtained from the Rotterdam CT repository leading to 600 coronary segments and subsequent 15786 cross-sectional images. According to the results, the proposed method quantified coronary vessel stenosis i.e. severity of the non-calcified plaque with an overall accuracy of 83%. Moreover, for individual grading, the proposed model show promising results with accuracy equal to 86%, 90% and 79% respectively for severe, moderate and mild stenosis. The stenosis grading performance of the proposed model was further validated by performing lumen-area versus wall-thickness analysis as per annotations of manual experts. The statistical results for lumen area analysis precisely correlates with the quantification performance of the model with a mean deviation of 5% only.

CONCLUSION

The overall results demonstrates capability of the proposed model to grade the vessel stenosis with reasonable accuracy and precision equivalent to human experts.

The impact of carbohydrate restriction-induced elevations in low-density lipoprotein cholesterol on progression of coronary atherosclerosis: the ketogenic diet trial study design

BACKGROUND

Despite innovations in pharmacotherapy to lower lipoprotein cholesterol and apolipoprotein B, risk factors for atherosclerotic cardiovascular disease (ASCVD), ASCVD persists as the leading global cause of mortality. Elevations in low-density lipoprotein cholesterol (LDL-C) are a well-known risk factor and have been a main target in the treatment of ASCVD. The latest research suggests that ketogenic diets are effective at improving most non-LDL-C/apolipoprotein B cardiometabolic risk factors. However, ketogenic diets can induce large increases in LDL-C to >190 mg/dl in some individuals. Interestingly, these individuals are often otherwise lean and healthy. The influence of increased levels of LDL-C resulting from a carbohydrate-restricted ketogenic diet on the progression of atherosclerosis in otherwise metabolically healthy individuals is poorly understood. This observational study aims to assess and describe the progression of coronary atherosclerosis in this population within 12 months.

METHODS

Hundred relatively lean individuals who adopted ketogenic diets and subsequently exhibited hypercholesterolemia with LDL-C to >190 mg/dl, in association with otherwise good metabolic health markers, were enrolled and observed over a period of 12 months. Participants underwent serial coronary computed tomography angiography scans to assess the progression of coronary atherosclerosis in a year.

RESULTS

Data analysis shall begin following the conclusion of the trial with results to follow.

CONCLUSION

Ketogenic diets have generated debate and raised concerns within the medical community, especially in the subset exhibiting immense elevations in LDL-C, who interestingly are lean and healthy. The relationship between elevated LDL-C and ASCVD progression in this population will provide better insight into the effects of diet-induced hypercholesterolemia.

Standards for quantitative assessments by coronary computed tomography angiography (CCTA): An expert consensus document of the society of cardiovascular computed tomography (SCCT)

In current clinical practice, qualitative or semi-quantitative measures are primarily used to report coronary artery disease on cardiac CT. With advancements in cardiac CT technology and automated post-processing tools, quantitative measures of coronary disease severity have become more broadly available. Quantitative coronary CT angiography has great potential value for clinical management of patients, but also for research. This document aims to provide definitions and standards for the performance and reporting of quantitative measures of coronary artery disease by cardiac CT.

Application of Quantitative Assessment of Coronary Atherosclerosis by Coronary Computed Tomographic Angiography

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations.

A comparative analysis of deep learning-based location-adaptive threshold method software against other commercially available software

Automatic segmentation of the coronary artery using coronary computed tomography angiography (CCTA) images can facilitate several analyses related to coronary artery disease (CAD). Accurate segmentation of the lumen or plaque region is one of the most important factors. This study aimed to analyze the performance of the coronary artery segmentation of a software platform with a deep learning-based location-adaptive threshold method (DL-LATM) against commercially available software platforms using CCTA. The dataset from intravascular ultrasound (IVUS) of 26 vessel segments from 19 patients was used as the gold standard to evaluate the performance of each software platform. Statistical analyses (Pearson correlation coefficient [PCC], intraclass correlation coefficient [ICC], and Bland-Altman plot) were conducted for the lumen or plaque parameters by comparing the dataset of each software platform with IVUS. The software platform with DL-LATM showed the bias closest to zero for detecting lumen volume (mean difference = -9.1 mm3, 95% confidence interval [CI] = -18.6 to 0.4 mm3) or area (mean difference = -0.72 mm2, 95% CI = -0.80 to -0.64 mm2) with the highest PCC and ICC. Moreover, lumen or plaque area in the stenotic region was analyzed. The software platform with DL-LATM showed the bias closest to zero for detecting lumen (mean difference = -0.07 mm2, 95% CI = -0.16 to 0.02 mm2) or plaque area (mean difference = 1.70 mm2, 95% CI = 1.37 to 2.03 mm2) in the stenotic region with significantly higher correlation coefficient than other commercially available software platforms (p < 0.001). The result shows that the software platform with DL-LATM has the potential to serve as an aiding system for CAD evaluation.

Atherosclerosis evaluation and cardiovascular risk estimation using coronary computed tomography angiography

Clinical risk scores based on traditional risk factors of atherosclerosis correlate imprecisely to an individual's complex pathophysiological predisposition to atherosclerosis and provide limited accuracy for predicting major adverse cardiovascular events (MACE). Over the past two decades, computed tomography scanners and techniques for coronary computed tomography angiography (CCTA) analysis have substantially improved, enabling more precise atherosclerotic plaque quantification and characterization. The accuracy of CCTA for quantifying stenosis and atherosclerosis has been validated in numerous multicentre studies and has shown consistent incremental prognostic value for MACE over the clinical risk spectrum in different populations. Serial CCTA studies have advanced our understanding of vascular biology and atherosclerotic disease progression. The direct disease visualization of CCTA has the potential to be used synergistically with indirect markers of risk to significantly improve prevention of MACE, pending large-scale randomized evaluation.

Innovations in cardiac computed tomography: Imaging in coronary artery disease

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool in the non-invasive evaluation of coronary artery disease (CAD). Recent advancements in imaging techniques, quantitative plaque assessment methods, assessment of coronary physiology, and perivascular coronary inflammation have propelled CCTA to the forefront of CAD management, enabling precise risk stratification, disease monitoring, and evaluation of treatment response. However, challenges persist, including the need for cardiovascular outcomes data for therapy modifications based on CCTA findings and the lack of standardized quantitative plaque assessment techniques to establish universal guidelines for treatment strategies. This review explores the current utilization of CCTA in clinical practice, highlighting its clinical impact and discussing challenges and opportunities for future development. By addressing these nuances, CCTA holds promise for revolutionizing coronary imaging and improving CAD management in the years to come. Ultimately, the goal is to provide precise risk stratification, optimize medical therapy, and improve cardiovascular outcomes while ensuring cost-effectiveness for healthcare systems.

Aortic valve perivascular adipose tissue computed tomography attenuation in patients with aortic stenosis

OBJECTIVE

Aortic stenosis (AS) shares pathophysiological similarities with atherosclerosis including active inflammation. CT attenuation of perivascular adipose tissue provides a measure of vascular inflammation that is linked to prognosis and has the potential to be applied to the aortic valve. We investigated perivascular adipose tissue attenuation around the aortic valve in patients with AS.

METHODS

CT attenuation was measured in the perivascular adipose tissue extending 3 mm radially and 10 mm longitudinally around the aortic valve in patients with and without AS. Associations between perivascular adipose tissue attenuation and AS disease severity, activity and progression were investigated.

RESULTS

Perivascular adipose tissue attenuation around the aortic valve demonstrated good intraobserver and interobserver repeatability (interobserver: intraclass correlation coefficient 0.977 (95% CI: 0.94, 0.99)) but was similar between patients with AS (n=120) and control subjects (n=80) (-62.4 (-68.7, -56.5) Hounsfield units (HU) vs -61.2 (-65.3, -55.6) HU, p=0.099). There were no differences between perivascular adipose tissue attenuation in patients with mild (-60.2 (-66.9, -55.1) HU), moderate (-62.8 (-69.6, -56.80) HU) or severe (-62.3 (-69.3, -55.4) HU) AS (all p>0.05), and perivascular adipose tissue attenuation did not demonstrate an association with AS severity as assessed by echocardiography or CT calcium scoring, nor with disease activity assessed by 18F-sodium fluoride positron emission tomography. Moreover, there was no association between baseline aortic valve perivascular adipose tissue attenuation and subsequent AS progression (annualised change in peak velocity: r=0.072, p=0.458). Similar results were found using five other image analysis methods.

CONCLUSIONS

CT-derived aortic valve perivascular adipose tissue attenuation is not associated with AS disease severity, activity or progression suggesting that it has no value in the investigation and management of patients with AS.

Automatic Coronary Artery Plaque Quantification and CAD-RADS Prediction Using Mesh Priors

Coronary artery disease (CAD) remains the leading cause of death worldwide. Patients with suspected CAD undergo coronary CT angiography (CCTA) to evaluate the risk of cardiovascular events and determine the treatment. Clinical analysis of coronary arteries in CCTA comprises the identification of atherosclerotic plaque, as well as the grading of any coronary artery stenosis typically obtained through the CAD-Reporting and Data System (CAD-RADS). This requires analysis of the coronary lumen and plaque. While voxel-wise segmentation is a commonly used approach in various segmentation tasks, it does not guarantee topologically plausible shapes. To address this, in this work, we propose to directly infer surface meshes for coronary artery lumen and plaque based on a centerline prior and use it in the downstream task of CAD-RADS scoring. The method is developed and evaluated using a total of 2407 CCTA scans. Our method achieved lesion-wise volume intraclass correlation coefficients of 0.98, 0.79, and 0.85 for calcified, non-calcified, and total plaque volume respectively. Patient-level CAD-RADS categorization was evaluated on a representative hold-out test set of 300 scans, for which the achieved linearly weighted kappa ( κ ) was 0.75. CAD-RADS categorization on the set of 658 scans from another hospital and scanner led to a κ of 0.71. The results demonstrate that direct inference of coronary artery meshes for lumen and plaque is feasible, and allows for the automated prediction of routinely performed CAD-RADS categorization.

Predictors of percutaneous coronary intervention derived from CCTA in patients with chronic coronary syndrome

BACKGROUND

To identify anatomical and morphological plaque features predictors of PCI and create a multiparametric score to increase the predictive yield. Moreover, we assessed the incremental predictive value of FFRCT (Fractional Flow Reserve derived from CCTA) trans-lesion gradient (ΔFFRCT) when integrated into the score.

METHODS

Observational cohort study including patients undergoing CCTA for suspected coronary artery disease, with FFRCT available, referred to invasive coronary angiogram and assessment of fractional flow reserve. Plaque analysis was performed using validated semi-automated software. Logistic regression was performed to identify anatomical and morphological plaque features predictive of PCI. Optimal thresholds were defined by area under the receiver-operating characteristics curve (AUC) analysis. A scoring system was developed in a derivation cohort (70 ​% of the study population) and tested in a validation cohort (30 ​% of patients).

RESULTS

The overall study population included 340 patients (455 vessels), among which 238 patients (320 vessels) were included in the derivation cohort. At multivariate logistic regression analysis, absence of left main disease, diameter stenosis (DS), non-calcified plaque (NCP) volume, and percent atheroma volume (PAV) were independent predictors of PCI. Optimal thresholds were: DS ​≥ ​50 ​%, volume of NCP>113 ​mm3 and PAV>17 ​%. A weighted score (CT-PCI Score) ranging from 0 to 11 was obtained. The AUC of the score was 0.80 (95%CI 0.74-0.86). The integration of ΔFFRCT in the CT-PCI score led to a mild albeit not significant increase in the AUC (0.82, 95%CI 0.77-0.87, p ​= ​0.328).

CONCLUSIONS

Plaque anatomy and morphology derived from CCTA could aid in identifying patients amenable to PCI.

Efficacy of human experts and an automated segmentation algorithm in quantifying disease pathology in coronary computed tomography angiography: A head-to-head comparison with intravascular ultrasound imaging

BACKGROUND

Coronary computed tomography angiography (CCTA) analysis is currently performed by experts and is a laborious process. Fully automated edge-detection methods have been developed to expedite CCTA segmentation however their use is limited as there are concerns about their accuracy. This study aims to compare the performance of an automated CCTA analysis software and the experts using near-infrared spectroscopy-intravascular ultrasound imaging (NIRS-IVUS) as a reference standard.

METHODS

Fifty-one participants (150 vessels) with chronic coronary syndrome who underwent CCTA and 3-vessel NIRS-IVUS were included. CCTA analysis was performed by an expert and an automated edge detection method and their estimations were compared to NIRS-IVUS at a segment-, lesion-, and frame-level.

RESULTS

Segment-level analysis demonstrated a similar performance of the two CCTA analyses (conventional and automatic) with large biases and limits of agreement compared to NIRS-IVUS estimations for the total atheroma (ICC: 0.55 vs 0.25, mean difference:192 (-102-487) vs 243 (-132-617) and percent atheroma volume (ICC: 0.30 vs 0.12, mean difference: 12.8 (-5.91-31.6) vs 20.0 (0.79-39.2). Lesion-level analysis showed that the experts were able to detect more accurately lesions than the automated method (68.2 ​% and 60.7 ​%) however both analyses had poor reliability in assessing the minimal lumen area (ICC 0.44 vs 0.36) and the maximum plaque burden (ICC 0.33 vs 0.33) when NIRS-IVUS was used as the reference standard.

CONCLUSIONS

Conventional and automated CCTA analyses had similar performance in assessing coronary artery pathology using NIRS-IVUS as a reference standard. Therefore, automated segmentation can be used to expedite CCTA analysis and enhance its applications in clinical practice.

Continuous Positive Airway Pressure but Not GLP1-mediated Weight Loss Improves Early Cardiovascular Disease in Obstructive Sleep Apnea: A Randomized Proof-of-Concept Study

Rationale: Obstructive sleep apnea (OSA) is an independent risk factor for cardiovascular (CV) morbidity and mortality, but the benefit of continuous positive airway pressure (CPAP) is uncertain. However, most randomized controlled trials have focused on the role of CPAP in secondary prevention, although there is growing evidence of a potential benefit on early CV disease. Weight loss in combination with CPAP may be superior but is difficult to achieve and maintain with conventional measures alone. Objectives: The aim of this study was to gain insights into the effect of CPAP on early atherosclerotic processes and to compare it with a glucagon-like peptide (GLP)-1-mediated weight loss regimen in patients with OSA. Methods: We performed a randomized proof-of-concept study comparing CPAP, a GLP1-mediated weight-loss regimen (liraglutide [Lir]), and both in combination for 24 weeks in 30 consecutive patients with OSA (apnea-hypopnea index >15 events/h; body mass index 30-40 kg/m2; and no history of diabetes, heart failure, or unstable CV disease). In addition to extensive evaluation for CV risk factors and endothelial function at baseline and end of study, subjects underwent 18F-fluoro-2-deoxy-D-glucose positron emission tomography-computed tomography (18F-FDG PET-CT) for the measurement of aortic wall inflammation (target-to-background ratio) and coronary computed tomography angiography for semiautomated coronary plaque analysis. Results: Baseline characteristics were similar between groups. CPAP alone and in combination resulted in greater reduction in apnea-hypopnea index than Lir alone (mean difference, -45 and -43 events/h, respectively, vs. -12 events/h; P < 0.05). Both Lir and combination treatment led to significant weight loss, but only CPAP alone resulted in significant decrease in vascular inflammation (aortic wall target-to-background ratio from 2.03 ± 0.34 to 1.84 ± 0.43; P = 0.010), associated with an improvement in endothelial function and a decrease in C-reactive protein. Low-attenuation coronary artery plaque volume as a marker of unstable plaque also decreased with CPAP (from 571 ± 490 to 334 ± 185 mm3) and with combination therapy (from 401 ± 145 to 278 ± 126 mm3) but not with Lir. Conclusions: These data suggest that CPAP therapy, but not GLP1-mediated weight loss, improves vascular inflammation and reduces unstable plaque volume in patients with OSA. Further large randomized controlled studies are warranted to assess the benefit of CPAP therapy in modifying early CV disease. Clinical trial registered with www.clinicaltrials.gov (NCT04186494).

Age- and Sex-Specific Nomographic CT Quantitative Plaque Data From a Large International Cohort

BACKGROUND

With growing adoption of coronary computed tomographic angiography (CTA), there is increasing evidence for and interest in the prognostic importance of atherosclerotic plaque volume. Manual tools for plaque segmentation are cumbersome, and their routine implementation in clinical practice is limited.

OBJECTIVES

The aim of this study was to develop nomographic quantitative plaque values from a large consecutive multicenter cohort using coronary CTA.

METHODS

Quantitative assessment of total atherosclerotic plaque and plaque subtype volumes was performed in patients undergoing clinically indicated coronary CTA, using an Artificial Intelligence-Enabled Quantitative Coronary Plaque Analysis tool.

RESULTS

A total of 11,808 patients were included in the analysis; their mean age was 62.7 ± 12.2 years, and 5,423 (45.9%) were women. The median total plaque volume was 223 mm3 (IQR: 29-614 mm3) and was significantly higher in male participants (360 mm3; IQR: 78-805 mm3) compared with female participants (108 mm3; IQR: 10-388 mm3) (P < 0.0001). Total plaque increased with age in both male and female patients. Younger patients exhibited a higher prevalence of noncalcified plaque. The distribution of total plaque volume and its components was reported in every decile by age group and sex.

CONCLUSIONS

The authors developed pragmatic age- and sex-stratified percentile nomograms for atherosclerotic plaque measures using findings from coronary CTA. The impact of age and sex on total plaque and its components should be considered in the risk-benefit analysis when treating patients. Artificial Intelligence-Enabled Quantitative Coronary Plaque Analysis work flows could provide context to better interpret coronary computed tomographic angiographic measures and could be integrated into clinical decision making.

Sex-Specific Association Between Perivascular Inflammation and Plaque Vulnerability

BACKGROUND

It is not known whether there is a sex difference in the association between perivascular inflammation and plaque vulnerability. The aim of this study was to investigate the sex-specific association between perivascular inflammation and plaque vulnerability.

METHODS

Patients who underwent coronary computed tomography angiography and optical coherence tomography were enrolled. All images were analyzed at a core laboratory. The level of perivascular inflammation was assessed by pericoronary adipose tissue attenuation on computed tomography angiography and the level of plaque vulnerability by optical coherence tomography. Patients were classified into 3 groups according to tertile levels of culprit vessel pericoronary adipose tissue attenuation (low inflammation, ≤-73.1 Hounsfield units; moderate inflammation, -73.0 to -67.0 Hounsfield units; or high inflammation, ≥-66.9 Hounsfield units).

RESULTS

A total of 968 lesions in 409 patients were included: 184 lesions in 82 women (2.2 plaques per patient) and 784 lesions in 327 men (2.4 plaques per patient). Women were older (median age, 71 versus 65 years; P<0.001) and had less severe coronary artery disease with a lower plaque burden than men. In women, it was found that perivascular inflammation was significantly associated with plaque vulnerability, with a higher prevalence of thin-cap fibroatheroma and greater macrophage grades in the high inflammation group compared with the low inflammation group (low versus moderate versus high inflammation in women: 18.5% versus 31.8% versus 46.9%, P=0.002 for low versus high inflammation; 3 versus 4 versus 12, P<0.001 for low versus high inflammation, respectively). However, no significant differences were observed among the 3 groups in men.

CONCLUSIONS

Perivascular inflammation was associated with a higher prevalence of thin-cap fibroatheroma and more significant macrophage accumulation in women but not in men.

REGISTRATION

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

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.

Patient-level explainable machine learning to predict major adverse cardiovascular events from SPECT MPI and CCTA imaging

BACKGROUND

Machine learning (ML) has shown promise in improving the risk prediction in non-invasive cardiovascular imaging, including SPECT MPI and coronary CT angiography. However, most algorithms used remain black boxes to clinicians in how they compute their predictions. Furthermore, objective consideration of the multitude of available clinical data, along with the visual and quantitative assessments from CCTA and SPECT, are critical for optimal patient risk stratification. We aim to provide an explainable ML approach to predict MACE using clinical, CCTA, and SPECT data.

METHODS

Consecutive patients who underwent clinically indicated CCTA and SPECT myocardial imaging for suspected CAD were included and followed up for MACEs. A MACE was defined as a composite outcome that included all-cause mortality, myocardial infarction, or late revascularization. We employed an Automated Machine Learning (AutoML) approach to predict MACE using clinical, CCTA, and SPECT data. Various mainstream models with different sets of hyperparameters have been explored, and critical predictors of risk are obtained using explainable techniques on the global and patient levels. Ten-fold cross-validation was used in training and evaluating the AutoML model.

RESULTS

A total of 956 patients were included (mean age 61.1 ±14.2 years, 54% men, 89% hypertension, 81% diabetes, 84% dyslipidemia). Obstructive CAD on CCTA and ischemia on SPECT were observed in 14% of patients, and 11% experienced MACE. ML prediction's sensitivity, specificity, and accuracy in predicting a MACE were 69.61%, 99.77%, and 96.54%, respectively. The top 10 global predictive features included 8 CCTA attributes (segment involvement score, number of vessels with severe plaque ≥70, ≥50% stenosis in the left marginal coronary artery, calcified plaque, ≥50% stenosis in the left circumflex coronary artery, plaque type in the left marginal coronary artery, stenosis degree in the second obtuse marginal of the left circumflex artery, and stenosis category in the marginals of the left circumflex artery) and 2 clinical features (past medical history of MI or left bundle branch block, being an ever smoker).

CONCLUSION

ML can accurately predict risk of developing a MACE in patients suspected of CAD undergoing SPECT MPI and CCTA. ML feature-ranking can also show, at a sample- as well as at a patient-level, which features are key in making such a prediction.

Advances in Coronary Computed Tomographic Angiographic Imaging of Atherosclerosis for Risk Stratification and Preventive Care

The diagnostic evaluation of coronary artery disease is undergoing a dramatic transformation with a new focus on atherosclerotic plaque. This review details the evidence needed for effective risk stratification and targeted preventive care based on recent advances in automated measurement of atherosclerosis from coronary computed tomography angiography (CTA). To date, research findings support that automated stenosis measurement is reasonably accurate, but evidence on variability by location, artery size, or image quality is unknown. The evidence for quantification of atherosclerotic plaque is unfolding, with strong concordance reported between coronary CTA and intravascular ultrasound measurement of total plaque volume (r >0.90). Statistical variance is higher for smaller plaque volumes. Limited data are available on how technical or patient-specific factors result in measurement variability by compositional subgroups. Coronary artery dimensions vary by age, sex, heart size, coronary dominance, and race and ethnicity. Accordingly, quantification programs excluding smaller arteries affect accuracy for women, patients with diabetes, and other patient subsets. Evidence is unfolding that quantification of atherosclerotic plaque is useful to enhance risk prediction, yet more evidence is required to define high-risk patients across varied populations and to determine whether such information is incremental to risk factors or currently used coronary computed tomography techniques (eg, coronary artery calcium scoring or visual assessment of plaque burden or stenosis). In summary, there is promise for the utility of coronary CTA quantification of atherosclerosis, especially if it can lead to targeted and more intensive cardiovascular prevention, notably for those patients with nonobstructive coronary artery disease and high-risk plaque features. The new quantification techniques available to imagers must not only provide sufficient added value to improve patient care, but also add minimal and reasonable cost to alleviate the financial burden on our patients and the health care system.

Computed Tomography Assessment of Coronary Atherosclerosis: From Threshold-Based Evaluation to Histologically Validated Plaque Quantification

Arterial plaque rupture and thrombosis is the primary cause of major cardiovascular and neurovascular events. The identification of atherosclerosis, especially high-risk plaques, is therefore crucial to identify high-risk patients and to implement preventive therapies. Computed tomography angiography has the ability to visualize and characterize vascular plaques. The standard methods for plaque evaluation rely on the assessment of plaque burden, stenosis severity, the presence of positive remodeling, napkin ring sign, and spotty calcification, as well as Hounsfield Unit (HU)-based thresholding for plaque quantification; the latter with multiple shortcomings. Semiautomated threshold-based segmentation techniques with predefined HU ranges identify and quantify limited plaque characteristics, such as low attenuation, non-calcified, and calcified plaque components. Contrary to HU-based thresholds, histologically validated plaque characterization, and quantification, an emerging Artificial intelligence-based approach has the ability to differentiate specific tissue types based on a biological correlate, such as lipid-rich necrotic core and intraplaque hemorrhage that determine plaque vulnerability. In this article, we review the relevance of plaque characterization and quantification and discuss the benefits and limitations of the currently available plaque assessment and classification techniques.

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.

Coronary low-attenuation plaque and high-sensitivity cardiac troponin

OBJECTIVE

In patients with acute chest pain who have had myocardial infarction excluded, plasma cardiac troponin I concentrations ≥5 ng/L are associated with risk of future adverse cardiovascular events. We aim to evaluate the association between cardiac troponin and coronary plaque composition in such patients.

METHODS

In a prespecified secondary analysis of a prospective cohort study, blinded quantitative plaque analysis was performed on 242 CT coronary angiograms of patients with acute chest pain in whom myocardial infarction was excluded. Patients were stratified by peak plasma cardiac troponin I concentration ≥5 ng/L or <5 ng/L. Associations were assessed using univariable and multivariable logistic regression analyses.

RESULTS

The cohort was predominantly middle-aged (62±12 years) men (69%). Patients with plasma cardiac troponin I concentration ≥5 ng/L (n=161) had a higher total (median 33% (IQR 0-47) vs 0% (IQR 0-33)), non-calcified (27% (IQR 0-37) vs 0% (IQR 0-28)), calcified (2% (IQR 0-8) vs 0% (IQR 0-3)) and low-attenuation (1% (IQR 0-3) vs 0% (IQR 0-1)) coronary plaque burden compared with those with concentrations <5 ng/L (n=81; p≤0.001 for all). Low-attenuation plaque burden was independently associated with plasma cardiac troponin I concentration ≥5 ng/L after adjustment for clinical characteristics (adjusted OR per doubling 1.62 (95% CI 1.17 to 2.32), p=0.005) or presence of any visible coronary artery disease (adjusted OR per doubling 1.57 (95% CI 1.07 to 2.37), p=0.026).

CONCLUSION

In patients with acute chest pain but without myocardial infarction, plasma cardiac troponin I concentrations ≥5 ng/L are associated with greater burden of low-attenuation coronary plaque.

Sex differences in computed tomography angiography-derived coronary plaque burden in relation to invasive fractional flow reserve

BACKGROUND

Distinct sex-related differences exist in coronary artery plaque burden and distribution. We aimed to explore sex differences in quantitative plaque burden by coronary CT angiography (CCTA) in relation to ischemia by invasive fractional flow reserve (FFR).

METHODS

This post-hoc analysis of the PACIFIC trial included 581 vessels in 203 patients (mean age 58.1 ​± ​8.7 years, 63.5% male) who underwent CCTA and per-vessel invasive FFR. Quantitative assessment of total, calcified, non-calcified, and low-density non-calcified plaque burden were performed using semiautomated software. Significant ischemia was defined as invasive FFR ≤0.8.

RESULTS

The per-vessel frequency of ischemia was higher in men than women (33.5% vs. 7.5%, p ​< ​0.001). Women had a smaller burden of all plaque subtypes (all p ​< ​0.01). There was no sex difference on total, calcified, or non-calcified plaque burdens in vessels with ischemia; only low-density non-calcified plaque burden was significantly lower in women (beta: -0.183, p ​= ​0.035). The burdens of all plaque subtypes were independently associated with ischemia in both men and women (For total plaque burden (5% increase): Men, OR: 1.15, 95%CI: 1.06-1.24, p ​= ​0.001; Women, OR: 1.96, 95%CI: 1.11-3.46, p ​= ​0.02). No significant interaction existed between sex and total plaque burden for predicting ischemia (interaction p ​= ​0.108). The addition of quantitative plaque burdens to stenosis severity and adverse plaque characteristics improved the discrimination of ischemia in both men and women.

CONCLUSIONS

In symptomatic patients with suspected CAD, women have a lower CCTA-derived burden of all plaque subtypes compared to men. Quantitative plaque burden provides independent and incremental predictive value for ischemia, irrespective of sex.

Identification of vulnerable non-culprit lesions by coronary computed tomography angiography in patients with chronic coronary syndrome and diabetes mellitus

Background

Among patients with diabetes mellitus (DM) and chronic coronary syndrome (CCS), non-culprit lesions (NCLs) are responsible for a substantial number of future major adverse cardiovascular events (MACEs). Thus, we aimed to establish the natural history relationship between adverse plaque characteristics (APCs) of NCLs non-invasively identified by coronary computed tomography angiography (CCTA) and subsequent MACEs in these patients.

Methods

Between January 2016 and January 2019, 523 patients with DM and CCS were included in the present study after CCTA and successful percutaneous coronary intervention (PCI). All patients were followed up for MACEs (the composite of cardiac death, myocardial infarction, and unplanned coronary revascularization) until January 2022, and the independent clinical event committee classified MACEs as indeterminate, culprit lesion (CL), and NCL-related. The primary outcome was MACEs arising from untreated NCLs during the follow-up. The association between plaque characteristics detected by CCTA and primary outcomes was determined by Marginal Cox proportional hazard regression.

Results

Overall, 1,248 NCLs of the 523 patients were analyzed and followed up for a median of 47 months. The cumulative rates of indeterminate, CL, and NCL-related MACEs were 2.3%, 14.5%, and 20.5%, respectively. On multivariate analysis, NCLs associated with recurrent MACEs were more likely to be characterized by a plaque burden >70% [hazard ratio (HR), 4.35, 95% confidence interval (CI): 2.92-6.44], a low-density non-calcified plaque (LDNCP) volume >30 mm³ (HR: 3.40, 95% CI: 2.07-5.56), a minimal luminal area (MLA) <4 mm² (HR: 2.30, 95% CI: 1.57-3.36), or a combination of three APCs (HR: 13.69, 95% CI: 9.34-20.12, p < 0.0001) than those not associated with recurrent MACEs. Sensitivity analysis regarding all indeterminate MACEs as NCL-related ones demonstrated similar results.

Conclusions

In DM patients who presented with CCS and underwent PCI, half of the MACEs occurring during the follow-up were attributable to recurrence at the site of NCLs. NCLs responsible for unanticipated MACEs were frequently characterized by a large plaque burden and LDNCP volume, a small MLA, or a combination of these APCs, as determined by CCTA.

Anatomical validation of automatic respiratory motion correction for coronary 18F-sodium fluoride positron emission tomography by expert measurements from four-dimensional computed tomography

BACKGROUND

Respiratory motion correction is of importance in studies of coronary plaques employing ¹⁸ F-NaF; however, the validation of motion correction techniques mainly relies on indirect measures such as test-retest repeatability assessments. In this study, we aim to compare and, thus, validate the respiratory motion vector fields obtained from the positron emission tomography (PET) images directly to the respiratory motion observed during four-dimensional cine-computed tomography (CT) by an expert observer.

PURPOSE

To investigate the accuracy of the motion correction employed in a software (FusionQuant) used for evaluation of ¹⁸ F-NaF PET studies by comparing the respiratory motion of the coronary plaques observed in PET to the respiratory motion observed in 4D cine-CT images.

METHODS

This study included 23 patients who undertook thoracic PET scans for the assessment of coronary plaques using ¹⁸ F-sodium fluoride (¹⁸ F-NaF). All patients underwent a 5-s cine-CT (4D-CT), a coronary CT angiography (CTA), and ¹⁸ F-NaF PET. The 4D-CT and PET scan were reconstructed into 10 phases. Respiratory motion was estimated for the non-contrast visible coronary plaques using diffeomorphic registrations (PET) and compared to respiratory motion observed on 4D-CT. We report the PET motion vector fields obtained in the three principal axes in addition to the 3D motion. Statistical differences were examined using paired t-tests. Signal-to-noise ratios (SNR) are reported for the single-phase images (end-expiratory phase) and for the motion-corrected image-series (employing the motion vector fields extracted during the diffeomorphic registrations).

RESULTS

In total, 19 coronary plaques were identified in 16 patients. No statistical differences were observed for the maximum respiratory motion observed in x, y, and the 3D motion fields (magnitude and direction) between the CT and PET (X direction: 4D CT = 2.5 ± 1.5 mm, PET = 2.4 ± 3.2 mm; Y direction: 4D CT = 2.3 ± 1.9 mm, PET = 0.7 ± 2.9 mm, 3D motion: 4D CT = 6.6 ± 3.1 mm, PET = 5.7 ± 2.6 mm, all p ≥ 0.05). Significant differences in respiratory motion were observed in the systems' Z direction: 4D CT = 4.9 ± 3.4 mm, PET = 2.3 ± 3.2 mm, p = 0.04. Significantly improved SNR is reported for the motion corrected images compared to the end-expiratory phase images (end-expiratory phase = 6.8±4.8, motion corrected = 12.2±4.5, p = 0.001).

CONCLUSION

Similar respiratory motion was observed in two directions and 3D for coronary plaques on 4D CT as detected by automatic respiratory motion correction of coronary PET using FusionQuant. The respiratory motion correction technique significantly improved the SNR in the images.

Plaque Burden and 1-Year Outcomes in Acute Chest Pain: Results From the Multicenter RAPID-CTCA Trial

BACKGROUND

In patients with stable chest pain, computed tomography (CT) plaque burden is an independent predictor of future coronary events.

OBJECTIVES

The purpose of this study was to determine whether plaque burden and characteristics can predict subsequent death or myocardial infarction in patients with acute chest pain.

METHODS

In a post hoc analysis of a multicenter trial of early coronary CT angiography, the authors performed quantitative plaque analysis to assess the association between primary endpoint of 1-year all-cause death or nonfatal myocardial infarction and the GRACE (Global Registry of Acute Coronary Events) score, presence of obstructive coronary artery disease, and plaque burden in 404 patients with suspected acute coronary syndrome.

RESULTS

Following the index event, 25 patients had a primary event that was associated with a higher GRACE score (134 ± 44 vs 113 ± 35; P = 0.012), larger burdens of total (46% [IQR: 43%-50%] vs 36% [IQR: 21%-46%]; P < 0.001), noncalcified (41% [IQR: 37%-%47] vs 33% [IQR: 20%-41%]; P < 0.001), and low-attenuation plaque (4.22% [IQR: 3.3%-5.68%] vs 2.14% [IQR: 0.5%-4.88%]; P < 0.001), but not obstructive coronary artery disease (P = 0.065). Total, noncalcified, and low-attenuation plaque burden were the strongest predictors of future events independent of GRACE score and obstructive coronary artery disease (P ≤ 0.002 for all). Patients with a low-attenuation burden above the median had nearly an 8-fold increased risk of the primary endpoint (HR: 7.80 [95% CI: 2.33-26.0]; P < 0.001), outperforming either a GRACE score of >140 (HR: 3.80 [95% CI :1.45-6.98]; P = 0.004) or obstructive coronary artery disease (HR: 2.07 [95% CI: 0.94-4.53]; P = 0.07).

CONCLUSIONS

In patients with suspected acute coronary syndrome, low-attenuation plaque burden is a major predictor of 1-year death or recurrent myocardial infarction. (Rapid Assessment of Potential Ischaemic Heart Disease With CTCA [RAPID-CTCA]; NCT02284191).

Distinguishing Type 1 from Type 2 Myocardial Infarction by Using CT Coronary Angiography

Purpose

To determine whether quantitative plaque characterization by using CT coronary angiography (CTCA) can discriminate between type 1 and type 2 myocardial infarction.

Materials and Methods

This was a secondary analysis of two prospective studies (ClinicalTrials.gov registration nos. NCT03338504 [2014-2019] and NCT02284191 [2018-2020]) that performed blinded quantitative plaque analysis on findings from CTCA in participants with type 1 myocardial infarction, type 2 myocardial infarction, and chest pain without myocardial infarction. Logistic regression analyses were performed to identify predictors of type 1 myocardial infarction.

Results

Overall, 155 participants (mean age, 64 years ± 12 [SD]; 114 men) and 36 participants (mean age, 67 years ± 12; 19 men) had type 1 and type 2 myocardial infarction, respectively, and 136 participants (62 years ± 12; 78 men) had chest pain without myocardial infarction. Participants with type 1 myocardial infarction had greater total (median, 44% [IQR: 35%-50%] vs 35% [IQR: 29%-46%]), noncalcified (39% [IQR: 31%-46%] vs 34% [IQR: 29%-40%]), and low-attenuation (4.15% [IQR: 1.88%-5.79%] vs 1.64% [IQR: 0.89%-2.28%]) plaque burdens (P < .05 for all) than those with type 2. Participants with type 2 myocardial infarction had similar low-attenuation plaque burden to those with chest pain without myocardial infarction (P = .4). Low-attenuation plaque was an independent predictor of type 1 myocardial infarction (adjusted odds ratio, 3.44 [95% CI: 1.84, 6.96]; P < .001), with better discrimination than noncalcified plaque burden and maximal area of coronary stenosis (C statistic, 0.75 [95% CI: 0.67, 0.83] vs 0.62 [95% CI: 0.53, 0.71] and 0.61 [95% CI: 0.51, 0.70] respectively; P ≤ .001 for both).

Conclusion

Higher low-attenuation coronary plaque burden in patients with type 1 myocardial infarction may help distinguish these patients from those with type 2 myocardial infarction.Keywords: Ischemia/Infarction, CT Angiography, Quantitative CTClinical trial registration nos. NCT03338504 and NCT02284191 Supplemental material is available for this article. © RSNA, 2022.

Influence of intensive lipid-lowering on CT derived fractional flow reserve in patients with stable chest pain: Rationale and design of the FLOWPROMOTE study

INTRODUCTION

Coronary CT angiography (CTA) derived fractional flow reserve (FFR_CT ) shows high diagnostic performance when compared to invasively measured FFR. Presence and extent of low attenuation plaque density have been shown to be associated with abnormal physiology by measured FFR. Moreover, it is well established that statin therapy reduces the rate of plaque progression and results in morphology alterations underlying atherosclerosis. However, the interplay between lipid lowering treatment, plaque regression, and the coronary physiology has not previously been investigated.

AIM

To test whether lipid lowering therapy is associated with significant improvement in FFR_CT , and whether there is a dose-response relationship between lipid lowering intensity, plaque regression, and coronary flow recovery.

METHODS

Investigator driven, prospective, multicenter, randomized study of patients with stable angina, coronary stenosis ≥50% determined by clinically indicated first-line CTA, and FFR_CT  ≤ 0.80 in whom coronary revascularization was deferred. Patients are randomized to standard (atorvastatin 40 mg daily) or intensive (rosuvastatin 40 mg + ezetimibe 10 mg daily) lipid lowering therapy for 18 months. Coronary CTA scans with blinded coronary plaque and FFR_CT analyses will be repeated after 9 and 18 months. The primary endpoint is the 18-month difference in FFR_CT using (1) the FFR_CT value 2 cm distal to stenosis and (2) the lowest distal value in the vessel of interest. A total of 104 patients will be included in the study.

CONCLUSION

The results of this study will provide novel insights into the interplay between lipid lowering, and the pathophysiology in coronary artery disease.

Radiomics-Based Precision Phenotyping Identifies Unstable Coronary Plaques From Computed Tomography Angiography

OBJECTIVES

The aim of this study was to precisely phenotype culprit and nonculprit lesions in myocardial infarction (MI) and lesions in stable coronary artery disease (CAD) using coronary computed tomography angiography (CTA)-based radiomic analysis.

BACKGROUND

It remains debated whether any single coronary atherosclerotic plaque within the vulnerable patient exhibits unique morphology conferring an increased risk of clinical events.

METHODS

A total of 60 patients with acute MI prospectively underwent coronary CTA before invasive angiography and were matched to 60 patients with stable CAD. For all coronary lesions, high-risk plaque (HRP) characteristics were qualitatively assessed, followed by semiautomated plaque quantification and extraction of 1,103 radiomic features. Machine learning models were built to examine the additive value of radiomic features for discriminating culprit lesions over and above HRP and plaque volumes.

RESULTS

Culprit lesions had higher mean volumes of noncalcified plaque (NCP) and low-density noncalcified plaque (LDNCP) compared with the highest-grade stenosis nonculprits and highest-grade stenosis stable CAD lesions (NCP: 138.1 mm3 vs 110.7 mm3 vs 102.7 mm3; LDNCP: 14.2 mm3 vs 9.8 mm3 vs 8.4 mm3; both Ptrend < 0.01). In multivariable linear regression adjusted for NCP and LDNCP volumes, 14.9% (164 of 1,103) of radiomic features were associated with culprits and 9.7% (107 of 1,103) were associated with the highest-grade stenosis nonculprits (critical P < 0.0007) when compared with highest-grade stenosis stable CAD lesions as reference. Hierarchical clustering of significant radiomic features identified 9 unique data clusters (latent phenotypes): 5 contained radiomic features specific to culprits, 1 contained features specific to highest-grade stenosis nonculprits, and 3 contained features associated with either lesion type. Radiomic features provided incremental value for discriminating culprit lesions when added to a machine learning model containing HRP and plaque volumes (area under the receiver-operating characteristic curve 0.86 vs 0.76; P = 0.004).

CONCLUSIONS

Culprit lesions and highest-grade stenosis nonculprit lesions in MI have distinct radiomic signatures compared with lesions in stable CAD. Within the vulnerable patient may exist individual vulnerable plaques identifiable by coronary CTA-based precision phenotyping.

Coronary Artery and Cardiac Disease in Patients With Type 2 Myocardial Infarction: A Prospective Cohort Study

BACKGROUND

Type 2 myocardial infarction is caused by myocardial oxygen supply-demand imbalance, and its diagnosis is increasingly common with the advent of high-sensitivity cardiac troponin assays. Although this diagnosis is associated with poor outcomes, widespread uncertainty and confusion remain among clinicians as to how to investigate and manage this heterogeneous group of patients with type 2 myocardial infarction.

METHODS

In a prospective cohort study, 8064 consecutive patients with increased cardiac troponin concentrations were screened to identify patients with type 2 myocardial infarction. We excluded patients with frailty or renal or hepatic failure. All study participants underwent coronary (invasive or computed tomography angiography) and cardiac (magnetic resonance or echocardiography) imaging, and the underlying causes of infarction were independently adjudicated. The primary outcome was the prevalence of coronary artery disease.

RESULTS

In 100 patients with a provisional diagnosis of type 2 myocardial infarction (median age, 65 years [interquartile range, 55-74 years]; 43% women), coronary and cardiac imaging reclassified the diagnosis in 7 patients: type 1 or 4b myocardial infarction in 5 and acute myocardial injury in 2 patients. In those with type 2 myocardial infarction, median cardiac troponin I concentrations were 195 ng/L (interquartile range, 62-760 ng/L) at presentation and 1165 ng/L (interquartile range, 277-3782 ng/L) on repeat testing. The prevalence of coronary artery disease was 68% (63 of 93), which was obstructive in 30% (28 of 93). Infarct-pattern late gadolinium enhancement or regional wall motion abnormalities were observed in 42% (39 of 93), and left ventricular systolic dysfunction was seen in 34% (32 of 93). Only 10 patients had both normal coronary and normal cardiac imaging. Coronary artery disease and left ventricular systolic dysfunction were previously unrecognized in 60% (38 of 63) and 84% (27 of 32), respectively, with only 33% (21 of 63) and 19% (6 of 32) on evidence-based treatments.

CONCLUSIONS

Systematic coronary and cardiac imaging of patients with type 2 myocardial infarction identified coronary artery disease in two-thirds and left ventricular systolic dysfunction in one-third of patients. Unrecognized and untreated coronary or cardiac disease is seen in most patients with type 2 myocardial infarction, presenting opportunities for initiation of evidence-based treatments with major potential to improve clinical outcomes.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT03338504.

Respiration-averaged CT versus standard CT attenuation map for correction of 18F-sodium fluoride uptake in coronary atherosclerotic lesions on hybrid PET/CT

BACKGROUND

To evaluate the impact of respiratory-averaged computed tomography attenuation correction (RACTAC) compared to standard single-phase computed tomography attenuation correction (CTAC) map, on the quantitative measures of coronary atherosclerotic lesions of 18F-sodium fluoride (18F-NaF) uptake in hybrid positron emission tomography and computed tomography (PET/CT).

METHODS

This study comprised 23 patients who underwent 18F-NaF coronary PET in a hybrid PET/CT system. All patients had a standard single-phase CTAC obtained during free-breathing and a 4D cine-CT scan. From the cine-CT acquisition, RACTAC maps were obtained by averaging all images acquired over 5 seconds. PET reconstructions using either CTAC or RACTAC were compared. The quantitative impact of employing RACTAC was assessed using maximum target-to-background (TBRMAX) and coronary microcalcification activity (CMA). Statistical differences were analyzed using reproducibility coefficients and Bland-Altman plots.

RESULTS

In 23 patients, we evaluated 34 coronary lesions using CTAC and RACTAC reconstructions. There was good agreement between CTAC and RACTAC for TBRMAX (median [Interquartile range]): CTAC = 1.65 [1.23 to 2.38], RACTAC = 1.63 [1.23 to 2.33], p = 0.55), with coefficient of reproducibility of 0.18, and CMA: CTAC = 0.10 [0 to 1.0], RACTAC = 0.15 [0 to 1.03], p = 0.55 with coefficient of reproducibility of 0.17 CONCLUSION: Respiratory-averaged and standard single-phase attenuation correction maps provide similar and reproducible methods of quantifying coronary 18F-NaF uptake on PET/CT.

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study

BACKGROUND

Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accurate assessment of coronary artery disease burden and prognosis. We sought to develop and validate a deep learning system for CCTA-derived measures of plaque volume and stenosis severity.

METHODS

This international, multicentre study included nine cohorts of patients undergoing CCTA at 11 sites, who were assigned into training and test sets. Data were retrospectively collected on patients with a wide range of clinical presentations of coronary artery disease who underwent CCTA between Nov 18, 2010, and Jan 25, 2019. A novel deep learning convolutional neural network was trained to segment coronary plaque in 921 patients (5045 lesions). The deep learning network was then applied to an independent test set, which included an external validation cohort of 175 patients (1081 lesions) and 50 patients (84 lesions) assessed by intravascular ultrasound within 1 month of CCTA. We evaluated the prognostic value of deep learning-based plaque measurements for fatal or non-fatal myocardial infarction (our primary outcome) in 1611 patients from the prospective SCOT-HEART trial, assessed as dichotomous variables using multivariable Cox regression analysis, with adjustment for the ASSIGN clinical risk score.

FINDINGS

In the overall test set, there was excellent or good agreement, respectively, between deep learning and expert reader measurements of total plaque volume (intraclass correlation coefficient [ICC] 0·964) and percent diameter stenosis (ICC 0·879; both p<0·0001). When compared with intravascular ultrasound, there was excellent agreement for deep learning total plaque volume (ICC 0·949) and minimal luminal area (ICC 0·904). The mean per-patient deep learning plaque analysis time was 5·65 s (SD 1·87) versus 25·66 min (6·79) taken by experts. Over a median follow-up of 4·7 years (IQR 4·0-5·7), myocardial infarction occurred in 41 (2·5%) of 1611 patients from the SCOT-HEART trial. A deep learning-based total plaque volume of 238·5 mm3 or higher was associated with an increased risk of myocardial infarction (hazard ratio [HR] 5·36, 95% CI 1·70-16·86; p=0·0042) after adjustment for the presence of deep learning-based obstructive stenosis (HR 2·49, 1·07-5·50; p=0·0089) and the ASSIGN clinical risk score (HR 1·01, 0·99-1·04; p=0·35).

INTERPRETATION

Our novel, externally validated deep learning system provides rapid measurements of plaque volume and stenosis severity from CCTA that agree closely with expert readers and intravascular ultrasound, and could have prognostic value for future myocardial infarction.

FUNDING

National Heart, Lung, and Blood Institute and the Miriam & Sheldon G Adelson Medical Research Foundation.

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.

Pericoronary fat attenuation index and coronary plaque quantified from coronary computed tomography angiography identify ischemia-causing lesions

BACKGROUND

The association between pericoronary fat attenuation index (FAI), plaque characteristics, and lesion-specific ischemia identified by fractional flow reserve (FFR) remains unclear.

METHODS

Coronary computed tomography angiography (CCTA) stenosis, FAI, plaque characteristics, FFR derived from computed tomography (FFR_CT) and FFR were assessed in 280 vessels of 247 patients. Stenosis ≥50% was considered obstructive. Optimal thresholds of FAI and plaque variables were defined by the area under the receiver-operating characteristics curve (AUC) analysis. Ischemia was defined by FFR ≤ 0.80.

RESULTS

FAI ≥ -71.9 HU, low-attenuation plaque (LAP) ≥ 49.62 mm³ and aggregate plaque volume (APV) ≥ 28.91% predicted ischemia independent of other plaque characteristics. The addition of FAI ≥ -71.9 HU improved discrimination (AUC, 0.720 vs. 0.674, P = 0.035) and reclassification abilities (category-free net reclassification index [NRI], 0.470, P < 0.001; relative integrated discrimination improvement [IDI], 0.047, P < 0.001) of ischemia compared with stenosis evaluation alone, with further discrimination (AUC, 0.772 vs. 0.720, P = 0.028) and reclassification abilities (NRI, 0.385, P = 0.001; relative IDI, 0.077, P < 0.001) of ischemia by adding information regarding LAP ≥49.62 mm³ + APV ≥ 28.91%. And the diagnostic performance of combination approach was comparable to that of FFR_CT alone (AUC, 0.772 vs. 0.762, P = 0.771).

CONCLUSIONS

Stenosis severity, FAI, plaque characteristics predicted lesion-specific ischemia. The combination of FAI and plaque assessment improved the discrimination of ischemia compared with stenosis assessment alone.

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.

Coronary CT Angiography to Guide Percutaneous Coronary Intervention

Coronary CT angiography (CCTA) has emerged as a powerful noninvasive tool for characterizing the presence, extent, and severity of coronary artery disease (CAD) in patients with stable angina. Recent technological advancements in CT scanner hardware and software have augmented the rich information that can be derived from a single CCTA study. Beyond merely identifying the presence of CAD and assessing stenosis severity, CCTA now allows for the identification and characterization of plaques, lesion length, and fluoroscopic angle optimization, as well as enables the assessment of the physiologic extent of stenosis through CT-derived fractional flow reserve, and may even allow for the prediction of the response to revascularization. These and other features make CCTA capable of not only guiding invasive coronary angiography referral, but also give it the unique ability to help plan coronary intervention. This review summarizes current and future applications of CCTA in procedural planning for percutaneous coronary intervention, provides rationale for wider integration of CCTA in the workflow of the interventional cardiologist, and details how CCTA may help improve patient care and clinical outcomes. Keywords: CT Angiography © RSNA, 2022.

Observer repeatability and interscan reproducibility of 18F-sodium fluoride coronary microcalcification activity

BACKGROUND

We aimed to establish the observer repeatability and interscan reproducibility of coronary 18F-sodium-fluoride positron emission tomography (PET) uptake using a novel semi-automated approach, coronary microcalcification activity (CMA).

METHODS

Patients with multivessel coronary artery disease underwent repeated hybrid PET and computed tomography angiography (CTA) imaging (PET/CTA). CMA was defined as the integrated standardized uptake values (SUV) in the entire coronary tree exceeding 2 standard deviations above the background SUV. Coefficients of repeatability between the same observer (intraobserver repeatability), between 2 observers (interobserver repeatability) and coefficient of reproducibility between 2 scans (interscan reproducibility), were determined at vessel and patient level.

RESULTS

In 19 patients, CMA was assessed twice in 43 coronary vessels on two PET/CT scans performed 12 ± 5 days apart. There was excellent intraclass correlation for intraobserver and interobserver repeatability as well as interscan reproducibility (all ≥ 0.991). There was 100% intraobserver, interobserver and interscan agreement for the presence (CMA > 0) or absence (CMA = 0) of coronary18F-NaF uptake. Mean CMA was 3.12 ± 0.62 with coefficients of repeatability of ≤ 10% for all measures: intraobserver 0.24 and 0.22, interobserver 0.30 and 0.29 and interscan 0.33 and 0.32 at a per-vessel and per-patient level, respectively.

CONCLUSIONS

CMA is a repeatable and reproducible global measure of coronary atherosclerotic activity.

Association of Lipoprotein(a) With Atherosclerotic Plaque Progression

BACKGROUND

Lipoprotein(a) [Lp(a)] is associated with increased risk of myocardial infarction, although the mechanism for this observation remains uncertain.

OBJECTIVES

This study aims to investigate whether Lp(a) is associated with adverse plaque progression.

METHODS

Lp(a) was measured in patients with advanced stable coronary artery disease undergoing coronary computed tomography angiography at baseline and 12 months to assess progression of total, calcific, noncalcific, and low-attenuation plaque (necrotic core) in particular. High Lp(a) was defined as Lp(a) ≥ 70 mg/dL. The relationship of Lp(a) with plaque progression was assessed using linear regression analysis, adjusting for body mass index, segment involvement score, and ASSIGN score (a Scottish cardiovascular risk score comprised of age, sex, smoking, blood pressure, total and high-density lipoprotein [HDL]-cholesterol, diabetes, rheumatoid arthritis, and deprivation index).

RESULTS

A total of 191 patients (65.9 ± 8.3 years of age; 152 [80%] male) were included in the analysis, with median Lp(a) values of 100 (range: 82 to 115) mg/dL and 10 (range: 5 to 24) mg/dL in the high and low Lp(a) groups, respectively. At baseline, there was no difference in coronary artery disease severity or plaque burden. Patients with high Lp(a) showed accelerated progression of low-attenuation plaque compared with low Lp(a) patients (26.2 ± 88.4 mm3 vs -0.7 ± 50.1 mm3; P = 0.020). Multivariable linear regression analysis confirmed the relation between Lp(a) and low-attenuation plaque volume progression (β = 10.5% increase for each 50 mg/dL Lp(a), 95% CI: 0.7%-20.3%). There was no difference in total, calcific, and noncalcific plaque volume progression.

CONCLUSIONS

Among patients with advanced stable coronary artery disease, Lp(a) is associated with accelerated progression of coronary low-attenuation plaque (necrotic core). This may explain the association between Lp(a) and the high residual risk of myocardial infarction, providing support for Lp(a) as a treatment target in atherosclerosis.

Coronary Atherosclerotic Plaque Regression: JACC State-of-the-Art Review

Over the last 3 decades there have been substantial improvements in treatments aimed at reducing cardiovascular (CV) events. As these treatments have been developed, there have been parallel improvements in coronary imaging modalities that can assess plaque volumes and composition, using both invasive and noninvasive techniques. Plaque progression can be seen to precede CV events, and therefore, many studies have longitudinally assessed changes in plaque characteristics in response to various treatments, aiming to demonstrate plaque regression and improvements in high-risk features, with the rationale being that this will reduce CV events. In the past, decisions surrounding treatments for atherosclerosis have been informed by population-based risk scores for initiation in primary prevention and low-density lipoprotein cholesterol levels for titration in secondary prevention. If outcome data linking plaque regression to reduced CV events emerge, it may become possible to directly image plaque treatment response to guide management decisions.

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.

Impact of vascular morphology and plaque characteristics on computed tomography derived fractional flow reserve in early stage coronary artery disease

BACKGROUND

Computed-tomography (CT) derived fractional-flow-reserve (FFR_CT) gradually may decrease from proximal to distal vessels even without apparent coronary artery disease (CAD). It may be unclear whether the decrease in FFR_CT at the distal coronal artery is physiological or due to stenosis. We decided to study predictive factors of an FFR_CT decline below the pathological value of 0.80 in no-apparent CAD.

METHODS

A total of 150 consecutive patients who had both CT angiography coupled to FFR_CT analysis and invasive angiogram showing < 20% coronary stenosis were included. Vessels were divided into two groups according to FFR_CT at the distal vessel: FFR_CT > 0.80 (n = 317) and FFR_CT ≤ 0.80 (n = 114). ΔFFR_CT was defined as the change in FFR_CT from proximal to distal vessel. Vessel morphology (vessel length and lumen volume) and plaque characteristics [low-attenuation plaque volume, intermediate-attenuation (IAP) plaque volume, and calcified plaque volume] were evaluated.

RESULTS

FFR_CT decreased from proximal to distal for the three major vessels in both FFR_CT > 0.80 and FFR_CT ≤ 0.80. Compared to FFR_CT > 0.80, IAP volume was significantly higher in all three major vessels in FFR_CT ≤ 0.80. ΔFFR_CT was correlated with vessel length and lumen volume in FFR_CT > 0.80, whereas ΔFFR_CT was correlated with IAP volume in FFR_CT ≤ 0.80. IAP volume above 44.8 mm³ was the strongest predictor of distal FFR_CT of ≤ 0.80.

CONCLUSIONS

The presence of IAP is a major predictor of gradual decrease of FFR_CT below 0.80 in no-apparent CAD vessels. Vessel morphology and plaque characteristics should be considered when interpreting FFR_CT.

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.

Reproducibility of quantitative plaque measurement in advanced coronary artery disease

BACKGROUND

The ability to characterize and to quantify the extent of coronary artery disease has the potential to improve the prognostic capability of coronary computed tomography angiography. Although reproducible techniques have been described in those with mild coronary disease, this has yet to be assessed in patients with advanced disease.

METHODS

Twenty patients with known multivessel disease underwent repeated computed tomography coronary angiography, 2 weeks apart. Coronary artery segments were analysed using semi-automated software by two trained observers to determine intraobserver, interobserver and interscan reproducibility.

RESULTS

Overall, 149 coronary arterial segments were analysed. There was excellent intraobserver and interobserver agreement for all plaque volume measurements (Lin's coefficient 0.95 to 1.0). There were no substantial interscan differences (P ​> ​0.05 for all) for total (2063 ​± ​1246 ​mm3, mean of differences -35.6 ​mm3), non-calcified (1795 ​± ​910 ​mm3, mean of differences -4.3 ​mm3), calcified (298 ​± ​425 ​mm3, mean of differences -31.3 ​mm3) and low-attenuation (13 ​± ​13 ​mm3, mean of differences -2.6 ​mm3) plaque volumes. Interscan agreement was highest for total and noncalcified plaque volumes. Calcified and low-attenuation plaque (-236.6 to 174 ​mm3 and -15.8 to 10.5 ​mm3 respectively) had relatively wider 95% limits of agreement reflecting the lower absolute plaque volumes.

CONCLUSION

In the presence of advanced coronary disease, semi-automated plaque quantification provides excellent reproducibility, particularly for total and non-calcified plaque volumes. This approach has major potential to assess change in disease over time and optimize risk stratification in patients with established coronary artery disease.

Association of Coronary Artery Atherosclerosis With Brain White Matter Hyperintensity

[Figure: see text].

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.

Pericoronary adipose tissue computed tomography attenuation distinguishes different stages of coronary artery disease: a cross-sectional study

AIMS

Vascular inflammation inhibits local adipogenesis in pericoronary adipose tissue (PCAT) and this can be detected on coronary computed tomography angiography (CCTA) as an increase in CT attenuation of PCAT surrounding the proximal right coronary artery (RCA). In this cross-sectional study, we assessed the utility of PCAT CT attenuation as an imaging biomarker of coronary inflammation in distinguishing different stages of coronary artery disease (CAD).

METHODS AND RESULTS

Sixty patients with acute myocardial infarction (MI) were prospectively recruited to undergo CCTA within 48 h of admission, prior to invasive angiography. These participants were matched to patients with stable CAD (n = 60) and controls with no CAD (n = 60) by age, gender, BMI, risk factors, medications, and CT tube voltage. PCAT attenuation around the proximal RCA was quantified per-patient using semi-automated software. Patients with MI had a higher PCAT attenuation (-82.3 ± 5.5 HU) compared with patients with stable CAD (-90.6 ± 5.7 HU, P < 0.001) and controls (-95.8 ± 6.2 HU, P < 0.001). PCAT attenuation was significantly increased in stable CAD patients over controls (P = 0.01). The association of PCAT attenuation with stage of CAD was independent of age, gender, cardiovascular risk factors, epicardial adipose tissue volume, and CCTA-derived quantitative plaque burden. No interaction was observed for clinical presentation (MI vs. stable CAD) and plaque burden on PCAT attenuation.

CONCLUSION

PCAT CT attenuation as a quantitative measure of global coronary inflammation independently distinguishes patients with MI vs. stable CAD vs. no CAD. Future studies should assess whether this imaging biomarker can track patient responses to therapies in different stages of CAD.

Coronary plaque assessment of Vasodilative capacity by CT angiography effectively estimates fractional flow reserve

BACKGROUND

To evaluate the feasibility of non-invasive fractional flow reserve (FFR) estimation using histologically-validated assessment of plaque morphology on coronary CTA (CCTA) as inputs to a predictive model further validated against invasive FFR.

METHODS

Patients (n = 113, 59 ± 8.9 years, 77% male) with suspected coronary artery disease (CAD) who had undergone CCTA and invasive FFR between August 2013 and May 2018 were included. Commercially available software was used to extract quantitative plaque morphology inclusive of both vessel structure and composition. The extracted plaque morphology was then fed as inputs to an optimized artificial neural network to predict lesion-specific ischemia/hemodynamically significant CAD with performance validated by invasive FFR.

RESULTS

A total of 122 lesions were considered, 59 (48%) had low FFR values. Plaque morphology-based FFR assessment achieved an area under the curve, sensitivity and specificity of 0.94, 0.90 and 0.81, respectively, versus 0.71, 0.71, and 0.50, respectively, for an optimized threshold applied to degree of stenosis. The optimized ridge regression model for continuous value estimation of FFR achieved a cross-correlation coefficient of 0.56 and regression slope of 0.59 using cross validation, versus 0.18 and 0.10 for an optimized threshold applied to degree of stenosis.

CONCLUSIONS

Our results show that non-invasive plaque morphology-based FFR assessment may be used to predict lesion-specific ischemia resulting in hemodynamically significant CAD. This substantially outperforms degree of stenosis interpretation and has a comparable level of sensitivity and specificity relative to publicly reported results from computational fluid dynamics-based approaches.

Repeatability of quantitative pericoronary adipose tissue attenuation and coronary plaque burden from coronary CT angiography

BACKGROUND

High pericoronary adipose tissue (PCAT) attenuation and non-calcified plaque burden (NCP) measured from coronary CT angiography (CTA) have been implicated in future cardiac events. We aimed to evaluate the interobserver and intraobserver repeatability of PCAT attenuation and NCP burden measurement from CTA, in a sub-study of the prospective SCOT-HEART trial.

METHODS

Fifty consecutive CTAs from participants of the CT arm of the prospective SCOT-HEART trial were included. Two experienced observers independently measured PCAT attenuation and plaque characteristics throughout the whole coronary tree from CTA using semi-automatic quantitative software.

RESULTS

We analyzed proximal segments in 157 vessels. Intraobserver mean differences in PCAT attenuation and NCP plaque burden were -0.05HU and 0.92% with limits of agreement (LOA) of ±1.54 and ± 5.97%. Intraobserver intraclass correlation coefficients (ICC) for PCAT attenuation and NCP burden were excellent (0.999 and 0.978). Interobserver mean differences in PCAT attenuation and NCP plaque burden were 0.13HU [LOA ±1.67HU] and -0.23% (LOA ±9.61%). Interobserver ICC values for PCAT attenuation and NCP burden were excellent (0.998 and 0.944).

CONCLUSION

PCAT attenuation and NCP burden on CTA has high intraobserver and interobserver repeatability, suggesting they represent a repeatable and robust method of quantifying cardiovascular risk.

Coronary Artery Lumen Segmentation Using Location-Adaptive Threshold in Coronary Computed Tomographic Angiography: A Proof-of-Concept

OBJECTIVE

To compare the lumen parameters measured by the location-adaptive threshold method (LATM), in which the inter- and intra-scan attenuation variabilities of coronary computed tomographic angiography (CCTA) were corrected, and the scan-adaptive threshold method (SATM), in which only the inter-scan variability was corrected, with the reference standard measurement by intravascular ultrasonography (IVUS).

MATERIALS AND METHODS

The Hounsfield unit (HU) values of whole voxels and the centerline in each of the cross-sections of the 22 target coronary artery segments were obtained from 15 patients between March 2009 and June 2010, in addition to the corresponding voxel size. Lumen volume was calculated mathematically as the voxel volume multiplied by the number of voxels with HU within a given range, defined as the lumen for each method, and compared with the IVUS-derived reference standard. Subgroup analysis of the lumen area was performed to investigate the effect of lumen size on the studied methods. Bland-Altman plots were used to evaluate the agreement between the measurements.

RESULTS

Lumen volumes measured by SATM was significantly smaller than that measured by IVUS (mean difference, 14.6 mm³; 95% confidence interval [CI], 4.9-24.3 mm³); the lumen volumes measured by LATM and IVUS were not significantly different (mean difference, -0.7 mm³; 95% CI, -9.1-7.7 mm³). The lumen area measured by SATM was significantly smaller than that measured by LATM in the smaller lumen area group (mean of difference, 1.07 mm²; 95% CI, 0.89-1.25 mm²) but not in the larger lumen area group (mean of difference, -0.07 mm²; 95% CI, -0.22-0.08 mm²). In the smaller lumen group, the mean difference was lower in the Bland-Altman plot of IVUS and LATM (0.46 mm²; 95% CI, 0.27-0.65 mm²) than in that of IVUS and SATM (1.53 mm²; 95% CI, 1.27-1.79 mm²).

CONCLUSION

SATM underestimated the lumen parameters for computed lumen segmentation in CCTA, and this may be overcome by using LATM.