Automated 3-dimensional quantification of noncalcified and calcified coronary plaque from coronary CT angiography

Using artificial intelligence to study atherosclerosis from computed tomography imaging: A state-of-the-art review of the current literature

With the enormous progress in the field of cardiovascular imaging in recent years, computed tomography (CT) has become readily available to phenotype atherosclerotic coronary artery disease. New analytical methods using artificial intelligence (AI) enable the analysis of complex phenotypic information of atherosclerotic plaques. In particular, deep learning-based approaches using convolutional neural networks (CNNs) facilitate tasks such as lesion detection, segmentation, and classification. New radiotranscriptomic techniques even capture underlying bio-histochemical processes through higher-order structural analysis of voxels on CT images. In the near future, the international large-scale Oxford Risk Factors And Non-invasive Imaging (ORFAN) study will provide a powerful platform for testing and validating prognostic AI-based models. The goal is the transition of these new approaches from research settings into a clinical workflow. In this review, we present an overview of existing AI-based techniques with focus on imaging biomarkers to determine the degree of coronary inflammation, coronary plaques, and the associated risk. Further, current limitations using AI-based approaches as well as the priorities to address these challenges will be discussed. This will pave the way for an AI-enabled risk assessment tool to detect vulnerable atherosclerotic plaques and to guide treatment strategies for patients.

Interaction Between Risk Factors, Coronary Calcium, and CCTA Plaque Characteristics in Patients Age 18-45

AIMS

The atherosclerotic profile and advanced plaque subtype burden in symptomatic patients ≤45 years old have not been established. This study aimed to assess the prevalence and predictors of coronary artery calcium (CAC), plaque subtypes, and plaque burden by coronary computed tomography angiography (CCTA) in symptomatic young patients.

METHODS AND RESULTS

We included 907 symptomatic young patients (18-45 years) from Montefiore undergoing CCTA for chest pain evaluation. Prevalence and predictors of CAC, plaque subtypes, and burden were evaluated using semi-automated software. In the overall population (55% female and 44% Hispanic), 89% had CAC = 0. The likelihood of CAC or any plaque by CCTA increased with >3 risk factors (RF, OR 7.13 [2.14-23.7] and OR 10.26 [3.36-31.2], respectively). Any plaque by CCTA was present in 137 (15%); the strongest independent predictors were age ≥35 years (OR 3.62 [2.05-6.41]) and family history of premature CAD (FHx) (OR 2.76 [1.67-4.58]). Stenosis ≥50% was rare (1.8%), with 31% of those having CAC = 0. Significant non-calcified (NCP, 37.2%) and low-attenuation (LAP, 4.24%) plaque burdens were seen, even in those with non-obstructive stenosis. Among patients with CAC = 0, 5% had plaque, and the only predictor of exclusively non-calcified plaque was FHx (OR 2.29 [1.08-4.86]).

CONCLUSIONS

In symptomatic young patients undergoing CCTA, the prevalence of CAC or any coronary atherosclerosis was not negligible, and the likelihood increased with RF burden. The presence of coronary stenosis ≥50% was rare and most often accompanied by CAC > 0 but there was a significant burden of NCP and LAP even within the non-obstructive group.

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.

Coronary artery disease reporting and data system (CAD-RADS), vascular inflammation and plaque vulnerability

BACKGROUND

Coronary artery disease reporting and data system (CAD-RADS) predicts future cardiovascular events in patients with coronary artery disease (CAD). However, information on vascular inflammation and vulnerability remains scarce.

METHODS

Patients who underwent coronary computed tomography angiography (CTA) and optical coherence tomography (OCT) prior to coronary intervention were enrolled. All three coronary arteries were evaluated for CAD-RADS score and pericoronary adipose tissue (PCAT) attenuation, while the culprit vessel was analyzed for plaque vulnerability by OCT.

RESULTS

A total of 385 patients with 915 lesions were divided into two groups based on CAD-RADS score: 103 (26.8%) were categorized as CAD-RADS 4b/5 and 282 (73.2%) as CAD-RADS ≤4a. Patients with CAD-RADS 4b/5 had a higher level of PCAT attenuation (mean of 3 coronary arteries) than those with CAD-RADS ≤4a (-68.4 ​± ​6.7 HU vs. -70.1 ​± ​6.5, P ​= ​0.022). The prevalence of macrophage was higher, and lipid index was greater in patients with CAD-RADS 4b/5 than CAD-RADS ≤4a (94.2% vs. 83.0%, P ​= ​0.004, 1845 vs. 1477; P ​= ​0.003). These associations were significant in the culprit vessels of patients with chronic coronary syndrome but not in those with acute coronary syndromes.

CONCLUSIONS

Higher CAD-RADS score was associated with higher levels of vascular inflammation and plaque vulnerability.

Quantification of Low-Attenuation Plaque Burden from Coronary CT Angiography: A Head-to-Head Comparison with Near-Infrared Spectroscopy Intravascular US

Purpose

To determine the association between low-attenuation plaque (LAP) burden at coronary CT angiography (CCTA) and plaque morphology determined with near-infrared spectroscopy intravascular US (NIRS-IVUS) and to compare the discriminative ability for NIRS-IVUS-verified high-risk plaques (HRPs) between LAP burden and visual assessment of LAP.

Materials and Methods

This Health Insurance Portability and Accountability Act-compliant retrospective study included consecutive patients who underwent CCTA before NIRS-IVUS between October 2019 and October 2022 at two facilities. LAPs were visually identified as having a central focal area of less than 30 HU using the pixel lens technique. LAP burden was calculated as the volume of voxels with less than 30 HU divided by vessel volume. HRPs were defined as plaques with one of the following NIRS-IVUS-derived high-risk features: maximum 4-mm lipid core burden index greater than 400 (lipid-rich plaque), an echolucent zone (intraplaque hemorrhage), or echo attenuation (cholesterol clefts). Multivariable analysis was performed to evaluate NIRS-IVUS-derived parameters associated with LAP burden. The discriminative ability for NIRS-IVUS-verified HRPs was compared using receiver operating characteristic analysis.

Results

In total, 273 plaques in 141 patients (median age, 72 years; IQR, 63-78 years; 106 males) were analyzed. All the NIRS-IVUS-derived high-risk features were independently linked to LAP burden (P < .01 for all). LAP burden increased with the number of high-risk features (P < .001) and had better discriminative ability for HRPs than plaque attenuation by visual assessment (area under the receiver operating characteristic curve, 0.93 vs 0.89; P = .02).

Conclusion

Quantification of LAP burden improved HRP assessment compared with visual assessment. LAP burden was associated with the accumulation of HRP morphology.Keywords: Coronary CT Angiography, Intraplaque Hemorrhage, Lipid-Rich Plaque, Low Attenuation Plaque, Near-Infrared Spectroscopy Intravascular Ultrasound Supplemental material is available for this article. See also the commentary by Ferencik in this issue.© RSNA, 2023.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

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.

Lectin-Like Oxidized Low-Density Lipoprotein Receptor 1 Inhibition in Type 2 Diabetes: Phase 1 Results

Background Blockade of the lectin-like oxidized low-density lipoprotein receptor-1 (LOX-1) is a potentially attractive mechanism for lowering inflammatory and lipid risk in patients with atherosclerosis. This study aims to assess the safety, tolerability, and target engagement of MEDI6570, a high-affinity monoclonal blocking antibody to LOX-1. Methods and Results This phase 1, first-in-human, placebo-controlled study (NCT03654313) randomized 88 patients with type 2 diabetes to receive single ascending doses (10, 30, 90, 250, or 500 mg) or multiple ascending doses (90, 150, or 250 mg once monthly for 3 months) of MEDI6570 or placebo. Primary end point was safety; secondary and exploratory end points included pharmacokinetics, immunogenicity, free soluble LOX-1 levels, and change in coronary plaque volume. Mean age was 57.6/58.1 years in the single ascending doses/multiple ascending doses groups, 31.3%/62.5% were female, and mean type 2 diabetes duration was 9.7/8.7 years. Incidence of adverse events was similar among cohorts. MEDI6570 exhibited nonlinear pharmacokinetics, with terminal half-life increasing from 4.6 days (30 mg) to 11.2 days (500 mg), consistent with target-mediated drug disposition. Dose-dependent reductions in mean soluble LOX-1 levels from baseline were observed (>66% at 4 weeks and 71.61-82.96% at 10 weeks in the single ascending doses and multiple ascending doses groups, respectively). After 3 doses, MEDI6570 was associated with nonsignificant regression of noncalcified plaque volume versus placebo (-13.45 mm3 versus -8.25 mm3). Conclusions MEDI6570 was well tolerated and demonstrated dose-dependent soluble LOX-1 suppression and a pharmacokinetic profile consistent with once-monthly dosing. Registration URL: https://clinicaltrials.gov/; Unique identifier: NCT03654313.

Learning coronary artery calcium scoring in coronary CTA from non-contrast CT using unsupervised domain adaptation

Deep learning methods have demonstrated the ability to perform accurate coronary artery calcium (CAC) scoring. However, these methods require large and representative training data hampering applicability to diverse CT scans showing the heart and the coronary arteries. Training methods that accurately score CAC in cross-domain settings remains challenging. To address this, we present an unsupervised domain adaptation method that learns to perform CAC scoring in coronary CT angiography (CCTA) from non-contrast CT (NCCT). To address the domain shift between NCCT (source) domain and CCTA (target) domain, feature distributions are aligned between two domains using adversarial learning. A CAC scoring convolutional neural network is divided into a feature generator that maps input images to features in the latent space and a classifier that estimates predictions from the extracted features. For adversarial learning, a discriminator is used to distinguish the features between source and target domains. Hence, the feature generator aims to extract features with aligned distributions to fool the discriminator. The network is trained with adversarial loss as the objective function and a classification loss on the source domain as a constraint for adversarial learning. In the experiments, three data sets were used. The network is trained with 1,687 labeled chest NCCT scans from the National Lung Screening Trial. Furthermore, 200 labeled cardiac NCCT scans and 200 unlabeled CCTA scans were used to train the generator and the discriminator for unsupervised domain adaptation. Finally, a data set containing 313 manually labeled CCTA scans was used for testing. Directly applying the CAC scoring network trained on NCCT to CCTA led to a sensitivity of 0.41 and an average false positive volume 140 mm³/scan. The proposed method improved the sensitivity to 0.80 and reduced average false positive volume of 20 mm³/scan. The results indicate that the unsupervised domain adaptation approach enables automatic CAC scoring in contrast enhanced CT while learning from a large and diverse set of CT scans without contrast. This may allow for better utilization of existing annotated data sets and extend the applicability of automatic CAC scoring to contrast-enhanced CT scans without the need for additional manual annotations. The code is publicly available at https://github.com/qurAI-amsterdam/CACscoringUsingDomainAdaptation.

Finetuned Super-Resolution Generative Adversarial Network (Artificial Intelligence) Model for Calcium Deblooming in Coronary Computed Tomography Angiography

The purpose of this study was to finetune a deep learning model, real-enhanced super-resolution generative adversarial network (Real-ESRGAN), and investigate its diagnostic value in calcified coronary plaques with the aim of suppressing blooming artifacts for the further improvement of coronary lumen assessment. We finetuned the Real-ESRGAN model and applied it to 50 patients with 184 calcified plaques detected at three main coronary arteries (left anterior descending [LAD], left circumflex [LCx] and right coronary artery [RCA]). Measurements of coronary stenosis were collected from original coronary computed tomography angiography (CCTA) and Real-ESRGAN-processed images, including Real-ESRGAN-high-resolution, Real-ESRGAN-average and Real-ESRGAN-median (Real-ESRGAN-HR, Real-ESRGAN-A and Real-ESRGAN-M) with invasive coronary angiography as the reference. Our results showed specificity and positive predictive value (PPV) of the Real-ESRGAN-processed images were improved at all of the three coronary arteries, leading to significant reduction in the false positive rates when compared to those of the original CCTA images. The specificity and PPV of the Real-ESRGAN-M images were the highest at the RCA level, with values being 80% (95% CI: 64.4%, 90.9%) and 61.9% (95% CI: 45.6%, 75.9%), although the sensitivity was reduced to 81.3% (95% CI: 54.5%, 95.9%) due to false negative results. The corresponding specificity and PPV of the Real-ESRGAN-M images were 51.9 (95% CI: 40.3%, 63.5%) and 31.5% (95% CI: 25.8%, 37.8%) at LAD, 62.5% (95% CI: 40.6%, 81.2%) and 43.8% (95% CI: 30.3%, 58.1%) at LCx, respectively. The area under the receiver operating characteristic curve was also the highest at the RCA with value of 0.76 (95% CI: 0.64, 0.89), 0.84 (95% CI: 0.73, 0.94), 0.85 (95% CI: 0.75, 0.95) and 0.73 (95% CI: 0.58, 0.89), corresponding to original CCTA, Real-ESRGAN-HR, Real-ESRGAN-A and Real-ESRGAN-M images, respectively. This study proves that the finetuned Real-ESRGAN model significantly improves the diagnostic performance of CCTA in assessing calcified plaques.

Association of coronary artery calcium score with qualitatively and quantitatively assessed adverse plaque on coronary CT angiography in the SCOT-HEART trial

AIMS

Coronary artery calcification is a marker of cardiovascular risk, but its association with qualitatively and quantitatively assessed plaque subtypes is unknown.

METHODS AND RESULTS

In this post-hoc analysis, computed tomography (CT) images and 5-year clinical outcomes were assessed in SCOT-HEART trial participants. Agatston coronary artery calcium score (CACS) was measured on non-contrast CT and was stratified as zero (0 Agatston units, AU), minimal (1-9 AU), low (10-99 AU), moderate (100-399 AU), high (400-999 AU), and very high (≥1000 AU). Adverse plaques were investigated by qualitative (visual categorization of positive remodelling, low-attenuation plaque, spotty calcification, and napkin ring sign) and quantitative (calcified, non-calcified, low-attenuation, and total plaque burden; Autoplaque) assessments. Of 1769 patients, 36% had a zero, 9% minimal, 20% low, 17% moderate, 10% high, and 8% very high CACS. Amongst patients with a zero CACS, 14% had non-obstructive disease, 2% had obstructive disease, 2% had visually assessed adverse plaques, and 13% had low-attenuation plaque burden >4%. Non-calcified and low-attenuation plaque burden increased between patients with zero, minimal, and low CACS (P < 0.001), but there was no statistically significant difference between those with medium, high, and very high CACS. Myocardial infarction occurred in 41 patients, 10% of whom had zero CACS. CACS >1000 AU and low-attenuation plaque burden were the only predictors of myocardial infarction, independent of obstructive disease, and 10-year cardiovascular risk score.

CONCLUSION

In patients with stable chest pain, zero CACS is associated with a good but not perfect prognosis, and CACS cannot rule out obstructive coronary artery disease, non-obstructive plaque, or adverse plaque phenotypes, including low-attenuation plaque.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Automatic coronary plaque detection, classification, and stenosis grading using deep learning and radiomics on computed tomography angiography images: a multi-center multi-vendor study

OBJECTIVES

An automatic system utilizing both the advantages of the neural network and the radiomics was proposed for coronary plaque detection, classification, and stenosis grading.

METHODS

This study retrospectively included 505 patients with 127,763 computed tomography angiography (CTA) images from 5 medical center. A convolutional neural network (CNN) model was used to segment the coronary artery, detect the plaque candidate, and extract the image patch with high computation efficiency. The manually designed radiomics feature extractor was utilized to collect plaque patterns, followed by the different classifiers to perform the plaque classification and stenosis grading.

RESULTS

The CNN model achieved 100% of sensitivity and the highest positive predictive value (83.9%) than U-Net and baseline model in plaque candidate detection. Twenty-six representative radiomics features were selected to construct the classifiers. Among different models, the gradient-boosting decision tree (GBDT) achieved the best performance in plaque classification (accuracy: 87.0%, sensitivity: 83.2%, specificity: 91.4%) and stenosis grading (accuracy: 90.9%, sensitivity: 84.1%, specificity: 95.7%). GBDT also achieved the highest AUC of 0.873 in plaque classification and 0.910 in stenosis grading. The computation time of processing one patient was 56.2 ± 5.7 s which was significantly less than radiologist manual analysis (285.6 ± 134.5 s, p = 0.0001).

CONCLUSIONS

In this study, an automatic workflow was proposed to detect and analyze coronary plaques with high accuracy and efficiency, showing the potential in clinical application.

KEY POINTS

• The proposed automatic system integrated deep learning and radiomics to perform the coronary plaque analysis. • The proposed automatic system achieved high accuracy in both plaque classification and stenosis grading. • The proposed automatic system was five times more efficient than radiologist manual analysis.

Additive value of epicardial adipose tissue quantification to coronary CT angiography-derived plaque characterization and CT fractional flow reserve for the prediction of lesion-specific ischemia

OBJECTIVES

Epicardial adipose tissue (EAT) from coronary CT angiography (CCTA) is strongly associated with coronary artery disease (CAD). We investigated the additive value of EAT volume to coronary plaque quantification and CT-derived fractional flow reserve (CT-FFR) to predict lesion-specific ischemia.

METHODS

Patients (n = 128, 60.6 ± 10.5 years, 61% male) with suspected CAD who had undergone invasive coronary angiography (ICA) and CCTA were retrospectively analyzed. EAT volume and plaque measures were derived from CCTA using a semi-automatic software approach, while CT-FFR was calculated using a machine learning algorithm. The predictive value and discriminatory power of EAT volume, plaque measures, and CT-FFR to identify ischemic CAD were assessed using invasive FFR as the reference standard.

RESULTS

Fifty-five of 152 lesions showed ischemic CAD by invasive FFR. EAT volume, CCTA ≥ 50% stenosis, and CT-FFR were significantly different in lesions with and without hemodynamic significance (all p < 0.05). Multivariate analysis revealed predictive value for lesion-specific ischemia of these parameters: EAT volume (OR 2.93, p = 0.021), CCTA ≥ 50% (OR 4.56, p = 0.002), and CT-FFR (OR 6.74, p < 0.001). ROC analysis demonstrated incremental discriminatory value with the addition of EAT volume to plaque measures alone (AUC 0.84 vs. 0.62, p < 0.05). CT-FFR (AUC 0.89) showed slightly superior performance over EAT volume with plaque measures (AUC 0.84), however without significant difference (p > 0.05).

CONCLUSIONS

EAT volume is significantly associated with ischemic CAD. The combination of EAT volume with plaque quantification demonstrates a predictive value for lesion-specific ischemia similar to that of CT-FFR. Thus, EAT may aid in the identification of hemodynamically significant coronary stenosis.

KEY POINTS

• CT-derived EAT volume quantification demonstrates high discriminatory power to identify lesion-specific ischemia. • EAT volume shows incremental diagnostic performance over CCTA-derived plaque measures in detecting lesion-specific ischemia. • A combination of plaque measures with EAT volume provides a similar discriminatory value for detecting lesion-specific ischemia compared to CT-FFR.

Artificial Intelligence Based Multimodality Imaging: A New Frontier in Coronary Artery Disease Management

Coronary artery disease (CAD) represents one of the most important causes of death around the world. Multimodality imaging plays a fundamental role in both diagnosis and risk stratification of acute and chronic CAD. For example, the role of Coronary Computed Tomography Angiography (CCTA) has become increasingly important to rule out CAD according to the latest guidelines. These changes and others will likely increase the request for appropriate imaging tests in the future. In this setting, artificial intelligence (AI) will play a pivotal role in echocardiography, CCTA, cardiac magnetic resonance and nuclear imaging, making multimodality imaging more efficient and reliable for clinicians, as well as more sustainable for healthcare systems. Furthermore, AI can assist clinicians in identifying early predictors of adverse outcome that human eyes cannot see in the fog of “big data.” AI algorithms applied to multimodality imaging will play a fundamental role in the management of patients with suspected or established CAD. This study aims to provide a comprehensive overview of current and future AI applications to the field of multimodality imaging of ischemic heart disease.

Sex-Specific Computed Tomography Coronary Plaque Characterization and Risk of Myocardial Infarction

OBJECTIVES

This study was designed to investigate whether coronary computed tomography angiography assessments of coronary plaque might explain differences in the prognosis of men and women presenting with chest pain.

BACKGROUND

Important sex differences exist in coronary artery disease. Women presenting with chest pain have different risk factors, symptoms, prevalence of coronary artery disease and prognosis compared to men.

METHODS

Within a multicenter randomized controlled trial, we explored sex differences in stenosis, adverse plaque characteristics (positive remodeling, low-attenuation plaque, spotty calcification, or napkin ring sign) and quantitative assessment of total, calcified, noncalcified and low-attenuation plaque burden.

RESULTS

Of the 1,769 participants who underwent coronary computed tomography angiography, 772 (43%) were female. Women were more likely to have normal coronary arteries and less likely to have adverse plaque characteristics (p < 0.001 for all). They had lower total, calcified, noncalcified, and low-attenuation plaque burdens (p < 0.001 for all) and were less likely to have a low-attenuation plaque burden >4% (41% vs. 59%; p < 0.001). Over a median follow-up of 4.7 years, myocardial infarction (MI) occurred in 11 women (1.4%) and 30 men (3%). In those who had MI, women had similar total, noncalcified, and low-attenuation plaque burdens as men, but men had higher calcified plaque burden. Low-attenuation plaque burden predicted MI (hazard ratio: 1.60; 95% confidence interval: 1.10 to 2.34; p = 0.015), independent of calcium score, obstructive disease, cardiovascular risk score, and sex.

CONCLUSIONS

Women presenting with stable chest pain have less atherosclerotic plaque of all subtypes compared to men and a lower risk of subsequent MI. However, quantitative low-attenuation plaque is as strong a predictor of subsequent MI in women as in men. (Scottish Computed Tomography of the HEART Trial [SCOT-HEART]; NCT01149590).

Association Between OSA and Quantitative Atherosclerotic Plaque Burden: A Coronary CT Angiography Study

BACKGROUND

Limited evidence is available regarding the association between OSA and coronary plaque assessed by using quantitative coronary CT angiography.

RESEARCH QUESTION

Are there any associations between OSA severity-related indexes and the presence and burden of coronary plaque?

STUDY DESIGN AND METHODS

Cross-sectional data from 692 patients who underwent sleep monitoring and coronary CT angiography were used for this study. Of these patients, 120 (17.3%) underwent polysomnography, and 572 (82.7%) underwent respiratory polygraphy. Multivariable logistic and linear regression analyses were used to investigate the associations of OSA severity-related indexes with the presence, volume, and composition of plaque.

RESULTS

In multivariable analyses, patients with moderate to severe OSA were more likely to have coronary plaques (P = .037), and plaques were more likely to contain a noncalcified plaque (NCP) component (P = .032) and a low-density NCP (LD NCP) component (P = .030). Furthermore, the apnea-hypopnea index and oxygen desaturation index as continuous variables were both associated with the presence of plaque, NCP, and LD NCP (all, P < .05). Multivariable linear regression models showed that moderate to severe OSA was associated with NCP volume (β = 50.328; P = .042) and LD NCP volume (β = 15.707; P = .011). Moreover, the apnea-hypopnea index (P = .015), oxygen desaturation index (P = .005), and percentage of nighttime with oxygen saturation < 90% (P = .017) were all significant predictors of LD NCP volume. Compared with those with no or mild OSA, patients with severe OSA had a significantly higher total plaque volume (P = .036), NCP volume (P = .036), and LD NCP volume (P = .013).

INTERPRETATION

OSA was independently associated with the presence and burden of coronary plaque, which suggests an increased risk of coronary events.

CLINICAL TRIAL REGISTRATION

Chinese Clinical Trial Registry; No. ChiCTR-ROC-17011027; http://chictr.org.cn.

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.

Extraction of Coronary Atherosclerotic Plaques From Computed Tomography Imaging: A Review of Recent Methods

Background: Atherosclerotic plaques are the major cause of coronary artery disease (CAD). Currently, computed tomography (CT) is the most commonly applied imaging technique in the diagnosis of CAD. However, the accurate extraction of coronary plaque geometry from CT images is still challenging.

Summary of Review: In this review, we focused on the methods in recent studies on the CT-based coronary plaque extraction. According to the dimension of plaque extraction method, the studies were categorized into two-dimensional (2D) and three-dimensional (3D) ones. In each category, the studies were analyzed in terms of data, methods, and evaluation. We summarized the merits and limitations of current methods, as well as the future directions for efficient and accurate extraction of coronary plaques using CT imaging.

Conclusion: The methodological innovations are important for more accurate CT-based assessment of coronary plaques in clinical applications. The large-scale studies, de-blooming algorithms, more standardized datasets, and more detailed classification of non-calcified plaques could improve the accuracy of coronary plaque extraction from CT images. More multidimensional geometric parameters can be derived from the 3D geometry of coronary plaques. Additionally, machine learning and automatic 3D reconstruction could improve the efficiency of coronary plaque extraction in future studies.

Development of a deep learning-based algorithm for the automatic detection and quantification of aortic valve calcium

PURPOSE

We aimed to develop a deep learning (DL)-based algorithm for automated quantification of aortic valve calcium (AVC) from non-enhanced electrocardiogram-gated cardiac CT scans and compare performance of DL-measured AVC volume and Agatston score with those of visual gradings by radiologist readers for classification of AVC severity.

METHOD

A total of 589 CT examinations performed at a single center between March 2010 and August 2017 were retrospectively included. The DL algorithm was designed to segment AVC and to quantify AVC volume, and Agatston score was calculated using attenuation values. Manually measured AVC volume and Agatston score were used as ground truth. To validate AVC segmentation performance, the Dice coefficient was calculated. For observer performance testing, four radiologists determined AVC grade in two reading rounds. The diagnostic performance of DL-measured AVC volume and Agaston score for classifying severe AVC was compared with that of each reader's assessment.

RESULTS

After applying the DL algorithm, the Dice coefficient score was 0.807. In patients with AVC, accuracy of DL-measured AVC volume for AVC grading was 97.0 % with area under the curve (AUC) of 0.964 (95 % confidence interval [CI] 0.923-1) in the test set, which was better than the radiologist readers (accuracy 69.7 %-91.9 %, AUC 0.762-0.923) with manually measured AVC volume as ground truth. When manually measured AVC Agatston score was used as ground truth, accuracy of DL-measured AVC Agatston score for AVC grading was 92.9 % with AUC of 0.933 (95 % CI 0.885-0.981) in the test set, which was also better than the radiologist readers (accuracy 77.8-89.9 %, AUC 0.791-0.903).

CONCLUSIONS

DL-based automated AVC quantification may be comparable with manual measurements. The diagnostic performance of the DL-measured AVC volume and Agatston score for classification of severe AVC outperforms radiologist readers.

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.

Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis

Cardiac computed tomography angiography (CCTA) is widely used as a diagnostic tool for evaluation of coronary artery disease (CAD). Despite the excellent capability to rule-out CAD, CCTA may overestimate the degree of stenosis; furthermore, CCTA analysis can be time consuming, often requiring advanced postprocessing techniques. In consideration of the most recent ESC guidelines on CAD management, which will likely increase CCTA volume over the next years, new tools are necessary to shorten reporting time and improve the accuracy for the detection of ischemia-inducing coronary lesions. The application of artificial intelligence (AI) may provide a helpful tool in CCTA, improving the evaluation and quantification of coronary stenosis, plaque characterization, and assessment of myocardial ischemia. Furthermore, in comparison with existing risk scores, machine-learning algorithms can better predict the outcome utilizing both imaging findings and clinical parameters. Medical AI is moving from the research field to daily clinical practice, and with the increasing number of CCTA examinations, AI will be extensively utilized in cardiac imaging. This review is aimed at illustrating the state of the art in AI-based CCTA applications and future clinical scenarios.

Coronary 18F-Fluoride Uptake and Progression of Coronary Artery Calcification

Supplemental Digital Content is available in the text.

Background

Positron emission tomography (PET) using ¹⁸F-sodium fluoride (¹⁸F-fluoride) to detect microcalcification may provide insight into disease activity in coronary atherosclerosis. This study aimed to investigate the relationship between ¹⁸F-fluoride uptake and progression of coronary calcification in patients with clinically stable coronary artery disease.

Methods

Patients with established multivessel coronary atherosclerosis underwent ¹⁸F-fluoride PET-computed tomography angiography and computed tomography calcium scoring, with repeat computed tomography angiography and calcium scoring at one year. Coronary PET uptake was analyzed qualitatively and semiquantitatively in diseased vessels by measuring maximum tissue-to-background ratio. Coronary calcification was quantified by measuring calcium score, mass, and volume.

Results

In a total of 183 participants (median age 66 years, 80% male), 116 (63%) patients had increased ¹⁸F-fluoride uptake in at least one vessel. Individuals with increased ¹⁸F-fluoride uptake demonstrated more rapid progression of calcification compared with those without uptake (change in calcium score, 97 [39–166] versus 35 [7–93] AU; P<0.0001). Indeed, the calcium score only increased in coronary segments with ¹⁸F-fluoride uptake (from 95 [30–209] to 148 [61–289] AU; P<0.001) and remained unchanged in segments without ¹⁸F-fluoride uptake (from 46 [16–113] to 49 [20–115] AU; P=0.329). Baseline coronary ¹⁸F-fluoride maximum tissue-to-background ratio correlated with 1-year change in calcium score, calcium volume, and calcium mass (Spearman ρ=0.37, 0.38, and 0.46, respectively; P<0.0001 for all). At the segmental level, baseline ¹⁸F-fluoride activity was an independent predictor of calcium score at 12 months (P<0.001). However, at the patient level, this was not independent of age, sex, and baseline calcium score (P=0.50).

Conclusions

Coronary ¹⁸F-fluoride uptake identifies both patients and individual coronary segments with more rapid progression of coronary calcification, providing important insights into disease activity within the coronary circulation. At the individual patient level, total calcium score remains an important marker of disease burden and progression.

Registration:

URL: https://www.clinicaltrials.gov; Unique identifier: NCT02110303.

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

AIMS

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

METHODS AND RESULTS

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

CONCLUSION

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

Coronary flow impairment in asymptomatic patients with early stage type-2 diabetes: Detection by FFRCT

PURPOSE

To determine the occurrence of physiological significant coronary artery disease (CAD) by coronary CT angiography (CTA) derived fractional flow reserve (FFRCT) in asymptomatic patients with a new diagnosis (<1 year) of type-2 diabetes mellitus (T2DM).

METHODS

FFRCT-analysis was performed from standard acquired coronary CTA data sets. The per-patient minimum distal FFRCT-value (d-FFRCT) in coronary vessels (diameter ⩾1.8 mm) was registered. The threshold for categorizing FFRCT-analysis as abnormal was a d-FFRCT ⩽0.75. Total plaque volume and volumes of calcified plaque, non-calcified plaque, and low-density non-calcified plaque (LD-NCP) were assessed by quantitative plaque analysis.

RESULTS

Overall, 76 patients; age, mean (SD): 56 (11) years; males, n (%): 49(65), were studied. A total of 57% of patients had plaques. The d-FFRCT was ⩽0.75 in 12 (16%) patients. The d-FFRCT, median (IQR), was 0.84 (0.79-0.87). Median (range) d-FFRCT in patients with d-FFRCT ⩽0.75 was 0.70 (0.6-0.74). Patients with d-FFRCT⩽0.75 versus d-FFRCT >0.75 had numerically higher plaque volumes for all plaques components, although only significant for the LD-NCP component.

CONCLUSION

Every sixth asymptomatic patient with a new diagnosis of T2DM has hemodynamic significant CAD as evaluated by FFRCT. Flow impairment by FFRCT was associated with coronary plaque characteristics.

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

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

Coronary plaque burden in Turner syndrome a coronary computed tomography angiography study

Turner syndrome (TS) is associated with coronary artery disease (CAD), an important cause of premature death in TS. However, the determinants of CAD in women with TS remain unknown. In a cross-sectional study design, 168 women without clinical evidence of CAD (115 with TS and 53 without TS) were assessed for the presence and volume of subclinical CAD using coronary CT angiography. Karyotype, the presence of congenital heart defects and conventional cardiovascular risk factors were also registered. Comparative analyses were performed (1) between women with and without TS and (2) in the TS group, between women with and without subclinical CAD. The prevalence of CAD, in crude and adjusted analyses, was not increased for women with TS (crude prevalence: 40 [35%] in TS vs. 25 [47%] in controls, p = 0.12). The volume of atherosclerosis was not higher in women with TS compared with controls (median and interquartile range 0 [0-92] in TS vs. 0 [0-81]mm³ in controls, p = 0.29). Among women with TS, women with subclinical CAD were older (46 ± 13 vs. 37 ± 11 years, p < 0.001), had higher blood pressure (systolic blood pressure 129 ± 16 vs. 121 ± 16 mmHg, p < 0.05) and were more frequently diagnosed with type 2 diabetes (5 [13%] vs. 2 [3%], p < 0.05). Karyotype or congenital heart defects were not associated with subclinical CAD. Some women with TS show early signs of CAD, however overall, not more than women without TS. Conventional cardiovascular risk factors were the principal determinants of CAD also in TS, and CAD prevention strategies should be observed.ClinicalTrial.gov Identifier: NCT01678261 ( https://clinicaltrials.gov/ct2/show/NCT01678261 ).

Low-Attenuation Noncalcified Plaque on Coronary Computed Tomography Angiography Predicts Myocardial Infarction: Results From the Multicenter SCOT-HEART Trial (Scottish Computed Tomography of the HEART)

BACKGROUND

The future risk of myocardial infarction is commonly assessed using cardiovascular risk scores, coronary artery calcium score, or coronary artery stenosis severity. We assessed whether noncalcified low-attenuation plaque burden on coronary CT angiography (CCTA) might be a better predictor of the future risk of myocardial infarction.

METHODS

In a post hoc analysis of a multicenter randomized controlled trial of CCTA in patients with stable chest pain, we investigated the association between the future risk of fatal or nonfatal myocardial infarction and low-attenuation plaque burden (% plaque to vessel volume), cardiovascular risk score, coronary artery calcium score or obstructive coronary artery stenoses.

RESULTS

In 1769 patients (56% male; 58±10 years) followed up for a median 4.7 (interquartile interval, 4.0-5.7) years, low-attenuation plaque burden correlated weakly with cardiovascular risk score (r=0.34; P<0.001), strongly with coronary artery calcium score (r=0.62; P<0.001), and very strongly with the severity of luminal coronary stenosis (area stenosis, r=0.83; P<0.001). Low-attenuation plaque burden (7.5% [4.8-9.2] versus 4.1% [0-6.8]; P<0.001), coronary artery calcium score (336 [62-1064] versus 19 [0-217] Agatston units; P<0.001), and the presence of obstructive coronary artery disease (54% versus 25%; P<0.001) were all higher in the 41 patients who had fatal or nonfatal myocardial infarction. Low-attenuation plaque burden was the strongest predictor of myocardial infarction (adjusted hazard ratio, 1.60 (95% CI, 1.10-2.34) per doubling; P=0.014), irrespective of cardiovascular risk score, coronary artery calcium score, or coronary artery area stenosis. Patients with low-attenuation plaque burden greater than 4% were nearly 5 times more likely to have subsequent myocardial infarction (hazard ratio, 4.65; 95% CI, 2.06-10.5; P<0.001).

CONCLUSIONS

In patients presenting with stable chest pain, low-attenuation plaque burden is the strongest predictor of fatal or nonfatal myocardial infarction. These findings challenge the current perception of the supremacy of current classical risk predictors for myocardial infarction, including stenosis severity. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01149590.

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

PURPOSE

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

Spotty Calcium on Cervicocerebral Computed Tomography Angiography Associates With Increased Risk of Ischemic Stroke

Background and Purpose- Cervicocerebral vascular calcification on computed tomography angiography is a known sign of advanced atherosclerosis. However, the clinical significance of calcification pattern remains unclear. In this study, we aimed to investigate the potential association between spotty calcium and acute ischemic stroke. Methods- This study included patients with first-time nonlacunar ischemic stroke (N=50) confirmed by brain magnetic resonance imaging or nonenhanced head computed tomography, as well as control subjects with asymptomatic carotid atherosclerosis (N=50) confirmed by carotid ultrasonography. Subjects in both groups underwent contrast-enhanced cervicocerebral computed tomography angiography within a week after the initial imaging examination. Spotty calcification was evaluated at 11 arterial segments commonly affected by atherosclerosis along the carotid and vertebrobasilar circulation. Statistical analysis was performed comparing the frequency and spatial pattern of spotty calcification between the 2 groups. Results- Spotty calcification in the Stroke group was markedly more prevalent than that in the Control group (total SC count: 8.74±4.96 versus 1.84±1.82, P<0.001). The odds ratio (95% CI) for stroke was 2.49 (1.55-4.00) for spotty calcification at bilateral carotid bifurcation, 1.52 (1.13-2.04) at carotid siphon, and 1.98 (1.45-2.69) at all evaluated locations. A total number of 3 spotty calcifications were determined as the optimal cutoff threshold for increased risk of stroke. Spotty calcium showed significantly greater area under the receiver operating characteristics curve than total calcium volume irrespective of size (0.88 versus 0.77). Within the Stroke group, ipsilateral lateral side showed significantly more spotty calcium than the contralateral side (5.18±3.05 versus 3.56±2.67, P<0.001). Conclusions- Nonlacunar ischemia stroke was associated with markedly increased incidence of spotty calcification with a distinct spatial pattern on cervicocerebral computed tomography compared with subclinical atherosclerosis, suggesting the potential role of spotty calcification for improving the risk stratification for ischemic stroke.

Performance of a deep learning algorithm for the evaluation of CAD-RADS classification with CCTA

BACKGROUND AND AIMS

Artificial intelligence (AI) is increasing its role in diagnosis of patients with suspicious coronary artery disease. The aim of this manuscript is to develop a deep convolutional neural network (CNN) to classify coronary computed tomography angiography (CCTA) in the correct Coronary Artery Disease Reporting and Data System (CAD-RADS) category.

METHODS

Two hundred eighty eight patients who underwent clinically indicated CCTA were included in this single-center retrospective study. The CCTAs were stratified by CAD-RADS scores by expert readers and considered as reference standard. A deep CNN was designed and tested on the CCTA dataset and compared to on-site reading. The deep CNN analyzed the diagnostic accuracy of the following three Models based on CAD-RADS classification: Model A (CAD-RADS 0 vs CAD-RADS 1-2 vs CAD-RADS 3,4,5), Model 1 (CAD-RADS 0 vs CAD-RADS>0), Model 2 (CAD-RADS 0-2 vs CAD-RADS 3-5). Time of analysis for both physicians and CNN were recorded.

RESULTS

Model A showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 47%, 74%, 77%, 46% and 60%, respectively. Model 1 showed a sensitivity, specificity, negative predictive value, positive predictive value and accuracy of 66%, 91%, 92%, 63%, 86%, respectively. Conversely, Model 2 demonstrated the following sensitivity, specificity, negative predictive value, positive predictive value and accuracy: 82%, 58%, 74%, 69%, 71%, respectively. Time of analysis was significantly lower using CNN as compared to on-site reading (530.5 ± 179.1 vs 104.3 ± 1.4 sec, p=0.01) CONCLUSIONS: Deep CNN yielded accurate automated classification of patients with CAD-RADS.

Improved Evaluation of Lipid-Rich Plaque at Coronary CT Angiography: Head-to-Head Comparison with Intravascular US

Purpose

To improve the evaluation of low-attenuation plaque (LAP) by using semiautomated software and to assess whether the use of a proposed automated function (LAP editor) that excludes voxels adjacent to the outer vessel wall improves the relationship between LAP and the presence and size of the lipid-rich component (LRC) verified at intravascular US. At coronary CT angiography, quantification of LAP can improve risk stratification. Plaque, defined as the area between the vessel and the lumen wall, is prone to partial volume effects from the surrounding pericoronary adipose tissue.

Materials and Methods

The percentage of LAP (%LAP), defined as the percentage of noncalcified plaque with an attenuation value lower than 30 HU (LAP/total plaque volume) at greater than or equal to 0 mm (%LAP₀), greater than or equal to 0.1 mm (%LAP_0.1), greater than or equal to 0.3 mm (%LAP_0.3), greater than or equal to 0.5 mm (%LAP_0.5), and greater than or equal to 0.7 mm (%LAP_0.7) inward from the vessel wall boundaries, were quantified in 155 plaques in 90 patients who underwent coronary CT angiography before intravascular US. At intravascular US, the LRC was identified by using echo attenuation, and its size was measured by using the attenuation score (summed score/analysis length) based on the attenuation arc (1 = < 90°, 2 = 90° to < 180°, 3 = 180° to < 270°, 4 = 270°-360°) for every 1 mm.

Results

Use of LAP editing improved the ability for discriminating LRC (areas under receiver operating characteristic curve: 0.667 with %LAP₀, 0.713 with %LAP_0.1 [P < .001 for comparison with %LAP₀]), 0.778 with %LAP_0.3 [P < .001], 0.825 with %LAP_0.5 [P < .001], 0.802 with %LAP_0.7 [P = .002]). %LAP_0.5 had the strongest correlation (r = 0.612, P < .001) with LRC size, whereas %LAP₀ resulted in the weakest correlation (r = 0.307; P < .001).

Conclusion

Evaluation of LAP at coronary CT angiography can be significantly improved by excluding voxels that are adjacent to the vessel wall boundaries by 0.5 mm.Supplemental material is available for this article.© RSNA, 2019.

Future Directions in Coronary CT Angiography: CT-Fractional Flow Reserve, Plaque Vulnerability, and Quantitative Plaque Assessment

Coronary computed tomography angiography (CCTA) is a well-validated and noninvasive imaging modality for the assessment of coronary artery disease (CAD) in patients with stable ischemic heart disease and acute coronary syndromes (ACSs). CCTA not only delineates the anatomy of the heart and coronary arteries in detail, but also allows for intra- and extraluminal imaging of coronary arteries. Emerging technologies have promoted new CCTA applications, resulting in a comprehensive assessment of coronary plaques and their clinical significance. The application of computational fluid dynamics to CCTA resulted in a robust tool for noninvasive assessment of coronary blood flow hemodynamics and determination of hemodynamically significant stenosis. Detailed evaluation of plaque morphology and identification of high-risk plaque features by CCTA have been confirmed as predictors of future outcomes, identifying patients at risk for ACSs. With quantitative coronary plaque assessment, the progression of the CAD or the response to therapy could be monitored by CCTA. The aim of this article is to review the future directions of emerging applications in CCTA, such as computed tomography (CT)-fractional flow reserve, imaging of vulnerable plaque features, and quantitative plaque imaging. We will also briefly discuss novel methods appearing in the coronary imaging scenario, such as machine learning, radiomics, and spectral CT.

Volumes of coronary plaque disease in relation to body mass index, waist circumference, truncal fat mass and epicardial adipose tissue in patients with type 2 diabetes mellitus and controls

OBJECTIVES

Coronary atherosclerosis in patients with type 2 diabetes mellitus may be promoted by regional fat distribution. We investigated the association between anthropometric measures of obesity, truncal fat mass, epicardial adipose tissue and coronary atherosclerosis in asymptomatic patients and matched controls.

METHODS

We examined 44 patients and 59 controls [mean (standard deviation) age 64.4 ± 9.9 vs 61.8 ± 9.7, male 50% vs 47%, diabetes duration mean (standard deviation) 7.7 ± 1.5] with coronary computed tomography angiography. Coronary plaques were quantified as total, calcified, non-calcified and low-density non-calcified plaque volumes (mm³). Regional fat distribution was assessed by dual-energy X-ray absorptiometry, body mass index (kg/m²), waist circumference (cm) and epicardial fat volume (mm³). Endothelial function and systemic inflammation were evaluated by peripheral arterial tonometry (log transformed Reactive Hyperemia Index) and C-reactive protein (mg/L).

RESULTS

Body mass index and waist circumference (p < 0.02) were associated with coronary plaque volumes. Body mass index was associated with low-density non-calcified plaque volume after adjustment for age, sex and diabetes status (p < 0.01). Truncal fat mass (p > 0.51), waist circumference (p > 0.06) and epicardial adipose tissue (p > 0.17) were not associated with coronary plaque volumes in adjusted analyses.

CONCLUSION

Body mass index is associated with coronary plaque volumes in diabetic as well as non-diabetic individuals.

Standardized volumetric plaque quantification and characterization from coronary CT angiography: a head-to-head comparison with invasive intravascular ultrasound

OBJECTIVES

We sought to evaluate the accuracy of standardized total plaque volume (TPV) measurement and low-density non-calcified plaque (LDNCP) assessment from coronary CT angiography (CTA) in comparison with intravascular ultrasound (IVUS).

METHODS

We analyzed 118 plaques without extensive calcifications from 77 consecutive patients who underwent CTA prior to IVUS. CTA TPV was measured with semi-automated software comparing both scan-specific (automatically derived from scan) and fixed attenuation thresholds. From CTA, %LDNCP was calculated voxels below multiple LDNCP thresholds (30, 45, 60, 75, and 90 Hounsfield units [HU]) within the plaque. On IVUS, the lipid-rich component was identified by echo attenuation, and its size was measured using attenuation score (summed score ∕ analysis length) based on attenuation arc (1 = < 90°; 2 = 90-180°; 3 = 180-270°; 4 = 270-360°) every 1 mm.

RESULTS

TPV was highly correlated between CTA using scan-specific thresholds and IVUS (r = 0.943, p < 0.001), with no significant difference (2.6 mm³, p = 0.270). These relationships persisted for calcification patterns (maximal IVUS calcium arc of 0°, < 90°, or ≥ 90°). The fixed thresholds underestimated TPV (- 22.0 mm³, p < 0.001) and had an inferior correlation with IVUS (p < 0.001) compared with scan-specific thresholds. A 45-HU cutoff yielded the best diagnostic performance for identification of lipid-rich component, with an area under the curve of 0.878 vs. 0.840 for < 30 HU (p = 0.023), and corresponding %LDNCP resulted in the strongest correlation with the lipid-rich component size (r = 0.691, p < 0.001).

CONCLUSIONS

Standardized noninvasive plaque quantification from CTA using scan-specific thresholds correlates highly with IVUS. Use of a < 45-HU threshold for LDNCP quantification improves lipid-rich plaque assessment from CTA.

KEY POINTS

• Standardized scan-specific threshold-based plaque quantification from coronary CT angiography provides an accurate total plaque volume measurement compared with intravascular ultrasound. • Attenuation histogram-based low-density non-calcified plaque quantification can improve lipid-rich plaque assessment from coronary CT angiography.

Carotid plaque composition by CT angiography in asymptomatic subjects: a head-to-head comparison to ultrasound

OBJECTIVES

To describe carotid plaque composition by computed tomography angiography (CTA) in asymptomatic subjects and to compare this to carotid plaque assessment by ultrasound, coronary plaques by coronary CTA, and inflammatory biomarkers in plasma.

METHODS

Middle-aged asymptomatic men, n = 43, without known cardiovascular disease and diabetes were included. Plaques in coronary and carotid arteries were evaluated using CTA. Total plaque volumes and plaque composition were assessed by a validated plaque analysis software. The 60% centile cut point was used to divide the population into low or high carotid total plaque volumes. The occurrence of carotid plaques and intima-media thickness (IMT) was estimated by ultrasound.

RESULTS

Carotid plaque by ultrasound was undiagnosed in 13 of 28 participants (46%) compared to CTA. Participants having carotid plaques by ultrasound had significantly higher absolute volumes of all CTA-defined carotid plaque subtypes and a higher fraction of calcified plaque. A high carotid total plaque volume was independently associated with age (adjusted odds ratio (OR) 1.41 [95% confidence interval (CI) 1.14-1.74], p = 0.001), IMT (adjusted OR 2.26 [95% CI 1.10-4.65], p = 0.03), and D-dimer (adjusted OR 8.86 [95% CI 1.26-62.37], p = 0.03). All coronary plaque features were significantly higher in participants with a high carotid total plaque volume.

CONCLUSION

The occurrence of carotid plaques in asymptomatic individuals is underestimated by ultrasound compared to plaque assessment by CTA. Carotid plaque composition by CTA is different in individuals with and without carotid plaques by ultrasound.

KEY POINTS

• The occurrence of carotid plaques by ultrasound was underestimated in 46% of participants who had plaques by carotid CTA. • Participants with carotid plaques by ultrasound had higher volumes of all plaque subtypes and a higher calcified plaque component as determined by carotid CTA compared to participants without carotid plaques by ultrasound. • A high carotid total plaque volume was independently associated with age, intima-media thickness, and D-dimer.

Deep learning-based stenosis quantification from coronary CT Angiography

BACKGROUND

Coronary computed tomography angiography (CTA) allows quantification of stenosis. However, such quantitative analysis is not part of clinical routine. We evaluated the feasibility of utilizing deep learning for quantifying coronary artery disease from CTA.

METHODS

A total of 716 diseased segments in 156 patients (66 ± 10 years) who underwent CTA were analyzed. Minimal luminal area (MLA), percent diameter stenosis (DS), and percent contrast density difference (CDD) were measured using semi-automated software (Autoplaque) by an expert reader. Using the expert annotations, deep learning was performed with convolutional neural networks using 10-fold cross-validation to segment CTA lumen and calcified plaque. MLA, DS and CDD computed using deep-learning-based approach was compared to expert reader measurements.

RESULTS

There was excellent correlation between the expert reader and deep learning for all quantitative measures (r=0.984 for MLA; r=0.957 for DS; and r=0.975 for CDD, p<0.001 for all). The expert reader and deep learning method was not significantly different for MLA (median 4.3 mm2 for both, p=0.68) and CDD (11.6 vs 11.1%, p=0.30), and was significantly different for DS (26.0 vs 26.6%, p<0.05); however, the ranges of all the quantitative measures were within inter-observer variability between 2 expert readers.

CONCLUSIONS

Our deep learning-based method allows quantitative measurement of coronary artery disease segments accurately from CTA and may enhance clinical reporting.

Sex difference in fibrin clot lysability: Association with coronary plaque composition

INTRODUCTION

Fibrin clot lysability is associated with development of cardiovascular disease (CVD). We evaluated sex-differences in fibrin clot lysability and the association with coronary plaque composition determined by computed tomography angiography (CTA).

METHODS

Middle-aged citizens without known CVD were randomly selected from a national registry. A coronary CTA assessed volumes of calcified-, non-calcified-, low-density non-calcified-, and total- plaque using a validated plaque quantification software. A non-enhanced cardiac CT scan assessed the Agatston score. Fibrin structure properties were determined using turbidimetric methods. Plasma concentrations of C-reactive protein and fibrinogen were assessed.

RESULTS

138 individuals (71 women) participated. Men more frequently had coronary plaques compared to women, P < 0.05. Coronary plaque features were comparable between men and women, P > 0.05. Women with total plaque volume > 0 mm³ had lower fibrin clot lysability compared to women with total plaque volume = 0 mm³, adjusted difference [95% confidence interval] 10.28 [1.42-19.15], P = 0.02, and a fibrinogen-dependent lower fibrin clot lysability compared to men with and without coronary plaques, 6.82 [-2.67-16.31], P = 0.16, and 8.73 [-0.43-17.89], P = 0.06, respectively. Fibrinogen correlated with all the coronary plaque features (correlation coefficient r = 0.42-0.57) only in women with total plaque volume > 0 mm³, all P < 0.01.

CONCLUSION

Asymptomatic women with coronary plaques assessed by coronary CTA have reduced fibrin clot lysability compared to both women without coronary plaques and men, suggesting a sex-dependent link between coronary atherosclerosis and fibrin clot lysability.

Clinical feasibility of catheter-directed selective intracoronary computed tomography angiography using an extremely low dose of iodine in patients with coronary artery disease

OBJECTIVE

This study aimed to evaluate the clinical feasibility of catheter-directed selective computed tomography angiography (S-CTA) in patients with coronary artery disease (CAD).

METHODS

We prospectively enrolled 65 patients diagnosed with CAD who underwent conventional computed tomography angiography (C-CTA). C-CTA was performed with 60-90 mL of contrast medium (370 mg iodine/mL), whereas S-CTA was performed with 15 mL of contrast medium and 17.19 mg iodine/mL. Luminal enhancement range, homogeneity of luminal enhancement, image quality, plaque volume (PV), and percent aggregate plaque volume (%APV) were measured. Paired Student's t test, Wilcoxon rank-sum test, and Pearson's correlation coefficient were used to compare two methods.

RESULTS

Luminal enhancement was significantly higher on S-CTA than on C-CTA (324.4 ± 8.0 Hounsfield unit (HU) vs. 312.0 ± 8.0 HU, p < 0.0001 in the per-vessel analysis). Transluminal attenuation gradient showed a significantly slower reduction pattern on S-CTA than on C-CTA (-0.65 HU/10 mm vs. -0.89 HU/10 mm, p < 0.0001 in the per-vessel analysis). Image noise was significantly lower on S-CTA than on C-CTA (39.6 ± 10.0 HU vs. 43.9 ± 9.4 HU, p < 0.0001). There was excellent correlation between S-CTA and C-CTA with respect to PV and %APV (r = 0.99, r = 0.98, respectively).

CONCLUSIONS

S-CTA might be useful in facilitating atherosclerotic plaque analysis and providing guidance for complex lesions such as chronic total occlusion, particularly in cases in which on-site procedure planning is required.

KEY POINTS

• Selective computed tomography angiography (S-CTA) can serve as an intraprocedural computed tomography angiography protocol. • S-CTA was performed with low dose of iodine compared with conventional computed tomography angiography. • S-CTA enables on-site atherosclerotic plaque analysis.

An automatic multi-class coronary atherosclerosis plaque detection and classification framework

Detection of different classes of atherosclerotic plaques is important for early intervention of coronary artery diseases. However, previous methods focused either on the detection of a specific class of coronary plaques or on the distinction between plaques and normal arteries, neglecting the classification of different classes of plaques. Therefore, we proposed an automatic multi-class coronary atherosclerosis plaque detection and classification framework. Firstly, we retrieved the transverse cross sections along centerlines from the computed tomography angiography. Secondly, we extracted the region of interests based on coarse segmentation. Thirdly, we extracted a random radius symmetry (RRS) feature vector, which incorporates multiple descriptions into a random strategy and greatly augments the training data. Finally, we fed the RRS feature vector into the multi-class coronary plaque classifier. In experiments, we compared our proposed framework with other methods on the cross sections of Rotterdam Coronary Datasets, including 729 non-calcified plaques, 511 calcified plaques, and 546 mixed plaques. Our RRS with support vector machine outperforms the intensity feature vector and the random forest classifier, with the average precision of 92.6 ± 1.9% and average recall of 94.3 ± 2.1%. The proposed framework provides a computer-aided diagnostic method for multi-class plaque detection and classification. Graphical abstract Diagram of the proposed automatic multi-class coronary atherosclerosis plaque detection and classification framework. ᅟ.

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

Aims

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

Methods and results

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

Conclusion

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

Multicenter AIDS Cohort Study Quantitative Coronary Plaque Progression Study: rationale and design

BACKGROUND AND AIM

The association of HIV with coronary atherosclerosis has been established; however, the progression of coronary atherosclerosis over time among participants with HIV is not well known. The Multicenter AIDS Cohort Study Quantitative Coronary Plaque Progression Study is a large prospective multicenter study quantifying progression of coronary plaque assessed by serial coronary computed tomography angiography (CTA).

PATIENTS AND METHODS

HIV-infected and uninfected men who were enrolled in the Multicenter AIDS Cohort Study Cardiovascular Substudy were eligible to complete a follow-up contrast coronary CTA 3-6 years after baseline. We measured coronary plaque volume and characteristics (calcified and noncalcified plaque including fibrous, fibrous-fatty, and low attenuation) and vulnerable plaque among HIV-infected and uninfected men using semiautomated plaque software to investigate the progression of coronary atherosclerosis over time.

CONCLUSION

We describe a novel, large prospective multicenter study investigating incidence, transition of characteristics, and progression in coronary atherosclerosis quantitatively assessed by serial coronary CTAs among HIV-infected and uninfected men.