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

The association between the triglyceride-glucose index and vulnerable plaques in patients with type 2 diabetes mellitus: insights from coronary computed tomography angiography

BACKGROUND

The triglyceride‒glucose index (TyG index) has been verified to be a useful predictor of insulin resistance (IR), and is associated with the occurrence of acute coronary syndrome (ACS). However, the effect of the TyG index on vulnerable plaques (VP), which were identified when at least two high-risk features are present within the same lesion, in type 2 diabetes mellitus (T2DM) patients is not fully understood. This study aimed to explore the association between the TyG index and the presence of VP.

METHODS

We retrospectively enrolled 2056 T2DM patients who underwent coronary computed tomography angiography (CCTA) examinations at West China Hospital from February 2017 to February 2022. These patients were divided into four groups on the basis of the quartiles of the TyG index. The high-risk coronary plaque features, vulnerable plaques, plaque type, coronary artery stenosis, segment involvement score (SIS), segment stenosis score (SSS) and multivessel disease (MVD) based on CCTA data were evaluated and compared among the four groups.

RESULTS

Patients with a higher TyG index had more noncalcified and mixed plaques, high-risk plaque features, vulnerable plaques and fewer calcified plaques (P < 0.05 for all). The proportion of patients with high-risk plaque features, including low-attenuation noncalcified plaques, positive remodeling and "napkin ring" sign was associated with the TyG index (P for trend < 0.05 for all). Multivariate analysis revealed that the TyG index was significantly associated with vulnerable plaques in T2DM patients [OR = 1.23 (95% CI 1.00-1.51), P = 0.046]. Subgroup analysis revealed that the association between the TyG index and vulnerable plaques varied with age and the prevalence of cardiovascular (CVD) symptoms, even after controlling for confounding factors (P for interaction < 0.05 for both).

CONCLUSION

The TyG index was independently associated with vulnerable plaques of the coronary artery among patients with T2DM. The TyG index could be regarded as a marker to reduce the incidence of cardiovascular events in the targeted population of T2DM patients.

Performance of large language models for CAD-RADS 2.0 classification derived from cardiac CT reports

BACKGROUND

The Coronary Artery Disease-Reporting and Data System (CAD-RADS) 2.0 offers standardized guidelines for interpreting coronary artery disease in cardiac CT. Accurate and consistent CAD-RADS 2.0 scoring is crucial for comprehensive disease characterization and clinical decision-making. This study investigates the capability of large language models (LLMs) to autonomously generate CAD-RADS 2.0 scores from cardiac CT reports.

METHODS

A dataset of cardiac CT reports was created to evaluate the performance of several state-of-the-art LLMs in generating CAD-RADS 2.0 scores via in-context learning. The tested models comprised GPT-3.5, GPT-4o, Mistral 7b, Mixtral 8 ​× ​7b, Llama3 8b, Llama3 8b with a 64k context length, and Llama3 70b. The generated scores from each model were compared to the ground truth, which was provided by two board-certified cardiothoracic radiologists in consensus based on the reports.

RESULTS

The final set comprised 200 cardiac CT reports. GPT-4o and Llama3 70b achieved the highest accuracy in generating full CAD-RADS 2.0 scores including all modifiers with a performance rate of 93 ​% and 92.5 ​%, respectively, followed by Mixtral 8 ​× ​7b with 78 ​%. In contrast, older LLMs, such as Mistral 7b and GPT-3.5 performed poorly (16 ​%) and Llama3 8b demonstrated intermediate results with an accuracy of 41.5 ​%.

CONCLUSION

LLMs enhanced with in-context learning are capable of autonomously generating CAD-RADS 2.0 scores for cardiac CT reports with excellent accuracy, potentially enhancing both the efficiency and consistency of cardiac CT reporting. Open-source models not only deliver competitive accuracy but also present the benefit of local hosting, mitigating concerns around data security.

Multimodal prediction of major adverse cardiovascular events in hypertensive patients with coronary artery disease: integrating pericoronary fat radiomics, CT-FFR, and clinicoradiological features

PURPOSE

People with both hypertension and coronary artery disease (CAD) are at a significantly increased risk of major adverse cardiovascular events (MACEs). This study aimed to develop and validate a combination model that integrates radiomics features of pericoronary adipose tissue (PCAT), CT-derived fractional flow reserve (CT-FFR), and clinicoradiological features, which improves MACE prediction within two years.

MATERIALS AND METHODS

Coronary-computed tomography angiography data were gathered from 237 patients diagnosed with hypertension and CAD. These patients were randomly categorized into training and testing cohorts at a 7:3 ratio (165:72). The least absolute shrinkage and selection operator logistic regression and linear discriminant analysis method were used to select optimal radiomics characteristics. The predictive performance of the combination model was assessed through receiver operating characteristic curve analysis and validated via calibration, decision, and clinical impact curves.

RESULTS

The results reveal that the combination model (Radiomics.

CLINICAL

Imaging) improves the discriminatory ability for predicting MACE. Its predictive efficacy is comparable to that of the Radiomics.Imaging model in both the training (0.886 vs. 0.872) and testing cohorts (0.786 vs. 0.815), but the combination model exhibits significantly improved specificity, accuracy, and precision. Decision and clinical impact curves further confirm the use of the combination prediction model in clinical practice.

CONCLUSIONS

The combination prediction model, which incorporates clinicoradiological features, CT-FFR, and radiomics features of PCAT, is a potential biomarker for predicting MACE in people with hypertension and CAD.

Fractional Flow Reserve Relates Stronger to Coronary Plaque Burden Than Nonhyperemic Pressure Indexes

BACKGROUND

The relationship between fractional flow reserve (FFR), resting full-cycle ratio (RFR), instantaneous wave-free ratio (iFR), resting distal pressure/aortic pressure (Pd/Pa), and plaque burden as well as phenotype requires further elucidation.

METHODS AND RESULTS

In this single-center cohort study, patients with suspected coronary artery disease who underwent invasive coronary angiography, including routine hyperemic (FFR) and nonhyperemic invasive pressure (Pd/Pa and iFR or RFR) interrogation and computed coronary tomography angiography were prospectively enrolled. Computed coronary tomography angiography was used to assess percentage atheroma volume (PAV), positive remodeling, and low-attenuation plaque.

Among 241 patients with 556 vessels, FFR correlated stronger to PAV compared with Pd/Pa (r=-0.56; versus r=-0.43; P<0.01) and iFR/RFR (r=-0.47; P=0.04). Vessels with FFR and Pd/Pa discordancy showed higher PAV in case of abnormal FFR (34% versus 14%; P<0.01), whereas vessels with FFR and iFR/RFR discordancy showed similar PAV levels. FFR and iFR/RFR, but not Pd/Pa, were independently associated with the presence of low-attenuation plaque (β, -0.03, P<0.01; β, -0.03, P=0.01; and β, -0.02, P=0.10, respectively). None of the invasive pressure measurements was independently associated with positive remodeling. Pressure index discordancy was not associated with positive remodeling or low-attenuation plaque.

CONCLUSIONS

FFR correlated stronger to plaque burden, as defined by PAV, than nonhyperemic pressure indexes. For plaque phenotype, both FFR and iFR/RFR were independently associated with low-attenuation plaque, whereas none of the invasive pressure indexes was associated with positive remodeling.

Characterising high-risk plaque on cardiac CT

Coronary computed tomography angiography (CCTA) is a well-established and reliable non-invasive imaging modality that provides a comprehensive assessment of coronary artery anatomy and luminal stenosis due to atherosclerosis. Owing to advances in CCTA software and technology, the composition and morphology of coronary plaque can be accurately evaluated. Adverse features which identify plaque as being high-risk or 'vulnerable' can provide a personalised cardiovascular risk assessment over and above stenosis severity. High-risk plaque features on CCTA include spotty calcification, low attenuation plaque, positive remodelling and the napkin ring sign. However, it can be challenging to characterise high-risk plaque accurately on CCTA, and as such, education and experience are required. In this pictorial essay, a comprehensive visual guide to high-risk plaque features on CCTA is provided, with clear examples and challenging cases that highlight common pitfalls. It is important for expert readers to properly identify these features given their association with adverse outcomes and potential future implications on intensive goal-directed medical therapy.

Coronary Plaque Quantification with Ultrahigh-Spatial-Resolution Photon-counting Detector CT: Intraindividual Comparison with Energy-integrating Detector CT

Background Other than enhancing the accuracy of stenosis measurements, the improved spatial resolution of photon-counting detector (PCD) CT may have an impact on quantitative plaque assessment at coronary CT angiography (CCTA). Purpose To evaluate the effect of PCD CT on coronary plaque quantification and characterization compared with that of energy-integrating detector (EID) CT. Materials and Methods Consecutive participants undergoing clinically indicated CCTA at EID CT (192 × 0.6-mm collimation) were enrolled to undergo ultrahigh-spatial-resolution (UHR) PCD CT (120 × 0.2-mm collimation) within 30 days. PCD CT was performed using equivalent or lower CT dose index and equivalent contrast media volume as the clinical scan. Total, calcified, fibrotic, and low-attenuation coronary plaque volumes were quantified and compared between scanners. Intra- and interreader reproducibility was assessed for both systems. Results A total of 164 plaques from 48 participants were segmented on both scans. Total plaque volume was lower at PCD CT compared with EID CT (723.5 mm3 [IQR, 500.6-1184.7 mm3] vs 1084.7 mm3 [IQR, 710.7-1609.8 mm3]; P < .001). UHR-based segmentations produced lower fibrotic (325.4 mm3 [IQR, 151.7-519.2 mm3] vs 627.7 mm3 [IQR, 385.8-795.1 mm3], respectively; P < .001) and higher low-attenuation plaque volumes (72.1 mm3 [IQR, 38.6-161.9 mm3] vs 58.1 mm3 [IQR, 23.4-102.3 mm3], respectively; P = .004) than EID CT-based measurements. Calcified plaque volumes did not differ significantly between PCD CT and EID CT (344.5 mm3 [IQR, 174.3-605.7 mm3] vs 342.1 mm3 [IQR, 180.4-607.5 mm3], respectively; P = .13). Total, calcified, and fibrotic plaque volumes demonstrated excellent agreement between repeated measurements and between readers for both PCD CT and EID CT (all intraclass correlation coefficients [ICCs] > 0.90). Whereas low-attenuation plaque volume had strong intrareader (ICC, 0.84; 95% CI: 0.57, 0.94) and interreader (ICC, 0.92; 95% CI: 0.81, 0.97) agreements for PCD CT, EID CT showed only moderate (ICC, 0.62; 95% CI: 0.11, 0.86) and poor (ICC, 0.47; 95% CI: 0.01, 0.79) intrareader and interreader reproducibility. Conclusion Compared with EID CT, PCD CT UHR imaging reduced segmented coronary plaque volume by nearly one-third and improved reproducibility of low-attenuation plaque measurements. © RSNA, 2025 Supplemental material is available for this article.

QUIET WARRIOR - Rationale and design: An ancillary study to the Women's IschemiA TRial to Reduce Events in Nonobstructive CAD (WARRIOR)

Background

Cardiovascular disease is the leading cause of death among women in the US, predominantly due to ischemic heart disease (IHD). There is a notable deficiency in therapies tailored for IHD in women, who often present with variable symptoms that delay diagnosis and treatment. In many cases, coronary angiography does not reveal obstructive coronary artery disease (CAD) despite increased risk for major adverse cardiac events (MACE) compared with sex and age-matched asymptomatic cohorts.

Objectives

The Women's IschemiA TRial to Reduce Events in Nonobstructive CAD (WARRIOR) evaluates intensive medical treatment for women with Ischemia with No Obstructive Coronary Arteries (INOCA). The QUIET WARRIOR sub-study aims to improve predictive tools for adverse outcomes by detailed analysis of Coronary Computed Tomography Angiography (CCTA) data and biorepository samples. These data will also uncover pathophysiological mechanisms associated with angina and MACE, improving predictive tools for symptomatic women with INOCA.

Methods

This ancillary study will analyze CCTA images from 600 WARRIOR subjects. It will assess clinical, social, and coronary artery variables, including plaque characteristics and markers of inflammation. Advanced imaging techniques and machine-learning models will be employed to quantify plaque features and predict clinical outcomes.

Expected results

The study aims to elucidate associations between CCTA-derived plaque characteristics, ischemic symptoms, and MACE. Anticipated findings include correlations of specific plaque attributes with angina severity and novel insights into inflammatory markers. Socioeconomic variables will also be examined for their impact on cardiovascular risk.

Conclusion

The QUIET WARRIOR sub-study will advance the understanding of INOCA in women, integrating clinical, imaging, and socioeconomic data to enhance risk prediction and guide personalized therapeutic strategies. This research will address critical gaps in managing nonobstructive CAD, promoting more equitable cardiovascular care.

Perspectives in the Diagnosis, Clinical Impact, and Management of the Vulnerable Plaque

Coronary artery disease is a highly prevalent disease that constitutes the leading cause of mortality worldwide. Acute coronary syndromes are the most devastating form of presentation of coronary disease, involving the acute formation of a thrombus within the coronary vessel lumen, further leading to flow limitation and diminished myocardial perfusion. Vulnerable plaques, which are characterized by thin-cap fibroatheroma, a large lipid pool, and macrophage infiltration and spotty calcification of the cap, pose a higher risk of coronary events despite not being flow-limiting. Iterations in intravascular imaging and coronary computed tomography have largely increased the ability to detect and define vulnerable plaques, and its clinical impact in early- and mid-term outcomes has been confirmed in several studies. In this review, we aimed to revise the current concept of vulnerable coronary plaque and its repercussion, to summarize the main pharmacological approaches for its management, and to provide an updated overview of the available evidence on preventive percutaneous interventional strategies in this clinical setting.

PlaqueViT: a vision transformer model for fully automatic vessel and plaque segmentation in coronary computed tomography angiography

OBJECTIVES

To develop and evaluate a deep learning model for segmentation of the coronary artery vessels and coronary plaques in coronary computed tomography angiography (CCTA).

MATERIALS AND METHODS

CCTA image data from the Swedish CardioPulmonary BioImage Study (SCAPIS) was used for model development (n = 463 subjects) and testing (n = 123) and for an interobserver study (n = 65). A dataset from Linköping University Hospital (n = 28) was used for external validation. The model's ability to detect coronary artery disease (CAD) was tested in a separate SCAPIS dataset (n = 684). A deep ensemble (k = 6) of a customized 3D vision transformer model was used for voxelwise classification. The Dice coefficient, the average surface distance, Pearson's correlation coefficient, analysis of segmented volumes by intraclass correlation coefficient (ICC), and agreement (sensitivity and specificity) were used to analyze model performance.

RESULTS

PlaqueViT segmented coronary plaques with a Dice coefficient = 0.55, an average surface distance = 0.98 mm and ICC = 0.93 versus an expert reader. In the interobserver study, PlaqueViT performed as well as the expert reader (Dice coefficient = 0.51 and 0.50, average surface distance = 1.31 and 1.15 mm, ICC = 0.97 and 0.98, respectively). PlaqueViT achieved 88% agreement (sensitivity 97%, specificity 76%) in detecting any coronary plaque in the test dataset (n = 123) and 89% agreement (sensitivity 95%, specificity 83%) in the CAD detection dataset (n = 684).

CONCLUSION

We developed a deep learning model for fully automatic plaque detection and segmentation that identifies and delineates coronary plaques and the arterial lumen with similar performance as an experienced reader.

KEY POINTS

Question A tool for fully automatic and voxelwise segmentation of coronary plaques in coronary CTA (CCTA) is important for both clinical and research usage of the CCTA examination. Findings Segmentation of coronary artery plaques by PlaqueViT was comparable to an expert reader's performance. Clinical relevance This novel, fully automatic deep learning model for voxelwise segmentation of coronary plaques in CCTA is highly relevant for large population studies such as the Swedish CardioPulmonary BioImage Study.

The Impact of MAFLD on Coronary Plaque Characteristics and Physiologic Status: A Coronary CT Angiography Study

RATIONALE AND OBJECTIVES

Metabolic dysfunction-associated fatty liver disease (MAFLD) is linked to an increased risk of cardiovascular events. Our study sought to determine the impact of MAFLD on both the anatomy and function of coronary plaques.

MATERIALS AND METHODS

A total of 203 participants (including 728 plaques) with suspected coronary artery disease (CAD) who underwent coronary CT angiography (CCTA) and abdominal ultrasound were prospectively enrolled. Participants were divided into MAFLD and non-MAFLD groups. For each plaque, necrotic core plaque volume and fractional flow reserve derived from CT (FFRCT) were measured. Obstructive CAD, segment involvement score (SIS) >4, high-risk plaque (HRP) and FFRCT ≤ 0.8 were assessed.

RESULTS

Compared to non-MAFLD, necrotic core plaque volume was higher in MAFLD at both participant level (p < 0.001) and plaque level (p = 0.001). MAFLD had a higher prevalence of obstructive CAD, SIS >4, HRP and FFRCT ≤ 0.8 at participant level (obstructive CAD: 35.9% vs 21.6%, p = 0.026; SIS >4: 39.7% vs 17.6%, p < 0.001; HRP: 55.1% vs 29.6%, p < 0.001; FFRCT ≤0.8: 33.3% vs 15.2%, p = 0.002). In addition, MAFLD predicted the presence of obstructive CAD (adjusted OR: 2.44; 95% CI: 1.22-4.87; p = 0.011), SIS >4 (adjusted OR: 3.64; 95% CI: 1.78-7.46; p < 0.001), HRP (adjusted OR: 2.52; 95% CI: 1.37-4.63; p = 0.003) and FFRCT ≤ 0.8 (adjusted OR: 3.53; 95% CI: 1.65-7.57; p = 0.001) independent of traditional cardiovascular risk factors.

CONCLUSION

MAFLD is associated with CCTA derived plaque characteristics, including the severity and extent of CAD, HRP, as well as physiologic status, independent of traditional risk factors.

The Prognostic Significance of the Characteristics of Atherosclerotic Plaques Left after Percutaneous Coronary Intervention in the Development of Cardiovascular Events in Patients With Acute Coronary Syndrome According to Computed Tomographic Angiography of the Coronary Arteries

AIM

To determine the characteristics of atherosclerotic plaques (ASP) remaining after percutaneous coronary intervention (PCI) for acute coronary syndrome (ACS), that are significantly associated with cardiovascular events (CVE), according to computed tomography angiography (CTA) data.

MATERIAL AND METHODS

CTA was performed in 249 ACS patients on days 3-7 of the disease (in 41 patients, on a 64-slice CT scanner, and in the rest, on a 320-slice CT scanner). CTA data of all patients were analyzed on a Vitrea workstation. Patients with at least one noncalcified atherosclerotic plaque were included.

RESULTS

During 39.1 [18.0; 57.4] months of follow-up (from 7 days to 128 months), 71 of 249 (28.5%) ACS patients had the primary endpoint (PEP), which included non-fatal myocardial infarction, unstable angina, cardiac death, PCI, and ischemic stroke. According to the univariate Cox analysis, 14 of 30 CTA characteristics of ASP turned out to be significant predictors of achieving the PEP: the number of involved arteries (HR=1.314, CI: 1.06-1.628, p=0.013, C=0.59); the total length of ASPs (HR=1.013, CI: 1.005-1.022, p=0.002, C=0.62); the number of ASPs with obstructive stenosis (HR=1.286, CI: 1.095-1.509, p=0.002, C=0.61); the minimum density (HR=0.968, CI: 0.949-0.987, p=0.001, C=0.64); a minimum density <30 HU (HR=2.695, CI: 1.495-4.869, p=0.0009, C=0.62); the number of ASPs with a minimum density <30 HU (HR=1.391, CI: 1.186-1.633, p=0.00005, C=0.64); the number of ASPs with a minimum density ≤46 HU (HR=1.211, CI: 1.043-1.407, p=0.012, C=0.58); the presence of a low-density area <30 HU (HR=2.387, CI: 1.389-4.101, p=0.001, C=0.57); the number of atherosclerotic plaques with a low-density area <30 HU (OR=1.912, CI: 1.317-2.775, p=0.001, C=0.57); the number of atherosclerotic plaques with spotty calcifications (HR=1.384, CI: 1.134-1.688, p=0.001, C=0.59); the maximum length (HR=1.014, CI: 1.001-1.028, p=0.041, C=0.61); the maximum stenosis (HR=1.018, CI: 1.002-1.033, p=0.025, C=0.61); the presence of a low-density area ≤46 HU (HR=2.049, CI: 1.24-3.386, p=0.005, C=0.57); the number of ASPs with a low-density area ≤46 HU (HR=1.643, CI: 1.191-2.265, p=0.002, C=0.58). [HR, hazard ratio; CI, 95% confidence interval; C, Harrell's C statistics]. According to the multivariate analysis, the first 10 of the listed CTA characteristics retained their prognostic significance, while the predictive significance was found for the "total plaque burden", a conditional characteristic we first proposed, which is the sum of the areas (burden) of all plaques identified by CTA in the patient.

CONCLUSION

14 CTA characteristics of ASPs in patients with ACS are significant predictors of future CVE, and 11 of them are independent of known risk factors.

Coronary CT Angiography in the Emergency Department: State of the Art and Future Perspectives

About 5% of annual access to emergency departments (EDs) and up to 25-30% of hospital admissions involve patients with symptoms suggestive of acute coronary syndrome (ACS). The process of evaluating and treating these patients is highly challenging for clinicians because failing to correctly identify an ACS can result in fatal or life-threatening consequences. However, about 50-60% of these patients who are admitted to the hospital because of chest pain are found to have no ACS. Coronary computed tomographic angiography (CCTA) has emerged as a proposed new frontline test for managing acute chest pain in the ED, particularly for patients with low-to-intermediate risk. This narrative review explores the potential of adopting an early CCTA-based approach in the ED, its significance in the era of high-sensitivity troponins, its application to high-risk patients and its prognostic value concerning atherosclerotic burden and high-risk plaque features. Additionally, we address clinical and technical issues related to CCTA use for triaging acute chest pain in the ED, as well as the role of functional testing. Finally, we aim to provide insight into future perspectives for the clinical application of CCTA in the ED.

Quantitative Plaque Characteristics/Pericoronary Fat Attenuation Index and Acute Coronary Syndrome in Patients With Stable Angina Pectoris

OBJECTIVE

Vascular inflammation affects acute coronary syndrome (ACS) occurrence in patients with stable angina. Coronary inflammation can be represented by the pericoronary fat attenuation index (FAI).This study investigated the quantitative prognostic value of plaque characteristics and FAI in patients with stable angina.

METHODS

Risk factors for ACS occurrence in patients with stable angina pectoris were retrospectively analyzed. The diagnostic value of FAI and plaque characteristics for ACS occurrence in these patients were determined; Kaplan-Meier curves were used to predict ACS event incidence.

RESULTS

After postpropensity score matching, data of 60 and 130 patients with and without ACS, respectively, were analyzed. Pericoronary FAI, lipid volume, and lipid percentage in the narrowest segment significantly improved ACS diagnosis in patients with stable angina. Luminal stenosis ≥50% and FAI >-88 Hounsfield units (HU) were independent risk factors for ACS occurrence in patients with stable angina. Perileft anterior descending artery (LAD) FAI >-88 HU better predicted ACS occurrence in patients with stable angina than did peri-LAD FAI ≤-88 HU.

CONCLUSIONS

In patients with stable angina, lipid volume and percentage and pericoronary FAI improved the diagnostic ability of luminal stenosis for ACS occurrence. Furthermore, peri-LAD FAI >-88 HU could predict ACS occurrence.

Evaluating Pericoronary Adipose Tissue Attenuation to Predict Cardiovascular Events: A Multicenter Study in East Asians

Background

Pericoronary adipose tissue attenuation (PCATA) is a novel imaging biomarker of pericoronary inflammation associated with coronary artery disease. Several studies have reported the usefulness of PCATA among people of European ethnicity; however, data are lacking concerning those of Asian ethnicity.

Objectives

This multicenter study aimed to evaluate the effect of PCATA on prognosis in East Asian patients.

Methods

Between August 2011 and December 2016, 2,172 patients underwent clinically indicated coronary computed tomography angiography (CTA) at 4 hospitals in Japan. Among them, 1,270 patients were analyzed. PCATA was evaluated using coronary CTA to measure pericoronary adipose tissue density surrounding the 3 major coronary arteries. The outcomes were composite cardiovascular events, including cardiovascular death and acute coronary syndrome; 33 cardiovascular events observed during a median follow-up of 6.0 years (Q1-Q3: 3.6-8.2 years).

Results

Right coronary artery (RCA)-PCATA was significantly higher in patients with cardiovascular events than in those without (-63.7 ± 8.9 HU vs -67.4 ± 9.1 HU, respectively; P = 0.021). High RCA-PCATA was significantly associated with cardiovascular events in a model that included the Hisayama risk score and adverse coronary CTA findings (HR: 1.55; 95% CI: 1.07-2.24; P = 0.019).

Conclusions

High RCA-PCATA showed significant association with future cardiovascular events after adjusting conventional risk factors and adverse coronary CTA findings in East Asian patients who underwent clinically indicated coronary CTA.

Clinical Validation of a Deep Learning Algorithm for Automated Coronary Artery Disease Detection and Classification Using a Heterogeneous Multivendor Coronary Computed Tomography Angiography Data Set

PURPOSE

We sought to clinically validate a fully automated deep learning (DL) algorithm for coronary artery disease (CAD) detection and classification in a heterogeneous multivendor cardiac computed tomography angiography data set.

MATERIALS AND METHODS

In this single-centre retrospective study, we included patients who underwent cardiac computed tomography angiography scans between 2010 and 2020 with scanners from 4 vendors (Siemens Healthineers, Philips, General Electrics, and Canon). Coronary Artery Disease-Reporting and Data System (CAD-RADS) classification was performed by a DL algorithm and by an expert reader (reader 1, R1), the gold standard. Variability analysis was performed with a second reader (reader 2, R2) and the radiologic reports on a subset of cases. Statistical analysis was performed stratifying patients according to the presence of CAD (CAD-RADS >0) and obstructive CAD (CAD-RADS ≥3).

RESULTS

Two hundred ninety-six patients (average age: 53.66 ± 13.65, 169 males) were enrolled. For the detection of CAD only, the DL algorithm showed sensitivity, specificity, accuracy, and area under the curve of 95.3%, 79.7%, 87.5%, and 87.5%, respectively. For the detection of obstructive CAD, the DL algorithm showed sensitivity, specificity, accuracy, and area under the curve of 89.4%, 92.8%, 92.2%, and 91.1%, respectively. The variability analysis for the detection of obstructive CAD showed an accuracy of 92.5% comparing the DL algorithm with R1, and 96.2% comparing R1 with R2 and radiology reports. The time of analysis was lower using the DL algorithm compared with R1 ( P < 0.001).

CONCLUSIONS

The DL algorithm demonstrated robust performance and excellent agreement with the expert readers' analysis for the evaluation of CAD, which also corresponded with significantly reduced image analysis time.

Cardiac CT in the context of value-based care

Cardiac computed tomography (CCT) is often used synonymously with coronary CT angiography (CCTA) and coronary artery calcium scoring (CACS), but also encompasses the use of CT for the assessment of structural, valvular, and congenital heart disease, and other cardiovascular pathology. This paper looks at the role of cardiac CT in the context of value-based care and predominantly focuses on the role of cardiac CT in the assessment of coronary artery disease (CAD), as this is where most of the clinical use and evidence of value can be found. Critical questions as to the defining of quality health care using cardiac CT are highllighted and the wider use of CT for the assessment of non-coronary disease is commented on towards the end of the manuscript but does not yet have the same level of health economic and value-based evidence.

Location-specific prognostic significance of plaque burden, stenosis, and plaque morphology in coronary artery disease

AIMS

To investigate the location-specific prognostic significance of plaque burden, diameter stenosis, and plaque morphology.

METHODS AND RESULTS

Patients without a documented cardiac history that underwent coronary computed tomography angiography (CCTA) for suspected coronary artery disease were included. Percentage atheroma volume (PAV), maximum diameter stenosis, and plaque morphology were assessed and classified into proximal, mid, or distal segments of the coronary tree. Major adverse cardiac events (MACE) were defined as death or non-fatal myocardial infarction. Among 2819 patients 267 events (9.5%) occurred during a median follow-up of 6.9 years. When adjusted for traditional risk factors and the presence of PAV in other locations, only proximal PAV was independently associated with MACE. However, PAV of the proximal segments was strongly correlated to PAV localized at the mid (R = 0.76) and distal segments (R = 0.74, P < 0.01 for both). When only adjusted for cardiovascular risk factors, the area under the curve (AUC) to predict MACE for proximal PAV was 0.73 (95% CI 0.69-0.76), which was similar compared with mid PAV (AUC 0.72, 95% CI 0.68-0.76) and distal PAV (AUC 0.72, 95% CI 0.68-0.76). Similar results were obtained using diameter stenosis instead of PAV. The presence of proximal low-attenuation plaque had borderline additional prognostic value.

CONCLUSION

Proximal PAV was the strongest predictor of MACE when adjusted for cardiovascular risk factors and plaque at other locations. However, when the presence of plaque was only adjusted for cardiovascular risk factors, proximal, mid, and distal plaque localization showed a similar predictive ability for MACE.

Characteristics of Atherosclerotic Plaques Left after Percutaneous Coronary Intervention in Patients with Acute Coronary Syndrome. Assessment According to Computed Tomographic Angiography of the Coronary Arteries

AIM

To evaluate characteristics of atherosclerotic plaques (ASP) remaining after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS) by coronary computed tomography angiography (CCTA).

MATERIAL AND METHODS

Among 249 patients (193 men) with ACS aged 58±10 years, 183 (73.5%) had myocardial infarction, 66 (26.5%) had unstable angina. CCTA was performed after PCI at 3-7 days after the onset of ACS according to the standard protocol: in 41 patients, on a 64-slice tomograph (Aquilion 64, Toshiba, Japan) and in 208 patients, on a 640-slice tomograph with 320 rows of detectors (Aquilion ONE Vision Edition, Toshiba, Japan). CCTA of all patients was performed on a Vitrea workstation. Patients with at least one non-calcified ASP were included.

RESULTS

Among all ASPs, non-calcified ASPs predominated, 609 of 785 (77.6%), including 400 soft and 209 combined ones. Signs of obstruction (stenosis ≥50%) were noted in 72.2% of non-calcified ASPs. ASPs were characterized by a pronounced burden, 69 [61.4; 74.2]%, and a low minimum density, 31 [23; 37] HU, which was consistent with mature plaques with a lipid core. Various signs of ASP instability were observed in 6-35.3% of cases. There were 2 [2;3] (1 to 6) affected coronary arteries (CAs) and 3 [2;4] (1 to 7) ASPs, including calcified ones, per patient. 77.7% of ASPs were located in the CA proximal and middle segments. Obstructive stenosis was detected in 92% of patients. The number of ASPs with obstructive stenosis ranged from 0 to 7 per patient, with a median of 2 [1;3]. In 44% of patients, stenosis was 70% or more. The maximum burden of non-calcified ASPs was high, 74.3±12.1%; their maximum and total length were 13.8±10.4 mm and 26.5±19.7 mm, respectively; and the ASP minimum density was low, 25 [17;32] HU. ASPs with a low-density area of ≤46 HU and ≤30 HU were detected in 24.9% and 14.8% of patients, respectively. Other CCTA signs of instability were quite common: punctate calcifications in 52.2% of patients, coronary positive remodeling in 37%, the presence of "ring-like enhancement" in 16.1%, an uneven plaque contour in 26.7%, and at least one sign of ASP instability in 73% of patients.

CONCLUSION

After PCI, patients with ACS still have rather many ASPs, including those with CCTA signs of instability, with stenosis >50%; more than a third of the plaques had stenosis >70%; the plaques were extended and localized mainly in the proximal and middle sections of the main CAs.

Computed tomography versus near-infrared spectroscopy for the assessment of coronary atherosclerosis

BACKGROUND

Coronary computed tomography angiography (CCTA) has been proposed as an alternative to intravascular imaging for assessing plaque pathology.

AIMS

We aimed to assess the efficacy of CCTA against near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS) in evaluating atheroma burden and composition and for guiding coronary interventions.

METHODS

Seventy patients with a chronic coronary syndrome were recruited and underwent CCTA and NIRS-IVUS. The imaging data were matched, and the estimations of lumen, vessel wall and plaque dimensions and composition of the two modalities were compared. The primary endpoint of the study was the efficacy of CCTA in detecting lipid-rich plaques identified by NIRS-IVUS. Secondary endpoints included the performance of CCTA in evaluating coronary artery pathology in the studied segments and its value in stent sizing, using NIRS-IVUS as the reference standard.

RESULTS

In total, 186 vessels were analysed. The attenuated plaque volume on CCTA had weak accuracy in detecting lipid-rich plaques (58%; p=0.029). Compared to NIRS-IVUS, CCTA underestimated the lumen volume (309.2 mm3 vs 420.4 mm3; p=0.001) and plaque dimensions (total atheroma volume 116.1 mm3 vs 292.8 mm3; p<0.001 and percentage atheroma volume 27.67% vs 41.06%; p<0.001) and overestimated the lipid component (lipid core burden index 48.6 vs 33.8; p=0.007). In the 86 lesions considered for revascularisation, CCTA underestimated the reference vessel area (8.16 mm2 vs 12.30 mm2; p<0.001) and overestimated the lesion length (23.5 mm vs 19.0 mm; p=0.029) compared to NIRS-IVUS.

CONCLUSIONS

CCTA has limited efficacy in assessing plaque composition and quantifying lumen and plaque dimensions and tissue types, which may potentially impact revascularisation planning.

Diagnostic Performance of AI-enabled Plaque Quantification from Coronary CT Angiography Compared with Intravascular Ultrasound

Purpose To assess the diagnostic performance of a coronary CT angiography (CCTA) artificial intelligence (AI)-enabled tool (AI-QCPA; HeartFlow) to quantify plaque volume, as compared with intravascular US (IVUS). Materials and Methods A retrospective subanalysis of a single-center prospective registry study was conducted in participants with ST-elevation myocardial infarction treated with primary percutaneous coronary intervention of the culprit vessel. Participants with greater than 50% stenosis in nonculprit vessels underwent CCTA, invasive coronary angiography, and IVUS of nonculprit lesion(s) between 2 and 40 days after primary percutaneous coronary intervention. Comparisons of plaque volumes obtained using AI-QCPA (HeartFlow) and IVUS were assessed using Spearman rank correlation (ρ) and Bland-Altman analysis. Results Thirty-three participants (mean age, 59.1 years ± 8.8 [SD]; 27 [82%] male and six [18%] female participants) and 67 vessels were included for analysis. There was strong agreement between AI-QCPA and IVUS in vessel (ρ = 0.94) and lumen volumes (ρ = 0.97). High agreement between AI-QCPA and IVUS was also found for total plaque volume (ρ = 0.92), noncalcified plaque (ρ = 0.91), and calcified plaque (ρ = 0.87). Bland-Altman analysis demonstrated AI-QCPA underestimated total plaque volume (-9.4 mm3) and calcified plaque (-11.4 mm3) and overestimated for noncalcified plaque (2.0 mm3) when compared with IVUS. Conclusion An AI-enabled automated plaque quantification tool for CCTA had high agreement with IVUS for quantifying plaque volume and characterizing plaque. Keywords: Coronary Plaque, Intravascular US, Coronary CT Angiography, Artificial Intelligence Supplemental material is available for this article. ClinicalTrials.gov registration no. NCT02926755 © RSNA, 2024.

Predicting major adverse cardiac events using radiomics nomogram of pericoronary adipose tissue based on CCTA: A multi-center study

BACKGROUND

The evolution of coronary atherosclerotic heart disease (CAD) is intricately linked to alterations in the pericoronary adipose tissue (PCAT). In recent epochs, characteristics of the PCAT have progressively ascended as focal points of research in CAD risk stratification and individualized clinical decision-making. Harnessing radiomic methodologies allows for the meticulous extraction of imaging features from these adipose deposits. Coupled with machine learning paradigms, we endeavor to establish predictive models for the onset of major adverse cardiovascular events (MACE).

PURPOSE

To appraise the predictive utility of radiomic features of PCAT derived from coronary computed tomography angiography (CCTA) in forecasting MACE.

METHODS

We retrospectively incorporated data from 314 suspected or confirmed CAD patients admitted to our institution from June 2019 to December 2022. An additional cohort of 242 patients from two external institutions was encompassed for external validation. The endpoint under consideration was the occurrence of MACE after a 1-year follow-up. MACE was delineated as cardiovascular mortality, newly diagnosed myocardial infarction, hospitalization (or re-hospitalization) for heart failure, and coronary target vessel revascularization occurring more than 30 days post-CCTA examination. All enrolled patients underwent CCTA scanning. Radiomic features were meticulously extracted from the optimal diastolic phase axial slices of CCTA images. Feature reduction was achieved through a composite feature selection algorithm, laying the groundwork for the radiomic signature model. Both univariate and multivariate analyses were employed to assess clinical variables. A multifaceted logistic regression analysis facilitated the crafting of a clinical-radiological-radiomic combined model (or nomogram). Receiver operating characteristic (ROC) curves, calibration, and decision curve analyses (DCA) were delineated, with the area under the ROC curve (AUCs) computed to gauge the predictive prowess of the clinical model, radiomic model, and the synthesized ensemble.

RESULTS

A total of 12 radiomic features closely associated with MACE were identified to establish the radiomic model. Multivariate logistic regression results demonstrated that smoking, age, hypertension, and dyslipidemia were significantly correlated with MACE. In the integrated nomogram, which amalgamated clinical, imaging, and radiomic parameters, the diagnostic performance was as follows: 0.970 AUC, 0.949 accuracy (ACC), 0.833 sensitivity (SEN), 0.981 specificity (SPE), 0.926 positive predictive value (PPV), and 0.955 negative predictive value (NPV). The calibration curve indicated a commendable concordance of the nomogram, and the decision curve analysis underscored its superior clinical utility.

CONCLUSIONS

The integration of radiomic signatures from PCAT based on CCTA, clinical indices, and imaging parameters into a nomogram stands as a promising instrument for prognosticating MACE events.

The Role of Cardiac Computed Tomography Angiography in Risk Stratification for Coronary Artery Disease

Coronary computed tomography angiography (CCTA) allows the assessment of the presence and severity of obstructive and nonobstructive atherosclerotic coronary artery disease. With software developments incorporating artificial intelligence-based automated image analysis along with improved spatial resolution of CT scanners, volumetric measurements of atherosclerotic plaque, detection of high-risk plaque features, and delineation of pericoronary adipose tissue density can now be readily and accurately evaluated for a given at-risk patient. Many of these expanded diagnostic measures have been shown to be prognostically useful for prediction of major adverse cardiac events. The incremental value of plaque quantification over diameter stenosis has yet to be thoroughly discovered in current studies. Furthermore, the physiological significance of lesions can also be assessed with CT-derived fractional flow reserve, myocardial CT perfusion, and more recently shear stress, potentially leading to selective invasive coronary angiography and revascularization. Along with these technological advancements, there has been additional high-quality evidence for CCTA including large randomized clinical trials supporting high-level recommendations from many international clinical practice guidelines. Current trials largely compare a CCTA vs functional testing strategy, yet there is minimal evidence on CCTA plaque-guided therapeutic trials to measure regression of atherosclerosis and prevention of major coronary artery disease events. In this review, we summarize current evidence on comprehensive risk assessment with CCTA and future directions.

Comparison of coronary CT angiography and invasive coronary angiography results

INTRODUCTION

Coronary artery disease (CAD) is a leading cause of death worldwide. Accurate diagnosis and management are critical. Non-invasive imaging, such as coronary computed tomography angiography (CCTA), is vital for early diagnosis and treatment planning. This study evaluates the accuracy of CAD-Reporting and Data System (CAD-RADS) scoring and the compatibility between CCTA and invasive coronary angiography (ICA) in patients suspected of having CAD.

MATERIALS AND METHODS

From January 1, 2022 to January 15, 2024, 214 patients suspected of CAD underwent both CCTA and ICA. CCTA artifacts led to the exclusion of 32 patients and 128 vessels, leaving 586 vessels for analysis. CAD-RADS scoring categorized coronary stenosis. Diagnostic performance was measured by specificity, sensitivity, accuracy, positive and negative predictive value (NPV). Extracardiac findings were analyzed with a wide field of view (FOV) during CCTA.

RESULTS

A total of 214 patients (67.3% male, median age 56) were examined. Hypertension, smoking, calcium score, and high-risk plaques correlated with CCTA and ICA CAD-RADS scores; calcium score also related to hypertension, smoking, diabetes, and dyslipidemia (p < 0.05). CCTA showed a sensitivity of 80.8% and NPV of 90.3% for detecting stenosis of 70% or more; for 50% stenosis, sensitivity was 93.5% and NPV 92.1%. Agreement between CCTA and ICA was excellent in bypass patients; stenosis detection in stented patients had 85.7% sensitivity and 96.2% NPV.

CONCLUSION

This study highlights the importance of CAD-RADS and CCTA in CAD diagnosis and treatment planning. CCTA effectively evaluates stents and grafts, emphasizing the benefits of extracardiac findings and a wide FOV.

Atherosclerosis quantification and cardiovascular risk: the ISCHEMIA trial

BACKGROUND AND AIMS

The aim of this study was to determine the prognostic value of coronary computed tomography angiography (CCTA)-derived atherosclerotic plaque analysis in ISCHEMIA.

METHODS

Atherosclerosis imaging quantitative computed tomography (AI-QCT) was performed on all available baseline CCTAs to quantify plaque volume, composition, and distribution. Multivariable Cox regression was used to examine the association between baseline risk factors (age, sex, smoking, diabetes, hypertension, ejection fraction, prior coronary disease, estimated glomerular filtration rate, and statin use), number of diseased vessels, atherosclerotic plaque characteristics determined by AI-QCT, and a composite primary outcome of cardiovascular death or myocardial infarction over a median follow-up of 3.3 (interquartile range 2.2-4.4) years. The predictive value of plaque quantification over risk factors was compared in an area under the curve (AUC) analysis.

RESULTS

Analysable CCTA data were available from 3711 participants (mean age 64 years, 21% female, 79% multivessel coronary artery disease). Amongst the AI-QCT variables, total plaque volume was most strongly associated with the primary outcome (adjusted hazard ratio 1.56, 95% confidence interval 1.25-1.97 per interquartile range increase [559 mm3]; P = .001). The addition of AI-QCT plaque quantification and characterization to baseline risk factors improved the model's predictive value for the primary outcome at 6 months (AUC 0.688 vs. 0.637; P = .006), at 2 years (AUC 0.660 vs. 0.617; P = .003), and at 4 years of follow-up (AUC 0.654 vs. 0.608; P = .002). The findings were similar for the other reported outcomes.

CONCLUSIONS

In ISCHEMIA, total plaque volume was associated with cardiovascular death or myocardial infarction. In this highly diseased, high-risk population, enhanced assessment of atherosclerotic burden using AI-QCT-derived measures of plaque volume and composition modestly improved event prediction.

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.

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

Importance

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

Objective

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

Design, Setting, and Participants

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

Exposures

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

Main Outcome and Measures

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

Results

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

Conclusions and Relevance

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

Charting the Unseen: How Non-Invasive Imaging Could Redefine Cardiovascular Prevention

Cardiovascular diseases (CVDs) remain a major global health challenge, leading to significant morbidity and mortality while straining healthcare systems. Despite progress in medical treatments for CVDs, their increasing prevalence calls for a shift towards more effective prevention strategies. Traditional preventive approaches have centered around lifestyle changes, risk factors management, and medication. However, the integration of imaging methods offers a novel dimension in early disease detection, risk assessment, and ongoing monitoring of at-risk individuals. Imaging techniques such as supra-aortic trunks ultrasound, echocardiography, cardiac magnetic resonance, and coronary computed tomography angiography have broadened our understanding of the anatomical and functional aspects of cardiovascular health. These techniques enable personalized prevention strategies by providing detailed insights into the cardiac and vascular states, significantly enhancing our ability to combat the progression of CVDs. This review focuses on amalgamating current findings, technological innovations, and the impact of integrating advanced imaging modalities into cardiovascular risk prevention, aiming to offer a comprehensive perspective on their potential to transform preventive cardiology.

Computed Tomography Angiography Identified High-Risk Coronary Plaques: From Diagnosis to Prognosis and Future Management

CT angiography has become, in recent years, a main evaluating modality for patients with coronary artery disease (CAD). Recent advancements in the field have allowed us to identity not only the presence of obstructive disease but also the characteristics of identified lesions. High-risk coronary atherosclerotic plaques are identified in CT angiographies via a number of specific characteristics and may provide prognostic and therapeutic implications, aiming to prevent future ischemic events via optimizing medical treatment or providing coronary interventions. In light of new evidence evaluating the safety and efficacy of intervening in high-risk plaques, even in non-flow-limiting disease, we aim to provide a comprehensive review of the diagnostic algorithms and implications of plaque vulnerability in CT angiography, identify any differences with invasive imaging, analyze prognostic factors and potential future therapeutic options in such patients, as well as discuss new frontiers, including intervening in non-flow-limiting stenoses and the role of CT angiography in patient stratification.

Advanced CT measures of coronary artery disease with intermediate stenosis in patients with severe aortic valve stenosis

BACKGROUND

Coronary artery disease (CAD) and severe aortic valve stenosis (AS) frequently coexist. While pre-transcatheter aortic valve replacement (TAVR) computed tomography angiography (CTA) allows to rule out obstructive CAD, interpreting hemodynamic significance of intermediate stenoses is challenging. This study investigates the incremental value of CT-derived fractional flow reserve (CT-FFR), quantitative coronary plaque characteristics (e.g., stenosis degree, plaque volume, and composition), and peri-coronary adipose tissue (PCAT) density to detect hemodynamically significant lesions among those with AS and CAD.

MATERIALS AND METHODS

We included patients with severe AS and intermediate coronary lesions (20-80% diameter stenosis) who underwent pre-TAVR CTA and invasive coronary angiogram (ICA) with resting full-cycle ratio (RFR) assessment between 08/16 and 04/22. CTA image analysis included assessment of CT-FFR, quantitative coronary plaque analysis, and PCAT density. Coronary lesions with RFR ≤ 0.89 indicated hemodynamic significance as reference standard.

RESULTS

Overall, 87 patients (age 77.9 ± 7.4 years, 38% female) with 95 intermediate coronary artery lesions were included. CT-FFR showed good discriminatory capacity (area under receiver operator curve (AUC) = 0.89, 95% confidence interval (CI) 0.81-0.96, p < 0.001) to identify hemodynamically significant lesions, superior to anatomical assessment, plaque morphology, and PCAT density. Plaque composition and PCAT density did not differ between lesions with and without hemodynamic significance. Univariable and multivariable analyses revealed CT-FFR as the only predictor for functionally significant lesions (odds ratio 1.28 (95% CI 1.17-1.43), p < 0.001). Overall, CT-FFR ≤ 0.80 showed diagnostic accuracy, sensitivity, and specificity of 88.4% (95%CI 80.2-94.1), 78.5% (95%CI 63.2-89.7), and 96.2% (95%CI 87.0-99.5), respectively.

CONCLUSION

CT-FFR was superior to CT anatomical, plaque morphology, and PCAT assessment to detect functionally significant stenoses in patients with severe AS.

CLINICAL RELEVANCE STATEMENT

CT-derived fractional flow reserve in patients with severe aortic valve stenosis may be a useful tool for non-invasive hemodynamic assessment of intermediate coronary lesions, while CT anatomical, plaque morphology, and peri-coronary adipose tissue assessment have no incremental or additional benefit. These findings might help to reduce pre-transcatheter aortic valve replacement invasive coronary angiogram.

KEY POINTS

• Interpreting the hemodynamic significance of intermediate coronary stenoses is challenging in pre-transcatheter aortic valve replacement CT. • CT-derived fractional flow reserve (CT-FFR) has a good discriminatory capacity in the identification of hemodynamically significant coronary lesions. • CT-derived anatomical, plaque morphology, and peri-coronary adipose tissue assessment did not improve the diagnostic capability of CT-FFR in the hemodynamic assessment of intermediate coronary stenoses.

Coronary Atherosclerotic Plaque Burden Assessment by Computed Tomography and Its Clinical Implications

Recent studies have demonstrated that coronary plaque burden carries greater prognostic value in predicting adverse atherosclerotic cardiovascular disease outcomes than myocardial ischemia, thereby challenging the existing paradigm. Advances in plaque quantification through both noncontrast and contrast-enhanced computed tomography (CT) methods have led to earlier and more cost-effective detection of coronary disease compared with traditional stress testing. The 2 principal techniques of noninvasive coronary plaque quantification assessment are coronary artery calcium scoring by noncontrast CT and coronary CT angiography, both of which correlate with disease burden on invasive angiography. Plaque quantification from these imaging modalities has shown utility in risk stratification and prognostication of adverse cardiovascular events, leading to increased incorporation into clinical practice guidelines and preventive care pathways. Furthermore, due to their expanding clinical value, emerging technologies such as artificial intelligence are being integrated into plaque quantification platforms, placing more advanced measures of plaque burden at the forefront of coronary plaque evaluation. In this review, we summarize recent clinical data on coronary artery calcium scoring and coronary CT angiography plaque quantification in the evaluation of adverse atherosclerotic cardiovascular disease in patients with and without chest pain, highlight how these methods compare to invasive quantification approaches, and directly compare the performance characteristics of coronary artery calcium scoring and coronary CT angiography.

Efficacy of Diagnostic Testing of Suspected Coronary Artery Disease: A Contemporary Review

BACKGROUND

Coronary artery disease (CAD) is a highly prevalent condition which can lead to myocardial ischemia as well as acute coronary syndrome. Early diagnosis of CAD can improve patient outcomes through guiding risk factor modification and treatment modalities.

SUMMARY

Testing for CAD comes with increased cost and risk; therefore, physicians must determine which patients require testing, and what testing modality will offer the most useful data to diagnose patients with CAD. Patients should have an initial risk stratification for pretest probability of CAD based on symptoms and available clinical data. Patients with a pretest probability less than 5% should receive no further testing, while patients with a high pretest probability should be considered for direct invasive coronary angiography. In patients with a pretest probability between 5 and 15%, coronary artery calcium score and or exercise electrocardiogram can be obtained to further risk stratify patients to low-risk versus intermediate-high-risk. Intermediate-high-risk patients should be tested with coronary computed tomography angiography (preferred) versus positron emission tomography or single photon emission computed tomography based on their individual patient characteristics and institutional availability.

KEY MESSAGES

This comprehensive review aimed to describe the available CAD testing modalities, detail their risks and benefits, and propose when each should be considered in the evaluation of a patient with suspected CAD.

BACKGROUND

Coronary artery disease (CAD) is a highly prevalent condition which can lead to myocardial ischemia as well as acute coronary syndrome. Early diagnosis of CAD can improve patient outcomes through guiding risk factor modification and treatment modalities.

SUMMARY

Testing for CAD comes with increased cost and risk; therefore, physicians must determine which patients require testing, and what testing modality will offer the most useful data to diagnose patients with CAD. Patients should have an initial risk stratification for pretest probability of CAD based on symptoms and available clinical data. Patients with a pretest probability less than 5% should receive no further testing, while patients with a high pretest probability should be considered for direct invasive coronary angiography. In patients with a pretest probability between 5 and 15%, coronary artery calcium score and or exercise electrocardiogram can be obtained to further risk stratify patients to low-risk versus intermediate-high-risk. Intermediate-high-risk patients should be tested with coronary computed tomography angiography (preferred) versus positron emission tomography or single photon emission computed tomography based on their individual patient characteristics and institutional availability.

KEY MESSAGES

This comprehensive review aimed to describe the available CAD testing modalities, detail their risks and benefits, and propose when each should be considered in the evaluation of a patient with suspected CAD.

Evaluating the American Heart Association/American College of Cardiology Guideline-Recommended and Contemporary Pretest Probability Models in a Mixed Asian Cohort: The Contribution of Coronary Artery Calcium

BACKGROUND

Most pretest probability (PTP) tools for obstructive coronary artery disease (CAD) were Western -developed. The most appropriate PTP models and the contribution of coronary artery calcium score (CACS) in Asian populations remain unknown. In a mixed Asian cohort, we compare 5 PTP models: local assessment of the heart (LAH), CAD Consortium (CAD2), risk factor-weighted clinical likelihood, the American Heart Association/American College of Cardiology and the European Society of Cardiology PTP and 3 extended versions of these models that incorporated CACS: LAH(CACS), CAD2(CACS), and the CACS-clinical likelihood.

METHODS AND RESULTS

The study cohort included 771 patients referred for stable chest pain. Obstructive CAD prevalence was 27.5%. Calibration, area under the receiver-operating characteristic curves (AUC) and net reclassification index were evaluated. LAH clinical had the best calibration (χ2 5.8; P=0.12). For CACS models, LAH(CACS) showed least deviation between observed and expected cases (χ2 37.5; P<0.001). There was no difference in AUCs between the LAH clinical (AUC, 0.73 [95% CI, 0.69-0.77]), CAD2 clinical (AUC, 0.72 [95% CI, 0.68-0.76]), risk factor-weighted clinical likelihood (AUC, 0.73 [95% CI: 0.69-0.76) and European Society of Cardiology PTP (AUC, 0.71 [95% CI, 0.67-0.75]). CACS improved discrimination and reclassification of the LAH(CACS) (AUC, 0.88; net reclassification index, 0.46), CAD2(CACS) (AUC, 0.87; net reclassification index, 0.29) and CACS-CL (AUC, 0.87; net reclassification index, 0.25).

CONCLUSIONS

In a mixed Asian cohort, Asian-derived LAH models had similar discriminatory performance but better calibration and risk categorization for clinically relevant PTP cutoffs. Incorporating CACS improved discrimination and reclassification. These results support the use of population-matched, CACS-inclusive PTP tools for the prediction of obstructive CAD.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

CLINICAL RELEVANCE STATEMENT

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

KEY POINTS

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

Hierarchical Auto-labeling of Coronary Arteries on CT Coronary Angiography Images

The auto-labeling of coronary artery segments plays an important role in the diagnosis of cardiovascular diseases. Due to the high degree of complexity and diversity in coronary artery structures, it is still a very challenging task after many years of exploration and study. In this paper, we propose a hierarchical scheme based on PointNet++ models and new topological structural features for automatic labeling of coronary artery segments. The inputs are 3D coronary artery centerline points extracted from CTCA images, and the outputs are the correspondent label indexes. The auto-labeling scheme include two stages: first stage is to identify the three main branches, LAD(LM), LCX and RCA. After that, utilizing the topological connectivity relationship with the three main branches, the indexes of sub-branches are identified in the second stage. We evaluated our method on a private clinical dataset. Experimental results show that the proposed method has achieved a satisfactory accuracy for clinical use.

Influencing factors and improvement methods of coronary artery plaque evaluation in CT

Accurate evaluation of the nature and composition of coronary plaque involves clinical follow-up and prognosis. Coronary CT angiography is the most commonly non-invasive method for plaque evaluation, however, the qualitative and quantitative evaluation of plaque based on CT value is inaccurate, due to the influence of luminal attenuation, tube voltage, parameter setting and the subjectivity.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Assessment of atherosclerotic plaque burden: comparison of AI-QCT versus SIS, CAC, visual and CAD-RADS stenosis categories

This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QCT) with qualitative approaches to atherosclerotic disease burden codified in the multisociety 2022 CAD-RADS 2.0 Expert Consensus. 105 patients who underwent cardiac computed tomography angiography (CCTA) for chest pain were evaluated by a blinded core laboratory through FDA-cleared software (Cleerly, Denver, CO) that performs AI-QCT through artificial intelligence, analyzing factors such as % stenosis, plaque volume, and plaque composition. AI-QCT plaque volume was then staged by recently validated prognostic thresholds, and compared with CAD-RADS 2.0 clinical methods of plaque evaluation (segment involvement score (SIS), coronary artery calcium score (CACS), visual assessment, and CAD-RADS percent (%) stenosis) by expert consensus blinded to the AI-QCT core lab reads. Average age of subjects were 59 ± 11 years; 44% women, with 50% of patients at CAD-RADS 1-2 and 21% at CAD-RADS 3 and above by expert consensus. AI-QCT quantitative plaque burden staging had excellent agreement of 93% (k = 0.87 95% CI: 0.79-0.96) with SIS. There was moderate agreement between AI-QCT quantitative plaque volume and categories of visual assessment (64.4%; k = 0.488 [0.38-0.60]), and CACS (66.3%; k = 0.488 [0.36-0.61]). Agreement between AI-QCT plaque volume stage and CAD-RADS % stenosis category was also moderate. There was discordance at small plaque volumes. With ongoing validation, these results demonstrate a potential for AI-QCT as a rapid, reproducible approach to quantify total plaque burden.

Coronary computed tomography angiography for clinical practice

Coronary artery disease (CAD) is a common condition caused by the accumulation of atherosclerotic plaques. It can be classified into stable CAD or acute coronary syndrome. Coronary computed tomography angiography (CCTA) has a high negative predictive value and is used as the first examination for diagnosing stable CAD, particularly in patients at intermediate-to-high risk. CCTA is also adopted for diagnosing acute coronary syndrome, particularly in patients at low-to-intermediate risk. Myocardial ischemia does not always co-exist with coronary artery stenosis, and the positive predictive value of CCTA for myocardial ischemia is limited. However, CCTA has overcome this limitation with recent technological advancements such as CT perfusion and CT-fractional flow reserve. In addition, CCTA can be used to assess coronary artery plaques. Thus, the indications for CCTA have expanded, leading to an increased demand for radiologists. The CAD reporting and data system (CAD-RADS) 2.0 was recently proposed for standardizing CCTA reporting. This RADS evaluates and categorizes patients based on coronary artery stenosis and the overall amount of coronary artery plaque and links this to patient management. In this review, we aimed to review the major trials and guidelines for CCTA to understand its clinical role. Furthermore, we aimed to introduce the CAD-RADS 2.0 including the assessment of coronary artery stenosis, plaque, and other key findings, and highlight the steps for CCTA reporting. Finally, we aimed to present recent research trends including the perivascular fat attenuation index, artificial intelligence, and the advancements in CT technology.

Impact of atherosclerosis imaging-quantitative computed tomography on diagnostic certainty, downstream testing, coronary revascularization, and medical therapy: the CERTAIN study

AIMS

The incremental impact of atherosclerosis imaging-quantitative computed tomography (AI-QCT) on diagnostic certainty and downstream patient management is not yet known. The aim of this study was to compare the clinical utility of the routine implementation of AI-QCT versus conventional visual coronary CT angiography (CCTA) interpretation.

METHODS AND RESULTS

In this multi-centre cross-over study in 5 expert CCTA sites, 750 consecutive adult patients referred for CCTA were prospectively recruited. Blinded to the AI-QCT analysis, site physicians established patient diagnoses and plans for downstream non-invasive testing, coronary intervention, and medication management based on the conventional site assessment. Next, physicians were asked to repeat their assessments based upon AI-QCT results. The included patients had an age of 63.8 ± 12.2 years; 433 (57.7%) were male. Compared with the conventional site CCTA evaluation, AI-QCT analysis improved physician's confidence two- to five-fold at every step of the care pathway and was associated with change in diagnosis or management in the majority of patients (428; 57.1%; P < 0.001), including for measures such as Coronary Artery Disease-Reporting and Data System (CAD-RADS) (295; 39.3%; P < 0.001) and plaque burden (197; 26.3%; P < 0.001). After AI-QCT including ischaemia assessment, the need for downstream non-invasive and invasive testing was reduced by 37.1% (P < 0.001), compared with the conventional site CCTA evaluation. Incremental to the site CCTA evaluation alone, AI-QCT resulted in statin initiation/increase an aspirin initiation in an additional 28.1% (P < 0.001) and 23.0% (P < 0.001) of patients, respectively.

CONCLUSION

The use of AI-QCT improves diagnostic certainty and may result in reduced downstream need for non-invasive testing and increased rates of preventive medical therapy.

Beyond early LDL cholesterol lowering to prevent coronary atherosclerosis in familial hypercholesterolaemia

AIMS

Familial hypercholesterolaemia (FH) patients are subjected to a high lifetime exposure to low density lipoprotein cholesterol (LDL-C), despite use of lipid-lowering therapy (LLT). This study aimed to quantify the extent of subclinical atherosclerosis and to evaluate the association between lifetime cumulative LDL-C exposure and coronary atherosclerosis in young FH patients.

METHODS AND RESULTS

Familial hypercholesterolaemia patients, divided into a subgroup of early treated (LLT initiated <25 years) and late treated (LLT initiated ≥25 years) patients, and an age- and sex-matched unaffected control group, underwent coronary CT angiography (CCTA) with artificial intelligence-guided analysis. Ninety genetically diagnosed FH patients and 45 unaffected volunteers (mean age 41 ± 3 years, 51 (38%) female) were included. Familial hypercholesterolaemia patients had higher cumulative LDL-C exposure (181 ± 54 vs. 105 ± 33 mmol/L ∗ years) and higher prevalence of coronary plaque compared with controls (46 [51%] vs. 10 [22%], OR 3.66 [95%CI 1.62-8.27]). Every 75 mmol/L ∗ years cumulative exposure to LDL-C was associated with a doubling in per cent atheroma volume (total plaque volume divided by total vessel volume). Early treated patients had a modestly lower cumulative LDL-C exposure compared with late treated FH patients (167 ± 41 vs. 194 ± 61 mmol/L ∗ years; P = 0.045), without significant difference in coronary atherosclerosis. Familial hypercholesterolaemia patients with above-median cumulative LDL-C exposure had significantly higher plaque prevalence (OR 3.62 [95%CI 1.62-8.27]; P = 0.001), compared with patients with below-median exposure.

CONCLUSION

Lifetime exposure to LDL-C determines coronary plaque burden in FH, underlining the need of early as well as potent treatment initiation. Periodic CCTA may offer a unique opportunity to monitor coronary atherosclerosis and personalize treatment in FH.

Prognostic value of metabolic dysfunction-associated steatotic liver disease over coronary computed tomography angiography findings: comparison with no-alcoholic fatty liver disease

BACKGROUND

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the proposed name change for non-alcoholic fatty liver disease (NAFLD). This study aimed to investigate the association of cardiovascular disease risk with MASLD and NAFLD in patients who underwent clinically indicated coronary computed tomography angiography (CCTA).

METHODS

This retrospective study included 2289 patients (60% men; mean age: 68 years) with no history of coronary artery disease who underwent CCTA. The steatotic liver was defined as a hepatic-to-spleen attenuation ratio of < 1.0 on CT just before CCTA. MASLD is defined as the presence of hepatic steatosis along with at least one of the five cardiometabolic risk factors. Adverse CCTA findings were defined as obstructive and/or high-risk plaques. Major adverse cardiac events (MACE) encompassed composite coronary events, including cardiovascular death, acute coronary syndrome, and late coronary revascularization.

RESULTS

MASLD and NAFLD were identified in 415 (18%) and 368 (16%) patients, respectively. Adverse CCTA findings were observed in 40% and 38% of the patients with MASLD and with NAFLD, respectively. Adverse CCTA findings were significantly associated with MASLD (p = 0.007) but not NAFLD (p = 0.253). During a median follow-up of 4.4 years, 102 (4.4%) MACE were observed. MASLD was significantly associated with MACE (hazard ratio 1.82, 95% CI 1.18-2.83, p = 0.007), while its association with NAFLD was not significant (p = 0.070). By incorporating MASLD into a prediction model of MACE, including the risk score and adverse CCTA findings, global chi-squared values significantly increased from 87.0 to 94.1 (p = 0.008).

CONCLUSIONS

Patients with MASLD are likely to have a higher risk of cardiovascular disease than those with NAFLD. Concurrent assessment of MASLD during CCTA improves the identification of patients at a higher risk of cardiovascular disease among those with clinically indicated CCTA.

Colchicine and plaque: A focus on atherosclerosis imaging

Colchicine is an anti-inflammatory medication, classically used to treat a wide spectrum of autoimmune diseases. More recently, colchicine has proven itself a key pharmacotherapy in cardiovascular disease (CVD) management, atherosclerotic plaque modification, and coronary artery disease (CAD) treatment. Colchicine acts on many anti-inflammatory pathways, which translates to cardiovascular event reduction, plaque transformation, and plaque reduction. With the FDA's 2023 approval of colchicine for reducing cardiovascular events, a novel clinical pathway opens. This advancement paves the route for CVD management that synergistically merges lipid lowering approaches with inflammation inhibition modalities. This pioneering moment spurs the need for this manuscript's comprehensive review. Hence, this paper synthesizes and surveys colchicine's new role as an atherosclerotic plaque modifier, to provide a framework for physicians in the clinical setting. We aim to improve understanding (and thereby application) of colchicine alongside existing mechanisms for CVD event reduction. This paper examines colchicine's anti-inflammatory mechanism, and reviews large cohort studies that evidence colchicine's blossoming role within CAD management. This paper also outlines imaging modalities for atherosclerotic analysis, reviews colchicine's mechanistic effect upon plaque transformation itself, and synthesizes trials which assess colchicine's nuanced effect upon atherosclerotic transformation.

Effects of adaptive or fixed thresholds and different platforms on the assessment of plaque characteristics using coronary computed tomography angiography

BACKGROUND

Coronary computed tomography angiography (CCTA) is used to evaluate components of atherosclerosis. Either adaptive or diverse, fixed Hounsfield Units (HU) are used to define components such as low attenuation (LAP), mixed (MP) and calcified plaque (CP). Comparisons of different platforms and different thresholding approaches have not been extensively evaluated. We compare two fixed threshold options to an adaptive threshold option within a specific platform and to fixed threshold options measured with another platform.

METHODS

Coronary segments (n ​= ​24) of good image quality, with well-defined boundaries and representing a broad range of atheroma were analyzed for LAP, MP and CP. Thresholds for LAP vs MP and MP vs CP were either Fixed30/350, Fixed75/350 or based on an automatically determined Adaptive option. Pearson correlation and Bland-Altman analyses were undertaken.

RESULTS

Within a single platform, measures were highly correlated irrespective of use of Adaptive or Fixed30/350 and Fixed75/350 thresholds (R ​≥ ​0.819, p ​< ​0.000001). The correlation slope for measures of LAP progressively diminished comparing the Adaptive versus Fixed30/350 and the Fixed75/350 versus the Fixed30/350 approaches but bias was small. Between-platform comparisons yielded less optimal results, particularly with respect to measures of LAP and with one platform yielding both very small LAP volumes and very small ranges of volumes.

CONCLUSION

Measures of plaque components are highly correlated irrespective of use of Adaptive or Fixed threshold approaches within a given platform. But measures are more affected by the specific proprietary algorithms employed than by specific thresholding options, especially for LAP.

Computed Tomography Angiography: Principles and Advances

This review describes current state-of-the-art computed tomography technology required to address human-physiology-based challenges unique to angiographic imaging. Challenges are based on the need to image a bolus of contrast agent traversing inside rapidly moving structures. This article reviews the latest methods to optimize contrast timing and minimize motion.

Progression of non-obstructive coronary plaque: a practical CCTA-based risk score from the PARADIGM registry

OBJECTIVES

No clear recommendations are endorsed by the different scientific societies on the clinical use of repeat coronary computed tomography angiography (CCTA) in patients with non-obstructive coronary artery disease (CAD). This study aimed to develop and validate a practical CCTA risk score to predict medium-term disease progression in patients at a low-to-intermediate probability of CAD.

METHODS

Patients were part of the Progression of AtheRosclerotic PlAque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry. Specifically, 370 (derivation cohort) and 219 (validation cohort) patients with two repeat, clinically indicated CCTA scans, non-obstructive CAD, and absence of high-risk plaque (≥ 2 high-risk features) at baseline CCTA were included. Disease progression was defined as the new occurrence of ≥ 50% stenosis and/or high-risk plaque at follow-up CCTA.

RESULTS

In the derivation cohort, 104 (28%) patients experienced disease progression. The median time interval between the two CCTAs was 3.3 years (2.7-4.8). Odds ratios for disease progression derived from multivariable logistic regression were as follows: 4.59 (95% confidence interval: 1.69-12.48) for the number of plaques with spotty calcification, 3.73 (1.46-9.52) for the number of plaques with low attenuation component, 2.71 (1.62-4.50) for 25-49% stenosis severity, 1.47 (1.17-1.84) for the number of bifurcation plaques, and 1.21 (1.02-1.42) for the time between the two CCTAs. The C-statistics of the model were 0.732 (0.676-0.788) and 0.668 (0.583-0.752) in the derivation and validation cohorts, respectively.

CONCLUSIONS

The new CCTA-based risk score is a simple and practical tool that can predict mid-term CAD progression in patients with known non-obstructive CAD.

CLINICAL RELEVANCE STATEMENT

The clinical implementation of this new CCTA-based risk score can help promote the management of patients with non-obstructive coronary disease in terms of timing of imaging follow-up and therapeutic strategies.

KEY POINTS

• No recommendations are available on the use of repeat CCTA in patients with non-obstructive CAD. • This new CCTA score predicts mid-term CAD progression in patients with non-obstructive stenosis at baseline. • This new CCTA score can help guide the clinical management of patients with non-obstructive CAD.

Predicting the presence of coronary plaques featuring high-risk characteristics using polygenic risk scores and targeted proteomics in patients with suspected coronary artery disease

BACKGROUND

The presence of coronary plaques with high-risk characteristics is strongly associated with adverse cardiac events beyond the identification of coronary stenosis. Testing by coronary computed tomography angiography (CCTA) enables the identification of high-risk plaques (HRP). Referral for CCTA is presently based on pre-test probability estimates including clinical risk factors (CRFs); however, proteomics and/or genetic information could potentially improve patient selection for CCTA and, hence, identification of HRP. We aimed to (1) identify proteomic and genetic features associated with HRP presence and (2) investigate the effect of combining CRFs, proteomics, and genetics to predict HRP presence.

METHODS

Consecutive chest pain patients (n = 1462) undergoing CCTA to diagnose obstructive coronary artery disease (CAD) were included. Coronary plaques were assessed using a semi-automatic plaque analysis tool. Measurements of 368 circulating proteins were obtained with targeted Olink panels, and DNA genotyping was performed in all patients. Imputed genetic variants were used to compute a multi-trait multi-ancestry genome-wide polygenic score (GPSMult). HRP presence was defined as plaques with two or more high-risk characteristics (low attenuation, spotty calcification, positive remodeling, and napkin ring sign). Prediction of HRP presence was performed using the glmnet algorithm with repeated fivefold cross-validation, using CRFs, proteomics, and GPSMult as input features.

RESULTS

HRPs were detected in 165 (11%) patients, and 15 input features were associated with HRP presence. Prediction of HRP presence based on CRFs yielded a mean area under the receiver operating curve (AUC) ± standard error of 73.2 ± 0.1, versus 69.0 ± 0.1 for proteomics and 60.1 ± 0.1 for GPSMult. Combining CRFs with GPSMult increased prediction accuracy (AUC 74.8 ± 0.1 (P = 0.004)), while the inclusion of proteomics provided no significant improvement to either the CRF (AUC 73.2 ± 0.1, P = 1.00) or the CRF + GPSMult (AUC 74.6 ± 0.1, P = 1.00) models, respectively.

CONCLUSIONS

In patients with suspected CAD, incorporating genetic data with either clinical or proteomic data improves the prediction of high-risk plaque presence.

TRIAL REGISTRATION

https://clinicaltrials.gov/ct2/show/NCT02264717 (September 2014).

Optimal diagnostic approach for using CT-derived quantitative flow ratio in patients with stenosis on coronary computed tomography angiography

BACKGROUND

Coronary computed tomography angiography (CCTA)-derived quantitative flow ratio (CT-QFR) is an on-site non-invasive technique estimating invasive fractional flow reserve (FFR). This study assesses the diagnostic performance of using most distal CT-QFR versus lesion-specific CT-QFR approach for identifying hemodynamically obstructive coronary artery disease (CAD).

METHODS

Prospectively enrolled de novo chest pain patients (n ​= ​445) with ≥50 ​% visual diameter stenosis on CCTA were referred for invasive evaluation. On-site CT-QFR was analyzed post-hoc blinded to angiographic data and obtained as both most distal (MD-QFR) and lesion-specific CT-QFR (LS-QFR). Abnormal CT-QFR was defined as ≤0.80. Hemodynamically obstructive CAD was defined as invasive FFR ≤0.80 or ≥70 ​% diameter stenosis by 3D-quantitative coronary angiography.

RESULTS

In total 404/445 patients had paired CT-QFR and invasive analyses of whom 149/404 (37 ​%) had hemodynamically obstructive CAD. MD-QFR and LS-QFR classified 188 (47 ​%) and 165 (41 ​%) patients as abnormal, respectively. Areas under the receiver-operating characteristic curve for MD-QFR was 0.83 vs. 0.85 for LS-QFR, p ​= ​0.01. Sensitivities for MD-QFR and LS-QFR were 80 ​% (95%CI: 73-86) vs. 77 ​% (95%CI: 69-83), p ​= ​0.03, respectively, and specificities were 73 ​% (95%CI: 67-78) vs. 80 ​% (95%CI: 75-85), p ​< ​0.01, respectively. Positive predictive values for MD-QFR and LS-QFR were 63 ​% vs. 69 ​%, p ​< ​0.01, respectively, and negative predictive values for MD-QFR and LS-QFR were 86 ​% vs. 85 ​%, p ​= ​0.39, respectively).

CONCLUSION

Using a lesion-specific CT-QFR approach has superior discrimination of hemodynamically obstructive CAD compared to a most distal CT-QFR approach. CT-QFR identified most cases of hemodynamically obstructive CAD while a normal CT-QFR excluded hemodynamically obstructive CAD in the majority of patients.

Diagnostic improvements of calcium-removal image reconstruction algorithm using photon-counting detector CT for calcified coronary lesions

OBJECTIVE

To investigate the diagnostic performance of a calcium-removal image reconstruction algorithm with photon-counting detector-computed tomography (PCD-CT), a technology that hides only the calcified plaque from the spectral data in coronary calcified lesions.

METHODS

This retrospective study included 17 patients who underwent PCD-coronary CT angiography (CCTA) with at least one significant coronary stenosis (≥50 %) with calcified plaque by CCTA and invasive coronary angiography (ICA) performed within 60 days of CCTA. A total of 162 segments with calcified plaque were evaluated for subjective image quality using a 4-point scale. Their calcium-removal images were reconstructed from conventional images, and both images were compared with ICA images as the reference standard. The contrast-to noise ratios for both images were calculated.

RESULTS

Conventional and calcium-removal images had a subjective image quality of 2.7 ± 0.5 and 3.2 ± 0.9, respectively (p < 0.001). The percentage of segments with a non-diagnostic image quality was 32.7 % for conventional images and 28.3 % for calcium-removal images (p < 0.001). The segment-based diagnostic accuracy revealed an area under the receiver operating characteristic curve of 0.87 for calcium-removal images and 0.79 for conventional images (p = 0.006). Regarding accuracy, the specificity and positive predictive value of calcium-removal images were significantly improved compared with those of conventional images (80.5 % vs. 69.5 %, p = 0.002 and 64.1 % vs. 52.0 %, p < 0.001, respectively). The objective image quality of the mean contrast-to-noise ratio did not differ between the images (13.9 ± 3.6 vs 13.3 ± 3.4, p = 0.356) CONCLUSIONS: Calcium-removal images with PCD-CT can potentially be used to evaluate diagnostic performance for calcified coronary artery lesions.