Coronary CTA Plaque Volume Severity Stages According to Invasive Coronary Angiography and FFR

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.

Head-to-head comparison of 18F-sodium fluoride coronary PET imaging between a silicon photomultiplier with digital photon counting and conventional scanners

BACKGROUND

We compared silicone photomultipliers with digital photon counting (SiPM) and photomultiplier tubes (PMT) PET in imaging coronary plaque activity with 18F-sodium fluoride (18F-NaF) and evaluated comprehensively SiPM PET reconstruction settings.

METHODS

In 25 cardiovascular disease patients (mean age 67±12 years), we conducted 18F-NaF PET on a SiPM (Biograph Vision) and conventional PET (Discovery 710) on the same day as part of a prospective clinical trial (NCT03689946). Following administration of 250 MBq of 18F-NaF, patients underwent a contrast-enhanced CT angiography and a 30-min PET acquisition in list mode on each PET consecutively. Image noise was defined as mean standard deviation of blood pool activity within the left atria. Target-to-background ratio (TBR) and signal-to-noise ratio (SNR) were measured within the whole-vessel tubular 3-dimensional volumes of interest on the cardiac motion and attenuation corrected 18F-NaF PET images using dedicated software.

RESULTS

There were significant differences in image noise and background activity between the two PETs (Image noise (%), PMT: 7.6±3.7 vs. SiPM: 4.0±2.3, p<0.001; background activity, PMT: 1.4±0.4 vs. SiPM: 1.0±0.3, p<0.001). Similarly, the SNR and TBR were significantly higher in vessels scanned with the SiPM PET (SNR, PMT: 16.3±11.5 vs. SiPM: 32.7±29.8, p<0.001; TBR, PMT: 0.8±0.4 vs. SiPM: 1.1±0.6, p<0.001). SiPM PET image reconstruction with a 256 matrix, 1.4 mm pixel, and 2 mm Gaussian filter provided best tradeoff in terms of maximal SNR, TBR and clinically practical file size.

CONCLUSIONS

In 18F-NaF coronary PET imaging, the SiPM PET showed superior image contrast and less image noise compared to PMT PET.

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

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

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

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

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.

Innovations in cardiac computed tomography: Imaging in coronary artery disease

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

Long-term prognostic implications of CT angiography-derived fractional flow reserve: Results from the DISCOVER-FLOW study

BACKGROUND & OBJECTIVES

The long-term prognostic implications of CT angiography-derived fractional flow reserve (FFRCT) remains unclear. We aimed to explore the long-term outcomes of FFRCT in the first-in-human study of it.

MATERIALS & METHODS

A total of 156 vessels from 102 patients with stable coronary artery disease, who underwent coronary CT angiography (CCTA) and invasive FFR measurement, were followed. The primary endpoint was target vessel failure (TVF), including cardiovascular death, target vessel myocardial infarction, and target vessel revascularization. Outcome analysis with FFRCT was performed on a per-vessel basis using a marginal Cox proportional hazard model.

RESULTS

During median 9.9 years of follow-up, TVF occurred in 20 (12.8%) vessels. FFRCT ​≤0.80 discriminated TVF (hazard ratio [HR] 2.61, 95% confidence interval [CI] 1.06, 6.45). Among 94 vessels with deferral of percutaneous coronary intervention (PCI), TVF risk was inversely correlated with FFRCT ​(HR 0.62 per 0.1 increase, 95% CI 0.44, 0.86), with the cumulative incidence of TVF being 2.6%, 15.2%, and 28.6% for vessels with FFRCT ​>0.90, 0.81-0.90, and ≤0.80, respectively (p-for-trend 0.005). Predictive value for clinical outcomes of FFRCT was similar to that of invasive FFR (c-index 0.79 vs 0.71, P ​= ​0.28). The estimated TVF risk was higher in the deferral of PCI group than the PCI group for vessels with FFRCT ≤0.81.

CONCLUSION

FFRCT showed improved long-term risk stratification and displayed a risk continuum similar to invasive FFR.

CLINICAL TRIAL REGISTRATION

NCT01189331.

AI-Guided Quantitative Plaque Staging Predicts Long-Term Cardiovascular Outcomes in Patients at Risk for Atherosclerotic CVD

BACKGROUND

The recent development of artificial intelligence-guided quantitative coronary computed tomography angiography analysis (AI-QCT) has enabled rapid analysis of atherosclerotic plaque burden and characteristics.

OBJECTIVES

This study set out to investigate the 10-year prognostic value of atherosclerotic burden derived from AI-QCT and to compare the spectrum of plaque to manually assessed coronary computed tomography angiography (CCTA), coronary artery calcium scoring (CACS), and clinical risk characteristics.

METHODS

This was a long-term follow-up study of 536 patients referred for suspected coronary artery disease. CCTA scans were analyzed with AI-QCT and plaque burden was classified with a plaque staging system (stage 0: 0% percentage atheroma volume [PAV]; stage 1: >0%-5% PAV; stage 2: >5%-15% PAV; stage 3: >15% PAV). The primary major adverse cardiac event (MACE) outcome was a composite of nonfatal myocardial infarction, nonfatal stroke, coronary revascularization, and all-cause mortality.

RESULTS

The mean age at baseline was 58.6 years and 297 patients (55%) were male. During a median follow-up of 10.3 years (IQR: 8.6-11.5 years), 114 patients (21%) experienced the primary outcome. Compared to stages 0 and 1, patients with stage 3 PAV and percentage of noncalcified plaque volume of >7.5% had a more than 3-fold (adjusted HR: 3.57; 95% CI 2.12-6.00; P < 0.001) and 4-fold (adjusted HR: 4.37; 95% CI: 2.51-7.62; P < 0.001) increased risk of MACE, respectively. Addition of AI-QCT improved a model with clinical risk factors and CACS at different time points during follow-up (10-year AUC: 0.82 [95% CI: 0.78-0.87] vs 0.73 [95% CI: 0.68-0.79]; P < 0.001; net reclassification improvement: 0.21 [95% CI: 0.09-0.38]). Furthermore, AI-QCT achieved an improved area under the curve compared to Coronary Artery Disease Reporting and Data System 2.0 (10-year AUC: 0.78; 95% CI: 0.73-0.83; P = 0.023) and manual QCT (10-year AUC: 0.78; 95% CI: 0.73-0.83; P = 0.040), although net reclassification improvement was modest (0.09 [95% CI: -0.02 to 0.29] and 0.04 [95% CI: -0.05 to 0.27], respectively).

CONCLUSIONS

Through 10-year follow-up, AI-QCT plaque staging showed important prognostic value for MACE and showed additional discriminatory value over clinical risk factors, CACS, and manual guideline-recommended CCTA assessment.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Atherosclerotic plaque features relevant to rupture-risk detected by clinical photon-counting CT ex vivo: a proof-of-concept study

BACKGROUND

To identify subjects with rupture-prone atherosclerotic plaques before thrombotic events occur is an unmet clinical need. Thus, this proof-of-concept study aims to determine which rupture-prone plaque features can be detected using clinically available photon-counting computed tomography (PCCT).

METHODS

In this retrospective study, advanced atherosclerotic plaques (ex vivo, paraffin-embedded) from the Carotid Plaque Imaging Project were scanned by PCCT with reconstructed energy levels (45, 70, 120, 190 keV). Density in HU was measured in 97 regions of interest (ROIs) representing rupture-prone plaque features as demonstrated by histopathology (thrombus, lipid core, necrosis, fibrosis, intraplaque haemorrhage, calcium). The relationship between HU and energy was then assessed using a mixed-effects model for each plaque feature.

RESULTS

Plaques from five men (age 79 ± 8 [mean ± standard deviation]) were included in the study. Comparing differences in coefficients (b1diff) of matched ROIs on plaque images obtained by PCCT and histology confirmed that calcium was distinguishable from all other analysed features. Of greater novelty, additional rupture-prone plaque features proved discernible from each other, particularly when comparing haemorrhage with fibrous cap (p = 0.017), lipids (p = 0.003) and necrosis (p = 0.004) and thrombus compared to fibrosis (p = 0.048), fibrous cap (p = 0.028), lipids (p = 0.015) and necrosis (p = 0.017).

CONCLUSIONS

Clinically available PCCT detects not only calcification, but also other rupture-prone features of human carotid plaques ex vivo.

RELEVANCE STATEMENT

Improved atherosclerotic plaque characterisation by photon-counting CT provides the ability to distinguish not only calcium, but also rupture-prone plaque features such as haemorrhage and thrombus. This may potentially improve monitoring and risk stratification of atherosclerotic patients in order to prevent strokes.

KEY POINTS

• CT of atherosclerotic plaques mainly detects calcium. • Many components, such as intra-plaque haemorrhage and lipids, determine increased plaque rupture risk. • Ex vivo carotid plaque photon-counting CT distinguishes haemorrhage and thrombus. • Improved plaque photon-counting CT evaluation may refine risk stratification accuracy to prevent strokes.

Use of coronary artery calcium score and coronary CT angiography to guide cardiovascular prevention and treatment

Currently, cardiovascular risk stratification to guide preventive therapy relies on clinical scores based on cardiovascular risk factors. However, the discriminative power of these scores is relatively modest. The use of coronary artery calcium score (CACS) and coronary CT angiography (CCTA) has surfaced as methods for enhancing the estimation of risk and potentially providing insights for personalized treatment in individual patients. CACS improves overall cardiovascular risk prediction and may be used to improve the yield of statin therapy in primary prevention, and possibly identify patients with a favorable risk/benefit relationship for antiplatelet therapies. CCTA holds promise to guide anti-atherosclerotic therapies and to monitor individual response to these treatments by assessing individual plaque features, quantifying total plaque volume and composition, and assessing peri-coronary adipose tissue. In this review, we aim to summarize current evidence regarding the use of CACS and CCTA for guiding lipid-lowering and antiplatelet therapy and discuss the possibility of using plaque burden and plaque phenotyping to monitor response to anti-atherosclerotic therapies.

Rationale and design of the INVICTUS Registry: (Multicenter Registry of Invasive and Non-Invasive imaging modalities to compare Coronary Computed Tomography Angiography, Intravascular Ultrasound and Optical Coherence Tomography for the determination of Severity, Volume and Type of coronary atherosclerosiS)

BACKGROUND

Coronary CT angiography (CCTA) is a first-line noninvasive imaging modality for evaluating coronary artery disease (CAD). Recent advances in CCTA technology enabled semi-automated detection of coronary arteries and atherosclerosis. However, there have been to date no large-scale validation studies of automated assessment of coronary atherosclerosis phenotype and coronary artery dimensions by artificial intelligence (AI) compared to current standard invasive imaging.

METHODS

INVICTUS registry is a multicenter, retrospective, and prospective study designed to evaluate the dimensions of coronary arteries, as well as the characteristic, volume, and phenotype of coronary atherosclerosis by CCTA, compared with the invasive imaging modalities including intravascular ultrasound (IVUS), near-infrared spectroscopy (NIRS)-IVUS and optical coherence tomography (OCT). All patients clinically underwent both CCTA and invasive imaging modalities within three months.

RESULTS

Patients data are sent to the core-laboratories to analyze for stenosis severity, plaque characteristics and volume. The variables for CCTA are measured using an AI-based automated software and assessed independently with the variables measured at the imaging core laboratories for IVUS, NIRS-IVUS, and OCT in a blind fashion.

CONCLUSION

The INVICTUS registry will provide new insights into the diagnostic value of CCTA for determining coronary atherosclerosis phenotype and coronary artery dimensions compared to IVUS, NIRS-IVUS, and OCT. Our findings will potentially shed new light on precision medicine informed by an AI-based coronary CTA assessment of coronary atherosclerosis burden, composition, and severity. (ClinicalTrials.gov: NCT04066062).

Non-Contrast and Contrast-Enhanced Cardiac Computed Tomography Imaging in the Diagnostic and Prognostic Evaluation of Coronary Artery Disease

In recent decades, cardiac computed tomography (CT) has emerged as a powerful non-invasive tool for risk stratification, as well as the detection and characterization of coronary artery disease (CAD), which remains the main cause of morbidity and mortality in the world. Advances in technology have favored the increasing use of cardiac CT by allowing better performance with lower radiation doses. Coronary artery calcium, as assessed by non-contrast CT, is considered to be the best marker of subclinical atherosclerosis, and its use is recommended for the refinement of risk assessment in low-to-intermediate risk individuals. In addition, coronary CT angiography (CCTA) has become a gate-keeper to invasive coronary angiography (ICA) and revascularization in patients with acute chest pain by allowing the assessment not only of the extent of lumen stenosis, but also of its hemodynamic significance if combined with the measurement of fractional flow reserve or perfusion imaging. Moreover, CCTA provides a unique incremental value over functional testing and ICA by imaging the vessel wall, thus allowing the assessment of plaque burden, composition, and instability features, in addition to perivascular adipose tissue attenuation, which is a marker of vascular inflammation. There exists the potential to identify the non-obstructive lesions at high risk of progression to plaque rupture by combining all of these measures.

The journal of cardiovascular computed tomography: A year in review: 2022

This review aims to summarize key articles published in the Journal of Cardiovascular Computed Tomography (JCCT) in 2022, focusing on those that had the most scientific and educational impact. The JCCT continues to expand; the number of submissions, published manuscripts, cited articles, article downloads, social media presence, and impact factor continues to grow. The articles selected by the Editorial Board of the JCCT in this review highlight the role of cardiovascular computed tomography (CCT) to detect subclinical atherosclerosis, assess the functional relevance of stenoses, and plan invasive coronary and valve procedures. A section is dedicated to CCT in infants and other patients with congenital heart disease, in women, and to the importance of training in CT. In addition, we highlight key consensus documents and guidelines published in JCCT last year. The Journal values the tremendous work by authors, reviewers, and editors to accomplish these contributions.

The Roles of Coronary Computed Tomography Angiography in Characterizing Coronary Plaque: Screening, Treatment, and Prevention

One of the major risk factors for coronary atherosclerosis is the gradual formation and maturation of coronary atherosclerotic plaque (CAP) [...].

Association between coronary plaque volume and myocardial ischemia detected by dynamic perfusion CT imaging

Introduction

We aimed to evaluate the relationship between quantitative plaque metrics derived from coronary CT angiography (CTA) and segmental myocardial ischemia using dynamic perfusion CT (DPCT).

Methods

In a prospective single-center study, patients with > 30% stenosis on rest CTA underwent regadenoson stress DPCT. 480 myocardium segments of 30 patients were analyzed. Quantitative plaque assessment included total plaque volume (PV), area stenosis, and remodeling index (RI). High-risk plaque (HRP) was defined as low-attenuation plaque burden > 4% or RI > 1.1. Absolute myocardial blood flow (MBF) and relative MBF (MBFi: MBF/75th percentile of all MBF values) were quantified. Linear and logistic mixed models correcting for intra-patient clustering and clinical factors were used to evaluate the association between total PV, area stenosis, HRP and MBF or myocardial ischemia (MBF < 101 ml/100 g/min).

Results

Median MBF and MBFi were 111 ml/100 g/min and 0.94, respectively. The number of ischemic segments were 164/480 (34.2%). Total PV of all feeding vessels of a given myocardial territory differed significantly between ischemic and non-ischemic myocardial segments (p = 0.001). Area stenosis and HRP features were not linked to MBF or MBFi (all p > 0.05). Increase in PV led to reduced MBF and MBFi after adjusting for risk factors including hypertension, diabetes, and statin use (per 10 mm³; β = −0.035, p < 0.01 for MBF; β = −0.0002, p < 0.01 for MBFi). Similarly, using multivariate logistic regression total PV was associated with ischemia (OR = 1.01, p = 0.033; per 10 mm³) after adjustments for clinical risk factors, area stenosis and HRP.

Conclusion

Total PV was independently associated with myocardial ischemia based on MBF, while area stenosis and HRP were not.