PURPOSE OF REVIEW
Nonobstructive coronary artery disease (NOCA) is now frequently detected by coronary CT angiography (CCTA), but the term compresses biologically distinct patterns into a single anatomic label. This review examines how CT-derived markers can reorganize NOCA around plaque burden, inflammatory activity, clinical expression, and temporal change.
RECENT FINDINGS
Recent work distinguishes three related but distinct tasks in NOCA: identify disease, stratify risk, and define phenotypes that may inform future prevention strategies. CCTA addresses the atherosclerotic and prognostic dimensions by quantifying plaque burden, plaque composition, and high-risk features; CT-derived inflammatory and cardiometabolic markers may further identify active vascular and metabolic phenotypes. In symptomatic patients, CCTA and fractional flow reserve CT can evaluate epicardial anatomy and lesion-specific hemodynamic significance, but normal or nonobstructive findings do not exclude coronary microvascular dysfunction or vasospasm. In asymptomatic patients, coronary artery calcium and CCTA can reveal subclinical atherosclerosis and refine preventive risk assessment. Serial imaging and intervention studies suggest that adverse plaque phenotypes can stabilize or change with intensive prevention, but outcome-proven CCTA-guided treatment algorithms are still lacking.
SUMMARY
CCTA is evolving into a multidimensional phenotyping tool for NOCA. Its immediate value is refined risk stratification; whether these markers will improve outcomes remains unproven and should be tested prospectively.
P. Piña, A. Filtz, Daniel Lorenzatti et al.· Current Opinion in Cardiolog...· 0 citations
Abstract Following technological developments and new landmark trials, the diagnostic work-up of symptomatic chronic coronary artery disease (CAD) has evolved. Clinical guidelines now favor noninvasive anatomical assessments by coronary CT angiography (CCTA) as the first-line modality to evaluate CAD in the majority of patients with chest pain. This shift from ischemia testing to stenosis and plaque characterization has resulted in the development of new imaging biomarkers reflecting a variety of coronary plaque features, many of which have proven to be important clinical risk markers. Consequently, there has been a transition from qualitative to semi-quantitative and fully quantitative plaque acquisitions over the entire coronary tree. With the integration of artificial intelligence, novel software enables rapid quantitative acquisitions of plaque components, making them feasible for use in clinical practice. CCTA has also enabled identification of precursor features associated with plaque development such as peri-coronary artery adipose tissue attenuation and epicardial adipose tissue volume. This review provides an overview of CCTA derived plaque features in CAD and associated imaging biomarkers of risk to highlight their potential applications in precision phenotyping and individualized management decisions. It further outlines anticipated future developments that may enable widespread clinical adoption of these novel imaging biomarkers.
J. Lenell, K. Grodecki, J. Kwieciński et al.· BJR|Open· 0 citations
Background and Aims: Epicardial adipose tissue (EAT) has emerged as an important cardiovascular biomarker that reflects both inflammatory and cardiometabolic risk. EAT volume and density vary significantly across populations, yet there is a lack of multicenter studies investigating the predictive value of population-specific EAT percentiles. Methods: In this multicenter study, we retrospectively analyzed low-dose computed tomography correction scans from 42,842 patients undergoing myocardial perfusion imaging. A derivation cohort of 15,082 patients was used to establish sex- and age-specific nomograms for EAT density and EAT volume indexed to body surface area. Percentile-based thresholds were tested for outcome prediction in a validation cohort of 27,760 patients. For clinical implementation, we developed an online EAT percentile calculator. Results: Percentile curves demonstrated increased BSA-indexed EAT volume and decreasing EAT density with age. Over a median follow-up of 3.6 years (IQR: 1.83 - 5.14), 4,956 patients experienced a nonfatal myocardial infarction or death. In multivariable Cox models, patients above the 95th sex- and age-specific percentile had significantly worse outcomes for BSA- indexed EAT volume [adjusted hazard ratio 1.30, 95% CI: 1.14 - 1.49, p < 0.001] and EAT density [adjusted hazard ratio 1.7, 95% CI: 1.51 - 1.92, p<0.001] when compared to patients below the 50th percentile (p<0.001). Conclusion: Age- and sex-specific EAT percentiles provide a clinically interpretable framework for contextualizing automated EAT measurements and identifying patients at increased cardiovascular risk. EAT density was a stronger prognostic marker and identified elevated risk even among patients with normal BMI, supporting its potential to provide information beyond conventional anthropometric assessment.
A. Kamagate, A. Shanbhag, M. Buchwald et al.· medRxiv· 0 citations
With the growing use of delayed dual-energy computed tomography (DECT) imaging for extracellular volume assessment, this study aimed to assess the accuracy of coronary artery calcium (CAC) and aortic valve calcification (AVC) quantification in virtual non-contrast (VNC) images derived from delayed DECT images. Eighty-eight patients undergoing pre-transcatheter aortic valve replacement (TAVR) cardiac CTA with DECT were retrospectively enrolled. We compared CAC score (CACS), CAC volume, AVC score (AVCS), and AVC volume between true non-contrast (TNC) and VNC images. VNC images were created by subtracting iodine from delayed CT angiography using commercial post-processing software. Concordance for the likelihood of severe aortic stenosis (AS) between TNC and VNC was assessed using guideline-based AVCS thresholds: men > 3,000 AU, women > 1,600 AU (highly likely); men > 2,000 AU, women > 1,200 AU (likely). CACS was lower in VNC than TNC (363.0 [13.7-1,154.0] AU vs. 470.1 [46.8-1,569.9] AU, p < 0.001), but the correlation was excellent (r = 0.966). No significant difference between VNC and TNC was observed in AVCS (959.5 [321.2-2,475.0] AU vs. 1,079.6 [492.2-2,329.4] AU, p = 0.521), with strong correlation (r = 0.966). Application of a correction factor (1.1-fold) improved agreement between VNC- and TNC-derived CACS (weighted κ = 0.839 to 0.869). Diagnostic concordance for severe AS between VNC and TNC was 92.1% (weighted kappa = 0.785) at the "highly likely" threshold and 97.7% (weighted kappa = 0.952) at the "likely" threshold. Delayed VNC images from DECT demonstrate strong agreement with TNC images for CACS and AVCS, suggesting that delayed VNC could potentially reduce the need for TNC acquisition in pre-TAVR assessment.
H. Fujito, K. R. Bookani, B. Gheyath et al.· The International Journal of...· 0 citations
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