Photon-counting detector computed tomography (PCD-CT) is an emerging advanced CT technology that differs from conventional energy-integrating detector CT (EID-CT) scanners in its ability to directly convert incident X-ray photon energies into electrical signals. Since its commercial market introduction in 2021, several studies have identified advantages of this new technology in the field of cardiovascular imaging, including improved image quality due to an enhanced contrast-to-noise ratio, superior spatial resolution, reduced artefacts, and a reduced radiation dose. Nonetheless, radiation exposure with PCD-CT can vary depending on the acquisition mode and protocol used, highlighting the importance of tailored optimization in clinical practice. In particular, this new technology appears feasible in patients with a high plaque burden independent of morphology, unravelling new phenotypes of plaque, in patients with stents due to the improved visualization of the coronary in-stent lumen, potentially expanding the scope of CT. Early studies and clinical experience support these potential applications of PCD-CT in cardiovascular diagnostics, suggesting workflow optimization and improved patient management. In this review, the authors aim to describe the role of PCD-CT not only in the exclusion of coronary artery disease, grading of coronary stenosis and plaque imaging, but also in evaluation of cardiac chambers and myocardium for tissue characterization trying to understand whether PCD-CT has yet led to a true revolution and significant progress in cardiovascular imaging.

Coronary computed tomography angiography (CCTA) can be used beyond diagnostic purposes to support the preprocedural planning of percutaneous coronary intervention (PCI). Advances in scanner technology, software platforms, and physiology- and plaque-based visualization tools have expanded the role of CCTA-guided PCI. CCTA provides detailed assessment of coronary anatomy, plaque and calcium morphology, lesion length, vessel size, and noninvasive physiology, offering opportunities to anticipate procedural complexity, optimize resource utilization, and individualize PCI strategy. Emerging data, including randomized studies in chronic total occlusions and ongoing multicenter trials, support the feasibility and potential clinical value of this approach. In April 2024, the first CCTA-guided PCI summit in the United States convened interventional cardiologists and cardiac imagers, as well as industry stakeholders, to discuss the evidence, technical considerations, clinical applications, and unmet needs related to CCTA-guided PCI. This manuscript summarizes the key discussions and conclusions specific to this meeting, with a focus on the transition of CCTA from a diagnostic to a therapeutic planning tool, emerging artificial intelligence applications, its complementary role with intravascular imaging, and opportunities to enhance procedural planning and decision-making. While early experience is promising, broader adoption will require broader educational efforts, access to purpose-built visualization software tools designed for interventional cardiologists, multidisciplinary collaboration, and additional randomized and real-world studies to define its impact on clinical outcomes and procedural efficiency.

Background Coronary computed tomography angiography (CCTA) is commonly utilized to inform coronary artery disease (CAD) management. The added impact of coronary Artificial Intelligence-Quantified Coronary Plaque Analysis (AI-CPA) on medical management is less understood. Methods An observational prospective cohort study included 105 consecutive patients undergoing CCTA between June 2024 and July 2025. The degree of luminal stenosis and total plaque volume (TPV) were quantified via AI-CPA (Heartflow, Inc.). Results Following CCTA and AI-CPA, 95% of patients had a better understanding of their overall risk and were initiated on new or additional lipid lowering therapy (LLT). A significant association was observed between the baseline LDL-C and TPV: TPV increase of 8.2 mm3 per 1 mg/dL increase in LDL-C, p < 0.001. Following LLT change, there was a 67% reduction in median LDL-C 45 mg/dL (IQR 32–60 mg/dL) compared to baseline 138 mg/dL (IQR 113–155 mg/dL, p < 0.001). Higher odds of achieving ≥50% RLR (OR 1.003, 95% CI 1.000–1.005, p = 0.028) were noted as TPV increased. Conclusion AI-CPA is associated with what appears to be greater LDL-C reduction. The association between AI-CPA findings and subsequent LDL-C reduction supports the potential role of AI-CPA in patient education and management.

Chronic total occlusion (CTO) percutaneous coronary intervention (PCI) can be technically complex. Coronary computed tomography angiography (CTA) is increasingly being used for planning CTO PCI. Coronary CTA can help evaluate cap morphology, lesion length, calcification, and distal vessel quality. The use of coronary CTA for CTO PCI may be enhanced by integration with artificial intelligence and real-time imaging. In a randomized controlled trial, preprocedural coronary CTA increased the success of CTO PCI. In this review, the authors describe how coronary CTA can help diagnose and characterize CTO lesions, estimate the time needed for guidewire crossing time, predict and facilitate CTO PCI technical success, and provide real-time procedural guidance.

Optical Flow Ratio (OFR) simulates fractional flow reserve (FFR) by analyzing coronary geometries from optical coherence tomography (OCT); however, its ability to assess pathophysiological coronary artery disease (CAD) patterns remains unclear. This study aimed to validate the accuracy of OFR-derived pullback pressure gradient (OFR-PPG) in characterizing CAD patterns using invasive pullback pressure gradient (PPG) as a reference. This is a pooled analysis of two multicenter prospective studies that included patients with hemodynamically significant CAD (FFR ≤ 0.80). Patients who underwent PPG assessment and OCT were included. The PPG algorithm was applied to the OFR pullback curves to derive OFR-PPG. The median value of invasive PPG was used as the threshold for defining focal and diffuse. A total of 110 patients (112 vessels) were analyzed. The median PPG was 0.60 (interquartile range [IQR], 0.49–0.73), while the median OFR-PPG was 0.55 (0.43–0.66). OFR-PPG showed a moderate correlation with PPG (r = 0.64; p < 0.001). The mean difference between OFR-PPG and invasive PPG was 0.06, with the limits of agreement − 0.19 to 0.31. Agreement in CAD pattern classification was moderate (Cohen’s κ = 0.52), with approximately one-quarter of vessels misclassified. Pathophysiological CAD patterns derived from OCT-derived FFR showed moderate agreement with invasively measured PPG.

BACKGROUND:In the assessment of coronary physiology, non-hyperemic pressure ratios (NHPRs) provide an alternative to fractional flow reserve (FFR) without the need for hyperemic agents, reducing procedural time, side effects, and costs. However, it remains unclear whether NHPRs have similar diagnostic performance in the different coronary arteries. This study evaluates the diagnostic performance of NHPRs compared with FFR, stratified by coronary artery, in stable patients with coronary artery disease. METHODS:We conducted a systematic review and individual patient-level data meta-analysis from prospective studies involving patients with intermediate to severe coronary stenosis who underwent physiological assessment with NHPRs and FFR. NHPRs included resting full-cycle ratio or instantaneous wave-free ratio (iFR). The diagnostic performance of NHPRs was calculated using a threshold of ≤0.89 for NHPRs with FFR ≤0.80 as the reference and by stratifying between the left anterior descending artery (LAD) and non-LAD vessels. RESULTS:A total of 2120 paired FFR and NHPRs (1257 resting full-cycle ratio, 863 iFR) measurements were analyzed. The LAD artery was the interrogated vessel in 67% of cases, the left circumflex artery in 15%, and the right coronary artery in 17%. The mean NHPR and FFR values were 0.80±0.17 and 0.71±0.14, respectively. The overall sensitivity, specificity, and accuracy of NHPRs were 82%, 86%, and 83%. In non-LAD vessels, NHPRs had significantly lower sensitivity and accuracy, but higher specificity compared with LAD (69% versus 87%, 76% versus 86%, and 91% versus 81%, respectively, P<0.001 for all). The optimal NHPRs cutoff for detecting significant lesions differed between LAD (≤0.88) and non-LAD (≤0.92). CONCLUSIONS:NHPRs demonstrated lower diagnostic performance in non-LAD vessels compared with the LAD. These results underscore the need for vessel-specific interpretation of NHPR measurements.

Cardiac imaging and in particular transthoracic echocardiography and computed tomography play a major role in the selection of the patients for surgical or transcatheter aortic valve replacement, for the assessment or procedural success and early prosthetic valve hemodynamics following aortic valve replacement, and for the evaluation and follow-up of the prosthetic valve structure and function in the longer-term, which is key to demonstrate the valve durability. The purpose of this review article is thus to present the role of cardiac imaging, and particularly transthoracic echocardiography and computed tomography, in: (1) patient selection for intervention; (2) assessment of procedural and device success, and of intended performance of the valve; and (3) assessment of the long-term success, valve durability, and prognosis, for clinical trials of intervention in patients with aortic stenosis. Transthoracic echocardiography is the primary imaging modality to detect and stage bioprosthetic valve dysfunction. However, multimodality imaging, including transesophageal echocardiography and computed tomography, is often necessary to determine the cause of bioprosthetic valve dysfunction and make the differential diagnosis between prosthesis-patient mismatch, structural valve deterioration, thrombosis, pannus, or endocarditis. The clinical trials in the field of structural heart disease, and particularly in the field of aortic valve intervention, include imaging end points as part of the primary or key secondary end points. Standardized methods and definitions should be applied to adjudicate these imaging end points, and ideally, these trial end points should be analyzed by independent imaging core labs.

INTRODUCTION:Coronary artery disease (CAD) on coronary computed tomography angiography (CCTA) is typically assessed using a dichotomous ≥ 50 % stenosis threshold. However, CAD diffuseness may also influence patient management and outcomes. The PRECISE trial provides high quality data to examine these relationships. METHODS AND RESULTS:In this PRECISE substudy, patients with stable suspected CAD undergoing CCTA with FFR-CT and quantitative plaque analysis were evaluated. The FFR-CT drop across a stenosis was defined as stenosisFFR-CT, and the drop attributed to diffuse disease as diffuseFFR-CT. Patients with ≥ 50 % stenosis were classified using cohort medians of stenosisFFR-CT and diffuseFFR-CT into four phenotypes: focal (FOC), diffuse (DIF), combined focal and diffuse (DIFFOC), or no hemodynamically significant CAD (NoHEM). Participants without ≥ 50 % stenosis constituted a fifth group. A total of 737 participants were included (mean age 60 ± 10 years, 44 % female): NoHEM (n = 37), DIF (n = 53), FOC (n = 57), DIFFOC (n = 37), and < 50 % stenosis (n = 553). Total plaque volume (TPV) was highest in DIFFOC (262 [175-504] mm3), followed by DIF (210 [97-302] mm3), FOC (209 [88-415] mm3), NoHEM (153 [87-254] mm3), and < 50 % stenosis (7 [0-59] mm3; p < 0.0001). FOC patients more frequently reported typical angina (p = 0.04) while symptom intensity was similar across the phenotypes. Revascularization was performed in 51 % (FOC), 49 % (DIFFOC), 6 % (DIF), 5 % (NoHEM), and 2 % (<50 % stenosis). CONCLUSION:Focal and mixed CAD phenotypes were clinically similar, aside from more typical angina in focal disease. Revascularization was performed in approximately half of patients with focal patterns, regardless of a diffuse component.

Background South Asians (SA) face disproportionately high rates of premature coronary artery disease (CAD), often underestimated by traditional risk calculators. We aim to characterize CT angiography (CTA)-derived plaque composition, plaque burden, and association with risk factors among SA in the DILWALE registry. Methods Clinically indicated coronary CTAs from 341 patients in the Baylor Scott and White DILWALE registry were analyzed using Artificial intelligence enabled quantitative coronary plaque analysis (AIQCPA) to characterize age- and sex-specific plaque burden. Results Of 341 patients, 63% (n=215) exhibited any plaque by AIQCPA. Non-calcified plaque (NCP) was the predominant plaque subtype across all age groups, but calcified plaque volumes increased with age. The median PAV was 3.5% (IQR 0-18.5%). Age, male sex, and statin use were significant predictors of the presence of any plaque, while age and male sex predicted the presence of low attenuation plaque ≥ 10 mm3. Conclusion This study represents one of the largest CTA based cohorts evaluating plaque characteristics in SA in the United States. Our findings highlight the value of AIQCPA CTA in revealing subclinical plaque, particularly non-calcified plaque in SA. Future studies should identify optimal imaging strategies for SA along with outcome-based validation of plaque characteristics.

The number of individuals engaging in sports continues to rise, and identifying those with cardiac substrates associated with increased risk of exercise-related adverse events is crucial. Athlete evaluation requires a refined diagnostic strategy to distinguish physiological cardiac remodelling from pathology. This joint European Association of Preventive Cardiology/European Association of Cardiovascular Imaging consensus provides a multimodality approach for advanced cardiovascular imaging in sports cardiology. Cardiovascular magnetic resonance, cardiac computed tomography, and nuclear imaging each offer complementary insights into cardiac structure, function, coronary anatomy, tissue characterization, perfusion, and inflammation. When integrated with clinical data and first-line tests, they improve diagnostic precision and risk stratification in scenarios frequently encountered in athletes, including ventricular arrhythmias, cardiomyopathies, congenital coronary anomalies, inflammatory myocardial disease, and coronary artery disease. Standardized protocols tailored to age, training, and clinical indication are essential to ensure reliability and avoid misinterpreting physiological adaptation as disease. The consensus emphasizes responsible reporting, considering performance and legal implications of diagnoses, and recommends second-line imaging when justified. Functional imaging, for ischaemia or inflammation, is central in guiding return-to-play decisions. Persistent evidence gaps include limited normative datasets across athletic subgroups and uncertain significance of subtle tissue abnormalities. Overall, this consensus supports harmonized, safe, and judicious multimodality imaging to protect athletes while preventing unnecessary sport restriction.

BACKGROUND:Although physiological assessment has been used in decision-making for revascularization, its role in predicting the future risk of acute coronary syndrome (ACS) remains underexplored. OBJECTIVES:This study aims to investigate the independent and combined prognostic significance of hemodynamic disease severity and distribution in identifying ACS culprit vessels, in conjunction with lumen and plaque characteristics. METHODS:The EMERALD-II study is an international, multicenter, internal case-control study enrolling 351 patients with ACS who underwent coronary computed tomography angiography (CTA) 1 month to 3 years before the event. Culprit and nonculprit vessels were identified by matching invasive coronary angiography with coronary CTA findings. High-risk plaque (HRP) characteristics, including minimum lumen area <4 mm2, plaque burden ≥70%, low-attenuation plaque, positive remodeling, spotty calcification, and napkin-ring sign, were assessed by a core laboratory, with HRP defined as ≥3 HRP characteristics. From coronary CTA, the authors derived both the hemodynamic severity of the disease (fractional flow reserve derived from computed tomography [FFRCT]) and its spatial distribution (diffuse vs focal), as assessed by the pullback pressure gradient derived from coronary CTA (PPGCT). Vessels were categorized into 4 hemodynamic disease patterns: nonischemic (FFRCT >0.80), hemodynamic diffuse (FFRCT ≤0.80 and PPGCT ≤0.50), mixed (FFRCT ≤0.80 and 0.50 < PPGCT ≤0.60), and focal disease (FFRCT ≤0.80 and PPGCT >0.60). RESULTS:Among 873 vessels, the mean FFRCT was 0.74 ± 0.17 and the mean PPGCT was 0.54 ± 0.14. Both lower FFRCT and higher PPGCT were independently associated with higher ACS risk (OR per 0.1 increase in FFRCT: 0.71 [95% CI: 0.65-0.77]; P < 0.001; OR per 0.1 increase in PPG: 1.22 [95% CI: 1.09-1.37]; P < 0.001). Among the 4 subgroups of hemodynamic disease pattern, hemodynamic focal disease showed the highest risk of ACS (relative risk [RR]: 2.02 [95% CI: 1.74-2.36]; P < 0.001), myocardial infarction (RR: 1.75 [95% CI: 1.43-2.14]; P < 0.001), and unstable angina (RR: 2.54 [95% CI: 2.00-3.22]; P < 0.001). It remained a predictor for ACS in nonobstructive lesions (OR: 3.56 [95% CI: 1.43-8.84]), obstructive lesions (OR: 3.16 [95% CI: 1.96-5.07]), non-HRP (OR: 6.69 [95% CI: 3.59-12.5]), and HRP (OR: 2.98 [95% CI: 1.83-4.87]). Although the maximal lesion-level ΔFFRCT (differences in FFRCT across the lesion) demonstrated superior model performance compared with models incorporating FFRCT and PPGCT, higher PPGCT was additionally associated with increased ACS risk, particularly among vessels with maximal ΔFFRCT ≥0.10. CONCLUSIONS:Hemodynamic disease distribution, as measured by PPGCT, complements FFRCT in predicting ACS risk. The integration of hemodynamic disease patterns provides additional prognostic value beyond lumen and plaque characteristics, with hemodynamic focal disease emerging as an independent predictor and a potential therapeutic target for ACS prevention. (Exploring the Mechanism of Plaque Rupture in Acute Coronary Syndrome Using Coronary CT Angiography and Computational Fluid Dynamics II [EMERALD II]; NCT03591328).

Coronary artery disease (CAD) continues to be a leading cause of death globally. Radiological evaluation of CAD generally consists of stenosis detection by cardiac computed tomographic angiography (CCTA). However, this approach can be inefficient and subject to inter-observer variability. In this review we explore the newest developments related to CAD evaluation by CCTA, with an emphasis on plaque quantification. Artificial Intelligence-based quantitative computed tomography (AI-QCT) offers an efficient and reproducible method to analyse plaque biomarkers that support more refined risk-stratification for major adverse cardiovascular events (MACE). Artificial intelligence-based coronary stenosis quantification (AI-CSQ) can streamline workflow and improve consistency. The utilisation of a photon counting detector CT (PCD-CT) has been demonstrated to enhance spatial resolution, thereby allowing more precise coronary lumen analysis and artifact reduction. Fractional flow reserve-computed tomography (FFR-CT) delivers a non-invasive physiologic assessment of stenotic lesions. Finally, we discuss the impact of these changes on risk stratification and guiding preventive therapy as well as possible future directions in this rapidly evolving field.

Background/Synopsis Coronary computed tomography angiography (CCTA) is commonly utilized to inform coronary artery disease (CAD) management. The impact of artificial intelligence (AI)-informed CCTA-derived coronary plaque volume quantification (AI-CPA) on medical management is less understood. Objective/Purpose To better understand the impact of AI-CPA on medical management. Methods An observational prospective cohort study included consecutive patients undergoing CCTA between June 2024 and July 2025. The degree of luminal stenosis and total plaque volume (TPV) were quantified via AI-CPA (HeartFlow, Inc.). Results One hundred and five patients were included. Following CCTA and AI-CPA, 95% of patients had a better understanding of their overall risk and were initiated on new or additional lipid-lowering therapy (LLT). A significant association was observed between the baseline low-density lipoprotein (LDL) and TPV: TPV increase of 8.2 mm³ per 1 mg/dL increase in LDL (P < 0.001). Following LLT change, there was a 66% reduction in median LDL (46, IQR 15–83 mg/dL compared to baseline 134, IQR 41–210 mg/dL; P < 0.001). A significant reduction in absolute LDL was noted among patients with higher TPV volume at baseline (> 101 mm³) compared to those with mild TPV volume (1–100 mm³), P < 0.001. Higher odds of achieving ≥50% relative LDL reduction (odds ratio [OR] 1.003, 95% CI 1.000–1.005, P = 0.028) were noted as TPV increased. Conclusions AI-CPA is associated with improved patient understanding of CAD risk and willingness to initiate LLT. The association between AI-CPA findings and subsequent LDL reduction supports the potential role of AI-CPA in patient education and management.Figures/Tables: 1

Background Infection with the severe acute respiratory syndrome coronavirus-2 (SARSCoV-2), the virus which causes the corona virus disease-2019 (COVID-19) has substantial evidence that patients with pre-existing coronary artery disease (CAD) have an increased risk of serious illness, adverse coronary events, and mortality following infection. The COVID-CT registry will assess whether COVID-19 alters progression of coronary atherosclerotic plaque in patients with previously defined anatomic CAD on coronary computed tomographic angiography (CCTA). Mediators and covariates such as disease severity, inflammation, and neighborhood deprivation will also be assessed. Design The COVID-CT registry is a multicenter, longitudinal observational registry enrolling patients including patients with pre-pandemic atherosclerosis observed by CCTA from New York City and Long Island to determine the impact of COVID-19 infection. The primary aim is to test the hypothesis that patients with previously defined anatomic CAD by CCTA who are subsequently infected with SARS-CoV-2 have accelerated progression of total and noncalcified atherosclerotic plaque volumes when compared to uninfected patients. We hypothesize that systemic inflammation is a key promoter in the formation and progression of atherosclerotic plaque. Additionally, we will test whether measurement of the perivascular fat attenuation index detects high risk, coronary artery inflammation following COVID infection. Summary The impact of this first in-kind registry will be foundational for revising standard diagnostic pathways and risk assessment used to guide preventive care for millions of patients with CAD at increased risk from viral infection.

Coronary computed tomography angiography (CCTA) is emerging as a valuable adjunct for chronic total occlusion (CTO) percutaneous coronary intervention (PCI), particularly for lesions in which angiography incompletely defines procedural anatomy. In this systematic review, the authors evaluated the role of CCTA in CTO diagnosis, lesion characterization, prediction of guidewire crossing and procedural success, and procedural guidance. CCTA provides a detailed assessment of key features that directly influence CTO PCI strategy and outcomes. Randomized and observational data suggest that preprocedural CCTA can improve procedural planning, increase technical success in complex lesions, and support safer and more efficient CTO PCI through fluoroscopic co-registration and other real-time guidance applications. These findings highlight the clinical value of CCTA as a tool that can enhance case selection, optimize crossing strategy, and improve procedural success in contemporary CTO PCI.

Aims To assess whether baseline functional performance assessed by exercise treadmill stress testing (EST) has additive value to coronary computed tomography angiography (CCTA) for risk stratification among patients with chronic coronary disease (CCD) and moderate or severe ischaemia.Methods and results We performed a subgroup analysis of the ISCHEMIA trial including participants who underwent EST and CCTA. EST data and severity of coronary artery disease (CAD) on CCTA were evaluated by core laboratories, blinded to clinical data and results of the other tests. The primary outcome for this analysis was all-cause death. Secondary outcomes were cardiovascular death, cardiovascular death or myocardial infarction (MI), MI and a composite of cardiovascular death, MI, or hospitalization for heart failure, unstable angina, or resuscitated cardiac arrest. EST and the number of vessels diseased on CCTA were both interpretable in 1864 patients (median age 62 years, IQR 55-68, 83% males). During a median follow-up of 3.1 years, 69 patients died. Higher peak metabolic equivalents (METs) achieved on the qualifying stress test was associated with lower all-cause death (HR 0.86, 95% CI 0.76-0.98; P = 0.025). The addition of peak METs to CAD severity improved the predictive ability of the all-cause death and CV death models by 10-20% and 8-13% respectively, depending on the metrics used for CCTA. Adding peak METs to CCTA anatomical models resulted in better prediction of MI by 11-17%, cardiovascular death or MI by 10-14%, and 5-component composite outcome by 12-16%.Conclusion Peak METs on EST, a marker of functional performance, added prognostic value to models including CCTA anatomical findings in patients with CCD and moderate or severe ischaemia.

Technological advances in coronary computed tomography angiography and artificial intelligence have resulted in an increasing capability to analyze and quantify information about atherosclerotic coronary plaque through noninvasive imaging. This has paved the way for a growing number of U.S. Food and Drug Administration-cleared products that can perform quantitative coronary plaque analysis (QCPA). To date, research has focused on the accuracy, prognostic value, and decision-making impact of QCPA, but there is no current consensus on its appropriate use in clinical practice. To address this gap, the American College of Cardiology convened a panel of experts for a 1-day symposium to discuss key questions related to the use of QCPA in clinical practice and develop consensus recommendations to guide cardiovascular clinicians and imagers on the use of QCPA. This scientific statement provides guidance on clinical indications (including possible uses of QCPA in serial imaging), methods for interpretation and reporting, and standardization. Future research directions are also addressed, including both the collection of ongoing registry data and potential for incorporation of QCPA into outcomes trials.

BACKGROUND:Coronary artery disease (CAD) is common in patients with severe aortic stenosis (AS) and may impact transcatheter aortic valve replacement (TAVR) procedural and long-term outcomes. CT coronary angiography (CTA) and CT-derived fractional flow reserve (FFRCT) are tools used to assess CAD. However, adoption in the TAVR population is hindered by safety concerns with nitroglycerin and beta-blockers. The safety, accuracy, and utility of CTA and FFRCT optimised with these medications for TAVR have not been established. METHODS:This international, multi-center, prospective registry included severe AS patients referred for TAVR, assessed for CAD with CTA and FFRCT. Patients all received nitroglycerin and beta-blockers as needed to optimise image quality. Severe ventricular dysfunction, recent syncope/heart failure, critical hemodynamics, or prior revascularization were excluded. Significant CAD was defined as CTA stenosis ≥50 ​% and FFRCT≤0.75. Primary endpoint was per-patient sensitivity and negative predictive value (NPV) of CTA compared to invasive coronary angiography (ICA). Secondary endpoints included specificity and positive predictive value (PPV) of CTA and FFRCT, safety, feasibility (non-evaluable rate), and the modelled potential of CTA ​+ ​FFRCT to reduce pre-TAVR ICA. RESULTS:327 patients (75.9 ​± ​9.7 years, 53 ​% male) underwent CTA. CTA was safe and well tolerated in nearly all patients, with transient hypotension in 4 (1.2 ​%). CTA was evaluable in 326 patients (99.7 ​%), with 9 (2.8 ​%) having a non-evaluable vessel. FFRCT and ICA were performed in 110 (33.6 ​%) and 133 (40.7 ​%) patients, respectively. Per-patient sensitivity, specificity, NPV, and PPV of CTA were 100 ​%, 71.4 ​%, 100 ​%, and 75.9 ​% and per-vessel 82.7 ​%, 78.9 ​%, 92.3 ​%, and 59.9 ​%. FFRCT improved specificity and PPV to 88.9 ​% and 88.0 ​% for per-patient and 95.1 ​% and 81.8 ​% for per-vessel analysis. Using a simulated triage model deferring ICA in patients with CTA <50 ​% or ≥50 ​% stenosis with FFRCT >0.75, 267 patients (81.7 ​%) could potentially have avoided ICA. CONCLUSION:Coronary CTA performed with nitroglycerin and selective use of beta-blockers is safe and effective for assessing CAD in stable severe AS patients. Combining CTA and FFRCT enhances diagnostic accuracy, potentially reducing the need for invasive angiography and streamlining TAVR workup.

Abstract Coronary artery disease (CAD) continues to be a leading cause of death globally. Radiological evaluation of CAD generally consists of stenosis detection by cardiac CT angiography (CCTA). However, this approach can be inefficient and subject to interobserver variability. In this review, we explore the newest developments related to CAD evaluation by CCTA, with an emphasis on plaque quantification. Artificial intelligence–based quantitative CT offers an efficient and reproducible method to analyze plaque biomarkers that support more refined risk stratification for major adverse cardiovascular events. Artificial intelligence–based coronary stenosis quantification can streamline workflow and improve consistency. The utilization of a photon-counting detector CT has been demonstrated to enhance spatial resolution, thereby allowing more precise coronary lumen analysis and artifact reduction. Fractional flow reserve-CT delivers a noninvasive physiologic assessment of stenotic lesions. Finally, we discuss the impact of these changes on risk stratification and guiding preventive therapy as well as possible future directions in this rapidly evolving field.