Search Results (637)

Transcatheter aortic valve implantation (TAVI) has become the predominant treatment strategy for severe aortic stenosis across all surgical risk categories. The coexistence of coronary artery disease (CAD) in 40–75% of TAVI candidates has traditionally mandated pre-procedural invasive coronary angiography (ICA). However, computed tomography coronary angiography (CTCA), which is already integral to TAVI planning for annular sizing and access route evaluation, offers the potential to assess coronary anatomy simultaneously. Accumulating evidence demonstrates that CTCA possesses excellent sensitivity (90–97%) and high negative predictive value (94–99%) for excluding significant proximal CAD, potentially serving as a reliable gatekeeper to avoid unnecessary ICA in a substantial proportion of patients. This approach is particularly attractive given the questionable benefit of routine pre-emptive coronary revascularization in stable TAVI candidates, as demonstrated by the ACTIVATION and NOTION-3 trials. This review synthesizes the current evidence on the diagnostic performance of CTCA, clinical outcomes with CT-guided strategies, technical considerations and limitations, and the evolving paradigm of coronary assessment in the contemporary TAVI era. We propose a practical algorithm integrating CTCA as a first-line screening tool, reserving ICA for patients with suspected significant proximal disease, thereby optimizing resource utilization while maintaining patient safety. Full article

Background: Artificial intelligence-based computer-aided detection (AI-CAD) systems are increasingly being used in endovascular practice to support time-sensitive detection, triage and prioritization tasks in imaging and procedural workflows. Despite rapid technological advancements and expanding regulatory clearances, the translation to lasting clinical benefit varies. Objective: This narrative review synthesizes AI-CAD applications in endovascular interventions and proposes an evaluation-oriented framework to support responsible clinical translation; this framework emphasizes detection-specific metrics, external validation, bias-aware assessment, and workflow integration. Methods: A structured narrative review was conducted using targeted searches in PubMed, Google Scholar, and IEEE Xplore (2020–2026); this review was supported by an examination of US FDA device databases and citation tracking. Evidence was assessed using a pragmatic hierarchical classification framework based on regulatory status and validation rigor. Results: AI-CAD applications were mapped across four main endovascular domains: neurovascular interventions (e.g., large vessel occlusion triage), coronary interventions (CCTA-based stenosis detection and intravascular imaging support), aortic interventions/EVAR (endoleak detection and sac monitoring), and peripheral interventions (lesion detection and angiographic decision support). Across the domains, performance reporting was heterogeneous and often relied on retrospective, single-center assessments. Key barriers to clinical readiness included acquisition variability and dataset shift due to artifacts, limited multicenter validation, annotation variability, and human–AI workflow factors. Evaluation priorities included whether to assess at the lesion level or case level, false positive burden and calibration, external validation under real-world heterogeneity, and clinical impact measures such as treatment timing and procedural decision-making. Conclusions: AI-CAD systems hold significant potential for improving endovascular care; however, clinical readiness depends on rigorous, endovascular feature-specific assessment and transparent reporting, beyond retrospective accuracy. The proposed evidence level framework and assessment checklist provide practical tools for distinguishing mature technologies from research prototypes and guiding future validation, implementation, and post-market monitoring. Full article

Cardiovascular emergencies most frequently arise from the sudden destabilization of atherosclerotic plaques. Conventional diagnostic strategies predominantly focus on luminal stenosis, despite the fact that most acute coronary events originate from non-obstructive lesions with high inflammatory activity. Recent advances in cardiac computed tomography (CCT) enable visualization of plaque morphology and surrounding perivascular fat, offering a unique window into coronary inflammation. The fat attenuation index (FAI), derived from pericoronary adipose tissue (PCAT) radiodensity, has emerged as a dynamic imaging biomarker capable of detecting vascular inflammation before clinical events occur. This review summarizes current evidence on the role of PCAT inflammation in plaque vulnerability, its implications for acute cardiovascular presentations, and recent technological innovations—including AI-enhanced analysis and photon-counting CT—that advance risk prediction. Inflammation-based imaging derived from CCT, including PCAT-FAI, has emerged as a promising research tool that may enhance risk stratification in patients presenting with chest pain. These developments signify a shift from purely anatomical assessment toward biological characterization of CAD, potentially transforming prevention and acute care. Full article

Background: Sortilin (SORT1), linked to the 1p13.3 coronary risk locus, is implicated in lipid trafficking and atherogenesis; however, clinical studies of circulating SORT1 have produced inconsistent results. We evaluated whether circulating SORT1 is associated with angiographic burden and lesion localization in patients with premature or early clinical debut coronary atherosclerosis. Methods: This single-center, cross-sectional study analyzed a dataset collected from January to May 2023. Participants were classified as coronary atherosclerosis cases if the dataset contained an age of clinical debut of clinically significant atherosclerosis (n = 101). Controls had no recorded debut age and 0% stenosis in all assessed coronary segments (n = 27). Blood was collected in clot activator tubes; serum was stored at −40 °C until analysis. SORT1 (ng/mL) was measured using an Aviscera Bioscience ELISA. Coronary stenoses were recorded as percent diameter stenosis for left main (LM), proximal/mid/distal LAD, proximal/mid/distal LCx, and proximal/mid/distal RCA. Burden metrics included the number of segments with any stenosis (>0%), the number of obstructive segments (≥50%), the number of diseased vessels, and maximum stenosis. The prespecified primary endpoint was obstructive proximal LAD stenosis (≥50%). Nonparametric tests and Spearman correlations were used. Logistic regression evaluated the association between log2-transformed SORT1 and proximal LAD obstruction, adjusted for age, sex, LDL-C, statin use, and smoking/diabetes/hypertension durations. Results: SORT1 was higher in cases than controls (8.60 [2.60–17.10] vs. 2.30 [1.25–10.65] ng/mL; p = 0.0058). Within cases, SORT1 did not correlate with global angiographic burden (any-stenosis segments: ρ = −0.066, p = 0.513; obstructive segments: ρ = −0.060, p = 0.552; diseased vessels: ρ = −0.045, p = 0.652; maximum stenosis: ρ = −0.084, p = 0.403). Obstructive proximal LAD stenosis occurred in 44/101 (43.6%) and was associated with higher SORT1 (12.25 [4.18–17.45] vs. 4.10 [2.20–11.60] ng/mL; p = 0.0093). Each doubling of SORT1 was independently associated with proximal LAD obstruction (adjusted OR 1.48, 95% CI 1.12–1.95; p = 0.005). Conclusions: In this cross-sectional cohort, circulating SORT1 was associated with obstructive proximal LAD stenosis but not with global angiographic burden metrics. These findings are hypothesis-generating and warrant validation in independent cohorts with standardized preanalytics and prospective designs to assess temporal relationships and clinical utility. Full article

Background/Objectives: We assessed the prevalence of impaired coronary flow velocity reserve (CFVR) and aimed to identify echocardiographic and clinical predictors of coronary microvascular dysfunction in adolescents after neonatal arterial switch operation (ASO). Methods: This single-center, cross-sectional study included patients that underwent neonatal ASO for simple D-transposition of the great arteries (D-TGA) during 1998–2013. All patients were evaluated by echocardiography with global left ventricular strain measurement (GLS) and cardiac catheterization, including coronary angiography. Coronary flow velocity reserve was assessed by transthoracic Doppler echocardiography in the left anterior descending artery (LAD) using adenosine induced hyperemia. Patients were stratified into two groups according to CFVR: group with impaired CFVR (<2.5) and group with normal CFVR (≥2.5). Spearman correlation was used to assess the relationship between CFVR and echocardiographic variables. Binary logistic regression was used to determine independent predictors of impaired CFVR. Results: Out of 48 patients included (median age 16 years, age range 13 to 23 years, 71% male), impaired CFVR was found in 21 patients (44%). These patients had decreased longitudinal tricuspid annular plane systolic excursion (TAPSE), greater Z scores for left ventricular end-systolic dimensions and higher mean pulmonary artery pressures (mPAP). CFVR showed modest but significant positive correlations with tricuspid annular plane systolic excursion (TAPSE). Left pulmonary artery branch stenosis, reduced TAPSE and mPAP ≥ 20 mmHg, were significantly associated with impaired CFVR, while decreased TAPSE remained independent predictor in multivariable analysis (odds ratio 5.6, 95% confidence interval 1.24–25.26, p = 0.025). Conclusions: Impaired CFVR appears to be frequently observed in adolescents after uncomplicated neonatal ASO for simple D-TGA. Importantly, impaired CFVR is associated with right ventricular dysfunction. Full article

Background: Patients with NSTEMI who are found with a totally occluded culprit vessel on coronary angiography are at higher risk of mortality and major adverse cardiac events. Artificial intelligence (AI) models can help identify this subgroup of NSTEMIs. Objectives: The purpose of this study was to examine the performance of an AI model in identifying patients with total thrombotic coronary artery occlusion myocardial infarctions (OMIs) using a single 12-lead ECG as input. Methods: In this retrospective cohort study, 12-lead ECGs corresponding to patients with suspected OMI were analyzed by an AI model. Confirmation of OMI was based on angiographic evidence of acute culprit coronary artery stenosis. Results: Over a one-year period, emergency physicians at our hospital identified 474 patients with suspected OMI, of whom 88 met STEMI criteria. Out of the 142 angiographically confirmed OMIs, the AI model correctly identified 115 (81%) with high confidence, corresponding to an accuracy of 89.4%, sensitivity of 90.0%, specificity of 93.2%, positive predictive value (PPV) of 84.6%, and negative predictive value (NPV) of 91.4%. Out of the 74 angiographically confirmed OMIs that did not meet STEMI criteria, the AI model correctly identified 49 (66%) with high confidence, corresponding to an accuracy of 87.9%, sensitivity of 66.2%, specificity of 93.4%, PPV of 72.1%, and NPV of 91.5%. Out of the 68 angiographically confirmed OMIs that met STEMI criteria, the AI model correctly identified 66 (97%) with high confidence, corresponding to an accuracy of 95.5%, sensitivity of 97.1%, specificity of 90.0%, PPV of 97.1%, and NPV of 90.0%. Conclusions: The AI model examined in this study outperformed the STEMI criteria for the identification of OMI with respect to accuracy, sensitivity, specificity, PPV, and NPV and accurately identified a significant portion of NSTEMIs found to have total thrombotic coronary artery occlusion. Full article

Objective: To evaluate the performance of photon-counting detector CT (PCD-CT) angiography for the detection and quantification of vascular stenosis. Methods: Web of Science, PubMed, and Cochrane databases were searched from January 1980 to December 2025 to identify studies assessing PCD-CT angiography for the detection and quantification of vascular stenosis, using invasive angiography as the reference standard. The risk of bias of the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. Diagnostic performance metrics, including sensitivity and specificity and quantification values, were extracted from the included studies and a formal narrative synthesis was performed. The meta-analysis included studies reporting true-positive, false-positive, true-negative, and false-negative data. A meta-analysis was conducted only when a minimum of two eligible studies assessed diagnostic performance within the given vascular territory. Statistical analyses were performed using R software (v4.5.0), applying a random-effects model for the meta-analysis. Results: Of 415 identified studies, 20 were included in the systematic review, comprising a total of 9165 participants, with the majority (17/20, 85%) focusing on coronary artery stenosis. In the meta-analysis of three studies, ultra-high-resolution (UHR) PCD-CT demonstrated excellent diagnostic performance for detecting coronary stenosis for patients with ≥50%, having a pooled sensitivity of 96.1% (95% confidence level (CI): 89.3–99.6), specificity of 87.5% (95% CI: 78.2–93.3), positive predictive value (PPV) of 91.9% (95% CI: 70.3–98.2), and negative predictive value (NPV) of 94.8% (95% CI: 86.0–98.6). Compared with conventional energy-integrating detector CT (EID-CT), PCD-CT consistently showed superior diagnostic performance, particularly in the specificity and PPV. In terms of stenosis quantification, PCD-CT showed closer agreement with reference standards than EID-CT, leading to the reclassification of coronary stenosis severity in up to 49% of patients. Evidence for non-coronary vascular territories, including intracranial and peripheral arteries remains limited but suggests promising diagnostic performance. For lower-limb arterial stenosis, the reported sensitivity was 77.4–91%, and specificity was 72.1–91%. For intracranial in-stent stenosis, PCD-CT demonstrated a sensitivity of 100% and a specificity of 89%. Conclusions: PCD-CT angiography provides high diagnostic performance and improved stenosis quantification for coronary artery stenosis. UHR PCD-CT has excellent diagnostic performance for detecting coronary stenosis and consistently outperforms conventional EID-CT, especially in the specificity and positive predictive value. Full article

Lipoprotein(a) [Lp(a)] is a low-density lipoprotein-like particle that contains a unique apolipoprotein(a) [apo(a)] component covalently bound to apolipoprotein B-100. Elevated levels of Lp(a) have been identified as a well-established and genetically determined risk factor for atherosclerotic cardiovascular disease, including coronary artery disease, stroke, and calcific aortic valve stenosis. In contrast to other lipids, Lp(a) concentrations are minimally influenced by lifestyle or traditional lipid-lowering therapies, emphasizing the necessity for novel treatment approaches. This narrative review summarizes current and emerging therapeutic strategies for reducing Lp(a) levels. Such strategies include traditional agents such as niacin and PCSK9 inhibitors, as well as innovative therapies such as antisense oligonucleotides, RNA interference-based molecules, and small-molecule inhibitors. The mechanisms of action of these agents, in addition to clinical trial data and their capacity to modify cardiovascular outcomes, are explored in further detail. Furthermore, the current status of clinical guidelines and the evolving role of Lp(a)-targeted therapies in cardiovascular risk stratification are reviewed. A particular emphasis is placed on therapies that are in the advanced stages of clinical development. These include late-phase outcome trials and orally administered agents, which have the potential to significantly impact future clinical practice. The integration of mechanistic data with ongoing and completed clinical studies has been undertaken in order to provide a comprehensive framework for understanding the therapeutic potential of Lp(a) in the context of cardiovascular prevention. Full article

Background and Objectives: This study aimed to compare coronary plaque characteristics between Asian and European populations undergoing coronary CT angiography and to examine associations between cardiovascular risk factors and coronary artery calcification. Materials and Methods: In this retrospective, two-center, cross-sectional observational study, 1591 adult patients (1203 of Asian and 388 of European descent) referred for coronary computed tomography angiography (CCTA) due to suspected coronary artery disease between 2008 and 2025 were included. Demographic, clinical characteristics, and laboratory data were obtained from medical records. Computed tomography (CT) was performed on different CT scanners, including a 64-slice Siemens SOMATOM Definition AS, a 250-slice Siemens SOMATOM, a 640-slice multi-detector Canon Aquilion ONE, and a 128-slice multi-detector GE Revolution scanner with prospective cardiac synchronization and 0.6 mm slice reconstruction. Coronary artery calcium (CAC) scores were quantified using automated software “Vitrea”. Associations between ethnicity, cardiovascular risk factors, and CAC were assessed using non-parametric analyses and multivariable regression models. Stata 18 software was used for all statistical analyses. Results: European participants demonstrated a higher prevalence of obesity, hypertension, tobacco use, and alcohol consumption compared with Asian participants. The prevalence of CAC > 0 was higher in Europeans than in Asians (60.6% vs. 50.3%, p < 0.01). European individuals were independently associated with CAC presence in multivariable analysis. Multivessel (≥2-vessel) stenosis and calcified plaques were more frequently observed in Europeans, whereas non-calcified and low-density plaques predominated among Asians. Conclusions: Within this referral-based cohort, differences in coronary plaque characteristics were observed between the studied groups within this clinical CCTA cohort. The European group was associated with a higher prevalence of calcified plaques, whereas non-calcified and low-density plaques were more frequently observed among Asian participants. These findings show associations between ethnicity and plaque characteristics within a clinical cohort and require confirmation in prospective studies. Full article

Background: The relationship between testosterone and coronary artery disease (CAD) remains a subject of debate. Most studies suggest an inverse association—lower testosterone, higher risk. However, data from Central European populations undergoing coronary angiography are limited. Objectives: To investigate the association between serum testosterone levels and angiographically confirmed coronary artery stenosis in a Slovak population. Methods: This cross-sectional study included 129 consecutive stable patients (84 men, 45 women; mean age 64.3 ± 9.7 years) undergoing elective coronary angiography for suspected stable coronary artery disease. Significant coronary stenosis was defined as ≥50% luminal narrowing in any major epicardial vessel. Serum testosterone, lipid profile, and traditional risk factors were assessed. Univariate and multivariate logistic regression models were constructed to evaluate independent associations of coronary stenosis. Results: Coronary stenosis ≥ 50% was present in 74 patients (57.4%). Notably, patients with stenosis had significantly higher testosterone levels (6.62 ± 2.79 vs. 4.85 ± 3.50 ng/mL, p = 0.002). In univariate analysis, testosterone showed a significant association (OR 1.197 per ng/mL, OR 1.784 per SD, p = 0.003). In multivariate analysis adjusted for age, sex, diabetes mellitus, and LDL (low-density lipoprotein) cholesterol, testosterone remained independently associated (adjusted OR 2.043 per SD, 95% CI 1.221–3.420, p = 0.007), as did diabetes mellitus (OR 2.60, p = 0.032). Conclusions: Elevated serum testosterone is paradoxically associated with increased prevalence of coronary stenosis in our cohort. These findings from stable, chronic CAD patients may work fundamentally differently from what is observed in acute coronary syndromes, where stress-induced testosterone suppression may confound observed associations. Full article

A significant proportion of patients undergoing invasive coronary angiography for angina have no obstructive coronary artery disease (CAD). In such patients, coronary microvascular dysfunction (CMD) and vasospastic angina (VSA) represent key pathophysiological mechanisms. We report a case of a 58-year-old male with exertional chest pain and exercise ECG changes typical of left main or multivessel CAD. Coronary computed tomography angiography (CCTA) showed borderline stenosis of the distal left main coronary artery. Coronary angiography revealed no critical stenosis. A comprehensive functional assessment demonstrated reduced coronary flow reserve (CFR = 2.0) and an elevated index of microcirculatory resistance (IMR = 25), consistent with CMD. An intracoronary acetylcholine provocation test induced severe focal vasospasm of the mid-left anterior descending artery (LAD) with ST-segment elevation and anginal pain, promptly relieved by nitroglycerin, confirming VSA. This case highlights the diagnostic and clinical importance of invasive functional testing in patients with angina and non-obstructive coronary arteries (ANOCA/INOCA). The coexistence of CMD and VSA (two distinct but overlapping pathophysiological endotypes) is increasingly recognized as a marker of adverse prognosis. Functional coronary assessment should be considered in all patients with angina and non-obstructive coronary arteries, as identifying mixed endotypes enables precise, mechanism-guided therapy. Full article

Background and Objectives: Non-O ABO blood groups have been linked to higher coronary risk, plausibly via hemostatic and lipid pathways. However, evidence in Japanese populations and imaging-defined disease is limited. We examined whether ABO status relates to serum lipids and coronary CT imaging findings in Japanese adults. Materials and Methods: We reviewed adults who underwent coronary CT angiography (CCTA) at our institution. After prespecified exclusions, 865 patients comprised the imaging cohort. For lipid analyses, we excluded patients receiving lipid-lowering therapy at the time of blood sampling, leaving 636 patients (lipid subset). ABO blood group was obtained from the medical record as recorded at registration (patient-reported) and was not re-confirmed by laboratory testing for this study. Outcomes were any coronary artery calcium (Agatston score > 0) and ≥50% luminal stenosis on CCTA. Results: In the lipid subset (n = 636), coronary calcium was present in 44–54% of patients across the four ABO groups and did not differ across groups (p = 0.33). Among assessable scans in the imaging cohort, ≥50% stenosis did not differ across the four ABO groups. In multivariable models (n = 636), older age, male sex, hypertension, and diabetes were independently associated with both outcomes (CAC presence and ≥50% stenosis) (all p < 0.05). For ≥50% stenosis, higher High-Density Lipoprotein-cholesterol (HDL-C) was additionally associated with lower odds (p < 0.05). ABO status (O vs. non-O) was not independently associated with either outcome. Conclusions: In Japanese adults undergoing CCTA, type O blood was tied to lower HDL-C and higher diastolic pressure—features that track with cardiometabolic risk—yet ABO type did not independently relate to coronary calcium or CT-defined stenosis once standard risk factors were considered. These data suggest that, in this setting, ABO adds little beyond conventional risk profiling. Full article

Objectives: To assess the diagnostic accuracy of a deep learning (DL)-based algorithm for non-invasive computation of fractional flow reserve (FFR-CT) from coronary computed tomography angiography (CCTA) and to evaluate the model’s ability to automatically assign cardiovascular risk categories according to the Coronary Artery Disease–Reporting and Data System (CAD-RADS). Materials and Methods: Sixty patients with suspected coronary artery disease who underwent both CCTA and invasive coronary angiography (ICA) were retrospectively included in this multicenter study. Curved multiplanar reconstructions derived from CCTA were analyzed by the deep learning-based model to estimate FFR-CT values and to automatically assign CAD-RADS risk categories. The diagnostic performance of the software for the identification of hemodynamically significant coronary stenoses was evaluated using ICA as the reference standard. Receiver operating characteristic (ROC) curve analysis was performed to determine the area under the curve (AUC), sensitivity, and specificity on both a per-patient and per-vessel basis. Finally, agreement between CAD-RADS risk categories assigned by the DL algorithm and those determined by an expert radiologist was assessed. Results: FFR-CT demonstrated high diagnostic accuracy, with AUC of 0.935, sensitivity of 93.2%, specificity of 93.7%, and excellent agreement with reference standard (k = 0.836) on a per-patient level. Per-vessel diagnostic performance was consistently high across all major coronary arteries, with the left anterior descending artery (LAD) showing the highest accuracy (AUC = 0.932). Automated CAD-RADS classifications generated by the software showed good agreement with those assigned by human (k = 0.765). Conclusions: The DL-based model demonstrated high diagnostic accuracy and represents a promising noninvasive approach for ischemia assessment and cardiovascular risk stratification. Full article

Background: The optimal management strategy for 50–70% chronic coronary artery stenosis in patients undergoing aortic valve surgery for aortic regurgitation (AR) remains controversial. This study evaluates the prognostic impact of chronic coronary obstruction severity on surgical outcomes and mid-term survival. Methods: This retrospective cohort study included 717 patients undergoing aortic valve surgery for AR, grouped by coronary stenosis into <50% (n = 641) and 50–70% (n = 76). Following 1:1 propensity score matching (72 patients per group), the primary outcome of major adverse cardiovascular events (MACE) and the secondary outcome of all-cause death were compared. Results: No intergroup differences emerged in perioperative mortality (1.32% vs. 1.56%, p = 1.000) or complication rate. With a median follow-up of 2.53 years, 50–70% coronary obstruction does not increase MACE (HR = 2.050; 95% CI 0.375–11.197; log-rank p = 0.397) and all-cause mortality (HR = 0.710; 95% CI 0.200–2.522; log-rank p = 0.595). Similar results were obtained in the competing risk regression and multivariable analyses. Conclusions: In patients with AR, 50–70% chronic coronary obstruction does not increase perioperative complications, MACE, and all-cause mortality. Full article

Transcatheter aortic valve replacement (TAVR) has revolutionized the treatment of severe aortic stenosis, evolving from a therapy reserved for inoperable patients to a first-line option across all surgical risk categories. As TAVR expands to younger patients with longer life expectancies, lifetime management strategies become paramount. This comprehensive review examines the important role of computed tomography (CT) planning in optimizing initial valve selection and predicting future reintervention feasibility. We discuss the decision framework between TAVR and surgical aortic valve replacement (SAVR) as initial therapy, strategies to optimize the index TAVR procedure, including minimizing patient-prosthesis mismatch, reducing paravalvular regurgitation, preventing conduction abnormalities and coronary obstruction, and facilitating future reinterventions. For patients requiring redo procedures, we analyse TAVR-in-TAVR considerations, including risk plane assessment, coronary access preservation, and leaflet modification techniques. Future directions include advances in valve design, artificial intelligence integration in procedural planning, and development of personalized risk assessment tools. Successful lifetime management requires multidisciplinary collaboration and individualized treatment planning to optimize outcomes throughout a patient’s lifetime journey with aortic valve disease. Full article