Renata Agoston

Objectives: The presence of a bicuspid aortic valve (BAV) is known to alter transvalvular flow and increase shear stress on the ascending aorta, contributing to alterations in aortic geometry and the progression of BAV-related aortopathy. The purpose of the current study was to characterize aortic flow abnormalities and their associations with aortic geometry and ventricular mechanics using cardiac magnetic resonance imaging (CMR). Methods: In this prospective cross-sectional study, 56 young adults with CMR-confirmed BAV and 56 age- and sex-matched healthy volunteers underwent standardized CMR. Biventricular volumes and function, LV global longitudinal strain (LV-GLS), LV torsional mechanics, ascending aortic geometry, pulse-wave velocity, aortic distensibility, and two-dimensional phase-contrast-derived forward and backward flow parameters were quantified. Associations between myocardial mechanics and haemodynamic variables were assessed using correlation analyses and multivariable linear regression. Results: Compared with healthy controls, patients with BAV exhibited preserved LV ejection fraction but impaired LV-GLS, reduced LV torsion, increased aortic stiffness, and a significantly greater backward-flow burden despite similar net aortic flow (all p < 0.001). Higher peak backward-to-forward flow-rate ratios were associated with less negative LV-GLS (p = 0.006), whereas greater aortic regurgitant volume was also associated with impaired longitudinal deformation (p = 0.001). In multivariable analysis, LV-GLS and aortic regurgitant volume remained associated with the peak backward-to-forward flow-rate ratio within the specified model, whereas ascending-aortic dimensions were not. The final model explained 52% of the variability in backward-flow burden. Conclusions: CMR identified a subclinical ventricular-aortic phenotype in young adults with BAV characterized by altered LV mechanics, increased aortic stiffness, and greater relative backward-flow burden despite preserved conventional LV systolic function. The association between backward-flow burden and LV longitudinal mechanics suggests that these abnormalities may represent interrelated manifestations of BAV disease; however, their temporal and causal relationships cannot be established from this cross-sectional study.

Background/Objectives: Bicuspid aortic valve (BAV) is frequently associated with valvular dysfunction and aortic remodeling. This exploratory study examined cross-sectional associations between circulating extracellular matrix-related biomarkers and concurrent echocardiographic characteristics in children with BAV. Methods: We included 43 pediatric participants—26 with BAV and 17 with tricuspid aortic valves (TAV). All participants underwent clinical assessment, transthoracic echocardiography, and serum biomarker quantification at the same study visit. MMP-2, MMP-9, TIMP-1, and TGF-β1 were measured using ELISA. Biomarker levels were compared between the BAV and TAV groups and, within the BAV group, according to the presence of concurrent aortopathy, aortic stenosis, and aortic regurgitation. Results: MMP-9, TIMP-1, and the MMP-9/TIMP-1 ratio were higher in the BAV group than in the TAV comparison group. Within the BAV cohort, none of the investigated biomarkers differed significantly between participants with and without aortopathy. TGF-β1 was higher in BAV patients with aortic stenosis, whereas the MMP-9/TIMP-1 ratio showed a borderline difference according to aortic regurgitation status; these subgroup findings are exploratory and limited by small sample size and multiple comparisons. Conclusions: In this selected pediatric cohort, circulating MMP-9 and TIMP-1 levels differed between children with BAV and the TAV comparison group. However, none of the investigated biomarkers differed significantly between BAV patients with and without aortopathy. These cross-sectional findings describe exploratory associations with the BAV phenotype but do not establish diagnostic, predictive, or prognostic utility. Larger longitudinal studies including the broader clinical spectrum of BAV and independent validation cohorts are required.

Background: Sudden cardiac death (SCD) is a major challenge in dilated (DCM) and non-dilated left ventricular cardiomyopathy (NDLVC). Current management strategies, based on left ventricular ejection fraction (LVEF), the presence or extent of myocardial scar, and selected high-risk genetic variants, are insufficient to accurately identify patients at risk. Mechanical dispersion (MD), derived from speckle-tracking echocardiography, is a potential marker of arrhythmic risk that reflects variability in regional myocardial contraction timing. Aim: The purpose of this narrative review is to synthesize current evidence on the predictive role of MD for ventricular arrhythmias (VA) and SCD in DCM and NDLVC, with particular emphasis on its relationship to myocardial fibrosis (MF) and established echocardiographic markers. Results: Across prospective and retrospective cohorts of DCM patients, increased MD has consistently identified individuals at higher arrhythmic risk, often independently of LVEF and global longitudinal strain (GLS). Reported threshold values for risk prediction range from 50 ms to 90 ms, with hazard ratios confirming incremental prognostic accuracy. The relationship between MD and MF assessed by late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) remains uncertain: some patients experience VA in the absence of LGE, while others display elevated MD despite no detectable focal MF, suggesting that additional mechanisms contribute to the arrhythmogenic substrate in DCM and NDLVC. Conclusions: MD may enhance SCD risk stratification in DCM and NDLVC by reflecting components of the arrhythmic substrate that are not detected by conventional markers.

Background/Objectives: For many years, catheter ablation (CA) has been a cornerstone in atrial fibrillation (AF) rhythm control therapy; however, recurrence remains common. Multiple parameters have been proposed to quantify AF arrhythmogenic substrate, yet reliable predictors of long-term outcomes are lacking. To assess the value of non-invasive amplified P-wave duration (PWD), echocardiographic parameters, biomarkers, and electroanatomical mapping (EAM) were used in predicting left atrial (LA) fibrosis and arrhythmia recurrence after CA. Methods: We included 196 patients undergoing first CA for paroxysmal or persistent AF. Amplified 12-lead ECG PWD parameters [Pmax, Pmin and left atrial P-wave (LAP)], echocardiographic parameters, and biomarkers were assessed pre-procedure. We measured low-voltage areas (LVA, 0.2–0.5 mV) on high-density voltage EAM during sinus rhythm as a surrogate of fibrosis. Freedom from arrhythmia was evaluated at 6 and 12 months. Results: Patients with LVA on EAM had prolonged Pmax (148 vs. 135 ms, p < 0.0001), Pmin (111 vs. 101.5 ms, p = 0.0001), LAP (73.5 vs. 55.5 ms, p < 0.0001), larger LA diameter (p = 0.0002), area (p = 0.0365) and volume (p = 0.004), higher E/E’ (p = 0.0007) and E/A ratios (p = 0.037), more mitral regurgitation (p = 0.0315), and higher pro-BNP levels (p = 0.0094). Univariate analysis showed 12-month recurrence rates higher with greater Pmax, Pmin, LAP, LVA presence and extent; however, in multivariate analysis, only P-wave parameters remained independently associated with recurrence. Conclusions: Prolonged PWD parameters strongly reflect LA substrate (Pmax, Pmin) and independently predict post-ablation AF recurrence (Pmax, Pmin, and LAP). LA size, diastolic dysfunction, and mitral regurgitation were associated with LA fibrosis, while pro-BNP was associated with both fibrosis and arrhythmia recurrence. Integrating these simple, non-invasive markers into a multimodal assessment alongside EAM could improve pre-procedural risk stratification and guide individualized ablation strategies.

Introduction: Cholangiocarcinoma (CCA) is a highly lethal malignancy originating in the bile ducts, often diagnosed late with poor prognosis. Differentiating benign from malignant biliary tumors remains challenging, necessitating advanced diagnostic techniques. Objective: This study aims to enhance the diagnostic accuracy of endoscopic ultrasound (EUS) for distal cholangiocarcinoma (dCCA) using advanced convolutional neural networks (CCNs) for the classification and segmentation of EUS images, specifically targeting dCCAs, the pancreas, and the bile duct. Materials and Methods: In this retrospective study, EUS images from patients diagnosed with dCCA via biopsy and an EUS-identified bile duct tumor were evaluated. A custom CNN was developed for classification, trained on 156 EUS images. To enhance the model’s robustness, image augmentation techniques were applied, generating a total of 1248 images. For tumor and organ segmentation, the DeepLabv3+ network with ResNet50 architecture was utilized, employing Tversky loss to manage unbalanced classes. Performance evaluation included metrics such as accuracy, sensitivity, specificity, and Intersection over Union (IoU). These methods were implemented in collaboration with the ADAPTED Research Group at the Technical University of Cluj-Napoca. Results: The classification model achieved a high accuracy of 97.82%, with precision and specificity both at 100% and sensitivity at 94.44%. The segmentation models for the pancreas and bile duct demonstrated global accuracies of 84% and 90%, respectively, with robust IoU scores indicating good overlap between predicted and actual contours. The application performed better than the UNet model, particularly in generalization and boundary delineation. Conclusions: This study demonstrates the significant potential of AI in EUS imaging for dCCA, presenting a robust tool that enhances diagnostic accuracy and efficiency. The developed MATLAB application serves as a valuable aid for medical professionals, facilitating informed decision-making and improving patient outcomes in the diagnosis of cholangiocarcinoma and related pathologies.

Background: Cholangiocarcinoma (CCA) is a highly aggressive cancer of the bile ducts with a poor prognosis and limited diagnostic markers. This study aims to investigate the potential of miR-18a and miR-532 as biomarkers for CCA by exploring their correlations with clinical parameters and traditional tumor markers such as CA19.9, CEA, and AFP. Methods: This study involved a cohort of patients diagnosed with CCA. Serum levels of miR-18a and miR-532 were measured and analyzed in relation to various clinical parameters, including age, tumor markers, and histological features. Results: Serum levels of miR-18a and miR-532 were upregulated in patients with extrahepatic cholangiocarcinoma (eCCA) compared to healthy controls (p < 0.05). MiR-18a and miR-532 levels were correlated with each other (p = 0.011, Spearman’s rho = 0.482) but showed no significant correlation with age or traditional tumor markers (CA19.9, CEA, AFP). No significant differences in miR-18a and miR-532 levels were observed concerning tumor localization or histological grading. For predicting tumor resectability, miR-532 at a cut-off point of 2.12 showed a sensitivity of 72.73%, specificity of 81.25%, and an AUC of 71.3%, while miR-18a, at a cut-off of 1.83, had a sensitivity of 63.64%, specificity of 75%, and an AUC of 59.7%. ROC curve analysis suggested moderate diagnostic potential for miR-18a and miR-532, with AUC values of 0.64 and 0.689, respectively. Conclusions: Although miR-18a and miR-532 showed significant upregulation in eCCA patients compared to healthy controls, they did not demonstrate significant associations with key clinical parameters, limiting their effectiveness as standalone diagnostic biomarkers. Further research involving larger, multi-center cohorts and additional molecular markers is necessary to validate these findings and explore the broader diagnostic potential of miRNAs in CCA.

Background: Aortic valve stenosis (AS) is the most common degenerative valvular heart disease, significantly impacting the outcome. Current guidelines recommend valve replacement only for symptomatic patients, but advanced cardiovascular imaging, particularly cardiac magnetic resonance (CMR), may refine these recommendations. Feature-tracking CMR (FT-CMR) effectively assesses left ventricular (LV) strain and shows promise in predicting major adverse cardiovascular events (MACEs), though data on AS are limited. This study explored the role of CMR-derived LV strain in predicting MACEs occurrence in patients with severe AS. Method: We prospectively assessed 84 patients with severe AS and 84 matched controls. Global longitudinal (GLS), circumferential (GCS), and radial strain (GRS) were evaluated using FT-CMR. A composite endpoint—cardiac death, ventricular tachyarrhythmias, and heart failure hospitalization—was analyzed over a median follow-up of 31 months. Results: GLS was considerably reduced in AS patients (−15.8% vs. −19.7%, p < 0.001) and significantly predicted MACEs (HR = 1.24, p = 0.002) after adjusting for LVEF, 6 min walk distance, native T1, and late gadolinium enhancement. This underscores GLS’s unique and robust predictive capability for MACEs in severe AS patients. Kaplan–Meier curves and ROC analysis both showed that GLS had the highest predictive performance for MACEs, with an AUC of 0.857. Conclusions: GLS provided independent incremental predictive value for outcome.

In this single-center cross-sectional study on patients undergoing coronary computed tomography angiography (CCTA), we assessed the prognostic significance of metabolic dysfunction associated steatotic liver disease (MASLD), metabolic syndrome (MetS), and CCTA-derived parameters for predicting major adverse cardiovascular events (MACE). Over a mean follow-up of 26.9 months, 2038 patients were analyzed, with 361 (17.7%) experiencing MACE. MASLD was associated with a higher MACE incidence (25.90% vs. 14.71% without MASLD, p < 0.001). Cox regression revealed significant associations between MASLD, coronary calcium score (CCS), number of plaques (NoP), epicardial fat volume (EFV), and MACE, with hazard ratios of 1.843, 1.001, 1.097, and 1.035, respectively (p < 0.001 for all). A composite risk score integrating CCS, NoP, EFV, and MASLD demonstrated superior predictive value for MACE (AUC = 0.948) compared to individual variables (p < 0.0001 for all). In conclusion, MASLD is linked to an elevated risk of MACE, and a comprehensive risk-scoring system incorporating imaging and clinical factors enhances MACE prediction accuracy.

Extrahepatic cholangiocarcinoma (CCA) is a rare and aggressive type of cancer, presenting as a mass or as a biliary stricture. This review summarizes the utility of endoscopic ultrasound (EUS) in the detection, staging, and determination of the differential diagnosis, especially when no cause of bile duct dilatation is revealed by cross-sectional imaging. The EUS detection rate for distal CCAs is higher than that for the proximal CCAs. The accuracy of T staging varies between 60 and 80%, and vascular involvement is correctly assessed by conventional EUS. EUS-tissue acquisition from the primary tumors is reserved for unresectable or metastatic CCA, especially in distal strictures or mass CCAs. For proximal lesions, EUS could be performed as an adjunctive to ERCP sampling when the latter is inconclusive. EUS is not appropriate for assessing the malignant features of lymph nodes in CCAs. Lymph node EUS-tissue acquisition should be performed only if it changes the surgical decision. Perhaps the development of EUS-fine needle biopsy and the detection of molecular genetic alteration will increase the diagnostic yield in CCAs.

Background: Myocardial scarring is a primary pathogenetic process in nonischemic dilated cardiomyopathy (NIDCM) that is responsible for progressive cardiac remodeling and heart failure, severely impacting the survival of these patients. Although several collagen turnover biomarkers have been associated with myocardial fibrosis, their clinical utility is still limited. Late gadolinium enhancement (LGE) determined by cardiac magnetic resonance imaging (CMR) has become a feasible method to detect myocardial replacement fibrosis. We sought to evaluate the association between collagen turnover biomarkers and replacement myocardial scarring by CMR and, also, to test their ability to predict outcome in conjunction with LGE in patients with NIDCM. Method: We conducted a prospective study on 194 patients (48.7 ± 14.3 years of age; 74% male gender) with NIDCM. The inclusion criteria were similar to those for the definition of NIDCM, performed exclusively by CMR: (1) LV dilation with an LV end-diastolic volume (LVEDV) of over 97 mL/m²; (2) global LV dysfunction, expressed as a decreased LVEF of under 45%. CMR was used to determine the presence and extent of LGE. Several collagen turnover biomarkers were determined at diagnosis, comprising galectin-3 (Gal3), procollagen type I carboxy-terminal pro-peptide (PICP) and N-terminal pro-peptide of procollagen type III (PIIINP). A composite outcome (all-cause mortality, ventricular tachyarrhythmias, heart failure hospitalization) was ascertained over a median of 26 months. Results: Gal3, PICP and PIIINP were considerably increased in those with LGE+ (p < 0.001), also being directly correlated with LGE mass (r² = 0.42; r² = 0.44; r² = 0.31; all p < 0.001). Receiver operating characteristic (ROC) analysis revealed a significant ability to diagnose LGE, with an area under the ROC of 0.816 for Gal3, 0.705 for PICP, and 0.757 for PIIINP (all p < 0.0001). Kaplan–Meier analysis showed that at a threshold of >13.8 ng/dL for Gal3 and >97 ng/dL for PICP, they were able to significantly predict outcome (HR = 2.66, p < 0.001; HR = 1.93, p < 0.002). Of all patients, 17% (n = 33) reached the outcome. In multivariate analysis, after adjustment for covariates, only LGE+ and Gal3+ remained independent predictors for outcome (p = 0.008; p = 0.04). Nonetheless, collagen turnover biomarkers were closely related to HF severity, providing incremental predictive value for severely decreased LVEF of under 30% in patients with NIDCM, beyond that with LGE alone. Conclusions: In patients with NIDCM, circulating collagen turnover biomarkers such as Gal3, PICP and PIIINP are closely related to the presence and extent of LGE and can significantly predict cardiovascular outcome. The joint use of LGE with Gal3 and PICP significantly improved outcome prediction.