Frontiers in Cardiovascular Medicine

HIV infection significantly elevated the odds of cardiovascular diseases, including myocardial fibrosis. We aimed to determine the difference of late gadolinium enhancement (LGE), extracellular volume (ECV), T1, and T2 using cardiac magnetic resonance imaging (CMR) in patients living with HIV (PLWH) and healthy controls. The databases Scopus, Web of Science, Embase, and PubMed were searched systematically using relevant keywords. STATA version 17 was used for meta-analysis using random effect and fixed effect models for heterogeneous and non-heterogeneous analyses. An overall number of 13 studies were included in the current analysis involving 1425 PLWH and 766 healthy controls. PLWH showed significantly higher LGE (OR: 5.47, 95% CI: 1.90-15.64, p<0.001) and ECV (mean difference: 1.46, 95% CI: 0.21-2.71, p=0.02) compared to controls. However, differences in Left Ventricular Ejection Fraction (LVEF) were not significant (mean difference: -1.41, 95% CI: -2.81- -0.01, p=0.05). There were no meaningful disparities in pro B-type natriuretic peptide (BNP) values (mean difference: 8.67, 95% CI: 0.04-17.29, p=0.05) or T2 values (mean difference: 0.91 ms, 95% CI: -1.04-2.86, p=0.36), but T1 values were significantly higher in PLWH (mean difference: 13.78 ms, 95% CI: 9.16-18.40, p<0.001). In meta regression, LGE was correlated with nadir CD4 (z=-3.41, p-value<0.001). In addition, ECV was correlated with white race (Z=-3.97, p-value<0.001), Hepatitis C (Z=-2.08, p-value=0.037), and smoking (Z=2.05, p-value=0.041). HIV is related to a significantly elevated rate of myocardial fibrosis, and factors such as lower nadir CD4, white race, hepatitis C, and smoking were correlated with hepatitis C. Keywords: Myocardial fibrosis, HIV, AIDS, Cardiovascular diseases, Heart failure

Introduction: In hypertrophic cardiomyopathy (HCM), wall stress and subclinical myocardial injury related in part to pathological hypercontractility, which in turn are associated with worse outcomes. Cell-free DNA (cfDNA) is released from cardiomyocytes (cfDNA-CM) through irreversible cellular injury and death. We investigated the feasibility of quantifying cfDNA-CM and its relationship to HCM patient characteristics. Methods: We analyzed 57 plasma samples from stable patients with HCM and 10 plasma samples from patients with acute myocardial infarction (AMI). Plasma cfDNA was isolated from both groups. Whole genome bisulfite sequencing (WGBS) libraries were generated and sequenced with short-read sequencing. Methylation patterns were used for tissue deconvolution analysis and cell-specific cfDNA quantification. Results: Yields of cfDNA (p = 0.003) and cfDNA-CM (p = 0.002) fractions were higher in AMI controls than HCM, supporting the validity of the assay. Within the HCM cohort, the median cfDNA yield was 12.22 ng [IQR: 7.77, 18.94]. The cfDNA-CM fraction in this cohort ranged from 0% to 6.4% of total cfDNA. Higher cfDNA-CM tertiles were associated with higher body mass index (BMI, p=0.001), a greater prevalence of BMI 30 kg/m2 (p<0.001), and a higher prevalence of obstructive sleep apnea (p=0.038). No significant differences were observed in other demographic, genetic, and laboratory characteristics. Higher cfDNA-CM tertile was numerically associated with higher New York Heart Association (NYHA) functional class and left ventricular outflow tract (LVOT) obstruction, while circulating biomarkers of wall stress (NT-proBNP) and myocardial injury (troponin) did not differ across tertiles (p=0.83 and p=0.29, respectively). Conclusion: Isolation and quantification of cfDNA as well as detection of cfDNA-CM in chronic stable patients with HCM are feasible. Higher cfDNA-CM fraction was associated with increasing BMI and cardiometabolic comorbidity burden. The absence of association with traditional circulating biomarkers suggests that cfDNA-CM may reflect a distinct domain of myocardial health, injury, and adverse remodeling.

Abstract Background The SYNTAX score (SS) quantifies the severity and complexity of coronary artery lesions and serves as an independent predictor of major adverse cardiovascular events and mortality in patients with acute coronary syndrome (ACS). However, few studies have examined the association between SS and in-hospital cardiac arrest (IHCA) in this population. Therefore, this study aims to elucidate the relationship between SS and the incidence of IHCA in patients with ACS. Methods This study consecutively enrolled 3,224 patients undergoing percutaneous coronary intervention (PCI). Logistic regression and restricted cubic spline (RCS) analyses were employed to examine the association between SS and the incidence of IHCA. Participants were stratified into three groups based on SS: Group T1 (SS ? 10, N = 1,097), Group T2 (10 < SS ? 18, N = 1,089), and Group T3 (SS > 18, N = 1,038). The primary endpoint was the incidence of IHCA. Results The overall incidence of IHCA was 4% (N=147). After adjusting for covariates, SS was significantly associated with the incidence of IHCA in ACS patients treated with PCI (OR = 1.0400; 95% confidence interval (CI) = 1.0200?1.0700; p < 0.001). Compared with the T1 group, the T3 group exhibited an increased risk of IHCA (OR = 2.1800; 95% CI = 1.2900?3.6900; p = 0.0040). Subgroup analyses revealed that, after covariate adjustment, patients with ST-segment elevation myocardial infarction (STEMI) had an increased risk of IHCA (OR = 1.0700; 95% CI = 1.0300?1.1100; p < 0.001). Similarly, both patients with diabetes mellitus (DM) (OR = 1.0400; 95% CI = 1.000?1.0700; p = 0.0270) and those without DM (OR = 1.0600; 95% CI = 1.0200?1.1000; p = 0.0020) showed an increased risk. Furthermore, elderly patients (?60 years) (OR = 1.0300; 95% CI = 1.0100?1.0700; p = 0.0210) and non-elderly patients (<60 years) (OR = 1.0500; 95% CI = 1.000?1.1000; p = 0.0470) had an increased risk, as did male patients (OR = 1.0500; 95% CI = 1.0200?1.0700; p = 0.0020). RCS analysis indicated a dose-response relationship between IHCA incidence and SS (nonlinear p-value = 0.906), with the risk of IHCA increasing when SS exceeded 23.975. Incorporating SS into the baseline risk model improved the predictive value for IHCA incidence in ACS patients undergoing PCI (Net reclassification improvement [NRI]: 0.3537 [0.1906?0.5167], p < 0.001; Integrated discriminant improvement [IDI]: 0.0104 [0.0025?0.0183], p = 0.0097). Conclusions Among patients with ACS undergoing PCI, SS is significantly associated with the incidence of IHCA. Consequently, SS may serve as an effective predictor of IHCA in this population.

ImportanceCardiovascular disease remains the leading cause of mortality worldwide. Although machine learning models have demonstrated strong predictive performance, limited attention has been given to uncertainty quantification and gender-specific risk factor identification, which are essential for clinically trustworthy artificial intelligence. ObjectiveTo develop and evaluate an interpretable and uncertainty-aware machine learning framework for cardiovascular disease prediction that integrates an association study on biomarkers, explainable artificial intelligence, and gender-stratified risk assessment. Design, Setting, and ParticipantsThis retrospective observational study utilized the UCI Heart Disease dataset comprising 918 participants, including 725 males and 193 females. Demographic, clinical, laboratory, and exercise-related variables were analyzed. Missing values were addressed using a hybrid imputation strategy combining MICE and supervised Random Forest imputation. MethodsAn ensemble machine learning imputation strategy was developed to address missingness. Then advanced machine learning models were developed and evaluated using stratified training/testing partitions and 5-fold cross-validation. Predictive performance was assessed using several evaluation metrics. Uncertainty was quantified through bootstrap resampling, predictive entropy, and mutual information. Linear Double machine learning and Causal Forest double machine learning were applied to estimate gender-specific averages and association studies for risk factors. ResultsRandom Forest achieved the strongest and most stable predictive performance across male and female cohorts, with ROC-AUC values exceeding 0.90 and robust cross-validation performance. Hybrid imputation improved classification performance, increasing the F1-score from 0.87 to 0.89 and ROC-AUC from 0.90 to 0.92. The causal association study analyzes identified the number of major vessels, ST-segment slope, thalassemia, and exercise-induced angina as the strongest determinants of heart disease, with notable differences observed between male and female subgroups. Conclusions and RelevanceIntegrating predictive modeling, uncertainty quantification, and association study machine learning provides a robust and clinically interpretable framework for cardiovascular disease risk assessment. The proposed approach improves prediction reliability while identifying gender-specific causally important risk factors, supporting precision cardiovascular medicine and trustworthy clinical artificial intelligence.

Abstract Routine blood tests can be used to calculate several inflammation-related ratios, including the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and platelet-to-lymphocyte ratio (PLR). These indices are widely reported as markers of cardiovascular risk, but it is unclear whether they provide comparable information or whether SII, which is derived from platelet count and NLR, adds anything beyond NLR. We analyzed two independent samples from the National Health and Nutrition Examination Survey (NHANES): 15,141 adults from 2005-2010 (development cohort) and 15,392 adults from 2011-2016 (validation cohort), each with complete blood count data and linked mortality follow-up. Survey-weighted Cox models, restricted cubic splines, multiple imputation, and model comparison were used, and the development model was applied to the validation cohort. During a median follow-up of 11.4 years, 795 cardiovascular deaths occurred in the development cohort; the validation cohort recorded 364 cardiovascular deaths over 5.75 years. In the development cohort, hazard ratios per 1-SD increase were 1.32 (95% CI 1.21-1.44) for NLR, 1.21 (1.12-1.32) for SII, and 1.13 (1.04-1.22) for PLR. When NLR and SII were entered together, only NLR remained associated (HR 1.49, 1.23-1.81). The validation cohort showed the same pattern: NLR was strongest (HR 1.35, 1.22-1.49), and neither SII nor PLR remained significant after mutual adjustment. The frozen model showed good discrimination (C-index 0.8991 to 0.9023) and calibration (slope 0.96). Adding NLR produced only a small improvement in discrimination, and reclassification results were inconsistent between cohorts.

Background: Aortic stenosis (AS) is a valvular heart disease which imposes chronic pressure overload on the left ventricle (LV). Although LV remodelling may regress following aortic valve replacement, the molecular determinants of reverse remodelling remain poorly understood. This study develops a machine learning-based model using myocardial microRNA (miRNA) expression profiles to predict LV mass normalization one year after valve replacement. Methods: Consensus selection combining Random Forest and Bayesian Network analyses was applied to miRNA sequencing data from LV biopsies of 12 matched patient pairs with AS. Selected miRNAs were qPCR quantified in an extended cohort of 89 AS patients and incorporated into predictive models. Sex-stratified analyses were performed. Model robustness was assessed using bootstrap resampling and cross-validation. Candidate miRNAs and target genes were evaluated in LV from a murine model of pressure overload induced by transverse aortic constriction (TAC). Results: The combined Random Forest-Bayesian Network approach identified a three-miRNA signature (miR-517a-3p, miR-122b-5p, and miR-4683) associated with LV mass normalization after valve replacement. Validation in an extensive cohort demonstrated good overall discrimination and achieved its highest performance in women (AUC >0.80). Functional analyses identified drebrin (DBN1) as a putative target of miR-517a-3p and supported its potential involvement in pressure overload-induced cardiac remodelling. Conclusion: Random Forest and Bayesian Network integrated analyses enabled the identification of a myocardial miRNA signature with sex-dependent predictive value for reverse cardiac remodelling after aortic valve replacement. Functional validation supports the relevance of selected miRNAs and their downstream targets, highlighting their potential as biomarkers and candidate regulators of myocardial recovery.

Background This study presents reference ranges for cardiovascular magnetic resonance (CMR)-derived myocardial strain from the Healthy Hearts Consortium, while evaluating variations by demographic characteristics (age, sex, and ethnicity) and technical factors (scanner vendor, magnetic field strength). We derived reference ranges and centile-based categories for ventricular, atrial, and rapid strain parameters. The prognostic relevance of these categories was assessed by examining their associations with incident cardiovascular events. Methods The dataset included 9,088 CMR studies. Automated image analysis pipelines were established using suiteHEART (NeoSoft Inc.) and cvi42 (Circle Cardiovascular Imaging). A three-step quality control framework was applied including exclusion of incomplete data, visual assessment of image and segmentation quality, and statistical outlier removal. Ventricular strain and strain rate were measured using both software solutions. Additional cvi42 derived metrics included velocity and displacement, annular plane systolic excursion metrics, and rapid strain parameters. Age- and sex-specific reference ranges were generated using lambda-mu-sigma (LMS) modeling with penalized splines. Reference ranges were defined as values between the 2.5th and 97.5th percentiles. For lower-tail classification, values below the 2.5th percentile were considered mildly out-of-range and values below the 0.5th percentile at least moderately out-of-range. Differences across scanner vendors (Siemens, Philips, GE) and magnetic field strengths (1.5 T vs. 3 T) were evaluated using adjusted linear models. The prognostic relevance of selected cvi42-derived categories was evaluated in approximately 45,000 UK Biobank participants using Cox regression adjusted for age, sex, and body mass index. Results After quality control, 8,975 CMR examinations (cvi42) and 8,992 (suiteHEART) were available for analysis; these represent software-specific analytic cohorts. Most exclusions occurred during visual quality control. Women had higher absolute ventricular and atrial strain values than men across all age groups. Left ventricular (LV) longitudinal strain and strain rate were slightly lower in older ages, whereas circumferential and radial parameters remained largely stable. Left atrial strain was also lower in older age groups, while right atrial strain did not vary by age. Annular plane systolic excursion and rapid strain metrics showed similar sex-specific patterns, with modestly lower atrial and displacement values in older groups. Ethnicity-related differences were modest, heterogeneous, and substantially smaller in magnitude than age- and sex-related differences. Technical effects were parameter specific. While LV longitudinal and circumferential strains were largely unaffected, radial strain was higher at 3 T and showed vendor-related differences. LMS-derived reference ranges and centile thresholds were applied both across all ethnicities and within ethnicity-specific analyses, and are presented stratified by age and sex. In the prognostic analysis, centile categories were most consistently associated with incident heart failure. LV longitudinal, circumferential, and radial strain below the 0.5th centile were associated with significantly increased risk of incident heart failure (HRs: 9.9 to 12.4, 95% CIs 7.00-13.90 to 8.49-18.06). Conclusion This study provides age- and sex-specific reference ranges and centile-based categories for CMR-derived strain parameters in a large reference population. Age and sex represent the primary determinants of myocardial deformation, whereas scanner-related effects are parameter-specific. Values in the lower extremes of the healthy reference distribution, particularly for LV strain, are associated with increased risk of incident heart failure. These findings enable standardized, centile-based classification of myocardial strain, facilitating consistent interpretation and improving risk stratification in research and clinical practice.

Mitochondrial transplantation has recently emerged as an alternative treatment for cardiovascular disease (CVD), aimed at increasing mitochondrial number and improving mitochondrial function. Though mitochondrial dysfunction is a key factor in the development of right ventricular hypertrophy/failure, the effects of mitochondrial transplantation on disease mitigation have been largely unexplored. Therefore, this in vitro study aimed to determine whether the transplantation of exogenous L6 myotube mitochondria mitigates negative outcomes in H9C2 cardiomyocytes that were stimulated to hypertrophy with phenylephrine. Control (CTL), control with mitochondrial transplantation (MitoTx), Phenylephrine only (Phe-only), and phenylephrine with mitochondrial transplantation (Phe+MitoTx) treatments were evaluated. Pilot experiments indicated mitochondrial transplantation into healthy cardiomyocytes acutely increased Complex I-linked oxidative phosphorylation (OXPHOS) capacity (p=0.005) and maximal respiratory capacity (p=0.022) within 24 hours, and these data alongside microscopic evidence of fluorescently labeled L6 mitochondria in H9C2 cardiomyocytes suggested successful transplantation. Regarding treatment comparisons, Phe-only showed a significant increase in cell area (p<0.05), while Phe+MitoTx blunted the hypertrophic cardiomyocyte response. Consistent with these results, proteomic analysis of 4,806 proteins showed that transplantation enriched the mitochondrial proteome, impacting pathways including OXPHOS, respiration, fatty acid and amino acid metabolism, while suppressing extracellular matrix remodeling and de-differentiation signatures. This response was observed in healthy and phenylephrine-stressed cardiomyocytes. In conclusion, our in vitro data indicates that transplantation of L6 skeletal muscle mitochondria mitigates negative effects induced by phenylephrine in H9C2 cardiomyocytes. However, more rigorous in vivo studies are needed to determine if this is a suitable approach for disease mitigation.

Introduction: The femoropopliteal artery undergoes substantial axial compression, bending, torsion, and pinching during limb flexion. When an implanted stent does not accommodate these deformations, repetitive biomechanical mismatch may alter the vascular response to implantation and contribute to restenosis. We tested whether designing a peripheral stent to better accommodate physiologic limb-flexion deformation reduces the subsequent inflammatory and neointimal response. Methods: A nitinol stent was developed using multi-objective computational optimization to maintain arterial apposition while reducing wall stress and luminal pinching during physiologic deformation. Sixteen Yucatan minipigs were studied in independent 3- and 6-month cohorts (n=8 each). Each animal received the optimized stent in one limb and a commercial stent with representative biomechanical behavior contralaterally. CTA quantified in vivo limb-flexion deformation, while CT and histology assessed stenosis, neointimal accumulation, inflammatory-cell burden, SMA-positive tissue, and extracellular-matrix composition. Results: The optimized stent accommodated greater axial shortening than the commercial comparator at both 3 months (11.2{+/-}2.7% vs. 6.6{+/-}2.1%, p=0.003) and 6 months (13.7{+/-}4.4% vs. 6.8{+/-}2.3%, p=0.004). Intimal hyperplasia volume was lower with the optimized stent at 3 months (227.5{+/-}85.2 vs. 350.0{+/-}130.5 mm3, p=0.002) and 6 months (183.6{+/-}46.2 vs. 261.2{+/-}60.6 mm3, p=0.001), with significantly lower maximum, mean, and median stenosis at both timepoints. At 3 months, macrophage and total inflammatory-cell counts were 51% and 45% lower, respectively, with the optimized stent. Histologic tissue area was 28% lower at 3 months and 12% lower at 6 months. SMA-positive tissue fraction was higher with the optimized stent at both timepoints, whereas elastin, glycosaminoglycan, and collagen fractions were similar between devices. Discussion: Improved accommodation of limb-flexion deformation was associated with a smaller inflammatory and neointimal response to stent implantation through 6 months, while overall neointimal matrix composition remained largely unchanged. These findings provide in vivo evidence that biomechanical compatibility with the dynamic lower-limb environment can influence vascular healing and should be considered a mechanistic design criterion for peripheral artery stents.

Background: Growth differentiation factor 15 (GDF-15) has emerged as a prognostic biomarker in patients with non-ST-segment-elevation acute coronary syndrome (NSTE-ACS). Our study evaluated the temporal evolution of GDF-15 in the acute phase and its association with recurrent ischemic events. Methods: Serum samples were collected from patients with NSTE-ACS at admission and at 1 and 3 hours after admission. GDF-15 levels, along with other prognostic biomarkers, NT-proBNP and hs-cTnT, were measured. Spearman rank-correlation coefficients and linear regression models were used to identify the variables associated with GDF-15 levels at admission and with their temporal changes. Associations between GDF-15 and clinical outcomes were evaluated using Cox proportional hazards models. To assess incremental prognostic value, the areas under the curve (AUC) were calculated for each model. Results: GDF-15 levels showed a slight increasing trend within 3 hours of admission. The 1-hour change in GDF-15 was correlated with hs-cTnT changes. Increased 1-hour GDF-15 levels, compared with the admission levels, were associated with a higher risk of recurrent ischemic events during the 1-year follow-up (1.9% vs. 17.5%, P =0.019) and were an independent predictor after adjusting for established clinical variables and biomarkers (adjusted hazard ratio, 1.71 (1.28 to 228.75), P =0.03). Furthermore, serial measurements of GDF-15 provided additional prognostic information beyond traditional risk factors. Conclusions: Serial measurements of GDF-15 of NSTE-ACS patients provided independent and incremental prognostic value for predicting recurrent ischemic events. These findings support the potential utility of GDF-15 as a dynamic biomarker for early risk stratification in the acute management of NSTE-ACS.

Background: Hypertension is a major risk factor for type B aortic dissections and rupture, with guidelines recommending systolic blood pressure (SBP) control below 130 mmHg to improve outcomes. While post-TEVAR blood pressure is often managed with a focus on mean SBP, little is known about temporal hemodynamic patterns and their association with surgical success. This study investigates blood pressure and heart rate (HR) time-series metrics within 24 hours post-TEVAR and their predictive potential for outcomes. Methods: Blood pressure (n = 560) and HR (n = 680) time-series data from 31 patients were analyzed alongside preoperative aortic geometry metrics. Exploratory data analysis identified correlations between BP variability and outcomes. Stationarity tests were performed on time-series data to assess statistical properties. Logistic regression models incorporating hemodynamic metrics, along with CT-derived features, were used to predict TEVAR outcomes. Results: Successful outcomes correlated with greater diastolic blood pressure variability and strictly stationary SBP. Logistic regression models combining these metrics along with heart rate standard deviation and preoperative aortic geometry achieved 96.67% 5-fold cross-validation accuracy in predicting outcomes. Conclusion: Post-TEVAR behaviors of hemodynamic variables are critical predictors of TEVAR success, with higher DBP standard deviation and strict stationarity of SBP significantly associated with favorable outcomes. These findings highlight the importance of hemodynamic variability and stationarity in optimizing post-TEVAR patient care.

Background: Transthoracic echocardiography (TTE) remains the gold standard for assessing left ventricular (LV) diastolic dysfunction (DD), but noninvasive alternatives are needed to overcome geometric and acoustic limitations. 4D-Flow MRI enables comprehensive assessment of intraventricular pressure differences (IVPDs) and flow propagation velocity (VP). We aimed to evaluate 4D-Flow-derived IVPDs and VP in patients with hypertrophic cardiomyopathy (HCM). Methods: Thirty-eight HCM patients and 38 age- and sex-matched healthy controls underwent TTE and 4D-Flow MRI. Spatiotemporal maps of velocity and IVPDs, decomposed into inertial and convective components, were derived along the main inflow streamline from the mitral valve to the apex. Peak early filling rate (PEFR) was used to normalize IVPDs and VP. Results: While absolute peak flow rates were comparable, HCM patients exhibited significantly faster VP (100.4 vs. 60.2 cm/s, p < 0.01) and higher positive early E IVPD (1.40 vs. 0.92 mmHg, p < 0.01) compared to controls. Normalizing IVPDs by PEFR amplified group differences, revealing a markedly increased flow-normalized E-IVPD (5.13 vs. 2.94 x 103 mmHg.ml1.s, p < 0.001) and deeper reverse ER IVPD (-6.06 vs. -4.61 x 103 mmHg.ml1.s, p < 0.01) in HCM. These differences were primarily driven by the inertial components. Multivariable analysis demonstrated that ER IVPD is independently determined by PEFR and the TTE E/E' ratio (r = 0.65, p < 0.001). Conclusions: 4D-Flow MRI-derived, flow-normalized IVPDs and propagation velocity provide robust, noninvasive markers of altered LV chamber stiffness and impaired diastolic filling in HCM, offering deeper 3D hemodynamic insights into diastolic dysfunction.

Purpose: Atrial fibrosis is associated with thromboembolic risk in atrial fibrillation, but how fibrosis-related contractile impairment alters blood transport in the left atrium (LA) and left atrial appendage (LAA) remains unclear. Prior multi-physics simulations coupled electromechanical (EM) and computational fluid dynamics (CFD) models to show that fibrosis impairs LA function and flow, but were limited to booster-only contraction and could not separate the effects of fibrosis burden from its spatial distribution. Here we examined how fibrosis burden and spatial pattern independently relate to long-term LA and LAA hemodynamics in full-cycle, multi-beat simulations on a common LA anatomy. Methods: Three fibrosis patterns derived from late gadolinium enhancement MRI were considered: one from the patient providing the common anatomy and two from additional patients, with the latter mapped onto the common anatomy via universal atrial coordinates. All three patterns were applied globally at matched burdens of 15.6% and 31.2%, yielding six global-fibrosis cases and a non-fibrotic reference. Two patterns were also confined to the LAA at three local burdens (10%, 25%, and 50%), yielding six LAA-fibrosis cases. A 3D EM model for the LA anatomy was coupled to a 0D circulatory model, so that the simulations resolved the reservoir, conduit, and booster phases. Full-cycle EM-derived wall motion drove subsequent multi-beat CFD simulations. Region-specific emptying fraction (EF), non-dimensional kinetic energy (KE), and the 90th percentile of blood residence time (TR) were evaluated for the LA and LAA. Results: Left ventricular stroke volume remained nearly constant across cases, while increasing global fibrosis burden progressively reduced LA and LAA EF (LA: 36% to 30-31%; LAA: 44% to 28-38%) and monotonically increased LA TR across all patterns. Non-dimensional LA KE showed an approximately quadratic association with LA EF across patterns, whereas LAA KE was more scattered but still increased with LAA EF. In contrast, the relationship between the 90th percentile of LAA TR and LAA EF showed pattern-specific, non-monotonic trends. Conclusions: Fibrosis burden and spatial distribution jointly shape LA and LAA hemodynamics, but through different mechanisms. LAA EF is a robust functional descriptor of chamber-averaged kinetic energy regardless of fibrosis pattern, whereas LAA blood stasis depends additionally on the spatial distribution of fibrosis beyond what bulk emptying fraction predicts. These findings support incorporating imaging-derived fibrosis pattern, and not only burden, alongside functional metrics when assessing thrombogenic risk in the LAA.

BACKGROUND: The chromosome 9p21.3 locus is among the strongest genetic risk loci for cardiovascular disease (CVD), yet the regulatory mechanisms underlying this association remain poorly understood. Previous vascular disease studies focused predominantly on the role of this locus in smooth muscle cell (SMC) dysfunction, whereas its potential role in endothelial cells (ECs) remains less well characterized. Here, we sought to identify candidate regulatory variants at 9p21.3, their distal target genes, and effector transcripts that contribute to CVD-related phenotypes in ECs. METHODS: Promoter capture Hi-C was used to map chromatin interactions at 9p21.3 in primary human ascending aortic SMCs (n=6), supplementing the previously obtained ECs (n=16) dataset. To support the regulatory relevance of these interactions, expression quantitative trait locus analysis was performed in 136 vascular biopsies. Variant effects were prioritized in silico using AlphaGenome. The regulatory activity of the prioritized region was validated using CRISPR activation. RESULTS: Chromatin interaction mapping identified a complex regulatory architecture at the 9p21.3 locus involving 19 putative regulatory elements and 15 genes across ECs and SMCs. MIR31HG showed the most recurrent distal promoter connectivity with the 9p21.3 region. Consistent with the chromatin interaction map, expression of MIR31HG transcripts was associated with genetic variation at the 9p21.3 locus. In ECs, the lncRNA MIR31HG, but not miR-31, was responsive to hemodynamic flow. Depletion of MIR31HG in ECs was associated with endothelial activation. Epigenetic tracks and deep learning predictions highlighted an active enhancer element at 9p21.3, which was subsequently validated by CRISPR activation and increased MIR31HG expression, confirming its capacity to regulate MIR31HG over a large genomic distance of approximately 538 kb. CONCLUSIONS: Altogether, these data implicate lncRNA MIR31HG as a likely effector of the 9p21.3 CVD locus, linking the cis-regulatory element and heritable genetic variation in the respective region to endothelial activation through long-range enhancer regulation.

Background: Mitral regurgitation (MR) is a common complication of mitral valve prolapse (MVP) and increases left ventricular (LV) preload, promotes LV remodeling and hypertrophy, but its impact on myocardial perfusion and coronary microvascular dysfunction remains unclear. Objectives: To assess myocardial perfusion using, for the first time, quantitative cardiac magnetic resonance (CMR) perfusion mapping in patients with significant MR due to MVP. Methods: Patients with significant primary MR, without coronary artery disease were prospectively enrolled and compared to age- and sex-matched controls without MR. All underwent 1.5T CMR including cine imaging, adenosine stress perfusion, native T1, native T2, extracellular volume (ECV) mapping and late gadolinium enhancement (LGE). Myocardial perfusion reserve (MPR) was calculated as the ratio of stress to rest myocardial perfusion. Results: In total 33 patients and 33 controls were included (age 56{+/-}13 vs. 58{+/-}12 years, 46% women in both groups). Patients with MR had increased LV mass and volumes, higher native T1 and ECV and a higher prevalence of LGE (36% vs 0%). No differences were observed in global myocardial perfusion at rest (0.88{+/-}0.27 vs. 0.85{+/-}0.30, p=0.52), at stress (2.6{+/-}0.56 vs. 2.8{+/-}0.73 ml/min/g, p=0.29) or for MPR (3.1{+/-}0.75 vs. 3.4{+/-}1.0, p=0.24). In age- and sex-adjusted linear regression, higher NYHA class was associated with lower MPR (0.60, p=0.04). Conclusion: In patients with significant MR due to MVP, myocardial perfusion appears preserved despite LV volume overload. However, lower MPR in symptomatic patients suggests that microvascular dysfunction may emerge in a more advanced disease stage.

BACKGROUND: While the systemic right and left ventricles have different functional prognoses, only a limited number of reports have addressed their myocardial architecture. This study analyzed myofiber orientation of human specimens with various congenital heart diseases using X-ray phase-contrast tomography. METHODS: Three specimens of each normal heart, ventricular septal defect, right atrial isomerism, left atrial isomerism, and ventricular inversion were examined. In reconstructed images of both ventricles, the center of the free wall was resliced parallel to the myocardial surface. A myofiber helical angle was identified in each slice and plotted from epicardium to endocardium. The plotted curves were compared between both ventricles. RESULTS: In all ventricles, the helical angle was changed from left-handed on epicardial slices to right-handed on endocardial slices. Whereas the right ventricle?s helical angle curves showed a plateau with or without a rapid rise on the endocardial side, the left ventricle?s curves had sustained increase with or without a plateau in the middle. The median wall-thickness?scaled helical angle change rates were 53{degrees} and 102{degrees} in the right and left ventricle, respectively, and their distribution of each specimen was higher in the left ventricle than in the right ventricle. CONCLUSIONS: Ventricular myofiber orientation has a consistent transmural helical transition independently of cardiac morphology and looping. Their transitions can have a plateau and rapid changes permitting the identification of layers within the ventricular wall. The left ventricle has more helical fibers and the right ventricle has more circumferential fibers, which may explain their difference of ventricular performance.

BACKGROUND: Because of the high mortality rate associated with fulminant myocarditis (FM), there is limited evidence regarding the prognostic efficacy of endomyocardial biopsy (EMB). In this study, we aimed to evaluate the influence of EMB in the early phase after admission on treatment and prognosis in FM using a large-scale nationwide registry in Japan. METHODS: Patients with FM who required catecholamine or mechanical circulatory support between 2012 and 2017 from 235 hospitals across Japan were included. The primary outcome of death or heart transplantation within 90 days according to performance of early EMB were determined using Kaplan-Meier and Cox regression analyses. Factors associated with performance of early EMB, and subsequent medical treatment were analyzed. RESULTS: The median age of 736 patients with clinical FM was 56 years, and 407 patients (55%) received EMB. Most EMB (89%) were performed during the early phase (within 5 days of admission) and 63% were performed on the first day of admission. The prognosis of FM patients who underwent EMB was more favorable than that of those who did not based on the landmark analysis (log-rank test, P=0.04). Factor analysis demonstrated that FM patients who underwent EMB had a lower left ventricular ejection fraction, higher incidence of cardiogenic shock on admission, and higher rate of early mechanical circulatory support, as well as early initiation of corticosteroids and guideline-directed medical therapy (GDMT) for heart failure. Absence of any GDMT was associated with a less favorable prognosis on multivariate analysis (hazard ratio, 4.34 [95% CI, 3.14?6.01]; P<0.0001). CONCLUSIONS: Although performing EMB in the early phase after admission depends on disease severity in FM patients, it is associated with early initiation of advanced medical treatment and may contribute to improving the prognosis.

Background: Mitral valve prolapse (MVP) causes mitral regurgitation (MR), leading to volume overload and maladaptive left ventricular (LV) remodelling. Objective: To comprehensively characterize markers of maladaptive LV remodelling across MR severity grades in MVP using cardiovascular magnetic resonance (CMR), and their association with functional status. Methods: Patients with MVP undergoing 1.5T CMR (2016-2025) were stratified by MR fraction: mild<20%, moderate 20-39%, and severe [&ge;]40%. Exclusion criteria were significant coronary artery disease, rheumatic valve disease, mitral stenosis, previous mitral valve procedures, endocarditis or signs of primary cardiomyopathy. Global native T1, T2, extracellular volume (ECV), indexed ECV (iECV), indexed intracellular volume (iICV), and late gadolinium enhancement (LGE) were quantified. Indexed LV end-diastolic volume (EDVI) and the EDV-to-LV mass ratio (EDV/LVM-ratio) were also calculated as indices of LV remodelling and adaptive hypertrophy. Functional status was assessed by NYHA class. Results: Among 112 MVP patients (23 mild, 48 moderate, 41 severe MR) and 20 controls, LGE prevalence (17% vs. 46% vs. 51% vs. 0%) and the proportion with LV dilatation (46% vs. 67% vs. 88% vs 15%) rose progressively with MR severity. Increased EDVI, prevalence of LGE, higher EDV/LVM-ratio, global native T1 and iECV showed the strongest associations with more severe MR, whereas EDV/LVM-ratio, iECV and global native T1 were independently related to NYHA class[&ge;]II. Conclusions: CMR markers of maladaptive LV remodelling were abnormal across all MR grades and increased markedly with MR severity. Global native T1, iECV and EDV/LVM-ratio correlated most strongly with symptom burden, rather than MR severity per se.

Aims: Myocardial strain enables sensitive assessment of cardiac function, but its clinical application has largely focused on individual chambers or selected patient populations. We evaluated the feasibility and clinical relevance of fully automated multi-chamber strain assessment in consecutive patients undergoing routine transthoracic echocardiography (TTE). Methods and results: This retrospective study included 8,350 consecutive adults undergoing TTE. A hospital-wide artificial intelligence (AI)-based system automatically measured left ventricular (LV) global longitudinal strain (LVGLS), left atrial (LA) reservoir strain (LASr), and right ventricular (RV) free-wall strain (RVFWS). AI-derived LVGLS was available from at least one apical view in 97.1% of patients and from all three views in 94.8%; LASr and RVFWS were available in 94.1% and 94.5%, respectively, resulting in complete multi-chamber strain assessment in 90.3%. Strain measures showed modest correlations with conventional chamber-specific echocardiographic parameters and differential associations with clinical outcomes. Gaussian mixture modeling identified three distinct clusters characterized by preserved multi-chamber function, RV-dominant dysfunction, and pan-chamber dysfunction. Compared with the preserved cluster, pan-chamber dysfunction was associated with the highest risk of all-cause death or heart failure hospitalization (adjusted hazard ratio, 3.44; 95% CI, 2.43-4.88; P<0.001). Prognostic associations remained evident in patients with LV ejection fraction (LVEF) [&ge;]50%, and cluster assignment provided incremental prognostic information beyond clinical factors, LVEF, and RV fractional area change. Conclusions: Fully automated multi-chamber strain assessment was feasible in a large consecutive TTE cohort. Integrating strain across cardiac chambers may provide complementary functional characterization and identify clinically relevant clusters with prognostic information beyond conventional assessment.

The biomechanical properties of the human aorta play a key role in cardiovascular function and disease, yet their population-wide trends and variations remain largely unknown. To fill this crucial gap, we quantified variations in aortic size, stiffness and stresses across 57,434 individuals from the UK Biobank using two-dimensional cine MR imaging and a combined deep-learning, probabilistic and biomechanical modelling framework. Aortic diameter and distensibility (inverse of stiffness) were calculated for the ascending and descending aorta, and their conditional distributions were characterised as a function of age, sex, body size and blood pressure. These observations were integrated with ex-vivo tissue mechanics to infer stress distributions across the aortic wall and the associated uncertainty. Our analysis revealed several new relationships. Larger aortas were found to be stiffer, and greater body size (height and/or weight) was associated with larger aortas with no change in stiffness. Aortic distensibility was negatively associated with systolic, but not diastolic, blood pressure. Apparent sex differences in aortic size were substantially reduced after accounting for body size. Importantly, the maximum stress was found to depend not only on aortic size, as previously thought, but also on distensibility, with lower distensibility associated with higher stresses. The results provide first-of-their-kind population-scale reference distributions for human aortic stiffness, which will improve the personalisation of computational models and digital twins. The correlation between stress and distensibility strongly supports progressing beyond the current diameter-based criteria (based on the law of Laplace) and for the inclusion of stiffness in the clinical risk assessment of aortic diseases. Overall, this study forms the foundation for personalised quantitative medicine and biomechanically informed risk stratification of aortic aneurysms and dissections.