Frontiers in Cardiovascular Medicine

BackgroundThe adult mammalian heart lacks the regenerative potential required to replenish depleted cardiomyocytes and restore cardiac function after injury. Ischemic cardiac injury contributes to heart failure, a leading cause of death worldwide. Neonatal mice possess the capacity to regenerate injured myocardium and macrophages contribute to this process. The mechanisms contributing to the regenerative crosstalk between macrophages and cardiomyocytes remain incompletely elucidated and offer potential to inform future therapeutic strategies. MethodsTo test the immune contribution during cardiac regeneration, we studied the response to myocardial ischemia in neonatal mice after silencing myeloid hypoxia inducible factor 1 (Hif1) and reconstituting HIF-dependent mitogens. In parallel, we examined epigenetic and transcriptional signatures of the cardiac macrophage response and focused on intercellular crosstalk with cardiomyocytes. ResultsIn myeloid Hif1 deficient mice, cardiac regenerative function was lost after coronary ligation. This manifested through loss of ventricular systolic function and elevated myocardial scarring. HIF1 was found to be activated in resident-type cardiac macrophages after ischemic insult. Hypoxia stimulated macrophages to secrete insulin-like growth factor 1 (IGF-1), and this required Hif1. Parallel multiomic analysis revealed epigenetic regenerative signatures. ConclusionsThe data reveal an age-restricted requirement for myeloid Hif1 in neonatal cardiac regeneration, likely through IGF-1 signaling.

Backgound: Accurate assessment of diastolic function and left ventricular (LV) filling pressure is central to heart failure diagnosis and risk stratification. Contemporary guideline algorithms rely on complex parameters that are not consistently available in routine clinical practice. Objective: To compare the diagnostic and prognostic performance of the 2016 American Society of Echocardiography/European Association of Cardiovascular Imaging (ASE/EACVI) and 2025 ASE guidelines with a deep learning model based on routinely acquired echocardiographic variables. Methods: This study evaluated the guideline-based algorithms and a deep learning model in participants from the Atherosclerosis Risk in Communities (ARIC) cohort (n=5450) for prognostication and two invasive hemodynamic validation cohorts from the United States (n=83) and Japan (n=130) for detection of elevated left ventricular filling pressure. Results: In the ARIC cohort, the deep learning model demonstrated superior prognostic performance compared with the 2016 and 2025 guidelines (C-index: 0.676 vs. 0.638 and 0.602, respectively; both p<0.001). Similar findings were observed among participants with preserved ejection fraction (C-index: 0.660 vs. 0.628 and 0.590; both p<0.001), with improved performance compared with the H2FPEF score (C-index: 0.660 vs. 0.607; p<0.001). In the US hemodynamic validation cohort, the deep learning model showed higher diagnostic performance than the 2025 guidelines (AUC: 0.879 vs. 0.822; p=0.041) and similar performance compared with the 2016 guidelines (AUC: 0.879 vs. 0.812; p=0.138). In the Japanese hemodynamic validation cohort, the deep learning model outperformed both guidelines (AUC: 0.816 vs. 0.634 and 0.694; both p<0.05). Conclusions: A deep learning model leveraging routinely available echocardiographic parameters demonstrated improved diagnostic and prognostic performance compared with contemporary guideline-based approaches, potentially offering a scalable alternative for assessing diastolic function and left ventricular filling pressures.

Abstract Background: Hypertrophic (HCM) and dilated (DCM) cardiomyopathy constitute the principal phenotypes of primary cardiomyopathy, yet both lack sufficient therapeutic options. Integrating genetic insights with detailed cardiac phenotyping offers a promising strategy to prioritize targets and elucidate their mechanisms of action. Methods: We conducted an three-stage analysis. First, drug-target Mendelian randomization (MR) was performed using cis-acting protein (pQTL) and expression (eQTL) quantitative trait loci as genetic instruments for potential drug targets. Second, we examined causal associations between 82 cardiac magnetic resonance (CMR)-derived imaging traits and HCM/DCM risk in a CMR-based MR analysis. Third, mediation MR was employed to quantify the proportion of the genetic effect of prioritized drug targets on cardiomyopathy risk that was mediated through specific CMR phenotypes. Results: Our analyses identified 19 and 13 potential therapeutic targets for HCM and DCM, respectively. CMR-based MR revealed that HCM risk was causally associated with increased right ventricular ejection fraction (RVEF) and greater left ventricular wall thickness, whereas DCM risk was linked to ventricular dilation, impaired myocardial strain, and altered aortic dimensions. Critically, mediation analysis established that these CMR traits served as significant intermediate pathways. The protective effect of ALPK3 on HCM risk was mediated through a reduction in myocardial wall thickness. Conversely, the effects of PDLIM5, HSPA4, and FBXO32 on DCM risk were exerted in part via alterations in aortic dimensions. Conclusion: This integrative genetic and imaging study systematically identify candidate therapeutic targets for HCM and DCM and delineates the specific CMR phenotypes through which they likely exert their causal effects. Our findings advance the understanding of disease pathogenesis and highlight new possibilities for improving the diagnosis and management of cardiomyopathy.

Introduction: Accurate stratification of hard atherosclerotic cardiovascular disease (ASCVD) risk remains challenging despite advances in prevention. Liver function biomarkers (LFBs), particularly gamma - glutamyl transferase (GGT), have been linked to cardiovascular outcomes, yet their contribution to hard ASCVD risk prediction is not well defined. Methods: This study analyzed data from the National Health and Nutrition Examination Survey (NHANES, 2005 - 2018) to assess cross - sectional associations between LFBs and 10 - year hard ASCVD risk estimated by the ACC/AHA Pooled Cohort Equations. Multivariable regression, restricted cubic splines, and mediation analyses were applied to examine independent and dose - response relationships. External validation was performed in the China Health and Retirement Longitudinal Study (CHARLS) and NHANES using machine learning models (CoxBoost, Naive Bayes and Random Forest). Results: Among 5,731 NHANES participants, GGT showed an independent linear association with hard ASCVD risk (P - trend = 0.003), partly mediated by systolic blood pressure (44.8%), HbA1c (19.0%), and high density lipoprotein cholesterol (13.4%). Machine learning (ML) models incorporating GGT, alkaline phosphatase (ALP), and globulin alongside traditional risk factors improved predictive accuracy, with Naive Bayes achieving an AUC of 0.751 in NHANES validation. Conclusions: GGT is an independent and biologically plausible biomarker of hard ASCVD risk, acting through cardiometabolic pathways. Incorporating LFBs into risk prediction models, particularly with machine learning, enhances risk stratification and may facilitate early identification of high - risk individuals.

BackgroundAccurate assessment of left ventricular outflow tract (LVOT) gradients is critical for hypertrophic cardiomyopathy (HCM) management, yet Doppler-based measurements are technically demanding and require expertise. ObjectiveTo develop a multi-view deep learning model capable of classifying LVOT obstruction (> 20mmHg) using routine 2D echocardiographic windows without reliance on Doppler imaging. MethodsWe trained and externally validated a cross-attention-based video-to-video fusion framework that integrated EchoPrime-derived video representations from three standard transthoracic echocardiographic views to classify LVOT gradients. ResultsTraining was performed on a derivation cohort (N = 1833) from a tertiary care system in the United States, with model performance evaluated on an internal held-out test set (N = 275) and a Korean external validation cohort (N = 46). Single-view baselines showed limited discrimination (external AUROCs 0.47-0.70). Conversely, domain-specific foundational model (EchoPrime) achieved superior single-view performance (AUROCs 0.75-0.80 internal; 0.79-0.83 external), highlighting the importance of echo-specific pretraining and temporal modeling. The proposed multi-view fusion further enhanced predictive performance, with the late fusion model reaching an AUROC of 0.84 on the external cohort with significant population-shift. ConclusionsThese results suggest LVOT physiology is encoded in routine 2D imaging and can be leveraged for clinically relevant gradient classification without Doppler input- proposed AI-guided strategy demonstrates substantial cost savings compared with the screen-all approach. By integrating complementary spatial-temporal information across multiple views, our approach generalizes robustly across populations and may enable real-time decision support, extend LVOT assessment to portable or resource-limited settings, and complement Doppler-based evaluation for longitudinal HCM management.

Cardiovascular disease (CVD) remains the leading cause of mortality in the United States, despite being largely preventable through effective management of risk factors. This study evaluates the impact of Phase II cardiac rehabilitation (CR) on functional capacity and quality of life, using data from the Montana Outcomes Project Cardiac Rehabilitation Registry. Functional capacity improvements were assessed via the six-minute walk test (6MWT) and Dartmouth COOP questionnaire, with statistical analyses exploring the influence of CR session attendance, demographic factors, and referring diagnoses. Results demonstrated significant gains in 6MWT, with a mean improvement of 330.73 feet (p < .0001), and quality of life scores across all subgroups. A dose-response relationship was observed, indicating greater improvements with increased CR sessions (p < .0001), though diminishing returns were observed beyond 24-35 visits. Demographic factors and complex conditions influenced outcomes, underscoring the need for tailored strategies to enhance CR access and effectiveness. These findings highlight the critical role of CR in improving patient outcomes and emphasize the importance of addressing barriers to participation in underserved populations.

Abstract Aims: While traditional anthropometric indices are established cardiovascular predictors, their prognostic value for incident infective endocarditis (IE) remains undefined. Methods: We included 386,859 participants (mean age 57.0 years; 52.9% female) from the UK Biobank between 2006 and 2010 with standardized baseline data on BMI, waist circumference (WC), waist-to-height ratio (WhtR), and the triglyceride-glucose (TyG) index.Multivariable Cox proportional hazard models with restricted cubic splines were used to estimate the hazard ratio (HR) of these indices, adjusting for demographic and clinical risk factors. Results: Over 16.87 median years (25th, 16.02; 75th, 17.60 percentile) of follow-up, there were a total of 1,124 incident IE events. During the follow-up period, 38,342 total deaths were recorded, of which 8,524 were cardiovascular disease (CVD)-related.Overall, compared to individuals with normal weight and baseline metabolic indices, those in the fourth quartile of WC, WHtR, and TyG index exhibited the highest risk of incident IE. Compared to other metabolic indices, WC (HR = 1.53, 95% CI 1.23?1.90,P < 0.001) and WHtR (HR = 1.46, 95% CI 1.20?1.78,P < 0.001) demonstrated higher relative increases in risk associated with IE. Furthermore, the risk of IE was significantly elevated among the younger population with abdominal obesity and concomitant diabetes. However, no significant increase in IE risk was observed among participants with pre-existing valvular heart disease (P = 0.796). Conclusion: Compared with BMI, higher WC and WHtR were robustly associated with increased risk of IE, even after adjusting for traditional risk factors. Furthermore, the risk of IE was markedly elevated among younger individuals with abdominal obesity and diabetes.

AimsCaveolae are plasmalemmal microdomains regulating stretch-dependent, nitric oxide (NO), and other signalling pathways governing myocardial structure, function and resilience. We have reported that global deletion of the scaffold protein cavin-1 disrupts caveolar biogenesis and impairs ventricular compliance and tolerance to ischaemic injury. However, cardiomyocyte-specific and sex-dependent roles of cavin-1 and caveolar complexes remain unresolved. Methods and ResultsWe generated a floxed Cavin-1 transgenic mouse, enabling cardiomyocyte-specific knockdown via adeno-associated virus (AAV) mediated expression of iCre recombinase driven by a cardiac-specific troponin T promoter. Knockdown was confirmed by RNA, protein, and immunofluorescence analyses, and cardiac function was assessed via echocardiography, left ventricular pressure-volume (PV) catheterisation, and ex vivo PV analysis of perfused hearts. Conditionally deleted hearts and myocytes exhibited up to 50% knockdown of Cavin-1 mRNA together with 15% deficiency in muscle-specific Caveolin-3, 70% depletion of caveolae, and mislocalisation of NO synthase (NOS) within cardiomyocytes. This was associated with elevated heart rate and shortened PR interval; reduced intraventricular and systolic blood pressures and peripheral resistance; and sex-dependent impairment of ventricular filling (females only). Diastolic dysfunction was detectable ex vivo, to a greater extent in male vs. female hearts. Mechanisms were sex-dependent, linked to interstitial fibrosis in females and NOS overactivity (inhibited by 100 {micro}M L-NAME) in males. Female hearts also exhibited increased susceptibility to ischaemia-reperfusion injury. Coronary function appeared preserved in both sexes, with intact reactive hyperaemic responses. ConclusionThis model identifies cardiomyocyte caveolae and cavin-1 as key determinants of myocardial function and compliance, involving sex-dependent remodelling and NOS signalling. By linking cardiomyocyte disruption to whole-organ and -body dysfunction, this model provides mechanistic insight into impaired function in heart failure and ageing. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=117 SRC="FIGDIR/small/717104v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1aabf7forg.highwire.dtl.DTLVardef@1026839org.highwire.dtl.DTLVardef@108ad11org.highwire.dtl.DTLVardef@9a6dfd_HPS_FORMAT_FIGEXP M_FIG C_FIG

Coronary artery disease is a leading cause of morbidity and mortality. Invasive coronary angiography is currently the gold standard in disease diagnosis. Several studies have attempted to use artificial intelligence (AI) to automate their interpretations with varying levels of success. However, most existing studies cannot generate detailed angiographic reports beyond simple classification or segmentation. This study aims to fine-tune and evaluate the performance of a Vision-Language Model (VLM) in coronary angiogram interpretation and report generation. Using twenty-thousand angiogram keyframes of 1987 patients collated across four unique datasets, we finetuned InternVL2-4B model with Low-Rank Adaptor weights that can perform stenosis detection, anatomy labelling, and report generation. The fine-tuned VLM achieved a precision of 0.56, recall of 0.64, and F1-score of 0.60 for stenosis detection. In anatomy segmentation, it attained a weighted precision of 0.50, recall of 0.43, and F1-score of 0.46, with higher scores in major vessel segments. Report generation integrating multiple angiographic projection views yielded an accuracy of 0.42, negative predictive value of 0.58 and specificity of 0.52. This study demonstrates the potential of using VLM to streamline angiogram interpretation to rapidly provide actionable information to guide management, support care in resource-limited settings, and audit the appropriateness of coronary interventions. AUTHOR SUMMARYCoronary artery disease has heavy disease burden worldwide and coronary angiogram is the gold standard imaging for its diagnosis. Interpreting these complex images and producing clinical reports require significant expertise and time. In this study, we fine-tuned and investigated an open-source VLM, InternVL2-4B, to interpret and report coronary angiogram images in key tasks including stenosis detection, anatomy identification, as well as full report generation. We also referenced the fine-tuned InternVL2-4B against state-of-the-art segmentation model, YOLOv8x, which was evaluated on the same test sets. We examined how machine learning metrics like the intersection over union score may not fully capture the clinical accuracy of model predictions and discussed the limitations of relying solely on these metrics for evaluating clinical AI systems. Although the model has not yet achieved expert-level interpretation, our results demonstrate the potential and feasibility of automating the reporting of coronary angiograms. Such systems could potentially assist cardiologists by improving reporting efficiency, highlightning lesions that may require review, and enabling automated calculations of clinical scores such as the SYNTAX score.

Background: Chronic conditions such as hypertension can significantly disrupt daily life and emotional wellbeing. The interaction between patients' perceptions, adherence to antihypertensive medication and quality of life (QoL) remains underexplored outside structured clinical settings. Objectives: To capture unprompted patient perspectives and assess whether hypertension affects QoL and to investigate if patient reported experiences are associated with self-reported antihypertensive medication adherence. Methods: Social media listening (SML) study analyzing 86,368 anonymized posts from individuals with hypertension in 12 countries, collected between January 2022 and May 2024. Posts from 11 countries (n=81,368) were analyzed using artificial intelligence-enabled natural language processing. Posts from China (n=5,000) were analyzed separately using a harmonized framework. Quantitative and qualitative methods assessed variations by country, age, and gender, and associations between emotional expression and antihypertensive medication adherence. Results: Across the 11-country core sample, 45% of posts mentioned at least one QoL impact, most commonly worry/anxiety (11%). Impacts varied across countries. Among 8,096 posts with age identified, individuals <40 years reported emotional balance impacts in 28% of posts versus 22% among those aged 40+. Work/Education impacts were mentioned in 17% of posts by those <40 years vs 12% in 40+. Among 7968 posts explicitly referencing adherence, expressed worry was associated with stricter adherence (62% association score), as were structured routines (79% score), home monitoring (77%), dietary changes (77%), and exercise (71%). In contrast, sadness/depression was associated with inconsistent adherence (71%), as were forgetfulness (79%), side effects (73%), and cost/insurance concerns (65%). Conclusions: These results emphasize the importance of the psychological and emotional impact of hypertension, including on adherence to medication regimens, reinforcing the value of a holistic approach to patient care.

Background. Patients with heart failure and reduced ejection fraction (HFrEF) commonly show signs of systemic inflammation. Interleukin-1 (IL-1) is a pro-inflammatory cytokine, known to modulate cardiac function. We aimed to determine the effects of treatment with anakinra, recombinant IL-1 receptor antagonist (IL-1Ra), on plasma IL-1Ra levels. Methods. We measured IL-1Ra levels at baseline and longest available follow-up to 24 weeks in 63 patients (44 males, 40 self-identified Black-Americans) with recent hospitalization for HFrEF, and systemic inflammation (C reactive protein [CRP] levels >2 mg/L) who were assigned to anakinra (N=42 [66.7%]) or placebo (N=21 [33.3%]) as part of the REDHART2 clinical trial (NCT0014686). Cardiorespiratory fitness was measured as peak oxygen consumption (peak VO2). Results. Baseline plasma IL-1Ra levels were 380 pg/ml (290 to 1046). On-treatment IL-1Ra levels were significantly higher in the patients treated with anakinra vs placebo (3,994 pg/ml [3,372 to 5,000] vs 492 pg/ml [304 to 1370], P<0.001). The longest available follow-up was 6 weeks in 10 patients (15.9%), 12 weeks in 12 patients (19%) and 24 weeks in 41 patients (65.1%). On-treatment IL-1Ra levels and interval change in IL-1Ra showed a modest inverse correlation with on-treatment CRP levels (R=-0.269, P=0.033 and R=-0.355, P=0.004, respectively) and no statistically significant correlations with peak VO2 values (P>0.05). Conclusions. Patients with recently decompensated HFrEF and systemic inflammation treated with recombinant IL-1Ra, anakinra, have a significant several-fold increase in plasma IL-1Ra levels. On-treatment IL-1Ra levels however show only a modest correlation with CRP levels and not with peak VO2.

Sickle cell disease (SCD) is associated with substantial cardiovascular morbidity, but echocardiographic data from Latin American populations remain scarce. We aimed to characterise the structural, functional, and haemodynamic echocardiographic profile of adults with SCD attending a tertiary referral centre in Cali, Colombia. We conducted an observational, cross-sectional study based on systematic review of medical records and transthoracic echocardiography reports of consecutive adult patients ([&ge;]18 years) with confirmed SCD evaluated between January 2022 and December 2024. Patients with complex congenital heart disease, severe valvular disease of unrelated aetiology, pregnancy, or echocardiograms of insufficient quality were excluded. Of 669 patients screened, 57 met inclusion criteria. Reporting followed STROBE recommendations. The median age was 24 years (interquartile range [IQR] 21-32) and 59.6% were female; the SS genotype was the most frequent (76.4%) and 71.4% were on hydroxyurea. Median haemoglobin was 10.2 g/dL (IQR 9.3-11.4) and median NT-proBNP 491 pg/mL (IQR 98-1290). Most patients had preserved left ventricular dimensions and systolic function (median ejection fraction 63%, IQR 57-66.5; mean global longitudinal strain -18.9% {+/-} 2.9). Right ventricular function was preserved (mean tricuspid annular plane systolic excursion 25.4 {+/-} 4.6 mm). Left ventricular geometry was normal in 42.1%, with concentric remodelling in 24.6%, concentric hypertrophy in 21.1%, and eccentric hypertrophy in 12.3%. Diastolic function was normal in 71.4%. Valvular disease, when present, was predominantly mild. Tricuspid regurgitation velocity exceeded 2.5 m/s in 29.8% of patients and exceeded 3.0 m/s in 10.5%, identifying a substantial subgroup at intermediate-to-high probability of pulmonary hypertension. In this Colombian cohort of relatively young adults with SCD, cardiac structure and biventricular function were largely preserved, but nearly one-third of patients had echocardiographic findings suggestive of pulmonary hypertension. These findings support the routine use of transthoracic echocardiography as an accessible tool for early cardiovascular risk stratification in adults with SCD in low- and middle-income settings.

BackgroundPatients who have undergone Anterior Cruciate Ligament Reconstruction (ACLR) have a 6-24% chance of either re-tearing or having subsequent knee surgery. To date there have been no practical validated risk prediction models that can be easily implemented into clinical workflow for re-injury risk. Micro-Doppler radar (MDR) provides a promising solution. ObjectiveThe purpose of this study was to investigate the predictive ability of MDR to identify persons with a previous ACLR relative to an age and sex matched healthy control. MethodsACLR patients (n=81) and controls (n=100) performed drop box jump, sit to stand (STS), and walking trials as MDR signatures were collected. A 1D Convolutional Neural Network was developed to evaluate each activity individually followed by the development of a fusion model validation using all three activities. ResultsThe STS model individually achieved the highest overall accuracy of 82.3%, with a sensitivity of 71.6% and specificity of 91.0%. The fusion model using all activities achieved a peak overall accuracy to detect ACLR of 86.2%, 80.3% sensitivity, and 91% specificity. ConclusionsCurrently, there is no clinically validated, efficient approach to objectively evaluate human motion at the point of care. When coupled with machine learning, MDR accurately differentiates ACLR from control groups by identifying complex biomechanical asymmetries, with classification performance comparable to or exceeding that of motion capture. Future research is needed to determine if MDR can be used in conjunction with risk prediction modeling. Key pointsMicro-Doppler radar provides a promising new solution to identify important human motion asymmetries in clinical settings. Here we evaluated a group of patients who have a history of Anterior Cruciate Ligament reconstruction versus a control group. Simple movements performed in the presence of the micro-Doppler radar system were used to identify the 2 groups with accuracy comparable or superior to motion capture systems.

Pregnancy complications such as preeclampsia are associated with circulating cell-free mitochondrial DNA (mtDNA), a damage-associated molecular pattern capable of activating Toll-like receptor 9 (TLR9). We hypothesized that acute mtDNA exposure induces maternal inflammation and endothelial dysfunction during pregnancy via TLR9 activation. Non-pregnant and pregnant rats (gestational days 14-15) were treated intravenously with saline or purified mtDNA and euthanized 4 h after treatment. mtDNA increased cytokine mRNA expression in lung and liver of non-pregnant and pregnant rats, with magnitude varying by pregnancy status and organ. Aortas from pregnant, but not non-pregnant, rats exhibited reduced acetylcholine (ACh)-induced relaxation following mtDNA treatment (Emax, saline: 90.1 {+/-} 3.9 % vs. mtDNA: 62.1 {+/-} 20.7 % KClmax, p<0.05), while uterine artery function was preserved, indicating vascular bed-specific effects. Ex vivo incubation of aortic rings with mtDNA {+/-} white blood cells did not replicate in vivo findings, implicating systemic rather than direct vascular mechanisms. Nuclear DNA did not affect ACh-induced relaxation (p>0.05), confirming that the vascular effects were mtDNA-specific. Pharmacological antagonism of TLR9 with ODN2088 partially attenuated mtDNA-induced maternal endothelial dysfunction. Although overt vascular ROS increases were not detected, aortas from pregnant rats had reduced sod-1 expression (p<0.05) and increased eNOS protein abundance (p<0.05). Acute mtDNA exposure during pregnancy induces maternal organ inflammation and impairs endothelium-dependent vasodilation, with partial TLR9 involvement. In conclusion, aortic transcriptional changes in antioxidant pathways and increased eNOS abundance were also observed, though their functional significance remains to be determined. New & NoteworthyTo our knowledge, this is the first study to demonstrate that acute exposure to circulating mtDNA induces pregnancy-specific maternal endothelial dysfunction and organ-selective inflammatory responses. Our findings reveal pregnancy- and vascular-bed specific responses of the maternal vasculature to mitochondrial danger signals, with partial TLR9 involvement. Aortic transcriptional changes in antioxidant pathways and increased nitric oxide synthase abundance were identified as molecular correlates of this dysfunction.

Conflicting evidence on scatter correction (SC) methods plagues quantitative myocardial perfusion SPECT (MPI), hindering standardized clinical protocols. This simulation study, utilizing the SIMIND Monte Carlo program and a highly realistic 4D XCAT phantom, systematically evaluates Dual Energy Window (DEW, with k=0.5) and Triple Energy Window (TEW) SC techniques. We uniquely investigate their performance across various photopeak window widths (2, 4, and 6 keV) and novel overlapped/non overlapped configurations specifically for Tc 99m MPI parameters largely unexplored in realistic cardiac models. Images were reconstructed with OSEM under uncorrected (UC), SC, and combined attenuation and scatter corrected (ACSC) conditions. Quantitative analysis focused on signal to noise ratio (SNR), contrast to noise ratio (CNR), defect contrast, and relative noise to background (RNB). Our findings consistently show ACSC's superior performance in CNR, SNR, and defect contrast, confirming its critical role. Interestingly, SC alone reduced noise but compromised defect contrast relative to UC, highlighting a potential trade-off without attenuation correction. Crucially, this study reveals minimal influence of photopeak window width and overlap configuration on image quality, and no significant difference between DEW and TEW across most metrics. These results provide essential evidence for optimizing quantitative MPI protocols, suggesting that for Tc 99m, the choice between DEW and TEW, and specific window settings, may be less critical than ensuring robust attenuation correction.

Introduction: Spontaneous coronary artery dissection (SCAD) is frequently accompanied by persistent symptoms of unknown pathogenesis after the index event. Autonomic dysfunction is a plausible mechanism for these but has not been systematically characterized. We quantified antecedent and contemporary autonomic symptoms in survivors of SCAD and examined their associations with cardiac and extra-cardiac symptoms and health-related quality of life. Methods: This cross-sectional study recruited 227 volunteers from multiple countries with a self-reported history of SCAD. Participants completed validated patient-reported measures, including the Composite Autonomic Symptom Score-31 (COMPASS-31), Anxiety Sensitivity Index-3 (ASI-3), and EuroQol-5 Dimension-5L (EQ-5D-5L). They also completed an internally derived retrospective autonomic predisposition score assessing symptoms during adolescence and early adulthood. Results: Participants were predominantly female (97.8%), median age 53 (47-58) years, and were surveyed a median of 3 (1-5) years after their index SCAD event. 21.6% reported SCAD recurrence. Moderate autonomic symptom burden (COMPASS-31 20) was present in 56.4% and severe burden (40) in 16.3%. History of antecedent autonomic symptoms was the strongest independent predictor of contemporary autonomic symptom burden after adjustment for demographic and clinical covariates (=0.514; P <0.001). Greater autonomic symptom burden independently predicted lower EQ-5D health utility (=0.150; P=0.029) and was associated with the ASI-3 physical concerns (=0.232; P <0.001), but not social concerns domain. Autonomic symptoms were not associated with SCAD recurrence. Conclusion: Symptoms of autonomic dysregulation are common in survivors of SCAD and are associated with reduced quality of life. Their association with antecedent dysautonomic features during adolescence and early adulthood suggests a longstanding predisposition, the significance of which warrants further evaluation.

PurposeObstructive sleep apnea (OSA) is a common comorbidity in heart failure (HF) patients with prevalence increasing as HF severity worsens. While CPAP/BiPAP has been shown to reduce disease burden and mortality in the general HF population, it is unclear whether these benefits extend to patients with left ventricular assist devices (LVADs). We sought to determine whether OSA affects long-term survival in newly implanted LVAD patients and whether CPAP/BiPAP treatment confers mortality benefits. MethodsThis single-center retrospective study included patients who underwent LVAD implantation between January 2007 and February 2022. Recipients were stratified by OSA status (OSA vs No-OSA), and those with OSA were further categorized based on CPAP/BiPAP compliance. Comparative statistics and Kaplan-Meier survival analyses were performed, with log-rank tests used to compare groups and assess survival differences. A Cox proportional hazards model was conducted to evaluate the association between risk factors and survival among patients with OSA and No-OSA. ResultsBefore LVAD implantation, patients with OSA had higher body mass index, hypertension, and a higher rate of implantable cardioverter-defibrillator placement than those without OSA. OSA was not associated with increased postoperative complications. Although survival did not differ significantly between OSA and No-OSA patients (p=0.33), CPAP/BiPAP-compliant OSA patients had significantly better survival than noncompliant patients (p=0.0099). ConclusionsLVAD patients with OSA who consistently use CPAP/BiPAP have better survival than those who do not. CPAP/BiPAP is a simple, low-risk treatment that can reduce mortality in this population. Therefore, increased perioperative screening for OSA should be considered for patients receiving LVADs. Multicenter studies are needed to confirm our findings further.

IntroductionPreterm pre-eclampsia is associated with increased risk of later cardiovascular disease. This study examines cardiometabolic health 3-6 years post-preterm pre-eclampsia and explores whether early postnatal cardiovascular phenotypes relate to later cardiovascular morbidity. MethodsPICk-UP trial participants who experienced preterm pre-eclampsia underwent assessments including anthropometry, blood pressure (BP), arteriography, echocardiography, biomarkers and cardiac magnetic resonance (CMR) imaging 3-6 years postpartum. The primary outcome was hypertension prevalence, with secondary outcomes including cardiac fibrosis, remodelling, and function, obesity, and lipid abnormalities. Associations between baseline, pregnancy and postnatal characteristics with the primary and secondary outcomes were explored. ResultsForty-five women were included; 37 underwent echocardiography and 20 had CMR. At 3-6 years, 53% had hypertension, 32% developed de novo hypertension, 30% had adverse left ventricular (LV) remodelling, 49% had diastolic dysfunction, and 27% were obese. Myocardial fibrosis was detected in 35% of CMR participants. No cardiovascular measures changed from 6 months postpartum to 3-6 years. Women who developed hypertension demonstrated higher BP and LV mass index, from 6 weeks postpartum, with distinct postnatal BP trajectories. Women with myocardial fibrosis exhibited higher sFlt and CRP concentrations from 6 weeks postpartum, with sFlt correlating with native T1 at 3-6 years. DiscussionWomen with prior preterm pre-eclampsia show significant cardiometabolic morbidity 3-6 years postpartum. Early postnatal phenotypes indicate long-term cardiovascular risk. Persistent anti-angiogenic imbalance and inflammation may contribute to myocardial fibrosis. Early BP, weight, and biomarker measurement may help identify at-risk women, warranting further studies on optimising postnatal care to mitigate cardiovascular risk after preterm pre-eclampsia.

Aims: Assessment of treatment response in HFrEF has largely relied on left ventricular (LV)-centric parameters, yet the left atrium (LA) plays a central role in modulating LV filling and reflects the cumulative hemodynamic burden. Whether discordant recovery between LV and LA function carries distinct prognostic implications in patients treated with ARNI-based therapy remains unknown. Methods and results: From the multicenter STRATS-HF-ARNI registry, 1,182 patients with HFrEF who underwent serial echocardiography at baseline and one-year follow-up were included. Patients were classified into four strain recovery phenotypes according to the direction of change in LVGLS and LASr at one year: Group A, concordant recovery (57.4%); Group B, discordant atrial non-recovery (11.2%); Group C, discordant ventricular non-recovery (15.6%); and Group D, concordant non-recovery (16.0%). Clinical outcomes included all-cause mortality, cardiovascular mortality, and HF hospitalization. Despite achieving LV functional improvement, Group B exhibited persistent LASr deterioration, accompanied by less favorable hemodynamic trajectories compared with Group A. On multivariable Cox regression, Group B was associated with significantly higher risks of all-cause mortality (adjusted hazard ratio [aHR] 3.53, 95% confidence interval [CI] 1.60-7.79) and cardiovascular mortality (aHR 5.68, 95% CI 1.91-16.92), comparable to Group D. Group C demonstrated higher HF hospitalization risk (aHR 2.25, 95% CI 1.31-3.86). The adverse prognostic impact of discordant atrial non-recovery was consistently observed across subgroups stratified by baseline LVGLS and LASr levels. Conclusion: In HFrEF patients treated with ARNI-based therapy, persistent LA dysfunction despite LV functional improvement identifies a high-risk phenotype comparable to concordant non-recovery. These findings suggest that concurrent assessment of LV and LA strain may provide incremental prognostic value beyond LV-centric metrics alone.

The recently published EHRA/EACVI consensus statement on a standardized bi-atrial regionalization provides new opportunities for consistent regional analyses across patients, imaging modalities and clinical centers. To make this standardized regionalization widely accessible, we developed the open-source software DIVAID, which automatically divides bi-atrial geometries according to the proposed regions, ensuring consistency, reproducibility and operator independence. We evaluated the accuracy of the algorithm by comparing its results to manual expert annotations across 140 geometries from multiple modalities and centers. Veins were automatically clipped correctly in 81% and orifices annotated correctly in 100% of cases. The median (interquartile range; IQR) Dice similarity coefficient (DSC) for left atrial regions was 0.98 (0.96-1.00) for DIVAID-expert and 0.98 (0.94-1.00) for inter-expert comparisons. For right atrial geometries, DSC was higher for DIVAID-expert than for inter-expert comparisons at 0.90 (0.80-0.95) and 0.88 (0.74-0.94), respectively. To assess the accuracy of regional boundaries, we computed the mean average surface distance (MASD) for boundaries derived from automatic or manual annotations. The median (IQR) MASD between DIVAID and experts was 0.17 mm (0.03-0.78) and 1.93 mm (0.65-3.96) in the left and right atrium, respectively. To conclude, DIVAID robustly divides anatomically diverse bi-atrial geometries according to the 15-segment model, while outperforming cardiac experts in both speed and consistency, and demonstrating an accuracy of regional boundaries comparable to the spatial resolution of cardiac imaging modalities. By providing automated, consistent atrial regionalization, DIVAID enables large-scale, standardized regional analyses and data-driven investigation of harmonized, multi-dimensional datasets, which may advance atrial arrhythmia research and personalized treatment strategies.