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Journal articleJoy G, Punjabi K, Searle G, et al., 2027, , Lancet Digit Health
BACKGROUND: Ejection fraction, a key measure of cardiac function, is used in health care for clinical decision making and risk stratification. We hypothesised that a deep-learning artificial intelligence (AI) segmentation of ejection fraction obtained from cardiac MRI (CMR) outperforms expert clinician segmentation for the prediction of all-cause mortality. METHODS: In this retrospective, multicentre, prognostic study, we studied a cohort of 27 382 consecutive patients who underwent cardiac MRI (CMR) in the UK and the USA. Patients were referred for CMR from nine hospitals to Barts Heart Centre (BHC), London. Patients were identified from the reporting archive at BHC as having undergone a CMR between Oct 1, 2014 and Dec 31, 2019. A further cohort of patients was also identified from University of Pittsburgh Medical Centre (UPMC), Pittsburgh, PA, USA, as having undergone a CMR between June 1, 2010 and March 31, 2016. Mortality data were obtained from national and local databases. AI segmentation was done on all CMR studies, and Cox proportional hazards models were fitted to compare the prognostic value of AI-measured versus clinician-measured left-ventricular volume metrics. Model fit was compared using the Akaike Information Criterion (AIC), discrimination using C indices and the incremental value of AI over clinician segmentation using likelihood-ratio tests of nested models. FINDINGS: 27 382 patients received a baseline CMR (26 106 patients from BHC and 1276 from UPMC). The median follow-up was 5·6 years (IQR 4·4-6·9), during which 3458 (13%) of 27 382 patients died. AI ejection fraction showed better model fit (AIC 57 936 vs 58 097, ΔAIC 161 favouring AI) and marginally better discrimination (C index 0·669 vs 0·637; ΔC 0·033 [95% CI 0·026-0·041]). AI ejection fraction significantly improved model fit when added to clinician ejection fraction (χ2=168
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Book chapterUfumaka I, Alibakhshi A, Fernandes P, et al., 2027, , Pages: 235-247
Automated left ventricular (LV) segmentation is fundamental to echocardiographic assessment of cardiac function, yet most models report aggregate performance without accounting for variation in image quality. In clinical practice, poor acoustic windows produce ambiguous endocardial boundaries where both automated predictions and expert annotations become unreliable. We propose a label-free quality surrogate, q<inf>dice</inf>, derived from pairwise Dice disagreement across 11 independent clinical experts, requiring no explicit quality labels. Using this surrogate, we conduct a quality-stratified evaluation of three architecturally distinct models (T1, T2, and T3) on the UnityLV-MultiX dataset. T1 is a sparse keypoint model, T2 uses a dense binary mask representation, and T3 is a triple-head hybrid architecture in which predicted keypoint heatmaps guide segmentation feature attention through a differentiable spatial gate. All models are trained on a single-expert dataset and evaluated against a multi-expert consensus using Dice, HD95, MSD, and ejection fraction MAE. A leave-one-out analysis enables direct comparison of model and expert consistency against a common multi-expert reference. All three models exceed every individual expert in overall Dice. T3 achieves the highest Dice across all quality bands (0.937, 0.952, and 0.960 at Q<inf>low</inf>, Q<inf>mid</inf>, and Q<inf>high</inf> respectively; 0.949 overall). It shows the lowest EF MAE overall (5.24%), representing a 38% reduction relative to the expert mean (8.46%). T3’s keypoint and segmentation heads agree far more closely with each other than any cross-model pair (ρ=0.856), yet residual disagreement between the two heads concentrates on low-quality frames, providing a built-in, single-inference reliability flag without any external reference.
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Book chapterAbdi A, Jeviskov J, Hussain A, et al., 2027, , Pages: 131-142
Cardiovascular diseases require precise, non-invasive diagnostic tools to assess regional myocardial function. While Speckle Tracking Echocardiography (STE) is widely used to measure myocardial strain, traditional block-matching and optical flow algorithms frequently fail due to acoustic noise and out-of-plane speckle decorrelation. This paper introduces MyoTrackerChrono, a hybrid deep learning architecture designed for robust, sparse point tracking in echocardiography. By integrating a Temporal Adapter between a spatial convolutional encoder and a tracking transformer, the model explicitly aggregates temporal context early in the feature extraction phase. This allows for stable tracking even during rapid cardiac phases or momentary signal loss. Validated on physics-based synthetic benchmarks, MyoTrackerChrono improves pixel-level tracking accuracy (Mean Absolute Error) by 33.0% over baseline models and reduces strain estimation error in mechanically complex mid-wall segments by over 64%. Furthermore, the architecture operates at an effective inference rate of 1382 FPS, confirming its feasibility for rapid post-acquisition clinical deployment.
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Book chapterAlibakhshi A, Jevsikov J, Ufumaka I, et al., 2027, , Pages: 17-30
Apical view acquisition errors in echocardiography can lead to inaccurate estimation of clinically important measurements, including ventricular volume, ejection fraction, and strain. In this work, we propose a phase-centred CNN-LSTM framework for automated regression of apical image quality in echocardiographic studies, investigating which backbone architecture can most effectively predict a continuous reduction in left ventricular long-axis length without relying on explicit mask-based measurements. A patient-specific reference standard was generated by first identifying end-diastole using a phase detection model and then measuring LV long-axis length. For each patient, the scan with the maximum observed LV length served as the patient-specific reference, and deviations across other scans were quantified using a heuristic formulation based on relative length reduction. Using this systematic labelling strategy, eight CNN-LSTM backbone architectures were trained and compared on 1,799 echocardiographic studies from 100 patients, comprising apical four-chamber and apical two-chamber views, with the goal of directly regressing the degree of length reduction from raw image sequences alone. Across backbone comparisons, convolution-based models showed the strongest overall performance, with EfficientNetV2 achieving the lowest regression error for apical four-chamber views and ConvNeXt-Tiny and ResNet50-level models showing competitive performance in apical two-chamber views. To assess clinical relevance, two expert-annotated evaluation datasets, each labelled by 10 experts, were used for ranking-based comparison against expert consensus. The proposed AI approach demonstrated agreement with expert consensus at a level comparable to several human experts and showed meaningful ability to identify scans associated with overestimation and underestimation of key echocardiographic measurements. These findings support the potential of backbone-driven regression of apical view qua
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Journal articleMazzarotto F, Kalay O, Arslan E, et al., 2026, , Genome Medicine, Vol: 18, ISSN: 1756-994X
BackgroundGene panels represent a widely used strategy for genetic testing in a vast range of Mendelian disorders. While this approach aids reliable bioinformatic detection of short coding variants, it often fails to detect many larger variants. Recent studies have recommended the adoption of pangenome references (as opposed to linear reference genomes like GRCh38) to augment detection of large variants from targeted sequencing, potentially providing diagnostic laboratories with the possibility to streamline diagnostic work-ups and reduce costs.MethodsHere, we analyze 1969 cardiomyopathy cases and 1805 controls sequenced with the Illumina Trusight Cardio panel using a pangenome-based workflow (GRAF) and five conventional orthogonal methodologies (GATK HaplotypeCaller, GATK-gCNV, ExomeDepth, Manta and Lumpy-SV) to detect variants ≥ 20 bp in size.ResultsFollowing lab-based variant validation by means of PCR and Sanger sequencing, we show that GRAF conjugates higher precision and recall (F1 score 0.86) compared with other methods (F1 0-0.57) in detecting potentially pathogenic variants ≥ 20 bp from short-read panel data. Results were complemented by a comparison of the tools’ performance in detecting ground truth variants on reference sample HG002 from Genome In A Bottle, which confirmed GRAF to outperform other tools also on exome sequencing (F1 0.97 vs. 0-0.94). Notably, in the HG002 benchmark dataset, GRAF also showed slightly improved performance compared to GATK HaplotypeCaller in the identification of small variants (1–19 bp; F1 0.975 vs. 0.968).ConclusionsOur results indicate that pangenome-based workflows aid improved detection of large variants from targeted sequencing data in the clinical context and suggest that they may contribute to more unified variant detection frameworks for all-size genetic variants in the future.
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Journal articleAlsharif A, Chang E, Wang Y, et al., 2026, , Eur J Pharmacol
BACKGROUND: Anaesthetic drugs used during the perioperative period may influence surgical outcomes in cancer patients. Recently, remimazolam besylate, a rapid-onset and ultra-short-acting sedative, has been introduced for sedation and anaesthesia maintenance. This study aimed to assess its potential anti-cancer effects on human lung carcinoma cells (A549) in vitro and in vivo, and to explore the underlying mechanisms. METHODS: Cultured A549 lung cancer cells were exposed to remimazolam besylate (0.1 to 500 μM) for up to 24 hours and their viability was assessed with the CCK-8 assay. The effects of remimazolam besylate on cancer cell proliferation, migration, mitochondrial mass, and apoptosis were assessed through RNA sequencing and immunofluorescence staining. Tumour growth was evaluated in a xenograft model of Balb/c nude mice after treatment with 5 mg/kg of remimazolam besylate via intraperitoneal injection for 21 consecutive days. Its cytotoxicity was also assessed with cultured HK-2 normal kidney cells. RESULTS: Remimazolam besylate significantly inhibited cell viability at 200 μM (61.2 ± 12.7 vs 103.8 ± 6.0, P = 0.003) and 300 μM (46 ± 10 vs 95 ± 21, P = 0.02). It suppressed migration (56.38 ± 3.06 vs 85.10 ± 10.84, P = 0.03) and reduced mitochondrial mass (63.5 ± 24.9 vs 150.5 ± 55.9, P = 0.02). Additionally, it increased caspase-3 and cleaved caspase-9 expression, and reduced tumour size by 74.6% compared to the control (P = 0.002). The 50% concentration of cytotoxicity (IC50) for remimazolam besylate in A549 cells was found to be 297.5 μM, whereas the IC50 for HK-2 cells was predicted to be significantly higher at 2,200 μM. CONCLUSION: Remimazolam besylate primarily and preferentially inhibits human lung carcinoma cells. It induces apoptosis associated with endoplasmic reticulum stress and cell death signaling pathways.
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Journal articleWang H, Lai E-C, Hua Z, et al., 2026, , J Physiol
Mechanical stretch can increase ventricular arrhythmia susceptibility during sympathetic activation, but the mechanisms linking stretch to altered β-adrenergic receptor (βAR) signalling, Ca2 + handling and electrical instability remain unclear. We tested whether left ventricular (LV) stretch alters Cav3-associated membrane organisation and enhances βAR-protein kinase A (PKA)-dependent arrhythmogenic signalling. Langendorff-perfused male rat hearts were studied using a fluid-filled LV balloon, with sham hearts fitted with an unstretched balloon. Optical mapping during S1-S2 programmed stimulation showed that LV stretch had limited effects at baseline but altered the response to βAR stimulation, increasing ventricular arrhythmia severity, prolonging APD50, reducing local conduction velocity and steepening APD80 restitution. H89 markedly reduced βAR stimulation-induced arrhythmia severity in stretched hearts, whereas KN93 did not provide comparable protection. LV stretch also increased cardiomyocyte length and altered Cav3 organisation at wheat germ agglutinin (WGA)-defined membrane regions. In isolated LV cardiomyocytes, hypoosmotic membrane deformation did not alter basal caffeine-induced Ca2 + release but enhanced isoprenaline-induced irregular activity and Ca2 +-transient amplitude, both of which were attenuated by PKA inhibition. Hypoosmotic membrane deformation also amplified isoprenaline-evoked PKA activity and increased RyR2 Ser2030 phosphorylation. These findings indicate that LV mechanical stretch alters the ventricular βAR response in association with altered Cav3-associated membrane organisation and enhanced βAR-PKA-dependent Ca2 + instability. KEY POINTS: Left ventricular (LV) balloon stretch has limited baseline electrophysiological effects but increases arrhythmia severity, slows conduction and steepens APD80 restitution during β-adrenergic stimulation. LV balloon stretch is associated with cardiomyocyte elongation
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Journal articleRajendra S, Salmasi Y, Raj B, et al., 2026, , ASAIO J, Vol: 72, Pages: 905-913
Right ventricular failure (RVF) is an important complication following implantation of a left ventricular assist device (LVAD) in patients with advanced heart failure. This study aims to identify perioperative hemodynamic predictors of RVF following LVAD implantation and develop an internally validated predictive model. Patients who underwent LVAD implantations between March 2013 and March 2023 at a large-volume tertiary center were retrospectively analyzed. The primary outcome was early post-implant RVF, defined by need for right ventricular assist device (RVAD), prolonged inotrope dependence (> 14 days), or death within 14 days while on inotropes. Perioperative hemodynamic variables were analyzed using univariate logistic regression. A prediction model was then developed using stepwise multivariate logistic regression, and internally validated using k -fold cross-validation. Among 210 patients, 73 patients (34.8%) developed early post-implant RVF. Decreased post-implant cardiac index (odds ratio [OR]: 0.0122, p = 0.001), decreased mean arterial pressure (OR: 0.932, p = 0.008), and simultaneously increased cardiac index and pulmonary pulse pressure (OR: 1.13, p = 0.021) independently predicted RVF. Preimplantation IV inotrope therapy was a significant confounder (OR: 3.96, p = 0.021). Our proposed predictive model achieved strong discriminatory power (area under the curve [AUC] of 0.830) and stable cross-validation performance. External validation with multicenter cohorts is warranted to confirm predictive accuracy and clinical applicability.
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Journal articleSattler S, 2026, , Jacc Basic to Translational Science, Vol: 11, ISSN: 2452-302X
Corresponding Author
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Journal articleBola H, Arif A, J Hon J, et al., 2026, , Pacing Clin Electrophysiol, Vol: 49, Pages: 1692-1705
INTRODUCTION: Pulmonary vein isolation (PVI) alone achieves modest arrhythmia freedom in persistent atrial fibrillation (PeAF). Cryoballoon ablation (CBA) offers a single-shot alternative to radiofrequency ablation (RFA) that streamlines procedural workflow. We aimed to quantify the clinical efficacy, procedural efficiency, and safety of CBA versus RFA through a meta-analysis of randomized controlled trials (RCTs). METHODS AND RESULTS: Systematic review of PubMed, Embase, and Scopus identified 5 RCTs enrolling 1,091 patients (515 CBA, 576 RFA). The primary endpoint was 12-month freedom from any atrial arrhythmia, with isolated AF, and atrial tachycardia/flutter evaluated as secondary endpoints. Random-effects models generated relative risks (RRs) and mean differences (MDs) with 95% confidence intervals (CI). Time-to-event data were pooled using a generic inverse-variance approach to derive hazard ratios (HR). CBA and RFA demonstrated equivalent freedom from any arrhythmia (RR 0.97, 95% CI 0.81-1.15; p = 0.71). Time-to-event analysis corroborated a comparable recurrence hazard (HR 0.91, 95% CI 0.67-1.24; p = 0.56; I2 = 0%). Repeat ablation rates were identical (RR 0.93; p = 0.50). CBA significantly reduced procedural time (MD -45.37 min; p < 0.0001), while major complications were comparable (1.5% vs. 2.7%; p = 0.18). Trial sequential analysis indicated that further randomization is unlikely to demonstrate superiority. CONCLUSION: In PeAF, CBA and RFA achieve equivalent 12-month arrhythmia-free survival and comparable repeat-ablation rates, while CBA confers a highly significant reduction in procedural time. However, reliance on 12-month follow-up and heterogeneous rhythm surveillance protocols may limit assessments of true long-term durability.
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Journal articleSu Y, Yu Z, Xiao Z, et al., 2026, , J Am Heart Assoc
BACKGROUND: While cardiac resynchronization therapy is effective in dyssynchronous heart failure, suboptimal response remains frequent. The acute hemodynamic profile of different left bundle-branch (LBB) area pacing modalities is poorly defined. Moreover, atrioventricular optimization guided by QRS duration (QRSd) may not yield the greatest hemodynamic benefit. METHODS: Twenty-four patients with heart failure, reduced ejection fraction, and LBB block underwent sequential testing of right ventricular septal pacing, left ventricular septal pacing, nonselective LBB pacing, and selective LBB pacing during cardiac resynchronization therapy implantation in a prospective, within-subject physiological study. At each modality, electrical end points were QRSd and vectorcardiographic QRS area; hemodynamics were assessed with beat-to-beat systolic blood pressure (SBP). The atrioventricular interval producing maximal SBP improvement was compared with that producing the narrowest QRSd. RESULTS: LBB area pacing modalities significantly reduced QRSd, compared with right ventricular septal pacing (nonselective LBB pacing, 114.0±16.8 milliseconds; selective LBB pacing, 118.4±14.1 milliseconds; left ventricular septal pacing, 124.6±16.0 milliseconds; right ventricular septal pacing, 144.4±27.6 milliseconds; all P<0.01). At the atrioventricular interval that produced maximized SBP improvement, QRSd remained narrower with LBB area pacing than right ventricular septal pacing, and selective LBB pacing provided the greatest hemodynamic improvement (ΔSBP 16.3±5.2 mm Hg), exceeding left ventricular septal pacing (13.5±6.2 mm Hg) and nonselective LBB pacing (12.8±6.3 mm Hg; all P<0.05). Across modalities, the atrioventricular interval that maximized ΔSBP was consistently shorter than that minimizing QRSd (mean difference, 18-29 milliseconds). CONCLUSI
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Journal articleEllard S, Hanson H, Cassidy E-J, et al., 2026, , J Med Genet, Vol: 63, Pages: 697-706
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Journal articleRosas Diaz AN, Stabenau HF, Tung P, et al., 2026, , JACC Adv, Vol: 5
BACKGROUND: Anthracycline use is limited by cardiotoxicity resulting in heart failure (HF). The spatial ventricular gradient (SVG) is a vectorcardiographic measurement of myocardial electrical heterogeneity associated with sudden death and incident HF. It is unclear if serial measurement of SVG after anthracycline initiation can help predict subsequent HF. OBJECTIVES: The objective of the study was to determine if time-varying SVG measurements are associated with anthracycline HF. METHODS: Retrospective, single-center study of adult patients with cancer treated with anthracyclines between 1992 to 2019. Standard 12-lead electrocardiograms obtained within 6 months before and up to 5 years after anthracycline initiation were analyzed. Patients with prior HF or ≤1 electrocardiogram within 5 years were excluded. Median vectorcardiograms were constructed, and the SVG vector was obtained by integrating under the X, Y, and Z QRST complexes. Multivariable competing-risks regression was performed with SVG parameters included as time-varying covariates, incident HF as the main outcome, and death as a competing outcome. RESULTS: Among 594 patients (median age 61 years, 48% male), 83 (14%) developed HF within 5 years. In multivariable competing-risks regression, time-varying SVG azimuth (circular angle in the transverse plane) was independently associated with HF (P = 0.0024), demonstrating a 9.4-fold gradient in risk across values. Leftward/anterior azimuth values were the lowest risk areas, whereas posterior/rightward orientations were the highest risk. CONCLUSIONS: Time-varying SVG azimuth was independently associated with HF risk in patients treated with anthracyclines. Assessing dynamic changes in SVG azimuth during anthracycline treatment may enhance early identification of patients at risk for HF and inform the use of cardioprotective strategies during cancer therapy.
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Journal articleTopriceanu C-C, Balakrishnan ID, Vissing CR, et al., 2026, , J Am Coll Cardiol, Vol: 88, Pages: 1850-1870
BACKGROUND: Patients with phenotypically mild hypertrophic cardiomyopathy (HCM) do not require symptom management, but may be at an earlier stage in the disease course, with potential to benefit from disease-modifying therapies. However, little is known about the natural history and predictors of major adverse cardiovascular events (MACE). OBJECTIVES: Using the Sarcomeric Human Cardiomyopathy Registry, we identified predictors of incident MACE and characterized disease progression in phenotypically mild HCM. METHODS: Phenotypically mild HCM was defined as: having shorter disease duration (<10 years since diagnosis or age ≤30 years), no previous MACE, being NYHA functional class I, and having a left ventricular (LV) maximal wall thickness (MWT) <25 mm. These individuals were followed prospectively for the development of symptoms or MACE: atrial fibrillation (AF), malignant ventricular arrhythmia (MVA) (sudden cardiac death, resuscitated arrest, or appropriate defibrillator therapy), heart failure (HF) (cardiac transplantation, LV assist device implantation, LV ejection fraction <35%, or NYHA functional class III or IV symptoms), stroke, or all-cause mortality. Cox regression identified MACE predictors. Linear and latent class mixed models characterized LV remodeling trajectories and risk clusters. RESULTS: Of 2,500 participants with phenotypically mild HCM (mean age 43 years, 31% women) followed for a mean duration of 7 ± 6 years, 534 (21%) developed MACE, including 289 with AF, 69 with MVA, and 193 with HF. Individuals who progressed from NYHA functional class I to ≥ II symptoms during follow-up (n = 585, 23%) were 2.79 times (95% CI: 2.30-3.39 times) more likely to experience MACE. Age at baseline (HR: 1.24; 95% CI: 1.17-1.32 per 10-year increase), body mass index (HR: 1.10; 95% CI: 1.01-1.21 per 5-kg/m2 increase), left atrial (LA) diameter (HR: 1.16; 95% CI: 1.09-1.25 per 5-mm increase), LV MWT (HR: 1.27; 95% CI: 1.10-1.46 per 5-mm increase)
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Journal articleBlackman J, Francis D, Krahn A, et al., 2026, , Heart
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Journal articlePalermi S, Zeidaabadi B, Vecchiato M, et al., 2026, , Int J Cardiol, Vol: 461
BACKGROUND: Pre-participation screening (PPS) in competitive athletes aims to identify cardiovascular diseases associated with sudden cardiac death (SCD). Although the 12鈥憀ead electrocardiogram (ECG) represents the cornerstone of PPS, structural abnormalities may demonstrate limited or incomplete electrical expression, particularly in asymptomatic athletes with physiological remodeling. Artificial intelligence (AI)-enabled ECG models have shown promising performance in hospital-based populations, but their transportability to low-prevalence athlete screening environments remains uncertain. OBJECTIVES: To develop and externally validate a deep learning (DL)-based AI-ECG ensemble model for detecting imaging-confirmed structural heart disease in competitive athletes undergoing PPS. METHODS: A convolutional neural network (CNN) ensemble was trained using hospital-derived ECG images from Beth Israel Deaconess Medical Center (BIDMC, Boston, USA) and externally validated in the Italian Team for Athlete CARDiac evaluation and AI-based Risk prediction (ITACARD-AI) registry. Separate CNNs were developed for valvular heart disease (VHD) and cardiomyopathies (CM) and combined using XGBoost meta-learning. Model performance was assessed using area under the receiver operating characteristic curve (AUROC), subgroup analyses, and threshold-based evaluation. RESULTS: The ITACARD-AI cohort included 1115 competitive athletes (mean age 26 ± 13 years; 70% male), including 48 athletes (4.3%) with VHD and 30 (2.7%) with CM. External validation demonstrated substantial performance degradation compared with hospital-based internal validation. AUROC values decreased to 0.70 (95% CI 0.64-0.75) for VHD and 0.69 (95% CI 0.60-0.78) for CM, indicating only modest discrimination in the screening population. Threshold analyses showed high negative predictive values (∼99%) but persistently low positive predictive values (≤8%), reflecting limited disease enrichment and st
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Journal articleMcGurk K, Curran L, Tayal U, 2026,
Rethinking myocarditis through genetics
, Journal of the American College of Cardiology, ISSN: 0735-1097 -
Journal articleAlibakhshi A, Fernandes P, Serej ND, et al., 2026, , Ultrasound Med Biol
OBJECTIVE: To evaluate whether preserving relative expert-derived structure during model training improves the automated assessment of rotational misalignment in apical four-chamber echocardiographic images. METHODS: A multi-expert dataset of apical four-chamber images was annotated using multiple-image ranking to derive consensus rotational orderings along a clockwise-to-anti-clockwise continuum. Conventional pointwise regression models were compared with shared-weight pairwise models that received two images and predicted the signed difference between their consensus rotational scores. Performance was evaluated across three independent expert-ranked test sets using pairwise agreement and Spearman correlation. Robustness was further assessed using leave-one-expert-out and cycle-consistency analyses, with saliency-based visualization used to examine the image regions influencing predictions. RESULTS: Pairwise learning increased the mean pairwise agreement from 74.86% to 84.29% and the mean Spearman correlation from 67.74% to 85.43% compared with pointwise regression. The best pairwise model achieved a pairwise agreement of up to 87.81% and a Spearman correlation of up to 91.23%. The performance remained stable when individual annotators were excluded, and a cycle-consistency analysis demonstrated few cyclic preferences on independent test data. Visual explanation maps indicated model attention to clinically relevant cardiac anatomy. CONCLUSION: Training directly on relative expert-derived structure improved agreement with multi-expert consensus compared with conventional pointwise regression. Pairwise learning therefore provides a robust framework for assessing qualitative, continuous echocardiographic image-quality attributes such as rotational alignment.
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Journal articleRowin EJ, Maron BJ, Siontis KC, et al., 2026, , Circulation, Vol: 154, Pages: 1290-1305
BACKGROUND: Implanted cardioverter-defibrillators (ICDs) have been used in patients with hypertrophic cardiomyopathy (HCM) to prevent sudden death, and have proven lifesaving for many patients. However, experience with ICD therapy has largely been derived from relatively small HCM cohorts confined to specific countries or regions of the world. Therefore, we sought to determine the effectiveness of ICDs in preventing sudden death due to life-threatening ventricular arrhythmias in a large international multicenter HCM population. METHODS: Databases from 25 HCM centers (8 in the United States, 9 in Europe, 4 in Asia, and 1 each in Australia, Africa, Mexico, and South America) were retrospectively interrogated to identify consecutive patients with HCM with ICDs (1992 to 2024) followed for 7±6 years (up to 32 years) for clinical outcomes. RESULTS: A total of 3387 patients were identified (63% men). They had a mean left ventricular thickness of 22±7 mm. The participants had received ICDs at a mean age of 47±17 years. Over follow-up, 550 patients (16%) experienced ≥1 appropriate ICD therapy (2.6%/y), including 86 of the 247 implanted for secondary prevention (35% [6.4%/y]) and 464 of the 3140 implanted for primary prevention (15% [2.2%/y]). Appropriate therapy occurred in the 464 primary prevention patients at a mean age of 49±17 years, with a median time to first appropriate therapy of 4 years after ICD implantation; 16% of these received their first appropriate therapy ≥10 years after implantation, and 47% experienced multiple interventions. Independent predictors of appropriate ICD therapy included unexplained syncope, left ventricular apical aneurysms, left ventricular systolic dysfunction, and nonsustained ventricular tachycardia on ambulatory monitoring. Of the 3140 primary prevention patients, 2946 survived (94%) and 194 died (6%) (0.8%/y), including 68 due to HCM (0.3%/y), predominantly of end-stage heart failure (n=43) or stroke (
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Journal articleXu W, Sa F, Song Y, et al., 2026, , JACC Cardiovasc Imaging, Vol: 19, Pages: 1222-1235
BACKGROUND: Pediatric and adolescent arrhythmogenic cardiomyopathy (ACM) is a clinically severe phenotype that remains underrepresented in cardiac magnetic resonance (CMR) research. The prognostic value of CMR-derived right ventricular deformation analysis in this population is unclear. OBJECTIVES: This study sought to describe the burden of severe cardiac outcomes in pediatric and adolescent ACM, and to assess the prognostic and incremental value of CMR-derived right ventricular global longitudinal strain (RVGLS) for risk stratification when incorporated into conventional clinical and CMR markers. METHODS: This multicenter study included consecutive pediatric and adolescent patients (≤21 years of age) with ACM who underwent baseline CMR evaluation. We assessed clinical, electrocardiographic, and CMR parameters according to the 2010 Task Force Criteria, along with biventricular strain parameters. Severe cardiac outcomes were defined as a composite of malignant ventricular arrhythmias (MVAs), heart transplantation, and heart failure-related death. RESULTS: The cohort included 102 patients (16.3 ± 3.4 years; 72% male) and 95 controls (mean age: 15.6 ± 3.3 years; 70% male). During a median of 58-month follow-up, 51 (50%) patients experienced severe cardiac outcomes and 28 (27.5%) MVA outcomes. Reduced RVGLS was independently associated with severe cardiac outcomes (HR: 1.14; P = 0.004) and MVA outcomes (subdistribution HR: 1.15; P < 0.001) after adjustment for clinical and conventional CMR parameters. Incorporation of RVGLS significantly improved prediction of severe cardiac outcomes beyond both right ventricular-based and left ventricular-based multivariable models, with significant improvement in discrimination and reclassification. Kaplan-Meier analysis further showed that RVGLS ≥-12.2% identified patients at higher risk of severe cardiac outcomes and MVA outcomes (both log-rank P < 0.001). CONCLUSIONS: Pediatric and adolescent ACM manifest
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