Journal of Cardiovascular Imaging最新文献

Background: Left bundle branch block (LBBB) significantly increases the risk of left ventricular systolic dysfunction (LVSD) due to cardiac dyssynchrony. Although artificial intelligence-enabled electrocardiography (AI-ECG) models show promise in detecting LVSD, their performance in LBBB patients remains underexplored. We hypothesized that an AI-ECG model clinically validated for detecting LVSD would accurately detect LVSD and predict future clinical outcomes in LBBB patients.

Methods: In this retrospective multicenter study, 5,689 expert-validated LBBB ECGs collected from 2,813 patients between 2016 and 2024 were analyzed using a previously developed and validated AI-ECG model. LVSD was defined as an ejection fraction of ≤ 40%. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), sensitivity, and specificity. Patients were stratified into high- and low-risk groups based on a threshold that achieved 90% sensitivity. A Kaplan-Meier analysis was used to compare clinical outcomes.

Results: Among the 2,813 LBBB patients (mean age, 70.7 years; male sex, 43.7%), hypertension and a history of heart failure were common. The AiTiALVSD model showed strong diagnostic performance for LVSD (AUROC, 0.930 [95% CI, 0.924-0.937]; AUPRC, 0.913 [95% CI, 0.902-0.923]; sensitivity, 0.979; specificity, 0.473). During the mean follow-up of 4.1 years, high-risk patients had significantly higher hazards than low-risk patients for all-cause mortality (adjusted hazard ratio [HR], 1.87; 95% CI, 1.53-2.28), implantable cardioverter defibrillator/cardiac resynchronization therapy implantation (adjusted HR, 15.2; 95% CI, 7.51-30.77), and cardiovascular hospitalization (adjusted HR, 1.11; 95% CI, 0.96-1.28).

Conclusions: AiTiALVSD effectively detects LVSD and stratifies long-term cardiovascular risk in LBBB patients, supporting its clinical utility for early detection and patient management.

Background: We aim to analyze the additive value of repeated transthoracic echocardiography (TTE) within a 1-week interval after a baseline TTE to diagnose infective endocarditis (IE) in patients admitted with Staphylococcus aureus bacteremia (SAB).

Methods: We prospectively enrolled consecutive patients with SAB who were referred for TTE and transesophageal echocardiography (TEE) to exclude IE between January 2017 to December 2019. All patients underwent a second TTE within 5 to 7 days. We excluded patients with poor echo windows, previous IE, valve repair/replacement, and those with cardiac devices or a dialysis catheter in place.

Results: A total of 105 patients were enrolled, of which 40 (38.1%) were female. The mean age was 52 ± 14 years. Sixty-four patients (61%) had a defined source of infection, and 36 (34.3%) were intravenous drug users. The majority (n = 74, 70.5%), had methicillin-sensitive S. aureus. Sixteen patients (15.2%) were diagnosed with definite IE based on TEE findings as follows: eight tricuspid valve IE, four mitral valve IE, three aortic valve IE, and one with double valve IE (mitral and tricuspid). The mortality rate was 7.6% (two patients with definite IE and six without IE). Vegetations were not detected in one patient on the first TTE, compared to TEE and the second TTE. The baseline TTE had a sensitivity of 93.8%, specificity of 87.6% and accuracy of 88.6% in identifying echocardiographic evidence of IE. The addition of second TTE findings increased the sensitivity to 100%, specificity to 95.5%, and diagnostic accuracy to 96.2% in comparison to TEE for the detection of IE.

Conclusions: A repeat TTE within 5 to 7 days of an initial study significantly enhances diagnostic accuracy for detecting IE in patients with SAB and may help reduce the need for TEE in selected low-risk cases.

Background: Transthoracic echocardiography derived left ventricular ejection fraction (LVEF) is a cornerstone in heart failure risk prevention. However, the lower limits of normal LVEF remains imprecisely defined. We aimed to define normal LVEF ranges by sex, age group, and self-reported race/ethnicity using data from population-based echocardiographic studies.

Methods: We systematically searched MEDLINE for studies published between January 1, 2000, and January 3, 2025, that reported the mean and standard deviation of LVEF measured by 2D or 3D echocardiography in healthy, community-based adult populations.

Results: In 10 studies (n = 10,427; female sex, 48%), the pooled mean LVEF was 62.8% (95% confidence interval, 61.0%-64.7%), with estimated lower and upper normal limits of 51.8% and 73.2%, respectively. Women had higher mean LVEF (63.7%) than men (61.9%), with corresponding lower normal limits of 52.7% and 51.7%, respectively. LVEF was similar across age groups. Individuals of Asian origin had 2 to 3 percentage points higher LVEF than Black or White individuals, with lower normal limits of 54% for women and 53% for men. Fewer than 1% of women and approximately 1% of men would be expected to have an LVEF below 50%. Across all demographic subgroups, the probability that an LVEF < 50% is within the normal range was < 5%. There was significant heterogeneity of the included studies (e.g., τ² = 8.82, I² = 99.7% for overall analysis) that appeared unexplained by sex, age, or echocardiography modality (2D vs. 3D).

Conclusions: In healthy adults, the lower limit of normal LVEF is approximately 53% for women and 52% for men, with slightly higher thresholds among individuals of Asian origin. An LVEF < 50% is highly unlikely to reflect normal function, regardless of sex, age, or self-reported race/ethnicity. Given the high statistical heterogeneity, the results should be interpreted with caution.

Hypertrophic cardiomyopathy (HCM) is a myocardial disorder characterized by unexplained myocardial hypertrophy. Although the diagnosis of HCM is traditionally based on increased left ventricular (LV) wall thickness, contemporary management requires a comprehensive multimodality imaging approach to accurately define disease phenotype, assess functional consequences, and guide risk stratification. Transthoracic echocardiography remains the first-line imaging modality, providing real-time evaluation of LV morphology, systolic and diastolic function, and LV outflow tract obstruction (LVOTO). However, its ability to assess myocardial tissue characteristics and complex morphologic variants may be limited in selected patients. Cardiac magnetic resonance (CMR) offers superior spatial resolution and allows detection of myocardial fibrosis using late gadolinium enhancement. Cardiac computed tomography serves as a complementary tool for evaluating coronary artery anatomy and detailed cardiac structure, particularly in patients with suboptimal echocardiographic windows or contraindications to CMR. This review summarizes the strengths and limitations of each imaging modality and highlights their complementary roles in the evaluation of cardiac morphology, systolic and diastolic function, LVOTO, and tissue characterization. An integrated imaging strategy is essential for optimized diagnosis, individualized risk stratification, and informed therapeutic decision-making in patients with HCM.

Background: Epicardial fat exerts both protective and deleterious effects on organs through diverse cytokine-mediated pathways. This study aimed to investigate computed tomography (CT)-based indexed epicardial fat volume (EFVi) in association with target organ damage parameters.

Methods: The prospectively enrolled cohort of 75 patients with nonobstructive coronary artery disease underwent electrocardiogram-gated CT and was evaluated for target organ damage parameters: estimated glomerular filtration rate, proteinuria, echocardiographic septal e' velocity, E/e' and tricuspid regurgitation velocity, brachial-ankle pulse wave velocity, and ankle-brachial index. EFVi was measured from semiautomated 3D segmentation of electrocardiogram-gated CT. Partial correlation, multiple linear regression, and receiver operating characteristic (ROC) analyses were conducted.

Results: Age and EFVi showed moderate positive linear correlation (r = 0.567, P < 0.001). After adjusting for age, EFVi was significantly correlated with the septal e' velocity (r = - 0.489, P < 0.001) and E/e' (r = 0.256, P = 0.034), but not with other target organ damage parameters (P > 0.05). Multiple linear regression analysis showed that the correlations of the EFVi with the septal e' velocity (β = -0.0003, P = 0.007) and E/e' (β = 0.0606, P = 0.024) remained significant after adjusting for potential confounders. ROC analysis identified optimal EFVi thresholds: 95.78 cm³/m² for reduced septal e' velocity (area under the ROC curve [AUC], 0.750; sensitivity, 88.2%; specificity, 56.8%) and 91.68 cm³/m² for elevated E/e' (AUC, 0.692; sensitivity, 71.4%; specificity, 64.8%).

Conclusions: EFVi was related to left ventricular diastolic function more than other target organ damage parameters, including renal function and arterial stiffness, which suggests that the epicardial fat may have a role in the pathogenesis of left ventricular diastolic dysfunction.

Background: The left atrial appendage (LAA) is a critical but frequently overlooked site of thrombus formation, reinforcing the need for accurate identification in routine cardiac imaging. This process is related to pathological dilation associated with endothelial injury and a proinflammatory status. This study assesses the performance of deep learning architectures based on U-Net, specifically UNet3D, Residual-UNet3D, 3D Attention-UNet, and Res16-PAC-UNet, in the semiautomated segmentation and volume measurement of LAA.

Methods: We retrospectively analyzed noncontrast cardiac computed tomography (NCCT) scans from 452 patients aged ≥ 60 years, acquired for chest pain evaluation, to compare the performance of four U-Net-based deep learning architectures (UNet3D, Residual-UNet3D, 3D Attention-UNet, and Res16-PAC-UNet) for semiautomated LAA segmentation and volume measurement. Segmentation accuracy was assessed with the Dice coefficient, and volumetric agreement with Pearson correlation and Bland-Altman analysis.

Results: Dice coefficients were 78.44 ± 1.93 for UNet3D, 78.97 ± 0.79 for Residual-UNet3D, 79.07 ± 1.43 for 3D Attention-UNet, and 77.68 ± 1.47 for Res16-PAC-UNet. All models showed strong correlations between predicted and manual volumes (P < 0.001), with the highest in 3D Attention-UNet (r = 0.800). Bland-Altman analysis indicated minimal bias and narrow limits of agreement for all architectures, confirming consistent reliability.

Conclusions: Deep learning-based segmentation on NCCT enables accurate, reproducible LAA morphological and volumetric assessment without contrast, offering a rapid and reliable tool to support cardiovascular risk stratification and treatment planning.

Background: Pulmonary hypertension (PH) is a progressive clinical condition that eventually leads to right ventricular (RV) failure. RV function is the primary determinant of morbidity and mortality in patients with PH. RV global longitudinal strain (RVGLS) is a promising echocardiographic metric used to assess RV function in this setting. Our study aimed to compare the ability of RVGLS, tricuspid annular plane systolic excursion (TAPSE) and fractional area change (FAC) to predict adverse outcomes in patients with PH.

Methods: We retrospectively evaluated 315 patients with PH of diverse etiologies with 62% constitute of WHO group 2 disease, who were followed at the PH clinic at the University of Virginia, from March 2012 to December 2018. We included all adult patients who met the hemodynamic definition of PH with right heart catheterization and who underwent echocardiography within 1 month of each other.

Results: Approximately half of the cohort was female, with a mean age of 64 ± 14 years. We found a strong correlation between RVGLS and FAC (r =  - 0.55, P < 0.001). Furthermore, there was a significant correlation between RVGLS and invasive hemodynamics. Compared with the TAPSE, the RVGLS stratified by quartiles was associated with mortality at 5 years and hospitalization.

Conclusion: RVGLS is an echocardiographic marker that correlates closely with FAC and invasive pulmonary hemodynamics. In this study, both RVGLS and FAC were associated with 5-year mortality, whereas TAPSE was not. Notably, only RVGLS showed a significant association with hospitalization, suggesting that it may provide additional prognostic value in patients with PH.

Hypertrophic cardiomyopathy has become a highly manageable condition due to recent therapeutic advances that have significantly reduced its overall mortality rate. However, sudden cardiac death continues to be a critical and unsolved threat, particularly in younger patients and competitive athletes. Even after recent updates to guidelines on sudden cardiac death risk evaluation in hypertrophic cardiomyopathy, new clinical evidence continues to emerge, further enriching our understanding of risk stratification and management. In this review, we summarize current research findings and explore recent advances to provide insights into future directions in the treatment of hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is a disease characterized by unexplained left ventricular hypertrophy and is caused by mutations in cardiac sarcomeric proteins. Despite advances in diagnostic modalities and risk stratification, therapeutic strategies have until recently mostly focused on the management of symptoms and the prevention of sudden cardiac death, rather than modifying the underlying sarcomeric dysfunction itself. Conventional pharmacological therapies such as β-blockers and nondihydropyridine calcium channel blockers are effective first-line treatments for obstructive HCM, and established invasive septal reduction therapies, such as surgical myectomy and alcohol septal ablation, provide effective relief of obstruction in refractory patients. However, these therapies address anatomical and hemodynamical consequences rather than the molecular etiology of the disease. In recent years, novel therapeutic approaches have emerged that target the pathophysiological mechanisms of HCM more directly. Sodium-glucose cotransporter 2 inhibitors have demonstrated clinical benefits in HCM through improvements in myocardial energetics. Cardiac myosin inhibitors directly attenuate sarcomeric hypercontractility and have shown improvements in symptoms, functional status, and hemodynamic parameters in obstructive HCM. Furthermore, preliminary gene-targeted therapies are under active investigation and offer the prospect of definitive cure. This review provides a comprehensive overview of current and emerging treatment modalities for HCM. Overall, the management of HCM is evolving toward a more mechanism-targeted approach spanning from gene to myocardium. Ongoing research will be essential to integrate the emerging molecularly targeted therapies with established management strategies into a personalized, multidisciplinary management of HCM.