In this paper we discuss the relevance of continuity equation based aortic valve area (AVA) calculation as a robust parameter suitable for accurate grading of aortic stenosis (AS) irrespective of flow conditions. Combining the AVA-based grading and echocardiography-based staging, can provide with the most comprehensive clinical assessment of patients with AS and preserved left ventricular systolic function to streamline management decisions.
Background: The left atrial (LA) volume has been demonstrated to be an important predictor of adverse outcome in patients with various cardiac conditions, including acute myocardial infarction (AMI). However, new treatment strategies in patients with AMI have led to better patient outcomes. We hypothesised that increased LA size could still predict mortality in patients with AMI despite improved treatment strategies.
Methods: We included patients with AMI in a prospective multicenter cohort study and the study patients were enrolled from 2014 to 2022. We recorded echocardiographic and clinical data during their index hospitalisation. Indexed LA volume (LAVi) was assessed in all patients and was used as a continuous variable in the univariate and multivariate Cox regression analysis. The study took place over a period of five years and median follow-up time was 3.8 years (range 3.1 to 5.0 years). The primary study outcomes were all-cause mortality and major adverse cardiac events (MACE). MACE was defined as hospital readmission due to myocardial infarction, cardiac arrest, stroke, heart failure, or onset of new atrial fibrillation.
Results: We included 487 patients (69 ± 12 years old, 26% female) with AMI. During the follow-up period all-cause mortality was 50 (10.3%) and patients who reached the primary outcomes were 153 (31.4%). The deceased patients had higher LAVi compared to survivors (40.0 ± 12.9 mL/m2 vs. 29.7 ± 11.2 mL/m2, p < 0.001). Factors associated with all-cause mortality and MACE were age, year of enrollment, left ventricular (LV) ejection fraction, LV global longitudinal strain (GLS), LV filling pressure, moderate or severe mitral regurgitation and LAVi. GLS and EF were segregated into two distinct models due to their moderately high correlation (r = 0.57, p < 0.001). LAVi remained as an independent echocardiographic predictor of primary outcomes after adjusting for the covariates above in two separates multivariable Cox regression models (hazard ratio 1.02/1.02 mL/m2 [95% CI 1.01-1.03/1.01-1.03], p = 0.006/0.003).
Conclusions: Our study demonstrated that LA dilatation is an independent echocardiographic predictor of mortality and MACE in patients with AMI despite improved treatment strategies. This finding highlights the potential of using LAVi as a marker for prognostication in these patients.
Background: Hypertrophic cardiomyopathy (HCM) can cause myocardial fibrosis, which can be a substrate for fatal ventricular arrhythmias and subsequent sudden cardiac death. Although late gadolinium enhancement (LGE) on cardiac magnetic resonance (CMR) represents myocardial fibrosis and is associated with sudden cardiac death in patients with HCM, CMR is resource-intensive, can carry an economic burden, and is sometimes contraindicated. In this study for patients with HCM, we aimed to distinguish between patients with positive and negative LGE on CMR using deep learning of echocardiographic images.
Methods: In the cross-sectional study of patients with HCM, we enrolled patients who underwent both echocardiography and CMR. The outcome was positive LGE on CMR. Among the 323 samples, we randomly selected 273 samples (training set) and employed deep convolutional neural network (DCNN) of echocardiographic 5-chamber view to discriminate positive LGE on CMR. We also developed a reference model using clinical parameters with significant differences between patients with positive and negative LGE. In the remaining 50 samples (test set), we compared the area under the receiver-operating-characteristic curve (AUC) between a combined model using the reference model plus the DCNN-derived probability and the reference model.
Results: Among the 323 CMR studies, positive LGE was detected in 160 (50%). The reference model was constructed using the following 7 clinical parameters: family history of HCM, maximum left ventricular (LV) wall thickness, LV end-diastolic diameter, LV end-systolic volume, LV ejection fraction < 50%, left atrial diameter, and LV outflow tract pressure gradient at rest. The discriminant model combining the reference model with DCNN-derived probability significantly outperformed the reference model in the test set (AUC 0.86 [95% confidence interval 0.76-0.96] vs. 0.72 [0.57-0.86], P = 0.04). The sensitivity, specificity, positive predictive value, and negative predictive value of the combined model were 0.84, 0.76, 0.78, and 0.83, respectively.
Conclusion: Compared to the reference model solely based on clinical parameters, our new model integrating the reference model and deep learning-based analysis of echocardiographic images demonstrated superiority in distinguishing LGE on CMR in patients with HCM. The novel deep learning-based method can be used as an assistive technology to facilitate the decision-making process of performing CMR with gadolinium enhancement.
Background: Obstructive sleep apnoea (OSA) is present in 40-80% of patients with cardiovascular morbidity and is associated with adverse effects on cardiovascular health. Continuous positive airway pressure (CPAP) maintains airway patency during sleep and is hypothesised to improve cardiac function. In the present study, we report on the impact of 12 weeks of CPAP and improvements in echocardiographic parameters of the right ventricle (RV).
Methods: Nineteen newly diagnosed patients with OSA and a respiratory disturbance index (RDI) greater than 10 were enrolled. Echocardiography was performed before treatment and with a follow-up assessment after 12 weeks of CPAP. Echocardiographic and Doppler measurements were made following the American Society for Echocardiography guidelines. The primary outcome was isovolumetric acceleration (IVA). Secondary outcomes include tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), RV % strain, TEI index and RV dimension (RVD1).
Results: There was significant improvement in isovolumetric acceleration of 0.5ms2 (P = 0.0012 (95% CI -0.72, -0.20)) and significant improvement of 2.05 mm in TAPSE (p = 0.0379 (95% CI -3.98 - -0.13). There was no significant difference in FAC, RV % strain, TEI index or RVD1 with twelve weeks of CPAP therapy.
Conclusion: The present study highlights significant improvement in TAPSE and IVA with 12 weeks of CPAP treatment and no significant improvement in FAC, RVD1 and RV % strain. These data indicate favourable characteristics on both load dependent and load independent markers of RV function with CPAP.
Background: Current risk stratification tools for acute myocardial infarction (AMI) have limitations, particularly in predicting mortality. This study utilizes cardiac ultrasound radiomics (i.e., ultrasomics) to risk stratify AMI patients when predicting all-cause mortality.
Results: The study included 197 patients: (a) retrospective internal cohort (n = 155) of non-ST-elevation myocardial infarction (n = 63) and ST-elevation myocardial infarction (n = 92) patients, and (b) external cohort from the multicenter Door-To-Unload in ST-segment-elevation myocardial infarction [DTU-STEMI] Pilot Trial (n = 42). Echocardiography images of apical 2, 3, and 4-chamber were processed through an automated deep-learning pipeline to extract ultrasomic features. Unsupervised machine learning (topological data analysis) generated AMI clusters followed by a supervised classifier to generate individual predicted probabilities. Validation included assessing the incremental value of predicted probabilities over the Global Registry of Acute Coronary Events (GRACE) risk score 2.0 to predict 1-year all-cause mortality in the internal cohort and infarct size in the external cohort. Three phenogroups were identified: Cluster A (high-risk), Cluster B (intermediate-risk), and Cluster C (low-risk). Cluster A patients had decreased LV ejection fraction (P < 0.01) and global longitudinal strain (P = 0.03) and increased mortality at 1-year (log rank P = 0.05). Ultrasomics features alone (C-Index: 0.74 vs. 0.70, P = 0.04) and combined with global longitudinal strain (C-Index: 0.81 vs. 0.70, P < 0.01) increased prediction of mortality beyond the GRACE 2.0 score. In the DTU-STEMI clinical trial, Cluster A was associated with larger infarct size (> 10% LV mass, P < 0.01), compared to remaining clusters.
Conclusions: Ultrasomics-based phenogroup clustering, augmented by TDA and supervised machine learning, provides a novel approach for AMI risk stratification.
Background: Due to the lack of oestrogen, premature ovarian insufficiency (POI) is an independent risk factor for ischaemic heart disease and overall cardiovascular disease. This study aimed to apply layer-specific myocardial strain for early quantitative evaluation of subclinical left ventricular myocardial systolic function changes in patients with POI.
Methods: Forty-eight newly diagnosed, untreated patients with POI (POI group) and fifty healthy female subjects matched for age, height and weight (control group) were enrolled. Standard transthoracic echocardiography was used to measure conventional parameters and layer-specific strain parameters.The layer-specific strain parameters included subendomyocardial global longitudinal strain (GLSendo), mid-layer myocardial global longitudinal strain (GLSmid), subepimyocardial global longitudinal strain (GLSepi), subendomyocardial global circumferential strain (GCSendo), mid-layer myocardial global circumferential strain (GCSmid), and subepimyocardial global circumferential strain (GCSepi).
Results: There were no significant differences in age, body mass index (BMI), blood pressure, or left ventricular ejection fraction (LVEF) between the two groups. The end-diastolic interventricular septal thickness (IVST) was greater in the POI group (8.29 ± 1.32 vs. 7.66 ± 0.82, P = 0.008), and the POI group had lower E, E/A, and lateral e' (all P < 0.05). As for systolic functions,the POI group had lower GLSendo, GLSmid, GLSepi, GCSendo, GCSmid, and GCSepi (all P < 0.05).The intraobserver and interobserver coefficients of GLSendo, GLSmid, GLSepi, GCSendo, GCSmid, and GCSepi were greater than 0.900.
Conclusions: POI patients with normal LVEF may suffer from subclinical left ventricular myocardial systolic dysfunction. Echocardiography of layer-specific myocardial strain could more sensitively detect subclinical impairment of left ventricular systolic function in POI patients.
Background: The development of heart failure is a turning point in the natural course of aortic stenosis (AS). Pulmonary oedema and elevated left ventricular pressure (LVP) are cardinal features of heart failure. Evaluating pulmonary oedema by lung ultrasound involves taking the upper hand with a bedside noninvasive tool that may reflect LVP.
Aim: We sought to assess the correlation between sonographic pulmonary congestion, invasive LV pre-A pressure, and echocardiographic LV end-diastolic pressure (LVEDP) in symptomatic AS patients receiving transcatheter aortic valve replacement.
Methods: Forty-eight consecutive patients with severe AS and planned transcatheter aortic valve implantation (TAVI) were enrolled. LVEDP was estimated to be normal or elevated using the ASE/EACVI algorithm and transmitral Doppler indices, the E/A ratio, the E/e', and the left atrial volume index. Invasive LV pre-A pressure was used as a reference, with > 12 mm Hg defined as elevated.
Results: Forty-eight patients (25 women (52%), mean age 75 years, standard deviation (SD) ± 7.7 years) were enrolled in the study. We detected severe B-lines (≥ 30) in 13 (27%) patients and moderate B-lines (15-30) in 33 (68.6%) patients. The number of B-lines increased significantly with the severity of New York Heart Association (NYHA) functional classes (Fig. 1). The B-line count was 14 ± 13 in NYHA class I patients, 20 ± 20 in class II patients, and 44 ± 35 in class III patients (p < 0.05, rho = 0.384). The number of B-lines was correlated with the E/E' ratio (R = 0.664, p < 0.0001) and the proBNP level (R = 0. 882, p < 0.008). We found no significant correlation with the LVEDP or LVEF. The LVEDP correlated well with the E/E' ratio (R = 0.491, p < 0.001) but not at all with E/A, DT, or LAVI. All patients had an elevated LVEDP > 12, with a mean pressure of 26 mmHg, a minimum of 13 mmHg, and a maximum of 45 mmHg, with an SD of 7.85.
Conclusion: Assessing lung ultrasonic B-lines is a straightforward and practical approach to identifying pulmonary oedema in AS patients. The number of B-lines correlated with the E/E' ratio and the functional status of patients but did not correlate with invasive LVEDP or LVEF. All patients had elevated LVEDP that correlated with E/E'.
Background: The pneumonitis associated with coronavirus disease 2019 (COVID-19) infection impacts the right ventricle (RV). However, the association between the disease severity and right ventricular systolic function needs elucidation.
Method: We conducted a retrospective study of 108 patients admitted to critical care with COVID-19 pneumonitis to examine the association between tricuspid annular plane systolic excursion (TAPSE) by transthoracic echocardiography as a surrogate for RV systolic function with PaO2/FiO2 ratio as a marker of disease severity and other respiratory parameters.
Results: The median age was 59 years [51, 66], 33 (31%) were female, and 63 (58%) were mechanically ventilated. Echocardiography was performed at a median of 3 days [2, 12] following admission to critical care. The PaO2/FiO2 and TAPSE medians were 20.5 [14.4, 32.0] and 21 mm [18, 24]. There was a statistically significant, albeit weak, association between the increase in TAPSE and the worsening of the PaO2/FiO2 ratio (r2 = 0.041, p = 0.04). This association was more pronounced in the mechanically ventilated (r2 = 0.09, p = 0.02). TAPSE did not correlate significantly with FiO2, PaO2, PaCO2, pH, respiratory rate, or mechanical ventilation. Patients with a TAPSE ≥ 17 mm had a considerably worse PaO2/FiO2 ratio than a TAPSE < 17 mm (18.6 vs. 32.1, p = 0.005). The PaO2/FiO2 ratio predicted TAPSE (OR = 0.94, p = 0.004) with good area under the curve (0.72, p = 0.006). Moreover, a PaO2/FiO2 ratio < 26.7 (moderate pneumonitis) predicted TAPSE > 17 mm with reasonable sensitivity (67%) and specificity (68%).
Conclusion: In patients admitted to critical care with COVID-19 pneumonitis, TAPSE increased as the disease severity worsened early in the course of the disease, especially in the mechanically ventilated. A TAPSE within the normal range is not necessarily reassuring in early COVID-19 pneumonitis.
Background: Global longitudinal active strain energy density (GLASED) is an innovative method for assessing myocardial function and quantifies the work performed per unit volume of the left ventricular myocardium. The GLASED, measured using MRI, is the best prognostic marker currently available. This study aimed to evaluate the feasibility of measuring the GLASED using echocardiography and to investigate potential differences in the GLASED among athletes based on age and sex.
Methods: An echocardiographic study was conducted with male controls, male and female young athletes, and male and female veteran athletes. GLASED was calculated from the myocardial stress and strain.
Results: The mean age (in years) of the young athletes was 21.6 for males and 21.4 for females, while the mean age of the veteran athletes was 53.5 for males and 54.2 for females. GLASED was found to be highest in young male athletes (2.40 kJ/m3) and lowest in female veterans (1.96 kJ/m3). Veteran males exhibited lower values (1.96 kJ/m3) than young male athletes did (P < 0.001). Young females demonstrated greater GLASED (2.28 kJ/m3) than did veteran females (P < 0.01). However, no significant difference in the GLASED was observed between male and female veterans.
Conclusion: Our findings demonstrated the feasibility of measuring GLASED using echocardiography. GLASED values were greater in young male athletes than in female athletes and decreased with age, suggesting possible physiological differences in their myocardium. The sex-related differences observed in GLASED values among young athletes were no longer present in veteran athletes. We postulate that measuring the GLASED may serve as a useful additional screening tool for cardiac diseases in athletes, particularly for those with borderline phenotypes of hypertrophic and dilated cardiomyopathies.
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