Filling patterns in left ventricular hypertrophy: A combined acoustic quantification and Doppler study

AbstractObjectives. The purpose of this study was to evaluate the potential of acoustic quantification compared with Doppler echocardiography for assessment of left ventricular diastolic dysfunction.Background. Diastolic dysfunction usually accompanies left ventricular hypertrophy. Although Doppler echocardiography is widely used, it has known limitations in the diagnosis of diastolic abnormalities. The ventricular area-change waveform obtained with acoustic quantification technology may provide an alternative to assess diastolic dysfunction.Methods. Potential acoustic quantification variables (peak rate of area change and mean slope of area change rate during rapid filling, amount of relative area change during rapid filling and atrial contraction) were obtained and compared with widely used Doppler indexes of ventricular filling (isovolumetric relaxation time, pressure half-time, peak early diastolic velocity/peak late diastolic velocity ratio, rapid filling, atrial contribution to filling) ia 16 healthy volunteers and 30 patients with left ventricular hypertrophy.Results. Criteria for abnormal relaxation were present in 68% of patients by acoustic quantification and in 64% of patients by Doppler echocardiography. However, abnormal relaxation was identified in 89% of patients by one or both methods. Acoustic quantification indicated abnormal relaxation in the presence of completely normalized Doppler patterns and in patients with mitral regurgitation or abnormal rhythm with unreliable Doppler patterns.Conclusions. Acoustic quantification potentially presents a new way to assess diastolic dysfunction. This technique may be regarded as complementary to Doppler echocardiography. The combined use of the methods may improve the diagnosis of left ventricular relaxation abnormalities

Asymptomatic cardiac disease following mediastinal irradiation

AbstractObjectivesThis study was designed to evaluate the potential benefit of screening previously irradiated patients with echocardiography.BackgroundMediastinal irradiation is known to cause cardiac disease. However, the prevalence of asymptomatic cardiac disease and the potential for intervention before symptom development are unknown.MethodsWe recruited 294 asymptomatic patients (mean age 42 ± 9 years, 49% men, mean mantle irradiation dose 43 ± 0.3 Gy) treated with at least 35 Gy to the mediastinum for Hodgkin's disease. After providing written consent, each patient underwent electrocardiography and transthoracic echocardiography.ResultsValvular disease was common and increased with time following irradiation. Patients who had received irradiation more than 20 years before evaluation had significantly more mild or greater aortic regurgitation (60% vs. 4%, p < 0.0001), moderate or greater tricuspid regurgitation (4% vs. 0%, p = 0.06), and aortic stenosis (16% vs. 0%, p = 0.0008) than those who had received irradiation within 10 years. The number needed to screen to detect one candidate for endocarditis prophylaxis was 13 (95% confidence interval [CI] 7 to 44) for patients treated within 10 years and 1.6 (95% CI 1.3 to 1.9) for those treated at least 20 years ago. Compared with the Framingham Heart Study population, mildly reduced left ventricular fractional shortening (<30%) was more common (36% vs. 3%), and age- and gender-adjusted left ventricular mass was lower (90 ± 27 g/m vs. 117 g/m) in irradiated patients.ConclusionsThere is a high prevalence of asymptomatic heart disease in general, and aortic valvular disease in particular, following mediastinal irradiation. Screening echocardiography should be considered for patients with a history of mediastinal irradiation

0038: Addressing the controversy of estimating right ventricular systolic pressure by echocardiography: insights from 307 patients with advanced lung disease or pulmonary arterial hypertension

BackgroundThere is a controversy on the reliability of echocardiography in estimating right ventricular systolic pressure (RVSP) in advanced lung disease (ALD) and idiopathic pulmonary arterial hypertension (PAH) patients. This study aimed to develop a quality control method for echocardiographic RVSP assessment to provide guidance.MethodsWe selected consecutive patients referred from 2001 to 2012 for ALD or PAH, in whom an echocardiogram and a right heart catheterization (RHC) were performed within five days. In order to assess reader level influence on echo interpretation, three levels of readers (multi-reader echo-lab, level 2 and 3) estimated RVSP (based on the tricuspid regurgitation TR maximal velocity). Invasive and non-invasive RVSPs were compared using Pearson’s coefficient and Bland-Altman analysis. PH classification performance was also assessed. Reasons for under- and overestimation were systematically analysed.ResultsAmong the 307 patients included (mean age 50±13, 41% male), two-thirds had pulmonary hypertension (PH). RVSP was measurable in 56% of patients. There was a strong correlation between echo and RHC (r=0.84 for echo-lab; 0.86 level 2 and 0.96 level 3). For PH classification, areas under the curve of level 2 and 3 RVSPs were excellent (0.94 and 0.97);>45mmHg was associated with 86% sensitivity and 100% specificity. No severe PH (mPAP≥35mmHg) was missed. The main reason for underestimation was the absence of a well-defined TR envelope and for overestimation the inability to identify the complete envelope by decreasing the gain.ConclusionEchocardiography’s reliability for RVSP estimation can be improved when careful attention is paid to simple practical signal quality parameters, clearly identified by the present study

High-Throughput Precision Phenotyping of Left Ventricular Hypertrophy with Cardiovascular Deep Learning

Left ventricular hypertrophy (LVH) results from chronic remodeling caused by a broad range of systemic and cardiovascular disease including hypertension, aortic stenosis, hypertrophic cardiomyopathy, and cardiac amyloidosis. Early detection and characterization of LVH can significantly impact patient care but is limited by under-recognition of hypertrophy, measurement error and variability, and difficulty differentiating etiologies of LVH. To overcome this challenge, we present EchoNet-LVH - a deep learning workflow that automatically quantifies ventricular hypertrophy with precision equal to human experts and predicts etiology of LVH. Trained on 28,201 echocardiogram videos, our model accurately measures intraventricular wall thickness (mean absolute error [MAE] 1.4mm, 95% CI 1.2-1.5mm), left ventricular diameter (MAE 2.4mm, 95% CI 2.2-2.6mm), and posterior wall thickness (MAE 1.2mm, 95% CI 1.1-1.3mm) and classifies cardiac amyloidosis (area under the curve of 0.83) and hypertrophic cardiomyopathy (AUC 0.98) from other etiologies of LVH. In external datasets from independent domestic and international healthcare systems, EchoNet-LVH accurately quantified ventricular parameters (R2 of 0.96 and 0.90 respectively) and detected cardiac amyloidosis (AUC 0.79) and hypertrophic cardiomyopathy (AUC 0.89) on the domestic external validation site. Leveraging measurements across multiple heart beats, our model can more accurately identify subtle changes in LV geometry and its causal etiologies. Compared to human experts, EchoNet-LVH is fully automated, allowing for reproducible, precise measurements, and lays the foundation for precision diagnosis of cardiac hypertrophy. As a resource to promote further innovation, we also make publicly available a large dataset of 23,212 annotated echocardiogram videos

Gender Differences in Ventricular Remodeling and Function in College Athletes, Insights from Lean Body Mass Scaling and Deformation Imaging

status: publishe