Obtaining focused right ventricular (RV) apical view remains challenging using conventional two-dimensional (2D) echocardiography. This study main objective was to determine whether measurements from RV focused views derived from three-dimensional (3D) echocardiography (3D-RV-focused) are closely related to measurements from magnetic resonance (CMR). A first cohort of 47 patients underwent 3D echocardiography and CMR imaging within 2 h of each other. A second cohort of 25 patients had repeat 3D echocardiography to determine the test-retest characteristics; and evaluate the bias associated with unfocused RV views. Tomographic views were extracted from the 3D dataset: RV focused views were obtained using the maximal RV diameter in the transverse plane, and unfocused views from a smaller transverse diameter enabling visualization of the tricuspid valve opening. Measures derived using the 3D-RV-focused view were strongly associated with CMR measurements. Among functional metrics, the strongest association was between RV fractional area change (RVFAC) and ejection fraction (RVEF) (r = 0.92) while tricuspid annular plane systolic excursion moderately correlated with RVEF (r = 0.47), all p < 0.001. Among RV size measures, the strongest association was found between RV end-systolic area (RVESA) and volume (r = 0.87, p < 0.001). RV unfocused views led on average to 10% underestimation of RVESA. The 3D-RV-focused method had acceptable test-retest characteristics with a coefficient of variation of 10% for RVESA and 11% for RVFAC. Deriving standardized RV focused views using 3D echocardiography strongly relates to CMR-derived measures and may improve reproducibility in RV 2D measurements.
Rationale Right ventricular (RV) dysfunction is common among patients hospitalized with coronavirus disease (COVID-19); however, its epidemiology may depend on the echocardiographic parameters used to define it. Objectives To evaluate the prevalence of abnormalities in three common echocardiographic parameters of RV function among patients with COVID-19 admitted to the intensive care unit (ICU), as well as the effect of RV dilatation on differential parameter abnormality and the association of RV dysfunction with 60-day mortality. Methods We conducted a retrospective cohort study of ICU patients with COVID-19 between March 4, 2020, and March 4, 2021, who received a transthoracic echocardiogram within 48 hours before to at most 7 days after ICU admission. RV dysfunction and dilatation, respectively, were defined by guideline thresholds for tricuspid annular plane systolic excursion (TAPSE), RV fractional area change, RV free wall longitudinal strain (RVFWS), and RV basal dimension or RV end-diastolic area. Association of RV dysfunction with 60-day mortality was assessed through logistic regression adjusting for age, prior history of congestive heart failure, invasive ventilation at the time of transthoracic echocardiogram, and Acute Physiology and Chronic Health Evaluation II score. Results A total of 116 patients were included, of whom 69% had RV dysfunction by one or more parameters, and 36.3% of these had RV dilatation. The three most common patterns of RV dysfunction were the presence of three abnormalities, the combination of abnormal RVFWS and TAPSE, and isolated TAPSE abnormality. Patients with RV dilatation had worse RV fractional area change (24% vs. 36%; P = 0.001), worse RVFWS (16.3% vs. 19.1%; P = 0.005), higher RV systolic pressure (45 mm Hg vs. 31 mm Hg; P = 0.001) but similar TAPSE (13 mm vs. 13 mm; P = 0.30) compared with those with normal RV size. After multivariable adjustment, 60-day mortality was significantly associated with RV dysfunction (odds ratio, 2.91; 95% confidence interval, 1.01–9.44), as was the presence of at least two parameter abnormalities. Conclusions ICU patients with COVID-19 had significant heterogeneity in RV function abnormalities present with different patterns associated with RV dilatation. RV dysfunction by any parameter was associated with increased mortality. Therefore, a multiparameter evaluation may be critical in recognizing RV dysfunction in COVID-19.
The use of echocardiography, whilst well established in cardiology, is a relatively new concept in critical care medicine. However, in recent years echocardiography's potential as both a diagnostic tool and a form of advanced monitoring in the critically ill patient has been increasingly recognised. In this series of Critical Care Echo Rounds, we explore the role of echocardiography in critical illness, beginning here with haemodynamic instability. We discuss the pathophysiology of the shock state, the techniques available to manage haemodynamic compromise, and the unique role which echocardiography plays in this complex process.CaseA 69-year-old female presents to the emergency department with a fever, confusion and pain on urinating. Her blood pressure on arrival was 70/40, with heart rate of 117 bpm Despite 3 l of i.v. fluid she remained hypotensive. A central venous catheter was inserted and noradrenaline infusion commenced, and she was admitted to the intensive care unit for management of her shock state. At 6 h post admission, she was on high dose of noradrenaline (0.7 μg/kg per min) but blood pressure remained problematic. An echocardiogram was requested to better determine her haemodynamic state.
Background: Echocardiographic strain measurements require extensive operator experience and have significant inter-vendor variability. This study sought to develop an automated deep learning strain (DLS) analysis pipeline and validate its performance both externally and prospectively. Methods: The DLS pipeline takes blood pool semantic segmentation results from the EchoNet-Dynamic network and derives longitudinal strain from the frame-by-frame change in the length of the left ventricular endocardial contour. The pipeline was developed using 7,465 echocardiographic videos, with preprocessing steps optimized to determine the change in endocardial length from systole to diastole. It was evaluated on a large external retrospective dataset and was prospectively compared with manual within-patient acquisition of repeated measures by two experienced sonographers and two separate vendor speckle-tracking methods on different machines. Results: In the external validation set, the DLS method maintained moderate agreement (intraclass correlation coefficient (ICC) 0.58, p<0.001) with a bias of -2.33% (limits of agreement -10.61 to 5.93%). The absolute difference in measurements was independent of subjective image quality (β: 0.12, SE: 0.10, p=0.21). Compared to readers on repeated measures, our method has reduced variability (standard deviation: 1.35 vs. 2.55%) and better inter-vendor agreement (ICC: 0.45 vs. 0.29). Conclusions: The DLS measurement provides lower variance than human measurements and similar quantitative results. The method is rapid, consistent, vendor-agnostic, publicly released, and robust across a wide range of imaging qualities.
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