The 21st Annual Feigenbaum Lecture: Beyond Artificial: Echocardiography from Elegant Images to Analytic Intelligence

Heart failure with preserved ejection fraction: diagnosis, risk assessment, and treatment

The aetiology of heart failure with preserved ejection fraction (HFpEF) is heterogenous and overlaps with that of several comorbidities like atrial fibrillation, diabetes mellitus, chronic kidney disease, valvular heart disease, iron deficiency, or sarcopenia. The diagnosis of HFpEF involves evaluating cardiac dysfunction through imaging techniques and assessing increased left ventricular filling pressure, which can be measured directly or estimated through various proxies including natriuretic peptides. To better narrow down the differential diagnosis of HFpEF, European and American heart failure guidelines advocate the use of different algorithms including comorbidities that require diagnosis and rigorous treatment during the evaluation process. Therapeutic recommendations differ between guidelines. Whilst sodium glucose transporter 2 inhibitors have a solid evidence base, the recommendations differ with regard to the use of inhibitors of the renin-angiotensin-aldosterone axis. Unless indicated for specific comorbidities, the use of beta-blockers should be discouraged in HFpEF. The aim of this article is to provide an overview of the current state of the art in HFpEF diagnosis, clinical evaluation, and treatment.

Artificial intelligence in the pediatric echocardiography laboratory: Automation, physiology, and outcomes

Artificial intelligence (AI) is frequently used in non-medical fields to assist with automation and decision-making. The potential for AI in pediatric cardiology, especially in the echocardiography laboratory, is very high. There are multiple tasks AI is designed to do that could improve the quality, interpretation, and clinical application of echocardiographic data at the level of the sonographer, echocardiographer, and clinician. In this state-of-the-art review, we highlight the pertinent literature on machine learning in echocardiography and discuss its applications in the pediatric echocardiography lab with a focus on automation of the pediatric echocardiogram and the use of echo data to better understand physiology and outcomes in pediatric cardiology. We also discuss next steps in utilizing AI in pediatric echocardiography.

Mechanical QT and JT intervals by M-mode echocardiography: An extrapolation from the concurrent electrocardiographic tracings

Background

Congenital long QT syndrome (CLQTS) is a life-threatening ion channelopathy leading to syncope and sudden death. Early diagnosis during the prenatal period and timely intervention can prevent sudden cardiac death and catastrophic consequences of this genetic ion channelopathy. Fetal magnetocardiography and fetal electrocardiography (ECG) enable the measurement of fetal QT and JT intervals, but their inherently technically challenging and/or resource-intensiveness nature preclude their routine clinical application. On the other hand, the high-temporal resolution of M-mode echocardiography makes it a well-suited and widely available modality for the measurement of cardiac events.

Aims and Objectives

We aimed to investigate the mechanical counterparts of the electrical QT and JT intervals on M-mode echocardiographic images of the tricuspid, mitral and aortic valves, and aortic wall.

Methods

We performed a prospective study on consecutive children referred to the outpatient pediatric cardiology clinic at a tertiary children's hospital. We defined M-mode echocardiographic landmark points on tracings of tricuspid annular planar systolic excursion, mitral and aortic valves, and aortic wall with simultaneous electrocardiographic recording. We measured the mean±SD of the absolute time difference and RR-adjusted time difference in cases with non-coincident ECG events and echocardiographic landmarks.

Results

Fifty healthy children were enrolled in the study. In 47 (94%) out of the 50 children, Q was coincident with the starting point of the tricuspid annular plane systolic excursion. In all children, the Q was coincident with the mid-point of the A-C line of the mitral valve. In 38 (76%) cases, there was a bump on the anterior wall of the aortic root immediately before the change in the slope of the aortic wall. This was coincident with the Q wave in 100% of cases. In all cases, the J point coincided with the point of acceleration of velocity on TAPSE. In all children, the J point coincided with the initial maximal opening of the aortic cusps. The end of the T wave occurred coincident with the peak of the tricuspid annular planar systolic excursion in 47 children (94%). In 48 children (96%), the end of the T wave coincided with the aortic cusps' closure point.

Conclusions

Based on our findings, we propose to measure the averaged mechanical QT and JT intervals by using an angled M-mode tracing of the aortic and mitral valve in five consecutive beats in the parasternal long-axis view. This is the first study on mechanical QT and JT intervals in healthy children. The study opens the horizons into the in-utero diagnosis of congenital long QT syndrome by measuring fetal QT and JT intervals using the widely available M-mode echocardiography.

The Year in Perioperative Echocardiography: Selected Highlights from 2020

This article is the fifth of an annual series reviewing the research highlights of the year pertaining to the subspecialty of perioperative echocardiography for the Journal of Cardiothoracic and Vascular Anesthesia. The authors thank Editor-in-Chief Dr. Kaplan and the editorial board for the opportunity to continue this series. In most cases, these will be research articles that are targeted at the perioperative echocardiography diagnosis and treatment of patients after cardiothoracic surgery; but in some cases, these articles will target the use of perioperative echocardiography in general.