Single-Site Experience with an Automated Artificial Intelligence Application for Left Ventricular Ejection Fraction Measurement in Echocardiography.

Left ventricular ejection fraction (LVEF) is a key parameter in evaluating left ventricular (LV) function using echocardiography (Echo), but its manual measurement by the modified biplane Simpson (MBS) method is time consuming and operator dependent. We investigated the feasibility of a server-based, commercially available and ready-to use-artificial intelligence (AI) application based on convolutional neural network methods that integrate fully automatic view selection and measurement of LVEF from an entire Echo exam into a single workflow. We prospectively enrolled 1083 consecutive patients who had been referred to Echo for diagnostic or therapeutic purposes. LVEF was measured independently using MBS and AI. Test-retest variability was assessed in 40 patients. The reliability, repeatability, and time efficiency of LVEF measurements were compared between the two methods. Overall, 889 Echos were analyzed by cardiologists with the MBS method and by the AI. Over the study period of 10 weeks, the feasibility of both automatic view classification and seamlessly measured LVEF rose to 81% without user involvement. LVEF, LV end-diastolic and end-systolic volumes correlated strongly between MBS and AI (R = 0.87, 0.89 and 0.93, p < 0.001 for all) with a mean bias of +4.5% EF, -12 mL and -11 mL, respectively, due to impaired image quality and the extent of LV function. Repeatability and reliability of LVEF measurement (n = 40, test-retest) by AI was excellent compared to MBS (coefficient of variation: 3.2% vs. 5.9%), although the median analysis time of the AI was longer than that of the operator-dependent MBS method (258 s vs. 171 s). This AI has succeeded in identifying apical LV views and measuring EF in one workflow with comparable results to the MBS method and shows excellent reproducibility. It offers realistic perspectives for fully automated AI-based measurement of LVEF in routine clinical settings.

Hypochlorhydria reduces mortality in heart failure caused by Kcne2 gene deletion.

Heart failure (HF) is an increasing global health crisis, affecting 40 million people and causing 50% mortality within 5 years of diagnosis. A fuller understanding of the genetic and environmental factors underlying HF, and novel therapeutic approaches to address it, are urgently warranted. Here, we discovered that cardiac-specific germline deletion in mice of potassium channel ß subunit-encoding Kcne2 (Kcne2CS-/- ) causes dilated cardiomyopathy and terminal HF (median longevity, 28 weeks). Mice with global Kcne2 deletion (Kcne2Glo-/- ) exhibit multiple HF risk factors, yet, paradoxically survived over twice as long as Kcne2CS-/- mice. Global Kcne2 deletion, which inhibits gastric acid secretion, reduced the relative abundance of species within Bacteroidales, a bacterial order that positively correlates with increased lifetime risk of human cardiovascular disease. Strikingly, the proton-pump inhibitor omeprazole similarly altered the microbiome and delayed terminal HF in Kcne2CS-/- mice, increasing survival 10-fold at 44 weeks. Thus, genetic or pharmacologic induction of hypochlorhydria and decreased gut Bacteroidales species are associated with lifespan extension in a novel HF model.

Predictive value of metabolomic biomarkers for cardiovascular disease risk: a systematic review and meta-analysis.

Background: Metabolomic analysis aids in the identification of novel biomarkers by revealing the metabolic dysregulations underlying cardiovascular disease (CVD) aetiology. The aim of this study was to evaluate which metabolic biomarkers could add value for the prognosis of CVD events using meta-analysis.Methods: The PRISMA guideline was followed for the systematic review. For the meta-analysis, biomarkers were included if they were tested in multivariate prediction models for fatal CVD outcomes. We grouped the metabolites in biological classes for subgroup analysis. We evaluated the prediction performance of models which reported discrimination and/or reclassification statistics.Results: For the systematic review, there were 22 studies which met the inclusion/exclusion criteria. For the meta-analysis, there were 41 metabolites grouped into 8 classes from 19 studies (45,420 subjects, 5954 events). A total of 39 of the 41 metabolites were significant with a combined effect size of 1.14 (1.07-1.20). For the predictive performance assessment, there were 21 studies, 54,337 subjects, 6415 events. The average change in c-statistic after adding the biomarkers to a clinical model was 0.0417 (SE 0.008).Conclusions: This study provides evidence that metabolomic biomarkers, mainly lipid species, have the potential to provide additional prognostic value. Current data are promising, although approaches and results are heterogeneous.

Isolation and Kv channel recordings in murine atrial and ventricular cardiomyocytes.

KCNE genes encode for a small family of Kv channel ancillary subunits that form heteromeric complexes with Kv channel alpha subunits to modify their functional properties. Mutations in KCNE genes have been found in patients with cardiac arrhythmias such as the long QT syndrome and/or atrial fibrillation. However, the precise molecular pathophysiology that leads to these diseases remains elusive. In previous studies the electrophysiological properties of the disease causing mutations in these genes have mostly been studied in heterologous expression systems and we cannot be sure if the reported effects can directly be translated into native cardiomyocytes. In our laboratory we therefore use a different approach. We directly study the effects of KCNE gene deletion in isolated cardiomyocytes from knockout mice by cellular electrophysiology - a unique technique that we describe in this issue of the Journal of Visualized Experiments. The hearts from genetically engineered KCNE mice are rapidly excised and mounted onto a Langendorff apparatus by aortic cannulation. Free Ca(2+) in the myocardium is bound by EGTA, and dissociation of cardiac myocytes is then achieved by retrograde perfusion of the coronary arteries with a specialized low Ca(2+) buffer containing collagenase. Atria, free right ventricular wall and the left ventricle can then be separated by microsurgical techniques. Calcium is then slowly added back to isolated cardiomyocytes in a multiple step comprising washing procedure. Atrial and ventricular cardiomyocytes of healthy appearance with no spontaneous contractions are then immediately subjected to electrophysiological analyses by patch clamp technique or other biochemical analyses within the first 6 hours following isolation.