Fully Automated Versus Standard Tracking of Left Ventricular Ejection Fraction and Longitudinal Strain the FAST-EFs Multicenter Study

none10siBACKGROUND: Echocardiographic determination of ejection fraction (EF) by manual tracing of endocardial borders is time consuming and operator dependent, whereas visual assessment is inherently subjective. OBJECTIVES: This study tested the hypothesis that a novel, fully automated software using machine learning-enabled image analysis will provide rapid, reproducible measurements of left ventricular volumes and EF, as well as average biplane longitudinal strain (LS). METHODS: For a total of 255 patients in sinus rhythm, apical 4- and 2-chamber views were collected from 4 centers that assessed EF using both visual estimation and manual tracing (biplane Simpson's method). In addition, datasets were saved in a centralized database, and machine learning-enabled software (AutoLV, TomTec-Arena 1.2, TomTec Imaging Systems, Unterschleissheim, Germany) was applied for fully automated EF and LS measurements. A reference center reanalyzed all datasets (by visual estimation and manual tracking), along with manual LS determinations. RESULTS: AutoLV measurements were feasible in 98% of studies, and the average analysis time was 8 ± 1 s/patient. Interclass correlation coefficients and Bland-Altman analysis revealed good agreements among automated EF, local center manual tracking, and reference center manual tracking, but not for visual EF assessments. Similarly, automated and manual LS measurements obtained at the reference center showed good agreement. Intraobserver variability was higher for visual EF than for manual EF or manual LS, whereas interobserver variability was higher for both visual and manual EF, but not different for LS. Automated EF and LS had no variability. CONCLUSIONS: Fully automated analysis of echocardiography images provides rapid and reproducible assessment of left ventricular EF and LS.openKnackstedt, Christian; Bekkers, Sebastiaan C.A.M.; Schummers, Georg; Schreckenberg, Marcus; Muraru, Denisa; Badano, Luigi; Franke, Andreas; Bavishi, Chirag; Omar, Alaa Mabrouk Salem; Sengupta, Partho P.Knackstedt, Christian; Bekkers, Sebastiaan C. A. M.; Schummers, Georg; Schreckenberg, Marcus; Muraru, Denisa; Badano, Luigi; Franke, Andreas; Bavishi, Chirag; Omar, Alaa Mabrouk Salem; Sengupta, Partho P

Coronary CT angiography for improved assessment of patients with acute chest pain and low-range positive high-sensitivity troponins: Study protocol for a prospective, observational, multicentre study (COURSE trial)

Introduction Current evaluation of patients suspected of a non-ST-elevation acute coronary syndrome (NSTE-ACS) involves the use of algorithms that incorporate clinical information, electrocardiogram (ECG) and high-sensitivity cardiac troponins (hs-troponins). While primarily designed to rule out NSTE-ACS safely, these algorithms can also be used for rule in of NSTE-ACS in some patients. Still, in a substantial number of patients, these algorithms do not provide a conclusive work-up. These patients often present with an atypical clinical profile and low-range positive hs-troponin values without a characteristic rise or fall pattern. They represent a heterogeneous group of patients with various underlying conditions; only a fraction (30%-40%) will eventually be diagnosed with a myocardial infarction. Uncertainty exists about the optimal diagnostic strategy and their management depends on the clinical perspective of the treating physician ranging from direct discharge to admission for invasive coronary angiography. Coronary CT angiography (CCTA) is a non-invasive test that has been shown to be safe, fast and reliable in the evaluation of coronary artery disease. In this study, we will determine the usefulness of CCTA in patients with acute chest pain and low-range positive hs-troponin values. Methods and analysis A prospective, double-blind, observational, multicentre study conducted in the Netherlands. Patients aged 30-80 years presenting to the emergency department with acute chest pain and a suspicion of NSTE-ACS, a normal or non-diagnostic ECG and low-range positive hs-troponins will be scheduled to undergo CCTA. The primary outcome is the diagnostic accuracy of CCTA for the diagnosis of NSTE-ACS at discharge, in terms of sensitivity and negative predictive value. Ethics and dissemination This study was approved by the Medical Research Ethics Committee of Erasmus Medical Center in Rotterdam, the Netherlands (registration number MEC-2017-506). Written informed consent to participate will be obtained from all participants. This study's findings will be published in a peer-reviewed journal. Trial registration number ClinicalTrials.gov (NCT03129659).</p

Expert consensus recommendations on the cardiogenetic care for patients with thoracic aortic disease and their first-degree relatives

Background: Thoracic aortic aneurysm (TAA) is a potentially life-threatening disorder with a strong genetic component. The number of genes implicated in TAA has increased exponentially over the last decade. Approximately 20% of patients with TAA have a positive family history. As most TAA remain asymptomatic for a long time, screening of at risk relatives is warranted to prevent complications. Existing international guidelines lack detailed instructions regarding genetic evaluation and family screening of TAA patients. We aimed to develop a consensus document to provide medical guidance for all health care professionals involved in the recognition, diagnosis and treatment of patients with thoracic aortic disease and their relatives. Methods: A multidisciplinary panel of experts including cardiologists, cardiothoracic surgeons, clinical geneticists and general practitioners, convened to review and discuss the current literature, guidelines and clinical practice on genetic testing and family screening in TAA. Results: There is a lack of high-quality evidence in the literature. This consensus statement, based on the available literature and expert opinions, summarizes our recommendations in order to standardize and optimize the cardiogenetic care for patients and families with thoracic aortic disease. In particular, we provide criteria to identify those patients most likely to have a genetic predisposition, and discuss the preferred modality and frequency of screening in their relatives. Conclusions: Age, family history, aortic size and syndromic features determine who is advised to have genetic testing as well as screening of first-degree relatives. There is a need for more prospective multicenter studies to optimize current recommendations

Precision phenotyping of dilated cardiomyopathy using multidimensional data

Background: Dilated cardiomyopathy (DCM) is a final common manifestation of heterogenous etiologies. Adverse outcomes highlight the need for disease stratification beyond ejection fraction. Objectives: The purpose of this study was to identify novel, reproducible subphenotypes of DCM using multiparametric data for improved patient stratification. Methods: Longitudinal, observational UK-derivation (n = 426; median age 54 years; 67% men) and Dutch-validation (n = 239; median age 56 years; 64% men) cohorts of DCM patients (enrolled 2009-2016) with clinical, genetic, cardiovascular magnetic resonance, and proteomic assessments. Machine learning with profile regression identified novel disease subtypes. Penalized multinomial logistic regression was used for validation. Nested Cox models compared novel groupings to conventional risk measures. Primary composite outcome was cardiovascular death, heart failure, or arrhythmia events (median follow-up 4 years). Results: In total, 3 novel DCM subtypes were identified: profibrotic metabolic, mild nonfibrotic, and biventricular impairment. Prognosis differed between subtypes in both the derivation (P &lt; 0.0001) and validation cohorts. The novel profibrotic metabolic subtype had more diabetes, universal myocardial fibrosis, preserved right ventricular function, and elevated creatinine. For clinical application, 5 variables were sufficient for classification (left and right ventricular end-systolic volumes, left atrial volume, myocardial fibrosis, and creatinine). Adding the novel DCM subtype improved the C-statistic from 0.60 to 0.76. Interleukin-4 receptor-alpha was identified as a novel prognostic biomarker in derivation (HR: 3.6; 95% CI: 1.9-6.5; P = 0.00002) and validation cohorts (HR: 1.94; 95% CI: 1.3-2.8; P = 0.00005). Conclusions: Three reproducible, mechanistically distinct DCM subtypes were identified using widely available clinical and biological data, adding prognostic value to traditional risk models. They may improve patient selection for novel interventions, thereby enabling precision medicine