Ultrasound – An Underutilized Diagnostic Tool For Ventricular Assist Device Driveline Infections

Patients with ventricular assist device (VAD) driveline infections (DLI) have reduced quality of life and increased risk of severe complications, such as sepsis, hemorrhagic or ischemic stroke, and wound infections. The management of VAD patients imposes a significant financial burden due to prolonged in-hospital stays, frequent re-admissions, expensive diagnostics, and the need for antibiotic therapy and/or surgical intervention. There is considerable room for improvement in DLI management, particularly in the early detection and treatment stages. Ultrasound, an easily applicable device available in almost every hospital, offers an unrecognized potential for the early detection of DLI. By increasing awareness about the potential advantages of ultrasound in DLI management, especially in specialized tertiary centers with a high number of VAD patients, this method may contribute to creating valuable databases, establishing recommendations, and improving outcomes

Effects of Sacubitril-Valsartan, versus Valsartan, in Women Compared to Men with Heart Failure and Preserved Ejection Fraction: Insights from PARAGON-HF

Unlike heart failure with reduced ejection fraction, there is no approved treatment for heart failure with preserved ejection fraction (HFpEF), the predominant phenotype in women. Therefore, there is a greater heart failure therapeutic deficit in women, compared with men. In a pre-specified subgroup analysis, we examined outcomes according to sex in the PARAGON-HF trial which compared sacubitril-valsartan and valsartan in patients with HFpEF. The primary outcome was a composite of first and recurrent hospitalizations for heart failure and death from cardiovascular causes. We also report secondary efficacy and safety outcomes. Overall, 2479 women (51.7%) and 2317 men (48.3%) were randomized. Women were older, had more obesity, less coronary disease, and lower estimated glomerular filtration rate and NT-proBNP levels than men. For the primary outcome, the rate ratio for sacubitril-valsartan versus valsartan was 0.73 (95% CI 0.59-0.90) in women and 1.03 (0.84-1.25) in men; P interaction=0.017. The benefit from sacubitril-valsartan was due to reduction in heart failure hospitalization. The improvement in NYHA class and renal function with sacubitril-valsartan was similar in women and men, whereas the improvement in KCCQ-CSS was less in women than in men. The difference in adverse events, between sacubitril-valsartan and valsartan, was similar in women and men. As compared with valsartan, sacubitril-valsartan seemed to reduce the risk of heart failure hospitalization more in women than in men. While the possible sex-related modification of the effect of treatment has several potential explanations, the present study does not provide a definite mechanistic basis for this finding. URL: https://clinicaltrials.gov Unique Identifier: NCT01920711

Image registration and atlas-based segmentation of cardiac outflow velocity profiles

Cardiovascular disease is the leading cause of death worldwide and for this reason computer-based diagnosis of cardiac diseases is a very important task. In this article, a method for segmentation of aortic outflow velocity profiles from cardiac Doppler ultrasound images is presented. The proposed method is based on the statistical image atlas derived from ultrasound images of healthy volunteers. The ultrasound image segmentation is done by registration of the input image to the atlas, followed by a propagation of the segmentation result from the atlas onto the input image. In the registration process, the normalized mutual information is used as an image similarity measure, while optimization is performed using a multiresolution gradient ascent method. The registration method is evaluated using an in-silico phantom, real data from 30 volunteers, and an inverse consistency test. The segmentation method is evaluated using 59 images from healthy volunteers and 89 images from patients, and using cardiac parameters extracted from the segmented image. Experimental validation is conducted using a set of healthy volunteers and patients and has shown excellent results. Cardiac parameter segmentation evaluation showed that the variability of the automated segmentation relative to the manual is comparable to the intra-observer variability. The proposed method is useful for computer aided diagnosis and extraction of cardiac parameters

Comprehensive data integration—Toward a more personalized assessment of diastolic function

Background and aim: The main challenge of assessing diastolic function is the balance between clinical utility, in the sense of usability and time‐efficiency, and overall applicability, in the sense of precision for the patient under investigation. In this review, we aim to explore the challenges of integrating data in the assessment of diastolic function and discuss the perspectives of a more comprehensive data integration approach. Methods: Review of traditional and novel approaches regarding data integration in the assessment of diastolic function. Results: Comprehensive data integration can lead to improved understanding of disease phenotypes and better relation of these phenotypes to underlying pathophysiological processes—which may help affirm diagnostic reasoning, guide treatment options, and reduce limitations related to previously unaddressed confounders. The optimal assessment of diastolic function should ideally integrate all relevant clinical information with all available structural and functional whole cardiac cycle echocardiographic data—envisioning a personalized approach to patient care, a high‐reaching future goal in medicine. Conclusion: Complete data integration seems to be a long‐lasting goal, the way forward in diastology, and machine learning seems to be one of the tools suited for the challenge. With perpetual evidence that traditional approaches to complex problems may not the optimal solution, there is room for a steady and cautious, and inherently very exciting paradigm shift toward novel diagnostic tools and workflows to reach a more personalized, comprehensive, and integrated assessment of cardiac function.This work was supported by Horizon 2020 European Commission Project H2020-MSCA-ITN-2016 (764738)

The shape of the aortic outflow velocity profile revisited: is there a relation between its asymmetry and ventricular function in coronary artery disease?

Aims Myocardium contracts in the beginning of ejection causing outflow acceleration, resulting in asymmetric outflow velocity profiles peaking around one-third of ejection and declining when force development declines. This article aimed to demonstrate that decreased contractility in coronary artery disease (CAD) changes outflow timing and profile symmetry. Methods and results Seventy-nine patients undergoing routine full dose dobutamine stress-echo (DSE) were divided into two groups based on resting wall motion and DSE response: DSE negative (DSE neg ) (35 of 79 patients) and positive (DSE pos ) (44 of 79 patients) which were compared with 32 healthy volunteers. Aortic CW-Doppler traces at rest were analysed semi-automatically; time-to-peak (T mod ), ejection-time (ET mod ), rise-time (t rise ), and fall-time (t fall ) were quantified. Asymmetry (asymm) was calculated as the normalized difference of left and right half of the spectrum. Normal curves were triangular, early-peaking, whereas patients showed more rounded shapes and later peaks. T rise was longest in DSE pos . T fall was shortest in DSE pos , followed by controls and DSE neg . Asymm was lowest in DSE pos , followed by controls and DSE neg . Abnormally symmetric profiles (asymm ,0.25) were found in none of the controls, 2.9% DSE neg , and 27.3% DSE pos . A good correlation was found between assym and ejection fraction (EF) and T mod /ET mod and EF. Notably, an LV dynamic gradient was induced in 71.4% DSE neg and in 18.2% DSE pos , associated with LV hypertrophy and supernormal (very asymmetric) traces. Conclusion Decreased myocardial function results in a more symmetrical outflow, while very asymmetrical traces suggest increased contractility, potentially inducing intra-cavity gradients during DSE. Therefore, including outflow symmetry as a clinical measurement provides additional information on patients with CAD

Inter-operator variability of shapes and strain patterns: insights from a myocardial strain course

International audienceno abstrac

The role of echocardiographic deformation imaging in hypertrophic myopathies

Echocardiography has a leading role in the routine assessment and diagnosis of hypertrophic ventricles. However, the use of M-mode echocardiography and measurement of global left ventricular function may be misleading. Traditionally, systolic function was thought to be preserved in patients with hypertrophic myopathies until the late stages of the disease, and hypertrophic myopathies were thought to affect the myocardium more diffusely than ischemic heart disease. Ultrasound deformation imaging, either by Doppler myocardial imaging or speckle tracking, provides more-sensitive detection of regional myocardial motion and deformation than standard echocardiography. Basic and clinical studies that apply these techniques have revealed early, often subclinical impairment in systolic function. This information allows the detection and treatment of myocardial dysfunction at an early stage, which is of high clinical importance. Physiological hypertrophic remodeling seen in athletes differs from pathological myocardial hypertrophy, which can be caused by compensatory reactive hypertrophy owing to pressure overload in patients with aortic stenosis or hypertension, as well as amyloidosis, Fabry disease or Friedreich ataxia. Each of the etiologies associated with hypertrophy demonstrate distinct regional changes in myocardial deformation, which allows identification of the underlying processes, and will improve the assessment and follow-up of patients with hypertrophic myopathies.status: publishe

A Computational model-based approach for atlas construction of aortic Doppler velocity profiles for segmentation purposes

Echocardiography is the leading imaging modality for cardiac disorders in clinical practice. During an echocardiographic exam, geometry and blood flow are quantified in order to assess cardiac function. In clinical practice, these imagebased measurements are currently performed manually. An automated approach is needed if more advanced analysis is desired. In this article, we propose a new hybrid framework for the construction of a disease-specific atlas to improve Doppler aortic outflow velocity profile segmentation. The proposed method is based on combining realistic computational simulations of the cardiovascular system for common cardiac conditions (using CircAdapt) with a validated image-based atlas construction method. The coupling is realized via model-based generation of echocardiographic images of virtual populations with a statistically approved parameter variation. We created virtual populations of 100 healthy individuals and 100 patients with aortic stenosis, synthesized their aortic Doppler velocity images and constructed the corresponding atlases. We validated atlases’ performances by comparing their segmentation of real clinical images with the manually segmented ground truth. The experimental results show that the segmentation accuracy obtained using the proposed atlases is comparable to the accuracy obtained using classical clinical image-based atlases. Moreover, this framework eliminates the time-consuming acquisition of a sufficient number of representative images in clinical practice, offering a substantial time efficiency and flexibility in creating a disease specific atlas and ensuring an observer-independent automated segmentation. The proposed approach can easily be extended towards the creation of atlases for segmenting any Doppler trace in the cardiovascular circulation in a specific disease.Research leading to these results has received funding from the Ministry of Science, Education and Sports, Republic of Croatia (036-0362214-1989), Subprograma de Proyectos de Investigacin en Salud (FIS), Instituto de Salud Carlos III, Spain (ref. PI11/01709); the Spanish Ministry of Economy and Competitiveness (grant TIN2014-52923-R) and FEDER and the Seventh Framework Programme (FP7/2007-2013) under grant agreement No. 611823. Additionally, we would like to thank Frank Weidemann for a subset of the patient images, and Catalina Tobon-Gomez and Georgina Palau-Caballero for provided CircAdapt support