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Prospective longitudinal follow‐up of left ventricular ejection fraction (LVEF) trajectories after acute cardiac decompensation of heart failure is lacking. We investigated changes in LVEF and covariates at 6‐months' follow‐up in patients with a predischarge LVEF ≤40%, and determined predictors and prognostic implications of LVEF changes through 18‐months' follow‐up.
Methods and Results
Interdisciplinary Network Heart Failure program participants (n=633) were categorized into subgroups based on LVEF at 6‐months' follow‐up: normalized LVEF (>50%; heart failure with normalized ejection fraction, n=147); midrange LVEF (41%–50%; heart failure with midrange ejection fraction, n=195), or persistently reduced LVEF (≤40%; heart failure with persistently reduced LVEF , n=291). All received guideline‐directed medical therapies. At 6‐months' follow‐up, compared with patients with heart failure with persistently reduced LVEF, heart failure with normalized LVEF or heart failure with midrange LVEF subgroups showed greater reductions in LV end‐diastolic/end‐systolic diameters (both P<0.001), and left atrial systolic diameter (P=0.002), more increased septal/posterior end‐diastolic wall‐thickness (both P<0.001), and significantly greater improvement in diastolic function, biomarkers, symptoms, and health status. Heart failure duration <1 year, female sex, higher predischarge blood pressure, and baseline LVEF were independent predictors of LVEF improvement. Mortality and event‐free survival rates were lower in patients with heart failure with normalized LVEF (P=0.002). Overall, LVEF increased further at 18‐months' follow‐up (P<0.001), while LV end‐diastolic diameter decreased (P=0.048). However, LVEF worsened (P=0.002) and LV end‐diastolic diameter increased (P=0.047) in patients with heart failure with normalized LVEF hospitalized between 6‐months' follow‐up and 18‐months' follow‐up.
Conclusions
Six‐month survivors of acute cardiac decompensation for systolic heart failure showed variable LVEF trajectories, with >50% showing improvements by ≥1 LVEF category. LVEF changes correlated with various parameters, suggesting multilevel reverse remodeling, were predictable from several baseline characteristics, and were associated with clinical outcomes at 18‐months' follow‐up. Repeat hospitalizations were associated with attenuation of reverse remodeling."
Despite important advances in diagnosis and treatment, heart failure (HF) remains a syndrome with substantial morbidity and dismal prognosis. Although implementation and optimization of existing technologies and drugs may lead to better management of HF, new or alternative strategies are desirable. In this regard, basic science is expected to give fundamental inputs, by expanding the knowledge of the pathways underlying HF development and progression, identifying approaches that may improve HF detection and prognostic stratification, and finding novel treatments. Here, we discuss recent basic science insights that encompass major areas of translational research in HF and have high potential clinical impact.
Growth, ageing and atherosclerotic plaque development alter the biomechanical forces acting on the vessel wall. However, monitoring the detailed local changes in wall shear stress (WSS) at distinct sites of the murine aortic arch over time has been challenging. Here, we studied the temporal and spatial changes in flow, WSS, oscillatory shear index (OSI) and elastic properties of healthy wildtype (WT, n = 5) and atherosclerotic apolipoprotein E-deficient (Apoe\(^{−/−}\), n = 6) mice during ageing and atherosclerosis using high-resolution 4D flow magnetic resonance imaging (MRI). Spatially resolved 2D projection maps of WSS and OSI of the complete aortic arch were generated, allowing the pixel-wise statistical analysis of inter- and intragroup hemodynamic changes over time and local correlations between WSS, pulse wave velocity (PWV), plaque and vessel wall characteristics. The study revealed converse differences of local hemodynamic profiles in healthy WT and atherosclerotic Apoe\(^{−/−}\) mice, and we identified the circumferential WSS as potential marker of plaque size and composition in advanced atherosclerosis and the radial strain as a potential marker for vascular elasticity. Two-dimensional (2D) projection maps of WSS and OSI, including statistical analysis provide a powerful tool to monitor local aortic hemodynamics during ageing and atherosclerosis. The correlation of spatially resolved hemodynamics and plaque characteristics could significantly improve our understanding of the impact of hemodynamics on atherosclerosis, which may be key to understand plaque progression towards vulnerability.
Aims
Heart failure (HF) leads to repeat hospitalisations and reduces the duration and quality of life. Pulmonary artery pressure (PAP)‐guided HF management using the CardioMEMS™ HF system was shown to be safe and reduce HF hospitalisation (HFH) rates in New York Heart Association (NYHA) class III patients. However, these findings have not been replicated in health systems outside the United States. Therefore, the CardioMEMS European Monitoring Study for Heart Failure (MEMS‐HF) evaluated the safety, feasibility, and performance of this device in Germany, The Netherlands, and Ireland.
Methods and results
A total of 234 NYHA class III patients (68 ± 11 years, 22% female, ≥1 HFH in the preceding year) from 31 centres were implanted with a CardioMEMS sensor and underwent PAP‐guided HF management. One‐year rates of freedom from device‐ or system‐related complications and from sensor failure (co‐primary outcomes) were 98.3% [95% confidence interval (CI) 95.8–100.0] and 99.6% (95% CI 97.6–100.0), respectively. Survival rate was 86.2%. For the 12 months post‐ vs. pre‐implant, HFHs decreased by 62% (0.60 vs. 1.55 events/patient‐year; hazard ratio 0.38, 95% CI 0.31–0.48; P < 0.0001). After 12 months, mean PAP decreased by 5.1 ± 7.4 mmHg, Kansas City Cardiomyopathy Questionnaire (KCCQ) overall/clinical summary scores increased from 47.0 ± 24.0/51.2 ± 24.8 to 60.5 ± 24.3/62.4 ± 24.1 (P < 0.0001), and the 9‐item Patient Health Questionnaire sum score improved from 8.7 ± 5.9 to 6.3 ± 5.1 (P < 0.0001).
Conclusion
Haemodynamic‐guided HF management proved feasible and safe in the health systems of Germany, The Netherlands, and Ireland. Physician‐directed treatment modifications based on remotely obtained PAP values were associated with fewer HFH, sustainable PAP decreases, marked KCCQ improvements, and remission of depressive symptoms.
Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI
(2021)
Background
Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only achieved in the narrow tasks networks are trained on. Performance drops dramatically when data characteristics differ from the training set properties. Moreover, neural networks are commonly considered black boxes, because it is hard to understand how they make decisions and why they fail. Therefore, it is also hard to predict whether they will generalize and work well with new data. Here we present a generic method for segmentation model interpretation. Sensitivity analysis is an approach where model input is modified in a controlled manner and the effect of these modifications on the model output is evaluated. This method yields insights into the sensitivity of the model to these alterations and therefore to the importance of certain features on segmentation performance.
Results
We present an open-source Python library (misas), that facilitates the use of sensitivity analysis with arbitrary data and models. We show that this method is a suitable approach to answer practical questions regarding use and functionality of segmentation models. We demonstrate this in two case studies on cardiac magnetic resonance imaging. The first case study explores the suitability of a published network for use on a public dataset the network has not been trained on. The second case study demonstrates how sensitivity analysis can be used to evaluate the robustness of a newly trained model.
Conclusions
Sensitivity analysis is a useful tool for deep learning developers as well as users such as clinicians. It extends their toolbox, enabling and improving interpretability of segmentation models. Enhancing our understanding of neural networks through sensitivity analysis also assists in decision making. Although demonstrated only on cardiac magnetic resonance images this approach and software are much more broadly applicable.
Purpose
Artificial neural networks show promising performance in automatic segmentation of cardiac MRI. However, training requires large amounts of annotated data and generalization to different vendors, field strengths, sequence parameters, and pathologies is limited. Transfer learning addresses this challenge, but specific recommendations regarding type and amount of data required is lacking. In this study, we assess data requirements for transfer learning to experimental cardiac MRI at 7T where the segmentation task can be challenging. In addition, we provide guidelines, tools, and annotated data to enable transfer learning approaches by other researchers and clinicians.
Methods
A publicly available segmentation model was used to annotate a publicly available data set. This labeled data set was subsequently used to train a neural network for segmentation of left ventricle and myocardium in cardiac cine MRI. The network is used as starting point for transfer learning to 7T cine data of healthy volunteers (n = 22; 7873 images) by updating the pre-trained weights. Structured and random data subsets of different sizes were used to systematically assess data requirements for successful transfer learning.
Results
Inconsistencies in the publically available data set were corrected, labels created, and a neural network trained. On 7T cardiac cine images the model pre-trained on public imaging data, acquired at 1.5T and 3T, achieved DICE\(_{LV}\) = 0.835 and DICE\(_{MY}\) = 0.670. Transfer learning using 7T cine data and ImageNet weight initialization improved model performance to DICE\(_{LV}\) = 0.900 and DICE\(_{MY}\) = 0.791. Using only end-systolic and end-diastolic images reduced training data by 90%, with no negative impact on segmentation performance (DICE\(_{LV}\) = 0.908, DICE\(_{MY}\) = 0.805).
Conclusions
This work demonstrates and quantifies the benefits of transfer learning for cardiac cine image segmentation. We provide practical guidelines for researchers planning transfer learning projects in cardiac MRI and make data, models, and code publicly available.
Impact of Interparticle Interaction on Thermodynamics of Nano-Channel Transport of Two Species
(2020)
Understanding the function and control of channel transport is of paramount importance for cell physiology and nanotechnology. In particular, if several species are involved, the mechanisms of selectivity, competition, cooperation, pumping, and its modulation need to be understood. What lacks is a rigorous mathematical approach within the framework of stochastic thermodynamics, which explains the impact of interparticle in-channel interactions on the transport properties of the respective species. To achieve this, stochastic channel transport of two species is considered in a model, which different from mean field approaches, explicitly conserves the spatial correlation of the species within the channel by analysis of the stochastic dynamics within a state space, the elements of which are the channel’s spatial occupation states. The interparticle interactions determine the stochastic transitions between these states. Local flow and entropy production in this state space reveal the respective particle flows through the channel and the intensity of the Brownian ratchet like rectifying forces, which these species exert mutually on each other, together with its thermodynamic effectiveness and costs. Perfect coupling of transport of the two species is realized by an attractive empty channel and strong repulsive forces between particles of the same species. This confines the state space to a subspace with circular topology, in which the concentration gradients as thermodynamic driving forces act in series, and channel flow of both species becomes equivalent. For opposing concentration gradients, this makes the species with the stronger gradient the driving, positive entropy producing one; the other is driven and produces negative entropy. Gradients equal in magnitude make all flows vanish, and thermodynamic equilibrium occurs. A differential interparticle interaction with less repulsive forces within particles of one species but maintenance of this interaction for the other species adds a bypass path to this circular subspace. On this path, which is not involved in coupling of the two species, a leak flow of the species with less repulsive interparticle interaction emerges, which is directed parallel to its concentration gradient and, hence, produces positive entropy here. Different from the situation with perfect coupling, appropriate strong opposing concentration gradients may simultaneously parallelize the flow of their respective species, which makes each species produce positive entropy. The rectifying potential of the species with the bypass option is diminished. This implies the existence of a gradient of the other species, above which its flow and gradient are parallel for any gradient of the less coupled species. The opposite holds for the less coupled species. Its flow may always be rectified and turned anti-parallel to its gradient by a sufficiently strong opposing gradient of the other one.
Background
Performance anxiety is the most frequently reported anxiety disorder among professional musicians. Typical symptoms are - on a physical level - the consequences of an increase in sympathetic tone with cardiac stress, such as acceleration of heartbeat, increase in blood pressure, increased respiratory rate and tremor up to nausea or flush reactions. These symptoms can cause emotional distress, a reduced musical and artistical performance up to an impaired functioning. While anxiety disorders are preferably treated using cognitive-behavioral therapy with exposure, this approach is rather difficult for treating music performance anxiety since the presence of a public or professional jury is required and not easily available. The use of virtual reality (VR) could therefore display an alternative. So far, no therapy studies on music performance anxiety applying virtual reality exposure therapy have investigated the therapy outcome including cardiovascular changes as outcome parameters.
Methods
This mono-center, prospective, randomized and controlled clinical trial has a pre-post design with a follow-up period of 6 months. 46 professional and semi-professional musicians will be recruited and allocated randomly to an VR exposure group or a control group receiving progressive muscle relaxation training. Both groups will be treated over 4 single sessions. Music performance anxiety will be diagnosed based on a clinical interview using ICD-10 and DSM-5 criteria for specific phobia or social anxiety. A behavioral assessment test is conducted three times (pre, post, follow-up) in VR through an audition in a concert hall. Primary outcomes are the changes in music performance anxiety measured by the German Bühnenangstfragebogen and the cardiovascular reactivity reflected by heart rate variability (HRV). Secondary outcomes are changes in blood pressure, stress parameters such as cortisol in the blood and saliva, neuropeptides, and DNA-methylation.
Discussion
The trial investigates the effect of VR exposure in musicians with performance anxiety compared to a relaxation technique on anxiety symptoms and corresponding cardiovascular parameters. We expect a reduction of anxiety but also a consecutive improvement of HRV with cardiovascular protective effects.
Trial registration
This study was registered on clinicaltrials.gov. (ClinicalTrials.gov Number: NCT05735860)
Background
Right ventricular dysfunction after CABG is associated with poor peri- and postoperative outcomes. We aimed to identify clinical and experimental predictors for preoperative inapparent right ventricular dysfunction and therefore hypothesized that reduced myofilament force development as well as altered levels of biomarkers might predict inapparent right ventricular dysfunction.
Methods
From 08/2016 to 02/2018, 218 patients scheduled for CABG were divided into two groups (TAPSE ≥ 20 mm, n = 178; TAPSE < 20 mm, n = 40). Baseline serum samples for biomarkers (Galectin, TGFß1, N Acyl-SDMA, Arginine, ADMA and Pentraxin-3), clinical laboratory and transthoracic echocardiographic parameters were evaluated. To examine the myocardial apparatus of the right ventricle intraoperative right auricular tissue was harvested for stepwise skinned fiber force measurements.
Results
Patients with TAPSE < 20 mm had a higher incidence of DM (55 vs. 34%, p = 0.018), preoperative AFib (43 vs. 16%, p < 0.001), reduced GFR (67 ± 18 vs. 77 ± 24 ml/min/1.73 m\(^2\), p = 0.013), larger LA area (22 ± 6 vs. 20 ± 5 cm\(^2\), p = 0.005) and reduced LVEF (50 vs. 55%, p = 0.008). Furthermore, higher serum ADMA (0.70 ± 0.13 vs. 0.65 ± 0.15 µmol/l, p = 0.046) and higher serum Pentraxin-3 levels (3371 ± 1068 vs. 2681 ± 1353 pg/dl, p = 0.004) were observed in these patients. Skinned fiber force measurements showed significant lower values at almost every step of calcium concentration (pCa 4.52 to pCa 5.5, p < 0.01 and pCa 5.75–6.0, p < 0.05). Multivariable analysis revealed DM (OR 2.53, CI 1.12–5.73, Euro Score II (OR 1.34, CI 1.02–1.78), preoperative AF (OR 4.86, CI 2.06–11.47), GFR (OR 7.72, CI 1.87–31.96), albumin (OR 1.56, CI 0.52–2.60), Pentraxin-3 (OR 19.68, CI 14.13–25.24), depressed LVEF (OR 8.61, CI 6.37–10.86), lower force values: (pCa 5.4; OR 2.34, CI 0.40–4.29 and pCa 5.2; OR 2.00, CI 0.39–3.60) as predictors for clinical inapparent right heart dysfunction.
Conclusions
These preliminary data showed that inapparent right heart dysfunction in CAD is already associated with reduced force development of the contractile apparatus.
Although heart failure following myocardial infarction (MI) represents a major health burden, underlying microstructural and functional changes remain incompletely understood. Here, we report on a case of unexpected MI after treatment with the catecholamine isoproterenol in an experimental imaging study in mice using different state-of-the-art imaging modalities. The decline in cardiac function was documented by ultrahigh-frequency echocardiography and speckle-tracking analyses. Myocardial microstructure was studied ex vivo at a spatial resolution of 100 × 100 × 100 μm\(^{3}\) using diffusion tensor magnetic resonance imaging (DT-MRI) and histopathologic analyses. Two weeks after ISO treatment, the animal showed an apical aneurysm accompanied by reduced radial strain in corresponding segments and impaired global systolic function. DT-MRI revealed a loss of contractile fiber tracts together with a disarray of remaining fibers as corresponding microstructural correlates. This preclinical case report provides valuable insights into pathophysiology and morphologic–functional relations of heart failure following MI using emerging imaging technologies.