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Space is an extreme environment for the human body, where during long-term missions microgravity and high radiation levels represent major threats to crew health. Intriguingly, space flight (SF) imposes on the body of highly selected, well-trained, and healthy individuals (astronauts and cosmonauts) pathophysiological adaptive changes akin to an accelerated aging process and to some diseases. Such effects, becoming manifest over a time span of weeks (i.e., cardiovascular deconditioning) to months (i.e., loss of bone density and muscle atrophy) of exposure to weightlessness, can be reduced through proper countermeasures during SF and in due time are mostly reversible after landing. Based on these considerations, it is increasingly accepted that SF might provide a mechanistic insight into certain pathophysiological processes, a concept of interest to pre-nosological medicine. In this article, we will review the main stress factors encountered in space and their impact on the human body and will also discuss the possible lessons learned with space exploration in reference to human health on Earth. In fact, this is a productive, cross-fertilized, endeavor in which studies performed on Earth yield countermeasures for protection of space crew health, and space research is translated into health measures for Earth-bound population.

Cardiovascular disease is one of the main causes of morbidity and mortality worldwide. Despite the availability of highly effective treatments, the contemporary burden of disease remains huge. Digital health interventions hold promise to improve further the quality and experience of cardiovascular care. This position paper provides a brief overview of currently existing digital health applications in different cardiovascular disease settings. It provides the reader with the most relevant challenges for their large-scale deployment in Europe. The potential role of different stakeholders and related challenges are identified, and the key points suggestions on how to proceed are given. This position paper was developed by the European Society of Cardiology (ESC) e-Cardiology working group, in close collaboration with the ESC Digital

Background-Echocardiographic contrast media have been used to assess myocardial perfusion and to enhance endocardial definition for improved assessment of left ventricular (LV) function. These methodologies, however, have been qualitative or have required extensive offline image analysis. Power modulation is a recently developed imaging technique that provides selective enhancement of microbubble-generated reflections. Our goal was to test the feasibility of using power modulation for combined quantitative assessment of myocardial perfusion and regional LV function in an animal model of acute ischemia. Methods and Results-Coronary balloon occlusions were performed in 18 anesthetized pigs. Transthoracic power modulation images (Agilent 5500) were obtained during continuous intravenous infusion of the contrast agent Definity (DuPont) at baseline and during brief coronary occlusion and reperfusion and were analyzed with custom software. At each phase, myocardial perfusion was assessed by calculation, in 6 myocardial regions of interest, of mean pixel intensity and the rate of contrast replenishment after high-power ultrasound impulses. LV function was assessed by calculation of regional fractional area change from semiautomatically detected endocardial borders. All ischemic episodes caused detectable and reversible changes in perfusion and function. Perfusion defects, validated with fluorescent microspheres, were visualized in real time and confirmed by a significant decrease in pixel intensity in the left anterior descending coronary artery territory after balloon inflation and reduced rate of contrast replenishment. Fractional area change decreased significantly in ischemic segments and was restored with reperfusion. Conclusions-Power modulation allows simultaneous online assessment of myocardial perfusion and regional LV wall motion, which may improve the echocardiographic diagnosis of myocardial ischemia.

AimsLeft-ventricular (LV) conduction disturbances are common in heart-failure patients and a left bundle-branch block (LBBB) electrocardiogram (ECG) type is often seen. The precise cause of this pattern is uncertain and is probably variable between patients, ranging from proximal interruption of the left bundle branch to diffuse distal conduction disease in the working myocardium. Using realistic numerical simulation methods and patient-tailored model anatomies, we investigated different hypotheses to explain the observed activation order on the LV endocardium, electrogram morphologies, and ECG features in two patients with heart failure and LBBB ECG.Methods and resultsVentricular electrical activity was simulated using reaction–diffusion models with patient-specific anatomies. From the simulated action potentials, ECGs and cardiac electrograms were computed by solving the bidomain equation. Model parameters such as earliest activation sites, tissue conductivity, and densities of ionic currents were tuned to reproduce the measured signals. Electrocardiogram morphology and activation order could be matched simultaneously. Local electrograms matched well at some sites, but overall the measured waveforms had deeper S-waves than the simulated waveforms.ConclusionTuning a reaction–diffusion model of the human heart to reproduce measured ECGs and electrograms is feasible and may provide insights in individual disease characteristics that cannot be obtained by other means.

Object: The aim of this paper is to investigate the use of fully-convolutional neural networks (FCNNs) to segment scar tissue in the left ventricle from cardiac magnetic resonance with late gadolinium enhancement (CMR-LGE) images. Methods: A successful FCNN in the literature (the ENet) was modified and trained to provide scar-tissue segmentation. Two segmentation protocols (Protocol 1 and Protocol 2) were investigated, the latter limiting the scar-segmentation search area to the left ventricular myocardial tissue region. CMR-LGE from 30 patients with ischemicheart disease were retrospectively analyzed, for a total of 250 images, presenting high variability in terms of scar dimension and location. Segmentation results were assessed against manual scar-tissue tracing using one-patient-out cross validation. Results: Protocol 2 outperformed Protocol 1 significantly (p-value < 0.05), with median sensitivity and Dice similarity coefficient equal to 88.07% (inter-quartile range (IQR) = 18.84%) and 71.25% (IQR = 31.82%), respectively. Discussion: Both segmentation protocols were able to detect scar tissues in the CMR-LGE images but higher performance was achieved when limiting the search area to the myocardial region. The findings of this paper represent an encouraging starting point for the use of FCNNs for the automatic segmentation of nonviable scar tissue from CMR-LGE images.

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Smartphones, mobile applications ('apps'), social media, analytics, and the cloud are profoundly changing the practice of medicine and the way health decisions are made. With the constant progress of technology, the measurement of vital signals becomes easier, cheaper, and practically a standard approach in clinical practice. The interest in measuring vital signals goes beyond medical professionals to the general public, patients, informal caregivers, and healthy individuals, who frequently lack any formal medical training. On smartphone platforms such as iOS and Android, a proliferation of health or medical 'apps' acquire and analyse a variety of vital signs through embedded sensors, interconnected devices or peripherals utilising on occasion analytics and social media. Smartphone vendors compete with traditional medical device manufacturers in the grey area between health care, wellness, and fitness, as US and EU regulatory bodies are setting and revising rules for these new technologies. On the other hand, in the absence of robust validation results, clinicians are hesitant to trust measurements by apps or recommend specific apps to their patients, partly also due to lack of a cost reimbursement policy. This review focuses on the acquisition and analysis on smartphones of three important vital signs in the cardiovascular and respiratory field as well as in rehabilitation i.e. heart or pulse rate, blood pressure, and blood oxygenation. The potential, pitfalls, and perspectives on mobile devices and smartphone apps for health management by patients and healthy individuals are discussed.