The European Network for Translational Research in Atrial Fibrillation (EUTRAF): objectives and initial results.

Atrial fibrillation (AF) is the most common sustained arrhythmia in the general population. As an age-related arrhythmia AF is becoming a huge socio-economic burden for European healthcare systems. Despite significant progress in our understanding of the pathophysiology of AF, therapeutic strategies for AF have not changed substantially and the major challenges in the management of AF are still unmet. This lack of progress may be related to the multifactorial pathogenesis of atrial remodelling and AF that hampers the identification of causative pathophysiological alterations in individual patients. Also, again new mechanisms have been identified and the relative contribution of these mechanisms still has to be established. In November 2010, the European Union launched the large collaborative project EUTRAF (European Network of Translational Research in Atrial Fibrillation) to address these challenges. The main aims of EUTRAF are to study the main mechanisms of initiation and perpetuation of AF, to identify the molecular alterations underlying atrial remodelling, to develop markers allowing to monitor this processes, and suggest strategies to treat AF based on insights in newly defined disease mechanisms. This article reports on the objectives, the structure, and initial results of this network

Deep learning for cardiac image segmentation: A review

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US) and major anatomical structures of interest (ventricles, atria and vessels). In addition, a summary of publicly available cardiac image datasets and code repositories are included to provide a base for encouraging reproducible research. Finally, we discuss the challenges and limitations with current deep learning-based approaches (scarcity of labels, model generalizability across different domains, interpretability) and suggest potential directions for future research

Deep Learning in Cardiology

The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data. Deep learning has emerged as a more accurate and effective technology in a wide range of medical problems such as diagnosis, prediction and intervention. Deep learning is a representation learning method that consists of layers that transform the data non-linearly, thus, revealing hierarchical relationships and structures. In this review we survey deep learning application papers that use structured data, signal and imaging modalities from cardiology. We discuss the advantages and limitations of applying deep learning in cardiology that also apply in medicine in general, while proposing certain directions as the most viable for clinical use.Comment: 27 pages, 2 figures, 10 table

Advances in Digital Processing of Low-Amplitude Components of Electrocardiosignals

This manual has been published within the framework of the BME-ENA project under the responsibility of National Technical University of Ukraine. The BME-ENA “Biomedical Engineering Education Tempus Initiative in Eastern Neighbouring Area”, Project Number: 543904-TEMPUS-1-2013-1-GR-TEMPUS-JPCR is a Joint Project within the TEMPUS IV program. This project has been funded with support from the European Commission.Навчальний посібник присвячено розробці методів та засобів для неінвазивного виявлення та дослідження тонких проявів електричної активності серця. Особлива увага приділяється вдосконаленню інформаційного та алгоритмічного забезпечення систем електрокардіографії високого розрізнення для ранньої діагностики електричної нестабільності міокарда, а також для оцінки функціонального стану плоду під час вагітності. Теоретичні основи супроводжуються прикладами реалізації алгоритмів за допомогою системи MATLAB. Навчальний посібник призначений для студентів, аспірантів, а також фахівців у галузі біомедичної електроніки та медичних працівників.The teaching book is devoted to development and research of methods and tools for non-invasive detection of subtle manifistations of heart electrical activity. Particular attention is paid to the improvement of information and algorithmic support of high resolution electrocardiography for early diagnosis of myocardial electrical instability, as well as for the evaluation of the functional state of the fetus during pregnancy examination. The theoretical basis accompanied by the examples of implementation of the discussed algorithms with the help of MATLAB. The teaching book is intended for students, graduate students, as well as specialists in the field of biomedical electronics and medical professionals

Different behaviour of the N-terminal and C-terminal fragment of proatrial natriuretic factor in plasma of healthy subjects as well as of patients with cirrhosis

N-terminal (atrial natriuretic factor (ANF) 1-98) and C-terminal (ANF 99-126) fragments of proatrial natriuretic factor (NTA and CTA, respectively) were determined in plasma of healthy subjects adopting different postures and in patients with cirrhosis. Seven healthy subjects were investigated while seated and 30 min after assuming a horizontal position. NTA plasma concentrations increased in subjects in the horizontal position (from 734±250 (SE) fmol/ml to 9021227 fmol/ml; p<0.05). In contrast, CTA plasma concentrations remained unchanged (9.2+1.3 fmol/ml vs 8.9±1.6 fmol/ml). In 10 patients with cirrhosis of the liver, NTA concentrations were markedly (p<0.001) elevated compared to 11 healthy subjects (2334±291 fmol/ml vs 743±155 fmol/ml). However, there was no difference of CTA plasma levels between cirrhotic patients and healthy subjects (8.7±1.3 fmol/ml vs 8.2±0.9 fmol/ml). These data demonstrate changes of the plasma concentration of the N-terminal fragment of proatrial natriuretic factor by posture and in liver disease, in contrast to unchanged levels of the C-terminal fragment

Experimental studies on coronary perfusion with pump-oxygenator

1. Methods of retrograde coronary perfusion and direct coronary artery perfusion in combination with a bubble oxygenator were investigated in dogs. 2. Ventricular fibrillation occurred more frequently during the operation in hypothermia than in the operation performed in combination with the extracorporeal circulation. 3. The optimal pressure of perfusion is considered to be 30 to 35 mm Hg in retroperfusion, whereas, 100 mm Hg in direct coronary artery perfusion. 4. Perfusion by the pressure bottle method is preferable to the gravity method because the fall of blood temperature in the irrigation tubing might cause ventricular fibrillation. 5. From the metabolic study of the methods is clear that there is a tendency to myocardial anoxia after 15 to 20 minutes of perfusion in both methods.</p