Characterization of Respiratory and Cardiac Motion from Electro-Anatomical Mapping Data for Improved Fusion of MRI to Left Ventricular Electrograms

Accurate fusion of late gadolinium enhancement magnetic resonance imaging (MRI) and electro-anatomical voltage mapping (EAM) is required to evaluate the potential of MRI to identify the substrate of ventricular tachycardia. However, both datasets are not acquired at the same cardiac phase and EAM data is corrupted with respiratory motion limiting the accuracy of current rigid fusion techniques. Knowledge of cardiac and respiratory motion during EAM is thus required to enhance the fusion process. In this study, we propose a novel approach to characterize both cardiac and respiratory motion from EAM data using the temporal evolution of the 3D catheter location recorded from clinical EAM systems. Cardiac and respiratory motion components are extracted from the recorded catheter location using multi-band filters. Filters are calibrated for each EAM point using estimates of heart rate and respiratory rate. The method was first evaluated in numerical simulations using 3D models of cardiac and respiratory motions of the heart generated from real time MRI data acquired in 5 healthy subjects. An accuracy of 0.6–0.7 mm was found for both cardiac and respiratory motion estimates in numerical simulations. Cardiac and respiratory motions were then characterized in 27 patients who underwent LV mapping for treatment of ventricular tachycardia. Mean maximum amplitude of cardiac and respiratory motion was 10.2±2.7 mm (min = 5.5, max = 16.9) and 8.8±2.3 mm (min = 4.3, max = 14.8), respectively. 3D Cardiac and respiratory motions could be estimated from the recorded catheter location and the method does not rely on additional imaging modality such as X-ray fluoroscopy and can be used in conventional electrophysiology laboratory setting

The Latest Trends in Electric Vehicles Batteries

Global energy demand is rapidly increasing due to population and economic growth, especially in large emerging countries, which will account for 90% of energy demand growth to 2035. Electric vehicles (EVs) play a paramount role in the electrification revolution towards the reduction of the carbon footprint. Here, we review all the major trends in Li-ion batteries technologies used in EVs. We conclude that only five types of cathodes are used and that most of the EV companies use Nickel Manganese Cobalt oxide (NMC). Most of the Li-ion batteries anodes are graphite-based. Positive and negative electrodes are reviewed in detail as well as future trends such as the effort to reduce the Cobalt content. The electrolyte is a liquid/gel flammable solvent usually containing a LiFeP6 salt. The electrolyte makes the battery and battery pack unsafe, which drives the research and development to replace the flammable liquid by a solid electrolyte

Toxicity Assessment of Buprofezin, Lufenuron, and Triflumuron to the Earthworm Aporrectodea caliginosa

Earthworms are particularly important soil macroinvertebrates and are often used in assessing the general impact of pesticide pollution in soil. The present study was conducted in order to investigate the toxicity of three insect growth regulators (IGRs) buprofezin, lufenuron, and triflumuron, at different application rates and exposure times toward mature earthworms Aporrectodea caliginosa. The effects of these pesticides on the growth rate in relation to the activities of acetylcholinesterase (AChE) and glutathione S-transferase (GST) as biochemical indicators were evaluated to elucidate the mechanisms of action. Toxicity studies indicated that lufenuron was the most harmful pesticide to mature earthworms, followed in descending order by buprofezin and triflumuron. A reduction in growth rate in all pesticide-treated worms was dose-dependent over the 28-day exposure period, which was accompanied by a decrease in AChE and GST activities. Relationships between growth rate, AChE, and GST provided strong evidence for the involvement of pesticidal contamination in the biochemical changes in earthworms, which can be used as a bioindicator of soil contamination by pesticides

Novel non-invasive algorithm to identify the origins of re-entry and ectopic foci in the atria from 64-lead ECGs: A computational study.

Atrial tachy-arrhytmias, such as atrial fibrillation (AF), are characterised by irregular electrical activity in the atria, generally associated with erratic excitation underlain by re-entrant scroll waves, fibrillatory conduction of multiple wavelets or rapid focal activity. Epidemiological studies have shown an increase in AF prevalence in the developed world associated with an ageing society, highlighting the need for effective treatment options. Catheter ablation therapy, commonly used in the treatment of AF, requires spatial information on atrial electrical excitation. The standard 12-lead electrocardiogram (ECG) provides a method for non-invasive identification of the presence of arrhythmia, due to irregularity in the ECG signal associated with atrial activation compared to sinus rhythm, but has limitations in providing specific spatial information. There is therefore a pressing need to develop novel methods to identify and locate the origin of arrhythmic excitation. Invasive methods provide direct information on atrial activity, but may induce clinical complications. Non-invasive methods avoid such complications, but their development presents a greater challenge due to the non-direct nature of monitoring. Algorithms based on the ECG signals in multiple leads (e.g. a 64-lead vest) may provide a viable approach. In this study, we used a biophysically detailed model of the human atria and torso to investigate the correlation between the morphology of the ECG signals from a 64-lead vest and the location of the origin of rapid atrial excitation arising from rapid focal activity and/or re-entrant scroll waves. A focus-location algorithm was then constructed from this correlation. The algorithm had success rates of 93% and 76% for correctly identifying the origin of focal and re-entrant excitation with a spatial resolution of 40 mm, respectively. The general approach allows its application to any multi-lead ECG system. This represents a significant extension to our previously developed algorithms to predict the AF origins in association with focal activities