This study presents the first histopathological validation of CMR and endocardial voltage mapping to define acute and chronic atrial ablation injury, including SI thresholds that best match histological lesion volumes. An understanding of these thresholds may allow a more informed assessment of the underlying atrial substrate immediately after ablation and before repeat catheter ablation for atrial arrhythmias.

BackgroundCoronary Wave Intensity Analysis (cWIA) is a technique capable of separating the effects of proximal arterial haemodynamics from cardiac mechanics. Studies have identified WIA-derived indices that are closely correlated with several disease processes and predictive of functional recovery following myocardial infarction. The cWIA clinical application has, however, been limited by technical challenges including a lack of standardization across different studies and the derived indices' sensitivity to the processing parameters. Specifically, a critical step in WIA is the noise removal for evaluation of derivatives of the acquired signals, typically performed by applying a Savitzky–Golay filter, to reduce the high frequency acquisition noise.MethodsThe impact of the filter parameter selection on cWIA output, and on the derived clinical metrics (integral areas and peaks of the major waves), is first analysed. The sensitivity analysis is performed either by using the filter as a differentiator to calculate the signals' time derivative or by applying the filter to smooth the ensemble-averaged waveforms.Furthermore, the power-spectrum of the ensemble-averaged waveforms contains little high-frequency components, which motivated us to propose an alternative approach to compute the time derivatives of the acquired waveforms using a central finite difference scheme.Results and ConclusionThe cWIA output and consequently the derived clinical metrics are significantly affected by the filter parameters, irrespective of its use as a smoothing filter or a differentiator. The proposed approach is parameter-free and, when applied to the 10 in-vivo human datasets and the 50 in-vivo animal datasets, enhances the cWIA robustness by significantly reducing the outcome variability (by 60%).

To be successful, a surgeon must master a variety of skills. To meet the high demand for surgical expertise, an extracurricular undergraduate project was launched. The extracurricular project consists of hands-on laparoscopic training and a mentorship programme. The project aims to find the best surgical talents among fourth-year medical students. The aim of the present paper is threefold: 1) to present the structure, i.e., the selection and training methods, of the Dream Team project; 2) to investigate the gender and grade distribution among the Dream Team students compared with their peers in medical school; and 3) to investigate the Dream Team students" evaluation of the project. Students (n=168) were satisfied with the 1-week course. This post-programme evaluation revealed a variation in satisfaction (n=68). The gender distribution on the Dream Team did not correlate with the gender distribution at the medical school. Dream Team students" grades showed variation, but generally matched the average grades obtained by medical school graduates. The 1-week extracurricular course increased students" interest in the surgical specialty. The role of the mentor was pivotal. Dream Team participants performed at an average level in medical school. Male students seemed to perform better in the laparoscopic tests.

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The number of registry-based studies on AF reported from Sweden and Denmark increased substantially from 2000 to 2014, had a great diversity, were well cited and have added information to the understanding of AF epidemiology.