Transcranial Magnetic Resonance guided Focused Ultrasound (TcMRgFUS) has been proven to be an effective treatment for some neurological disorders such as essential and Parkinson's tremor. However, magnetic resonance guidance at 3 Tesla (3T) frequencies and using the large hemispherical transducers required for TcMRgFUS results in artifactual low-signal bands that pass through key regions of the brain. The purpose of this work was to investigate the use of a circular conductive Radio Frequency (RF) screen, that is bent to have a 12 cm radius in one direction and positioned near the top or back of the head, to reduce or remove these artifactual low-signal bands in TcMRgFUS. The impact of using an RF screen to remove these low signal bands was studied in both imaging experiments and electromagnetic simulations. click here Hydrophone measurements of the acoustic transparency of the bronze 2 mm diameter square mesh screen used in the imaging studies were compared with temperature measurements with and without the screen in heating studies in the TcMRgFUS system. The imaging and simulation studies both show that for the different screen configurations studied in this work, RF screen removes the low-signal bands and increases both homogeneity and signal-to-noise ratio (SNR) throughout the region of the brain. Hydrophone and heating studies indicate that even a 2 mm wire mesh provides minimal attenuation to the ultrasound beam. Simulation results also suggest that a 1 cm mesh will provide adequate artifact suppression with even less ultrasound attenuation. An RF screen that disrupts the natural waveguide nature of the transducer in the 3T MR environment can change the electromagnetic field profile to reduce unwanted artifacts and provide an imaging region which has more homogeneity and higher SNR throughout the brain.We addressed comprehensively the performance of Shortest-Path HARP Refinement (SP-HR), SinMod, and DENSEanalysis using 2D slices of synthetic CSPAMM and DENSE images with realistic contrasts obtained from 3D phantoms. The three motion estimation techniques were interrogated under ideal and no-ideal conditions (with MR induced artifacts, noise, and through-plane motion), considering several resolutions and noise levels. Under noisy conditions, and for isotropic pixel sizes of 1.5 mm and 3.0 mm in CSPAMM and DENSE images respectively, the nRMSE obtained for the circumferential and radial strain components were 10.7 ± 10.8% and 25.5 ± 14.8% using SP-HR, 11.9 ± 2.5% and 29.3 ± 6.5% using SinMod, and 6.4 ± 2.0% and 18.2 ± 4.6% using DENSEanalysis. Overall, the results showed that SP-HR tends to fail for large tissue motions, whereas SinMod and DENSEanalysis gave accurate displacement and strain field estimations, being the last which performed the best. To date, little evidence is available to determine whether atopic dermatitis (AD) can be caused by exposure to air pollutants, including gases and particulate matter. We aimed to evaluate the relationship between air pollutants and incidence of AD using the National Health Insurance Service-National Sample Cohort database. We included 209,168 subjects from the general population previously not diagnosed with AD between 2008 and 2013. Long-term average concentration of air pollutants before diagnosis was calculated for each subject. For 1,030,324 person-years, incident cases of AD were observed in 3203 subjects. There was a significant positive association between incidence of AD and long-term average concentration of particulate matter smaller than 2.5μm in diameter (hazard ratio [HR], 1.420; 95% CI, 1.392-1.448; for 1μg/m ), particulate matter smaller than 10μm in diameter (HR, 1.333, 95% CI, 1.325-1.341; for 1μg/m ), sulfur dioxide (HR, 1.626; 95% CI, 1.559-1.695; for 1parts per billion), nitrogen dioxide (HR, 1.200; 95% CI, 1.187-1.212; for 1parts per billion), and carbon monoxide (HR, 1.005; 95% CI, 1.004-1.005; for 1parts per billion) after adjusting for age, sex, income, comorbid diseases, and meteorologic variables. The National Health Insurance Service database lacks detailed information on individual subjects. This study demonstrated that long-term exposure to air pollutants, including gases and particulate matter, is an independent risk factor for developing AD.This study demonstrated that long-term exposure to air pollutants, including gases and particulate matter, is an independent risk factor for developing AD.The presence of left ventricular systolic dysfunction (LVSD) alters clinical management and prognosis in most acute and chronic cardiovascular conditions. While transthoracic echocardiography (TTE) remains the most common diagnostic tool to screen for LVSD, it is operator-dependent, time-consuming, effort-intensive, and relatively expensive. Recent work has demonstrated the ability of an artificial intelligence-augment ECG (AI-ECG) model to accurately predict LVSD in critical intensive care unit (CICU) patients. We demonstrate that the AI-ECG algorithm can maintain its performance in these patients with and without AF despite their clinical differences. An AI-ECG algorithm can serve as a non-invasive, inexpensive, and rapid screening tool for early detection of LVSD in resource-limited settings, and potentially expedite clinical decision making and guideline-directed therapies in the acute care setting. We aim to evaluate the value of Cardiac magnetic resonance (CMR) feature tracking (CMR-FT) in addition to Task Force Criteria(TFC) in patients with (arrhythmogenic cardiomyopathy) AC biopsy-proved. Thirty-five patients with AC histologically proven who performed CMR with late gadolinium enhancement (LGE) acquisition were enrolled. The study population was divided in Group1 (negative CMR TFC and LV ejection fraction≥55%) and Group2 (positive CMR TFC and/or LVEF<55%) and compared to an age and gender-matched control group. CMR datasets of all patients were analyzed to calculate LV indexed end-diastolic (LVEDi) and end-systolic (LVESi) volumes and RV indexed end-diastolic (RVEDi) and end-systolic (RVESi) volumes, both LV ejection fraction (LVEF) and RV ejection fraction (RVEF). Moreover, LV and RV global longitudinal (GLS), circumferential (GCS) and radial (GRS) strain were measured. The AC patients showed both higher LVEDi (p0.002) and RVEDi (p0.017) and lower LVEF (p 0.016) as compared to control patients.