Catheter ablation of atrial fibrillation in Korea: results from the Korean Heart Rhythm Society Ablation Registry for Atrial Fibrillation (KARA)

Background This study aims to investigate the current status of AF (atrial fibrillation) catheter ablation in Korea. Methods The patients who underwent AF catheter ablation from September 2017 to December 2019 were prospectively enrolled from 37 arrhythmia centers. Demographic data, procedural characteristics, the extent of catheter ablation, acute success of the ablation lesion set, rate and independent risk factor for recurrence of AF were analyzed. Results A total of 2402 AF patients [paroxysmal AF (PAF) 45.7%, persistent AF (PeAF) 43.1% and redo AF 11.2%] were included. Pulmonary vein isolation (PVI) was performed in 2378 patients (99%) and acute success rate was 97.9%. Additional non-PV ablation (NPVA) were performed in 1648 patients (68.6%). Post-procedural complication rate was 2.2%. One-year AF-free survival rate was 78.6% and the PeAF patients showed poorer survival rate than the ones with other types (PeAF 72.4%, PAF 84.2%, redo AF 80.0%). Additional NPVA did not influence the recurrence of AF in the PAF patients (PVI 17.0% vs. NPVA 14.6%, P value 0.302). However, it showed lower AF recurrence rate in the PeAF patients (PVI 34.9% vs. NPVA 24.4%, P value 0.001). Valvular heart disease, left atrial diameter, PeAF, PVI alone, need of NPVA for terminating AF, and failed ablation were independent predictors of AF recurrence. Conclusions Additional NPVA was associated better rhythm outcome in the patients with PeAF, not in the ones with PAF. The independent risk factors for AF recurrence in Korean population were similar to previous studies. Further research is needed to discover optimal AF ablation strategy.This nationwide registry study was supported by a grant from the Korean Heart Rhythm Society 2017

Logarithmic-Domain Array Interpolation for Improved Direction of Arrival Estimation in Automotive Radars

In automotive radar systems, a limited number of antenna elements are used to estimate the angle of the target. Therefore, array interpolation techniques can be used for direction of arrival (DOA) estimation to achieve high angular resolution. In general, to generate interpolated array elements from original array elements, the method of linear least squares (LLS) is used. When the LLS method is used, the amplitudes of the interpolated array elements may not be equivalent to those of the original array elements. In addition, through the transformation matrix obtained from the LLS method, the phases of the interpolated array elements are not precisely generated. Therefore, we propose an array transformation matrix that generates accurate phases for interpolated array elements to improve DOA estimation performance, while maintaining constant amplitudes of the array elements. Moreover, to enhance the effect of our interpolation method, a power calibration method for interpolated received signals is also proposed. Through the simulation, we confirm that the array interpolation accuracy and DOA estimation performance of the proposed method are improved compared to those of the conventional method. Moreover, the performance and effectiveness of our proposed method are also verified using data obtained from the commercial radar system. Because the proposed method exhibits better performance when applied to actual measurement data, it can be utilized in commercial automotive radar systems

Practical review on photoacoustic computed tomography using curved ultrasound array transducer

Photoacoustic computed tomography (PACT) has become a promising imaging modality from laboratory to clinical research. Of many components of PACT system, the ultrasound (US) array transducer is an essential device to simultaneously receive photoacoustic (PA) signals from several directions in a parallel manner. Many research groups and companies have developed various types of US array transducers while accounting the properties of the PA waves to achieve better image quality, deeper imaging depth, faster imaging speed, and a wider field of view. In this review, we present the implementation and application of the state-of-the-art PACT systems using several types of curved US arrays: arc-shaped, ring-shaped, and hemispherical array transducers. Furthermore, we discuss the current limitations of PACT and also potential future directions for enhancing them.11Nsciescopuskc

Multi‐view convolutional neural network‐based target classification in high‐resolution automotive radar sensor

Abstract In this study, a target classification method based on point cloud data in a high‐resolution radar sensor is proposed. By using multiple antenna elements arranged in horizontal and vertical directions, pedestrians, cyclists and vehicles can be expressed as point cloud data in the three‐dimensional (3D) space. To perform target classification using the spatial characteristics (i.e. length, height and width) of the target, the 3D point cloud data is orthogonally projected onto the xy, yz and zx planes, respectively, and three types of images are generated. Then, a multi‐view convolutional neural network (CNN)‐based target classifier using those three images as inputs is designed. To this end, a method for synthesising the detection results of three directions in series or in parallel is proposed. The proposed classifier can learn the spatial characteristics of the target by using the detection results of multiple viewpoints. Compared to the CNN‐based classifier that uses only the detection result of a single plane as input, the proposed method shows 4.5%p higher classification accuracy in terms of the target with the lowest classification accuracy. In addition, the proposed multi‐view CNN structure shows improved classification performance and shorter training time compared to the well‐known deep learning methods for image classification

Advanced direction of arrival estimation using step‐learnt iterative soft‐thresholding for frequency‐modulated continuous wave multiple‐input multiple‐output radar

Abstract The number of antennas in automotive frequency‐modulated continuous wave (FMCW) multiple‐input multiple‐output (MIMO) radar systems is increasing. Existing greedy or subspace‐based methods cannot quickly and accurately estimate the direction of arrival (DoA) of the target. Therefore, we propose a fast and accurate DoA estimation algorithm for the automotive FMCW MIMO radar. To achieve both fastness and accuracy, we exploit the group sparsity in DoA estimation by defining the problem as a multiple measurement vector (MMV) compressive sensing and extend the step‐learnt iterative soft‐thresholding algorithm (SLISTA) to the MMV problem. To apply the extended SLISTA, we train the network in an unsupervised manner and normalise the input. We conduct experiments to evaluate the performance of the proposed method. Compared to the algorithms such as ISTA/FISTA/MFOCUSS that solve the same optimisation problem, the extended SLISTA exhibits the most accurate DoA estimation results for actual targets, with less execution time than a subspace‐based method. Moreover, the results show that the extended SLISTA prevents false detections, whereas greedy and subspace‐based methods do not

Effective Dose of Ramosetron for Prophylaxis of Postoperative Nausea and Vomiting in High-Risk Patients

Background. Postoperative nausea and vomiting (PONV) are common adverse events with an incidence of up to 80% in high-risk patients. Ramosetron, a selective 5-HT3 receptor antagonist, is widely used to prevent PONV. The purpose of this study was to evaluate the effective dose of ramosetron for the prevention of PONV in high-risk patients. Methods. Fifty-one patients were randomly allocated to 3 groups and were administered ramosetron 0.3 mg (group A), 0.45 mg (group B), or 0.6 mg (group C), at the end of their surgery. The episodes of PONV were assessed 1, 6, 24, and 48 hours after the injection and all the adverse events were observed. Results. The complete response rate in the postoperative period 6–24 hours after the anesthesia was higher in group C than in group A: 93% versus 44%. Group C’s experience score of Rhodes index was lower than group A’s: 0.81 ± 2.56 versus 3.94 ± 5.25. No adverse drug reaction could be observed in all groups. Conclusions. The effective dose of ramosetron to be injected for the near-complete prophylaxis of PONV 6 to 24 hours after surgery in high-risk patients is a 0.6 mg bolus injection at the end of the surgery