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BACKGROUND: Low-invasive stereotactic body radiation therapy is a novel anti-arrhythmic strategy. The mechanisms underlying its effects against ventricular tachycardia/fibrillation (VT/VF) are gradually becoming clear, whereas those underlying atrial tachycardia/fibrillation (AT/AF) remain unknown. This study investigated the effects of carbon ion beam on gap junction expression and sympathetic innervation.MethodsâandâResults: Atrial and ventricular tachyarrhythmia models was established in 26 hypercholesterolemic (HC) 3-year-old New Zealand white rabbits; 12 rabbits were irradiated with a single 15-Gy carbon ion beam (targeted heavy ion irradiation [THIR]) and 14 were not (HC group). Eight 3-month-old rabbits (Young) were used as a reference group. In vivo induction frequencies in the Young, HC, and HC+THIR groups were 0%, 9.9%, and 1.2%, respectively, for AT/AF and 0%, 7.8%, and 1.2%, respectively, for VT/VF (P<0.01). The conduction velocity of the atria and ventricles on optical mapping was significantly reduced in the HC group; this was reversed in the HC+THIR group. Connexin-40 immunolabelling in the atria was 66.1-78.7% lower in the HC than Young group; this downregulation was less pronounced in the HC+THIR group (by 23.1-44.4%; P<0.01). Similar results were obtained for ventricular connexin-43. Sympathetic nerve densities in the atria and ventricles increased by 41.9-65.3% in the HC vs. Young group; this increase was reversed in the HC+THIR group. CONCLUSIONS: Heavy ion radiation reduced vulnerability to AT/AF and VT/VF in HC elderly rabbits and improved cardiac conductivity. The results suggest involvement of connexin-40/43 upregulation and suppression of sympathetic nerve sprouting.
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Fibrilação Atrial , Íons Pesados , Taquicardia Ventricular , Animais , Coelhos , Átrios do Coração , Fibrilação Ventricular , Junções Comunicantes , Conexinas , CarbonoRESUMO
BACKGROUND: Recently, an interoperative catheter electrode mapping system, termed ExTRa Mapping (EXT), was developed for precise diagnosis and effective treatment of non-paroxysmal atrial fibrillations (non-PAF). However, the mapping accuracy of EXT is still unclear.MethodsâandâResults:In this study, the reliability of the EXT in comparison with that of high-resolution optical membrane potential mapping was compared. Spiral wave re-entries (SWRs) were induced in the excised rabbit hearts (n=8, 42 episodes). Electrical signals were measured by electrodes on a transparent silicone plate, with the same arrangement as in the clinical catheter, and fluorescence signals were recorded simultaneously across the plate. Based on the phase maps derived by EXT, activation patterns (one-directed propagations: 26, rotational activities: 16) were identified correctly with 95% accuracy (40/42), and the correlation coefficient of the ratio of the non-passive period was 0.95. In the rotational episodes (15), the mean position error of the centers of gravity of the SWR trajectory (2,000 ms) was 2.0 mm. For the one-directional episodes (25), the correlation coefficient of the directions of one-way propagation was 0.99. CONCLUSIONS: The phase map sequence by EXT is consistent with that by the analyses of high-resolution optical mapping. EXT is reliable for analyzing the activation pattern in the region of interest.
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Potenciais de Ação , Arritmias Cardíacas/diagnóstico , Cateterismo Cardíaco , Técnicas Eletrofisiológicas Cardíacas , Função Ventricular Direita , Imagens com Corantes Sensíveis à Voltagem , Animais , Arritmias Cardíacas/etiologia , Arritmias Cardíacas/fisiopatologia , Estimulação Cardíaca Artificial , Criocirurgia , Modelos Animais de Doenças , Feminino , Frequência Cardíaca , Preparação de Coração Isolado , Masculino , Valor Preditivo dos Testes , Coelhos , Reprodutibilidade dos Testes , Fatores de TempoRESUMO
The action mechanism of stimulation toward spiral waves (SWs) owing to the complex excitation patterns that occur just after point stimulation has not yet been experimentally clarified. This study sought to test our hypothesis that the effect of capturing excitable gap of SWs by stimulation can also be explained as the interaction of original phase singularity (PS) and PSs induced by the stimulation on the wave tail (WT) of the original SW. Phase variance analysis was used to quantitatively analyze the postshock PS trajectories. In a two-dimensional subepicardial layer of Langendorff-perfused rabbit hearts, optical mapping was used to record the excitation pattern during stimulation. After a SW was induced by S1-S2 shock, single biphasic point stimulation S3 was applied. In 70 of the S1-S2-S3 stimulation episodes applied on 6 hearts, the original PS was clearly observed just before the S3 point stimulation in 37 episodes. Pairwise PSs were newly induced by the S3 in 20 episodes. The original PS collided with the newly induced PSs in 16 episodes; otherwise, they did not interact with the original PS. SW shift occurred most efficiently when the S3 shock was applied at the relative refractory period, and PS shifted in the direction of the WT. In conclusion, quantitative tracking of PS clarified that stimulation in desirable conditions induces pairwise PSs on WT and that the collision of PSs causes SW shift along the WT. The results of this study indicate the importance of the interaction of shock-induced excitation with the WT for effective stimulation. NEW & NOTEWORTHY The quantitative analysis of spiral wave dynamics during stimulation clarified the action mechanism of capturing the excitable gap, i.e., the induction of pairwise phase singularities on the wave tail and spiral wave shift along the wave tail as a result of these interactions. The importance of the wave tail for effective stimulation was revealed.
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Arritmias Cardíacas/fisiopatologia , Coração/fisiologia , Modelos Cardiovasculares , Animais , CoelhosRESUMO
PURPOSE: Considering vessel deformation, endovascular navigation requires intraoperative geometric information. Mechanical intravascular ultrasound (IVUS) with an electromagnetic (EM) sensor can be used to reconstruct blood vessels with thin diameter. However, the integration design should be evaluated based on the factors affecting the reconstruction error. METHODS: The interference between the mechanical IVUS and EM sensor was measured in different relative positions. Two designs of the integrated catheter were evaluated by measuring the reconstruction errors using a rigid vascular phantom. RESULTS: When the distance from the EM sensor to the field generator was 75 mm, the interference from mechanical IVUS to an EM sensor was negligible, with position and rotation errors less than 0.1 mm and 0.6°, respectively. The reconstructed vessel model for proximal IVUS transducer had a smooth surface but an inaccurate shape at large curvature of the vascular phantom. When the distance to the field generator was 175 mm, the error increased significantly. CONCLUSION: Placing the IVUS transducer on the proximal side of the EM sensor is superior in terms of interference reduction but inferior in terms of mechanical stability compared to a distal transducer. The distal side is preferred due to better mechanical stability during catheter manipulation at larger curvature. With this configuration, surface reconstruction errors less than 1.7 mm (with RMS 0.57 mm) were achieved when the distance to the field generator was less than 175 mm.
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Fenômenos Eletromagnéticos , Desenho de Equipamento , Imagens de Fantasmas , Ultrassonografia de Intervenção , Ultrassonografia de Intervenção/métodos , Ultrassonografia de Intervenção/instrumentação , Humanos , TransdutoresRESUMO
Background: Predicting the origin of premature ventricular contraction (PVC) from the preoperative electrocardiogram (ECG) is important for catheter ablation therapies. We propose an explainable method that localizes PVC origin based on the semantic segmentation result of a 12-lead ECG using a deep neural network, considering suitable diagnosis support for clinical application. Methods: The deep learning-based semantic segmentation model was trained using 265 12-lead ECG recordings from 84 patients with frequent PVCs. The model classified each ECG sampling time into four categories: background (BG), sinus rhythm (SR), PVC originating from the left ventricular outflow tract (PVC-L), and PVC originating from the right ventricular outflow tract (PVC-R). Based on the ECG segmentation results, a rule-based algorithm classified ECG recordings into three categories: PVC-L, PVC-R, as well as Neutral, which is a group for the recordings requiring the physician's careful assessment before separating them into PVC-L and PVC-R. The proposed method was evaluated with a public dataset which was used in previous research. Results: The evaluation of the proposed method achieved neutral rate, accuracy, sensitivity, specificity, F1-score, and area under the curve of 0.098, 0.932, 0.963, 0.882, 0.945, and 0.852 on a private dataset, and 0.284, 0.916, 0.912, 0.930, 0.943, and 0.848 on a public dataset, respectively. These quantitative results indicated that the proposed method outperformed almost all previous studies, although a significant number of recordings resulted in requiring the physician's assessment. Conclusions: The feasibility of explainable localization of premature ventricular contraction was demonstrated using deep learning-based semantic segmentation of 12-lead ECG.Clinical trial registration: M26-148-8.
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Echo imaging in ultrasound computed tomography (USCT) using the synthetic aperture technique is performed with the assumption that the speed of sound is constant in the system. However, tissue heterogeneity causes a mismatch between the predicted arrival time and the actual arrival time of the echo signal, which will result in phase aberration, leading to the quality degradation of the reconstructed B-mode image. The conventional correction methods that use the correlation of each different channel require the presence of strong point scatterers and involve the problem of local solutions due to excessive correction. In this study, we propose a novel approach to correcting the signal distortion due to sound speed heterogeneity using a deep neural network (DNN). The DNN was trained to convert the distorted radio frequency (RF) inputs for the heterogeneous medium to the distortion-free RF outputs for the homogeneous medium. The network with U-net architecture using ResNet-34 as a backbone was trained using the hetero-homo corresponding channel-domain RF data generated via numerical simulations. The trained network performed phase aberration correction in the channel-domain RF, with the B-mode images reconstructed with the corrected RF demonstrating a higher contrast and an improved resolution compared with uncorrected cases. It was also demonstrated that the DNN model is robust to both varied reflection intensities and varied sound speed heterogeneities. The successful results demonstrated that the proposed DNN-based method is effective for phase aberration correction in US imaging.
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Aprendizado Profundo , Algoritmos , Ultrassonografia/métodos , Tomografia Computadorizada por Raios X , Redes Neurais de Computação , Imagens de Fantasmas , Processamento de Imagem Assistida por Computador/métodosRESUMO
PURPOSE: Tissue deformation recovery is to reconstruct the change in shape and surface strain caused by tool-tissue interaction or respiration, which is essential for providing motion and shape information that benefits the improvement of the safety of minimally invasive surgery. The binocular vision-based approach is a practical candidate for deformation recovery as no extra devices are required. However, previous methods suffer from limitations such as the reliance on biomechanical priors and the vulnerability to the occlusion caused by surgical instruments. To address the issues, we propose a deformation recovery method incorporating mesh structures and scene flow. METHODS: The method can be divided into three modules. The first one is the implementation of the two-step scene flow generation module to extract the 3D motion from the binocular sequence. Second, we propose a strain-based filtering method to denoise the original scene flow. Third, a mesh optimization model is proposed that strengthens the robustness to occlusion by employing contextual connectivity. RESULTS: In a phantom and an in vivo experiment, the feasibility of the method in recovering surface deformation in the presence of tool-induced occlusion was demonstrated. Surface reconstruction accuracy was quantitatively evaluated by comparing the recovered mesh surface with the 3D scanned model in the phantom experiment. Results show that the overall error is 0.70 ± 0.55 mm. CONCLUSION: The method has been demonstrated to be capable of continuously recovering surface deformation using mesh representation with robustness to the occlusion caused by surgical forceps and promises to be suitable for the application in actual surgery.
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Algoritmos , Cirurgia Assistida por Computador , Humanos , Telas Cirúrgicas , Cirurgia Assistida por Computador/métodos , Procedimentos Cirúrgicos Minimamente Invasivos/métodos , Movimento (Física)RESUMO
Conventionally, ultrasound (US) diagnosis is performed using hand-held rigid probes. Such devices are difficult to be used for long-term monitoring because they need to be continuously pressed against the body to remove the air between the probe and body. Flexible probes, which can deform and effectively adhere to the body, are a promising technology for long-term monitoring applications. However, owing to the flexible element array geometry, the reconstructed image becomes blurred and distorted. In this study, we propose a flexible probe U.S. imaging method based on element array geometry estimation from radio frequency (RF) data using a deep neural network (DNN). The input and output of the DNN are the RF data and parameters that determine the element array geometry, respectively. The DNN was first trained from scratch with simulation data and then fine-tuned with in vivo data. The DNN performance was evaluated according to the element position mean absolute error (MAE) and the reconstructed image quality. The reconstructed image quality was evaluated with peak-signal-to-noise ratio (PSNR) and mean structural similarity (MSSIM). In the test conducted with simulation data, the average element position MAE was 0.86 mm, and the average reconstructed image PSNR and MSSIM were 20.6 and 0.791, respectively. In the test conducted with in vivo data, the average element position MAE was 1.11 mm, and the average reconstructed image PSNR and MSSIM were 19.4 and 0.798, respectively. The average estimation time was 0.045 s. These results demonstrate the feasibility of the proposed method for long-term real-time monitoring using flexible probes.
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Redes Neurais de Computação , Ultrassonografia , Simulação por Computador , Razão Sinal-Ruído , Ultrassonografia/instrumentaçãoRESUMO
Laparoscopic vision-based ultrasound probe tracking systems have gained considerable attention in ultrasound-guided laparoscopic surgeries as replacements for external tracking systems (e.g. optical tracking and electromagnetic tracking systems), which increase cost and setting time, require additional operation space, and introduce new limitations. Most existing laparoscopic ultrasound (LUS) probe tracking systems rely on fiducial markers, which cannot easily realise fast and robust vision-based tracking in laparoscopic surgery owing to their design limitations. Therefore, we propose a novel binary dot array marker to realise a robust and fast LUS probe tracking system. The binary dot array marker comprises two dots (green and blue), which form multiple unique identification dot subarrays in the binary dot array. The binary dot array marker can be tracked when one of the identification dot subarrays is detected and identified; this novel design makes the binary dot array marker-based probe tracking system robust against occlusions during surgery. The evaluation results indicate that the proposed binary dot marker performs better in terms of robustness, computational efficiency, and tracking accuracy compared to the state-of-the-art fiducial markers used for vision-based probe tracking.
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Laparoscopia , Cirurgia Assistida por Computador , Fenômenos Eletromagnéticos , Marcadores Fiduciais , Laparoscopia/métodos , Cirurgia Assistida por Computador/métodos , Ultrassonografia/métodosRESUMO
Accurate morphological information on aortic valve cusps is critical in treatment planning. Image segmentation is necessary to acquire this information, but manual segmentation is tedious and time consuming. In this paper, we propose a fully automatic aortic valve cusps segmentation method from CT images by combining two deep neural networks, spatial configuration-Net for detecting anatomical landmarks and U-Net for segmentation of aortic valve components. A total of 258 CT volumes of end systolic and end diastolic phases, which include cases with and without severe calcifications, were collected and manually annotated for each aortic valve component. The collected CT volumes were split 6:2:2 for the training, validation and test steps, and our method was evaluated by five-fold cross validation. The segmentation was successful for all CT volumes with 69.26 s as mean processing time. For the segmentation results of the aortic root, the right-coronary cusp, the left-coronary cusp and the non-coronary cusp, mean Dice Coefficient were 0.95, 0.70, 0.69, and 0.67, respectively. There were strong correlations between measurement values automatically calculated based on the annotations and those based on the segmentation results. The results suggest that our method can be used to automatically obtain measurement values for aortic valve morphology.
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BACKGROUND: Electrical storm (ES) is a life-threatening emergency in patients at high risk of ventricular tachycardia/ventricular fibrillation (VF), but the pathophysiology and molecular basis are poorly understood. OBJECTIVE: The purpose of this study was to explore the electrophysiological substrate for experimental ES. METHODS: A model was created by inducing chronic complete atrioventricular block in defibrillator-implanted rabbits, which recapitulates QT prolongation, torsades des pointes (TdP), and VF episodes. RESULTS: Optical mapping revealed island-like regions with action potential duration (APD) prolongation in the left ventricle, leading to increased spatial APD dispersion, in rabbits with ES (defined as ≥3 VF episodes/24 h). The maximum APD and its dispersion correlated with the total number of VF episodes in vivo. TdP was initiated by an ectopic beat that failed to enter the island and formed a reentrant wave and perpetuated by rotors whose centers swirled in the periphery of the island. Epinephrine exacerbated the island by prolonging APD and enhancing APD dispersion, which was less evident after late Na+ current blockade with 10 µM ranolazine. Nonsustained ventricular tachycardia in a non-ES rabbit heart with homogeneous APD prolongation resulted from multiple foci with an electrocardiographic morphology different from TdP driven by drifting rotors in ES rabbit hearts. The neuronal Na+-channel subunit NaV1.8 was upregulated in ES rabbit left ventricular tissues and expressed within the myocardium corresponding to the island location in optically mapped ES rabbit hearts. The NaV1.8 blocker A-803467 (10 mg/kg, intravenously) attenuated QT prolongation and suppressed epinephrine-evoked TdP. CONCLUSION: A tissue island with enhanced refractoriness contributes to the generation of drifting rotors that underlies ES in this model. NaV1.8-mediated late Na+ current merits further investigation as a contributor to the substrate for ES.
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Bloqueio Atrioventricular/fisiopatologia , Taquicardia Ventricular/fisiopatologia , Torsades de Pointes/fisiopatologia , Potenciais de Ação , Animais , Bloqueio Atrioventricular/tratamento farmacológico , Desfibriladores Implantáveis , Modelos Animais de Doenças , Síndrome do QT Longo/fisiopatologia , Coelhos , Ranolazina/farmacologiaRESUMO
BACKGROUND: Precise analysis of cardiac spiral wave (SW) dynamics is essential for effective arrhythmia treatment. Although the phase singularity (PS) point in the spatial phase map has been used to determine the cardiac SW center for decades, quantitative detection algorithms that assume PS as a point fail to trace complex and rapid PS dynamics. Through a detailed analysis of numerical simulations, we examined our hypothesis that a boundary of spatial phase discontinuity induced by a focal conduction block exists around the moving SW center in the phase map. METHOD: In a numerical simulation model of a 2D cardiac sheet, three different types of SWs (short wavelength; long wavelength; and low excitability) were induced by regulating ion channels. Discontinuities of all boundaries among adjacent cells at each instance were evaluated by calculating the phase bipolarity (PB). The total amount of phase transition (PTA) in each cell during the study period was evaluated. RESULTS: Pivoting, drifting, and shifting SWs were observed in the short-wavelength, low-excitability, and long-wavelength models, respectively. For both the drifting and shifting cases, long high-PB edges were observed on the SW trajectories. In all cases, the conduction block (CB) was observed at the same boundaries. These were also identical to the boundaries in the PTA maps. CONCLUSIONS: The analysis of the simulations revealed that the conduction block at the center of a moving SW induces discontinuous boundaries in spatial phase maps that represent a more appropriate model of the SW center than the PS point.
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Coração , Modelos Cardiovasculares , Potenciais de Ação , Algoritmos , Arritmias Cardíacas , Simulação por Computador , HumanosRESUMO
Cardiac arrhythmias are a primary contributor to sudden cardiac death, a major unmet medical need. Because right ventricular (RV) dysfunction increases the risk for sudden cardiac death, we examined responses to RV stress in mice. Among immune cells accumulated in the RV after pressure overload-induced by pulmonary artery banding, interfering with macrophages caused sudden death from severe arrhythmias. We show that cardiac macrophages crucially maintain cardiac impulse conduction by facilitating myocardial intercellular communication through gap junctions. Amphiregulin (AREG) produced by cardiac macrophages is a key mediator that controls connexin 43 phosphorylation and translocation in cardiomyocytes. Deletion of Areg from macrophages led to disorganization of gap junctions and, in turn, lethal arrhythmias during acute stresses, including RV pressure overload and ß-adrenergic receptor stimulation. These results suggest that AREG from cardiac resident macrophages is a critical regulator of cardiac impulse conduction and may be a useful therapeutic target for the prevention of sudden death.
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Anfirregulina/fisiologia , Arritmias Cardíacas/complicações , Morte Súbita Cardíaca/prevenção & controle , Macrófagos/fisiologia , Miocárdio/metabolismo , Anfirregulina/metabolismo , Animais , Animais Recém-Nascidos , Células Cultivadas , Morte Súbita Cardíaca/etiologia , Feminino , Junções Comunicantes/fisiologia , Células HeLa , Humanos , Macrófagos/metabolismo , Masculino , Camundongos Endogâmicos C57BL , Camundongos Knockout , Miocárdio/citologia , Miócitos Cardíacos/citologia , Miócitos Cardíacos/metabolismo , Miócitos Cardíacos/fisiologia , Receptores Adrenérgicos beta/metabolismoRESUMO
A flexible ultrasonic array transducer able to be attached to the body has the potential to achieve long-term continuous unconstrained ultrasound (US) imaging. However, the quality of reconstructed US images is affected by the accuracy of the estimated array shape because the array shape is primitive for time-delay calculation in delay-and-sum beamforming. In this study, we propose an algorithm for estimating the array shape only from the backscattered US signal without using any external device. The proposed algorithm is based on the assumption that beam-summed images reconstructed using an array shape estimated at higher accuracy would have smaller entropy. The array shape is estimated by searching for the shape with minimal entropy, which was used as the index of the beam-summed image quality. Simulation experiments and phantom experiments were used to evaluate the proposed algorithm. In the simulation experiments, three different array shapes with 2.0 MHz, 20 elements, and 0.8-mm pitch transducers were estimated. In the phantom experiments, the array shapes of commercially available linear, convex, and concave transducers were estimated. The results showed that the proposed algorithm can estimate the correct array shape with an average element position error of less than one-eighth of the wavelength of the transmitted signals. These results indicate that the proposed algorithm can achieve sufficiently accurate shape estimation and has the potential to enable clear US imaging with flexible array transducers.
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BACKGROUND: Resection using a stapler is a popular approach to distal pancreatectomy. However, the resulting leakage of pancreatic juice represents a serious problem. We have developed a force-fluorescence measurement as a first step towards the quantitative evaluation of pancreatic leakage due to tissue tearing under compression. METHODS: The system comprises a testing machine with an indenter, similar in size to a stapler, which controls compression speed and measures reaction force, and a fluorescence measurement system to measure pancreatic juice leakage. Pancreatic juice leakage is measured as the maximum value of the increasing rate of fluorescence intensity (max value). Ten excised swine pancreases were compressed at a speed of 500, 100, and 10 mm/min until their thicknesses became 2 mm. RESULTS: A strong positive correlation (0.804) was observed between the increase in max value before and after compression and the amount of reaction force drop due to tissue destruction. No pancreatic juice leakage was observed when compressed slowly (10 mm/min). CONCLUSIONS: We have successfully developed a novel force-fluorescence measurement system that can detect and quantify pancreatic juice leakage caused by tissue tearing. This system can determine the optimal compression conditions for preventing pancreatic juice leakage.
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Pancreatectomia , Suco Pancreático , Fluorescência , Humanos , Pâncreas/cirurgia , Pancreatectomia/efeitos adversos , Fístula Pancreática , Complicações Pós-Operatórias , SuínosRESUMO
To measure the activity of tissue at the microscopic level, laminar optical tomography (LOT), which is a microscopic form of diffuse optical tomography, has been developed. However, obtaining sufficient recording speed to determine rapidly changing dynamic activity remains major challenges. For a high frame rate of the reconstructed data, we here propose a new LOT method using compressed sensing theory, called compressive laminar optical tomography (CLOT), in which novel digital micromirror device-based illumination and data reduction in a single reconstruction are applied. In the simulation experiments, the reconstructed volumetric images of the action potentials that were acquired from 5 measured images with random pattern featured a wave border at least to a depth of 2.5 mm. Consequently, it was shown that CLOT has potential for over 200 fps required for the cardiac electrophysiological phenomena.
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OBJECTIVE: Spiral reentry is a recognized cause of tachycardia. Detection and tracking of the spiral core are essential for understanding the spiral wave dynamics. The core of the spiral corresponds to a phase singularity (PS), which can be identified in an optical mapping image by a kernel convolution method. However, because of a large number of false positives, this method cannot automatically and stably track the core of sustaining spiral reentry in optical mapping data. METHOD: We developed a new PS detection algorithm that quantifies the variance of phase values in a phase map and identifies the position of PS as its peak. RESULTS: In comparison with the kernel convolution method, our method improved the precision of detecting a single sustaining spiral wave core from 73.1% to 99.8%. The precision of the proposed method for virtual-electrode-polarization-induced multiple PSs detections was also higher than the convolutional method. CONCLUSION: The proposed method detects PS by finding the peaks in the phase variance distribution of cardiac optical mapping image. It improved the precision of the core detection of the spiral wave in cardiac optical mapping images in comparison with the conventional kernel convolution method. SIGNIFICANCE: The proposed method will reveal the spiral wave dynamics in optical mapping images better than existing approaches. The objective analysis method of a spiral wave is important for understanding the mechanisms and dynamics of serious heart arrhythmias.