Computing in cardiology最新文献

{"title":"Effect of Myocardial Fiber Direction on Epicardial Activation Patterns.","authors":"Lindsay C Rupp,&nbsp;Wilson W Good,&nbsp;Jake A Bergquist,&nbsp;Brian Zenger,&nbsp;Karli Gillette,&nbsp;Gernot Plank,&nbsp;Rob S MacLeod","doi":"10.22489/cinc.2020.399","DOIUrl":"https://doi.org/10.22489/cinc.2020.399","url":null,"abstract":"<p><p>Fiber structure governs the spread of excitation in the heart, however, little is known about the effects of physiological variability in the fiber orientation on epicardial activation. To investigate these effects, we used computer simulation to compare ventricular activation sequences initiated from stimulus sites at regularly spaced depths within the myocardium under varying rule-based fiber ranges. We compared the effects using four characteristics of epicardial breakthrough (BKT): location, area, shape (calculated via the axis ratio of a fitted ellipse), and orientation. Our results showed changes in the BKT characteristics as pacing depth increased, e.g., the area increased, the shape became more circular, and the orientation rotated counterclockwise, regardless of the fiber orientation. Furthermore, the maximal differences in epicardial activation from a single pacing site for location, area, axis ratio, and orientation were 1.2 mm, 74 mm ^<i>2</i> , 0.16, and 26°, respectively. Our results suggest that variability in fiber orientation has a negligible effect on the location, area, and shape of the BKT, while fluctuations were observed in the BKT orientation in response to the fiber fields, especially for epicardial stimulation sites. Our results suggest the fiber field orientation plays only a minor role in activation simulations of ectopic beats.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084599/pdf/nihms-1694885.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38950940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Convolutional Neural Network-based Deformable Image Registration Method for Cardiac Motion Estimation from Cine Cardiac MR Images.","authors":"Roshan Reddy Upendra, Brian Jamison Wentz, Suzanne M Shontz, Cristian A Linte","doi":"10.22489/CinC.2020.204","DOIUrl":"10.22489/CinC.2020.204","url":null,"abstract":"<p><p>In this work, we describe an unsupervised deep learning framework featuring a Laplacian-based operator as smoothing loss for deformable registration of 3D cine cardiac magnetic resonance (CMR) images. Before registration, the input 3D images are corrected for slice misalignment by segmenting the left ventricle (LV) blood-pool, LV myocardium and right ventricle (RV) blood-pool using a U-Net model and aligning the 2D slices along the center of the LV blood-pool. We conducted experiments using the Automated Cardiac Diagnosis Challenge (ACDC) dataset. We used the registration deformation field to warp the manually segmented LV blood-pool, LV myocardium and RV blood-pool labels from end-diastole (ED) frame to the other frames in the cardiac cycle. We achieved a mean Dice score of 94.84%, 85.22% and 84.36%, and Hausdorff distance (HD) of 2.74 mm, 5.88 mm and 9.04 mm, for the LV blood-pool, LV myocardium and RV blood-pool, respectively. We also introduce a pipeline to estimate patient tractography using the proposed CNN-based cardiac motion estimation.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8168986/pdf/nihms-1705226.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39054095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Localization of Cardiac Geometry Using ECGI.","authors":"Jake A Bergquist, Jaume Coll-Font, Brian Zenger, Lindsay C Rupp, Wilson W Good, Dana H Brooks, Rob S MacLeod","doi":"10.22489/cinc.2020.273","DOIUrl":"10.22489/cinc.2020.273","url":null,"abstract":"<p><strong>Introduction: </strong>Electrocardiographic imaging (ECGI) requires a model of the torso, and inaccuracy in the position of the heart is a known source of error. We previously presented a method to localize the heart when body and heart surface potentials are known. The goal of this study is to extend this approach to only use body surface potentials.</p><p><strong>Methods: </strong>We used an iterative coordinate descent optimization to estimate the positions of the heart for several consecutive heartbeats relying on the assumption that the epicardial potential sequence is the same in each beat. The method was tested with data synthesized using measurements from a isolated-heart, torso-tank preparation. Improvement was evaluated in terms of both heart localization and ECGI accuracy.</p><p><strong>Results: </strong>The geometric correction resulted in cardiac geometries closely matching ground truth geometry. ECGI accuracy increased dramatically by all metrics using the corrected geometry.</p><p><strong>Discussion: </strong>Future studies will employ more realistic animal models and then human subjects. Success could impact clinical ECGI by reducing errors from respiratory movement and perhaps decrease imaging requirements, reducing both cost and logistical difficulty of ECGI, widening clinical applicability.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8082332/pdf/nihms-1695020.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38941200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-Capacity Cardiac Signal Acquisition System for Flexible, Simultaneous, Multidomain Acquisition.","authors":"Brian Zenger,&nbsp;Jake A Bergquist,&nbsp;Wilson W Good,&nbsp;Bruce Steadman,&nbsp;Rob S MacLeod","doi":"10.22489/cinc.2020.188","DOIUrl":"https://doi.org/10.22489/cinc.2020.188","url":null,"abstract":"<p><p>Capturing cardiac electrical propagation or electrocardiographic images demands simultaneous, multidomain recordings of electrocardiographic signals with adequate spatial and temporal resolution. Available systems can be cost-prohibitive or lack the necessary flexibility to capture signals from the heart and torso. We have designed and constructed a system that leverages affordable commercial products (Intantech, CA, USA) to create a complete, cardiac signal acquisition system that includes a flexible front end, analog signal conditioning, and defibrillation protection. The design specifications for this project were to (1) record up to 1024 channels simultaneously at a minimum of 1 kHz, (2) capture signals within the range of ± 30 mV with a resolution of 1 μV, and (3) provide a flexible interface for custom electrode inputs.We integrated the Intantech A/D conversion circuits to create a novel system, which meets all the required specifications. The system connects to a standard laptop computer under control of open-source software (Intantech). To test the system, we recorded electrograms from within the myocardium, on the heart surface, and on the body surface simultaneously from a porcine experimental preparation. Noise levels were comparable to both our existing, custom acquisition system and a commercial competitor. The cost per channel was $32 USD, totaling $33,800 USD for a complete system.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106231/pdf/nihms-1694881.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38966200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable XGBoost Based Classification of 12-lead ECGs Applying Information Theory Measures From Neuroscience.","authors":"Hardik Rajpal,&nbsp;Madalina Sas,&nbsp;Chris Lockwood,&nbsp;Rebecca Joakim,&nbsp;Nicholas S Peters,&nbsp;Max Falkenberg","doi":"10.22489/CinC.2020.185","DOIUrl":"https://doi.org/10.22489/CinC.2020.185","url":null,"abstract":"<p><p>Automated ECG classification is a standard feature in many commercial 12-Lead ECG machines. As part of the Physionet/CinC Challenge 2020, our team, \"Mad-hardmax\", developed an XGBoost based classification method for the analysis of 12-Lead ECGs acquired from four different countries. Our aim is to develop an interpretable classifier that outputs diagnoses which can be traced to specific ECG features, while also testing the potential of information theoretic features for ECG diagnosis. These measures capture high-level interdependencies across ECG leads which are effective for discriminating conditions with multiple complex morphologies. On unseen test data, our algorithm achieved a challenge score of 0.155 relative to a winning score of 0.533, putting our submission in 24th position from 41 successful entries.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610399/pdf/EMS118968.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25526814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying Potential Re-Entrant Circuit Locations From Atrial Fibre Maps.","authors":"Max Falkenberg,&nbsp;David Hickey,&nbsp;Louie Terrill,&nbsp;Alberto Ciacci,&nbsp;Nicholas S Peters,&nbsp;Kim Christensen","doi":"10.22489/CinC.2019.102","DOIUrl":"https://doi.org/10.22489/CinC.2019.102","url":null,"abstract":"<p><p>Re-entrant circuits have been identified as potential drivers of atrial fibrillation (AF). In this paper, we develop a novel computational framework for finding the locations of re-entrant circuits from high resolution fibre orientation data. The technique follows a statistical approach whereby we generate continuous fibre tracts across the tissue and couple adjacent fibres stochastically if they are within a given distance of each other. By varying the connection distance, we identify which regions are most susceptible to forming re-entrant circuits if muscle fibres are uncoupled, through the action of fibrosis or otherwise. Our results highlight the sleeves of the pulmonary veins, the posterior left atrium and the left atrial appendage as the regions most susceptible to re-entrant circuit formation. This is consistent with known risk locations in clinical AF. If the model can be personalised for individual patients undergoing ablation, future versions may be able to suggest suitable ablation targets.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":"2019 ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2019-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7279949/pdf/EMS86515.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38023412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental Validation of Image-Based Modeling of Torso Surface Potentials During Acute Myocardial Ischemia.","authors":"Brian Zenger,&nbsp;Jake A Bergquist,&nbsp;Wilson W Good,&nbsp;Brett M Burton,&nbsp;Jess D Tate,&nbsp;Rob S MacLeod","doi":"10.22489/cinc.2019.417","DOIUrl":"10.22489/cinc.2019.417","url":null,"abstract":"<p><strong>Introduction: </strong>Myocardial ischemia is an early clinical indicator of several underlying cardiac pathologies, including coronary artery disease, Takatsobu cardiomyopathy, and coronary artery dissection. Significant progress has been made in computing body-surface potentials from cardiac sources by solving the forward problem of electrocardiography. However, the lack of in vivo studies to validate such computations from ischemic sources has limited the translational potential of such models.</p><p><strong>Methods: </strong>To resolve this need, we have developed a large-animal experimental model that includes simultaneous recordings within the myocardium, on the epicardial surface, and on the torso surface during episodes of acute, controlled ischemia. Following each experiment, magnetic resonance images were obtained of the anatomy and electrode locations to create a subject-specific model for each animal. From the electrical recordings of the heart, we identified ischemic sources and used the finite element method to solve a static bidomain equation on a geometric model to compute torso surface potentials.</p><p><strong>Results: </strong>Across 33 individual heartbeats, the forward computed torso potentials showed only moderate agreement in both pattern and amplitude with the measured values on the torso surface. Qualitative analysis showed a more encouraging pattern of elevations and depressions shared by computed and measured torso potentials. Pearson's correlation coefficient, root mean squared error, and absolute error varied significantly by heartbeat (0.1642 ± 0.223, 0.10 ± 0.03mV, and 0.08 ± 0.03mV, respectively).</p><p><strong>Discussion: </strong>We speculate several sources of error in our computation including noise within torso surface recordings, registration of electrode and anatomical locations, assuming a homogeneous torso conductivities, and imposing a uniform \"transition zone\" between ischemic and non-ischemic tissues. Further studies will focus on characterizing these sources of error and understanding how they effect the study results.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7079820/pdf/nihms-1561973.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37752811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Isosbestic Point in Optical Mapping; Theoretical and Experimental Determination With Di-4-ANBDQPQ Transmembrane Voltage Sensitive Dye.","authors":"Ilija Uzelac,&nbsp;Christopher J Crowley,&nbsp;Flavio H Fenton","doi":"10.22489/CinC.2019.414","DOIUrl":"https://doi.org/10.22489/CinC.2019.414","url":null,"abstract":"<p><p>Optical mapping methods utilize fluorescence dyes to measure dynamic response of cardiac tissue such as changes in transmembrane potential (V_m). For the commonly used V_m sensitive dyes, a dye absorption and emission spectra shift as V_m changes. Signals relevant to V_m are calculated as a relative fluorescence change with respect to the fluorescence baseline. The amplitude of the change depends on the long-pass (LP) filter cut-on wavelength, placed on the sensor side, and the excitation wavelength. An excitation wavelength near the absorption peak, termed the isosbestic point, results in minimal absorption coefficient change as absorption spectra shifts. Consequentially the fluorescence intensity virtually does not change, when fluorescence across the entire emission spectra is measured, irrelevant of V_m changes. In this study we experimentally determined the isosbestic point for a near infrared dye Di-4-ANBDQPQ. We then present a theoretical study examining the dye linear or non-linear response as the fractional fluorescence change of V_m change, due to emission spectra shift and amplitude change, over a range of excitation wavelengths and LP filters. Linear \"optical\" response is important to quantify certain aspects of cardiac dynamics such as the action potential (AP) shape and duration, especially when studying drug effects and dynamical substrates for arrhythmia development.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552219/pdf/nihms-1747864.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39684574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interatrial Septum and Appendage Ostium in Atrial Fibrillation Patients: A Population Study.","authors":"Anupama Goparaju,&nbsp;Alan Morris,&nbsp;Ibolya Csecs,&nbsp;Riddhish Bhalodia,&nbsp;Tom Ditter,&nbsp;Kristine Fuimaono,&nbsp;Evgueni Kholmovski,&nbsp;Nassir Marrouche,&nbsp;Joshua Cates,&nbsp;Shireen Elhabian","doi":"10.22489/cinc.2019.439","DOIUrl":"https://doi.org/10.22489/cinc.2019.439","url":null,"abstract":"<p><p>Left atrial appendage (LAA) closure is performed in atrial fibrillation (AF) patients to help prevent stroke. LAA closure using an occlusion implant is performed under imaging guidance. However, occlusion can be a complicated process due to the highly variable and heterogeneous LAA shapes across patients. Patient-specific implant selection and insertion processes are keys to the success of the procedure, yet subjective in nature. A population study of the angle of entry at the interatrial septum relative to the appendage can assist in both catheter design and patient-specific implant choice. In our population study, we analyzed the inherent clusters of the angles that were obtained between the septum normal and the LAA ostium plane. The number of inherent angle clusters matched the LAA four morphological classifications reported in the literature. Further, our exploratory analysis revealed that the normal from the ostium plane does not intersect the septum in all the samples under study. The insights gained from this study can help assist in making objective decisions during LAA closure.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338039/pdf/nihms-1602928.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38124829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Baseline Wandering Removal in Optical Mapping Measurements With PID Control in Phase Space.","authors":"Shaun Eisner,&nbsp;Flavio H Fenton,&nbsp;Ilija Uzelac","doi":"10.22489/cinc.2019.442","DOIUrl":"https://doi.org/10.22489/cinc.2019.442","url":null,"abstract":"<p><p>Optical imaging methods on ex-vivo hearts have had large impact in furthering our understanding of cardiac electrophysiology. One common problem in this method is a baseline wandering of the fluorescence signals over time, caused by dye photo-bleaching, small variation of the excitation light source, or other similar artifacts. Due to its relative magnitude, the removal of baseline wandering can be a nontrivial task and has major implications for analyzing important physiological dynamics such as traveling waves and alternans. Here we present a computational technique for the removal of such baseline wandering based on Proportional-Integral-Derivative (PID) closed loop feedback. The PID method applied a continuous control stimulus to the input V_m based on an error value which is defined by Euclidean distance from a pre-computed setpoint in phase space. We quantify and validate the PID control method by adding a linear combination of arbitrary sinusoidal drift, of frequency less than the signal pacing frequency, to the system signal V_m. The PID control loop effectively removed the baseline wandering with minimal degradation to the input V_m, and thus provides a viable tool for baseline wandering removal when implemented in an appropriate phase space. The computational simplicity of the method also lends itself to implementation in embedded systems, such as Arduinos and Raspberry-Pis.</p>","PeriodicalId":72683,"journal":{"name":"Computing in cardiology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580294/pdf/nihms-1747852.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39721274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}