Abstract 13184: A New Intraprocedural Automated System for Localizing Idiopathic Ventricular Arrhythmia Origin Sites

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Shijie Zhou ◽  
Amir AbdelWahab ◽  
John L Sapp ◽  
Eric Sung ◽  
Konstantinos Aronis ◽  
...  
Keyword(s):  
Ventricular Arrhythmia ◽  
Automated System ◽  
Patient Specific ◽  
Localization Accuracy ◽  
Accurate Localization ◽  
Ventricular Activation ◽  
Specific Geometry ◽  
Pace Mapping ◽  
Activation Mapping ◽  
Better Than

Introduction: Few intraprocedural localization systems have been developed to predict idiopathic ventricular arrhythmia (IVA) source sites. However, an accurate and bi-ventricular patient-specific automated site of origin localization system remains elusive. To address this issue, we have developed a new automatic arrhythmia origin localization (AAOL) system that determines the sites of earliest activation in both ventricles and provides superior accuracy. Hypothesis: We hypothesized that the AAOL system can use electroanatomic mapping (EAM) geometry and accurately localize IVA source sites on patient-specific geometry of LV, RV and neighboring vessels using 3-lead ECGs. Methods: Twenty patients undergoing IVA catheter ablation had a 12-lead ECG recorded during clinical arrhythmia and during pacing at various locations identified on EAM geometries. The AAOL system combined 3-lead (III, V2, V6) 120-ms QRS integrals and patient-specific EAM geometry with intracardiac pacing to predict the site of earliest ventricular activation. The predicted site was projected onto the EAM geometry using the EAM triangular-mesh site nearest to the tip of the predicted site. Results: Twenty-three IVA source sites were clinically identified by activation mapping and/or pace mapping (8 RV, 15 LV, including 8 from the posteromedial papillary muscle; 2 from the aortic root; and 1 from the distal coronary sinus). The new system achieved a mean localization accuracy of 3.6 mm for the 23 mapped IVAs (Figure 1D), better than that achieved by previous systems. Conclusions: The new AAOL system offers highly accurate localization of IVA source sites in both ventricles and neighboring vessels, which could facilitate ablation procedures for patients with IVAs.

scholarly journals Assessment of an ECG‐Based System for Localizing Ventricular Arrhythmias in Patients With Structural Heart Disease

2021 ◽  
Author(s):  
Shijie Zhou ◽  
Amir AbdelWahab ◽  
John L. Sapp ◽  
Eric Sung ◽  
Konstantinos N. Aronis ◽  
...  
Keyword(s):  
Heart Disease ◽  
Case Series ◽  
Premature Ventricular Contraction ◽  
Structural Heart Disease ◽  
Patient Specific ◽  
Localization Error ◽  
Localization Accuracy ◽  
Accurate Localization ◽  
Prospective Case Series ◽  
Pace Mapping

Background We have previously developed an intraprocedural automatic arrhythmia‐origin localization (AAOL) system to identify idiopathic ventricular arrhythmia origins in real time using a 3‐lead ECG. The objective was to assess the localization accuracy of ventricular tachycardia (VT) exit and premature ventricular contraction (PVC) origin sites in patients with structural heart disease using the AAOL system. Methods and Results In retrospective and prospective case series studies, a total of 42 patients who underwent VT/PVC ablation in the setting of structural heart disease were recruited at 2 different centers. The AAOL system combines 120‐ms QRS integrals of 3 leads (III, V2, V6) with pace mapping to predict VT exit/PVC origin site and projects that site onto the patient‐specific electroanatomic mapping surface. VT exit/PVC origin sites were clinically identified by activation mapping and/or pace mapping. The localization error of the VT exit/PVC origin site was assessed by the distance between the clinically identified site and the estimated site. In the retrospective study of 19 patients with structural heart disease, the AAOL system achieved a mean localization accuracy of 6.5±2.6 mm for 25 induced VTs. In the prospective study with 23 patients, mean localization accuracy was 5.9±2.6 mm for 26 VT exit and PVC origin sites. There was no difference in mean localization error in epicardial sites compared with endocardial sites using the AAOL system (6.0 versus 5.8 mm, P =0.895). Conclusions The AAOL system achieved accurate localization of VT exit/PVC origin sites in patients with structural heart disease; its performance is superior to current systems, and thus, it promises to have potential clinical utility.

scholarly journals Prospective Assessment of an Automated Intraprocedural 12-Lead ECG-Based System for Localization of Early Left Ventricular Activation

2020 ◽  
Vol 13 (7) ◽  
Author(s):  
Shijie Zhou ◽  
Amir AbdelWahab ◽  
B. Milan Horáček ◽  
Paul J. MacInnis ◽  
James W. Warren ◽  
...  
Keyword(s):  
Population Based ◽  
Left Ventricular ◽  
Specific Site ◽  
Patient Specific ◽  
Localization Error ◽  
Localization Accuracy ◽  
Localization System ◽  
Contact Mapping ◽  
Ventricular Activation ◽  
Site Localization

Background: To facilitate ablation of ventricular tachycardia (VT), an automated localization system to identify the site of origin of left ventricular activation in real time using the 12-lead ECG was developed. The objective of this study was to prospectively assess its accuracy. Methods: The automated site of origin localization system consists of 3 steps: (1) localization of ventricular segment based on population templates, (2) population-based localization within a segment, and (3) patient-specific site localization. Localization error was assessed by the distance between the known reference site and the estimated site. Results: In 19 patients undergoing 21 catheter ablation procedures of scar-related VT, site of origin localization accuracy was estimated using 552 left ventricular endocardial pacing sites pooled together and 25 VT-exit sites identified by contact mapping. For the 25 VT-exit sites, localization error of the population-based localization steps was within 10 mm. Patient-specific site localization achieved accuracy of within 3.5 mm after including up to 11 pacing (training) sites. Using 3 remotes (67.8±17.0 mm from the reference VT-exit site), and then 5 close pacing sites, resulted in localization error of 7.2±4.1 mm for the 25 identified VT-exit sites. In 2 emulated clinical procedure with 2 induced VTs, the site of origin localization system achieved accuracy within 4 mm. Conclusions: In this prospective validation study, the automated localization system achieved estimated accuracy within 10 mm and could thus provide clinical utility.

Localization of ventricular activation origin using patient-specific geometry: Preliminary results

2018 ◽  
Vol 29 (7) ◽  
pp. 979-986 ◽  
Author(s):  
Shijie Zhou ◽  
John L. Sapp ◽  
Amir AbdelWahab ◽  
Petr Šťovíček ◽  
B. Milan Horáček
Keyword(s):  
Patient Specific ◽  
Preliminary Results ◽  
Ventricular Activation ◽  
Specific Geometry

Accuracy analysis of BLE beacon-based localization in smart buildings

2021 ◽  
pp. 1-20
Author(s):  
Rosen Ivanov
Keyword(s):  
Use Case ◽  
Accuracy Analysis ◽  
Localization Algorithm ◽  
Computing Power ◽  
Smart Buildings ◽  
Localization Accuracy ◽  
Positioning Systems ◽  
Deployment Strategy ◽  
Accurate Localization ◽  
Localization Algorithms

The majority of services that deliver personalized content in smart buildings require accurate localization of their clients. This article presents an analysis of the localization accuracy using Bluetooth Low Energy (BLE) beacons. The aim is to present an approach to create accurate Indoor Positioning Systems (IPS) using algorithms that can be implemented in real time on platforms with low computing power. Parameters on which the localization accuracy mostly depends are analyzed: localization algorithm, beacons’ density, deployment strategy, and noise in the BLE channels. An adaptive algorithm for pre-processing the signals from the beacons is proposed, which aims to reduce noise in beacon’s data and to capture visitor’s dynamics. The accuracy of five range-based localization algorithms in different use case scenarios is analyzed. Three of these algorithms are specially designed to be less sensitive to noise in radio channels and require little computing power. Experiments conducted in a simulated and real environment show that using proposed algorithms the localization accuracy less than 1 m can be obtained.

scholarly journals Fully Data-Driven Pseudohealthy Synthesis for Planning Valve-Sparing Aortic Root Reconstruction using Conditional Variational Autoencoders

2020 ◽  
Vol 6 (3) ◽  
pp. 284-287
Author(s):  
Jannis Hagenah ◽  
Mohamad Mehdi ◽  
Floris Ernst
Keyword(s):  
Aortic Root ◽  
Similarity Index ◽  
Ground Truth ◽  
Representation Learning ◽  
Patient Specific ◽  
Ultrasound Images ◽  
Specific Geometry ◽  
The Individual ◽  
Native Root ◽  
Original Information

AbstractAortic root aneurysm is treated by replacing the dilated root by a grafted prosthesis which mimics the native root morphology of the individual patient. The challenge in predicting the optimal prosthesis size rises from the highly patient-specific geometry as well as the absence of the original information on the healthy root. Therefore, the estimation is only possible based on the available pathological data. In this paper, we show that representation learning with Conditional Variational Autoencoders is capable of turning the distorted geometry of the aortic root into smoother shapes while the information on the individual anatomy is preserved. We evaluated this method using ultrasound images of the porcine aortic root alongside their labels. The observed results show highly realistic resemblance in shape and size to the ground truth images. Furthermore, the similarity index has noticeably improved compared to the pathological images. This provides a promising technique in planning individual aortic root replacement.

scholarly journals Patient-specific optimization of automated detection improves seizure onset zone localization based on high frequency oscillations

2020 ◽  
Author(s):  
Casey L. Trevino ◽  
Jack J. Lin ◽  
Indranil Sen-Gupta ◽  
Beth A. Lopour
Keyword(s):  
High Frequency ◽  
Classification Accuracy ◽  
Patient Specific ◽  
Seizure Onset ◽  
Data Set ◽  
Localization Accuracy ◽  
High Frequency Oscillations ◽  
Seizure Onset Zone ◽  
Wide Range ◽  
The Impact

AbstractHigh frequency oscillations (HFOs) are a promising biomarker of epileptogenicity, and automated algorithms are critical tools for their detection. However, previously validated algorithms often exhibit decreased HFO detection accuracy when applied to a new data set, if the parameters are not optimized. This likely contributes to decreased seizure localization accuracy, but this has never been tested. Therefore, we evaluated the impact of parameter selection on seizure onset zone (SOZ) localization using automatically detected HFOs. We detected HFOs in intracranial EEG from twenty medically refractory epilepsy patients with seizure free surgical outcomes using an automated algorithm. For each patient, we assessed classification accuracy of channels inside/outside the SOZ using a wide range of detection parameters and identified the parameters associated with maximum classification accuracy. We found that only three out of twenty patients achieved maximal localization accuracy using conventional HFO detection parameters, and optimal parameter ranges varied significantly across patients. The parameters for amplitude threshold and root-mean-square window had the greatest impact on SOZ localization accuracy; minimum event duration and rejection of false positive events did not significantly affect the results. Using individualized optimal parameters led to substantial improvements in localization accuracy, particularly in reducing false positives from non-SOZ channels. We conclude that optimal HFO detection parameters are patient-specific, often differ from conventional parameters, and have a significant impact on SOZ localization. This suggests that individual variability should be considered when implementing automatic HFO detection as a tool for surgical planning.

scholarly journals A Protocol for Automated a-posteriori Adaptive Meshing with SimVascular

2019 ◽  
Author(s):  
Akash Gupta ◽  
Ethan O. Kung
Keyword(s):  
Mesh Size ◽  
Patient Specific ◽  
A Posteriori ◽  
Adaptive Meshing ◽  
Considerable Effort ◽  
Error Metrics ◽  
Scenario Modelling ◽  
Order Of Magnitude ◽  
Novice Users ◽  
Specific Geometry

Abstract Objective: Operational details regarding the use of the adaptive meshing (AM) algorithm available in the SimVascular package are scarce despite its application in several studies. Lacking these details, novice users of the AM algorithm may experience undesirable outcomes post-adaptation such as increases in mesh error metrics, unpredictable increases in mesh size, and losses in geometric fidelity. Here we propose an iterative protocol that will help prevent these undesirable outcomes and enhance the utility of the AM algorithm. We present three trials (conservative, aggressive and moderate settings) of our proposed protocol applied to a scenario modelling a Fontan junction with a patient-specific geometry and physiologically realistic boundary conditions. Results: In all three trials, an overall reduction in mesh error metrics is observed (range 47%-86%). The increase in the number of elements through each adaptation never exceeded the mesh size of the pre-adaptation mesh by one order of magnitude. In all three trials, the protocol resulted in consistent, repeatable improvements in mesh error metrics, no losses of geometric fidelity and steady increments in the number of elements in the mesh. Our proposed protocol prevented the aforementioned undesirable outcomes and can potentially save new users considerable effort and computing resources.

Reducing Tracking Error in RFID Real-Time Localization Systems Using Kalman Filters

2014 ◽  
Vol 5 (3) ◽  
pp. 1-24
Author(s):  
Benjamin Sanda ◽  
Ikhlas Abdel-Qader ◽  
Abiola Akanmu
Keyword(s):  
Real Time ◽  
Radio Frequency Identification ◽  
Kalman Filters ◽  
Tracking Error ◽  
Time Of Arrival ◽  
Indoor Environments ◽  
Real World Data ◽  
Localization Accuracy ◽  
Accurate Localization ◽  
Localization Systems

The use of Radio Frequency Identification (RFID) has become widespread in industry as a means to quickly and wirelessly identify and track packages and equipment. Now there is a commercial interest in using RFID to provide real-time localization. Efforts to use RFID technology in this way experience localization errors due to noise and multipath effects inherent to these environments. This paper presents the use of both linear Kalman filters and non-linear Unscented Kalman filters to reduce the error rate inherent to real-time RFID localization systems and provide more accurate localization results in indoor environments. A commercial RFID localization system designed for use by the construction industry is used in this work, and a filtering model based on 3rd order motion is developed. The filtering model is tested with real-world data and shown to provide an increase in localization accuracy when applied to both raw time of arrival measurements as well as final localization results.

Evaluation of patient‐specific MR distortion correction schemes for improved target localization accuracy in SRS

2020 ◽  
Author(s):  
Dimitrios Dellios ◽  
Eleftherios P. Pappas ◽  
Ioannis Seimenis ◽  
Chryssa Paraskevopoulou ◽  
Kostas I. Lampropoulos ◽  
...  
Keyword(s):  
Distortion Correction ◽  
Target Localization ◽  
Patient Specific ◽  
Localization Accuracy

The Role of the Computer in Team Problem-Solving: Critiquing or Partial Automation?

1993 ◽  
Vol 37 (15) ◽  
pp. 1029-1029
Author(s):  
Stephanie A. E. Guerlain ◽  
Philip J. Smith
Keyword(s):  
Problem Solving ◽  
Computer System ◽  
Real World ◽  
Automated System ◽  
Computer Interface ◽  
Rule Base ◽  
Heuristic Strategy ◽  
System Designs ◽  
Better Than

A testbed was developed for studying the effects of different computer system designs on human-computer team problem-solving, using the real-world task of antibody identification. The computer interface was designed so that practitioners could solve antibody identification cases using the computer as they normally would using paper and pencil. A rule-base was then encoded into the computer such that it had knowledge for applying a heuristic strategy that is often helpful for solving cases. With this testbed, studies have been run comparing different computer system designs. A critiquing system was found to be better than a partially automated system on cases where the computer's knowledge is incompetent.

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