ArticlePhysiological measurement2020
Novel experimental model for studying the spatiotemporal electrical signature of acute myocardial ischemia: a translational platform.
Article in Physiological measurement, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 27 citations in OpenAlex.
- Uncertainty quantification via polynomial chaos expansion of myocardial fibre orientation and cardiac activation patterns.The Journal of physiology · 2026Article
- Predicting ventricular arrhythmia in myocardial ischemia using deep learning.Heart rhythm O2 · 2026Article
- Reconstructing ventricular activation sequences from epicardial data: Insights from Geodesic Back-Propagation optimization in porcine models.Computers in biology and medicine · 2025Article
- Predicting Ventricular Arrhythmia in Myocardial Ischemia Using Machine Learning.Computing in cardiology · 2025Article
- Machine Learning Estimation of Myocardial Ischemia Severity Using Body Surface ECG.Computing in cardiology · 2024Article
- Application of Order and Sample Selection in Uncertainty Quantification of Cardiac Models.Computing in cardiology · 2024Article
- High Density Body Surface Potential Mapping with Conducting Polymer-Eutectogel Electrode Arrays for ECG imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Capturing the Influence of Conduction Velocity on Epicardial Activation Patterns Using Uncertainty Quantification.Computing in cardiology · 2023Article
- Uncertainty Quantification of Fiber Orientation and Epicardial Activation.Computing in cardiology · 2023Article
- Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models.Frontiers in physiology · 2023Article
- Investigation into the importance of using natural PVCs and pathological models for potential-based ECGI validation.Frontiers in physiology · 2023Article
- A personalized real-time virtual model of whole heart electrophysiology.Frontiers in physiology · 2022Article
- Body Surface Potential Mapping: Contemporary Applications and Future Perspectives.Hearts (Basel, Switzerland) · 2021Article
- Estimation and Validation of Cardiac Conduction Velocity and Wavefront Reconstruction Using Epicardial and Volumetric Data.IEEE transactions on bio-medical engineering · 2021Article
- The effect of interpolating low amplitude leads on the inverse reconstruction of cardiac electrical activity.Computers in biology and medicine · 2021Article
- Myocardial Ischemia Detection Using Body Surface Potential Mappings and Machine Learning.Computing in cardiology · 2021Article
- The Role of Myocardial Fiber Direction in Epicardial Activation Patterns via Uncertainty Quantification.Computing in cardiology · 2021Article
- Uncertainty Quantification in Simulations of Myocardial Ischemia.Computing in cardiology · 2021Article
- Characterizing the transient electrocardiographic signature of ischemic stress using Laplacian Eigenmaps for dimensionality reduction.Computers in biology and medicine · 2020Article
- Effect of Myocardial Fiber Direction on Epicardial Activation Patterns.Computing in cardiology · 2020Article
Corrections and comments
- Erratum issued
Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
Myocardial ischemia is one of the most common cardiovascular pathologies and can indicate many severe and life threatening diseases. Despite these risks, current electrocardiographic detection techniques for ischemia are mediocre at best, with reported sensitivity and specificity ranging from 50%-70% and 70%-90%, respectively.
objectiveTo improve this performance, we set out to develop an experimental preparation to induce, detect, and analyze bioelectric sources of myocardial ischemia and determine how these sources reflect changes in body-surface potential measurements. APPROACH: We designed the experimental preparation with three important characteristics: (1) enable comprehensive and simultaneous high-resolution electrical recordings within the myocardial wall, on the heart surface, and on the torso surface; (2) develop techniques to visualize these recorded electrical signals in time and space; and (3) accurately and controllably simulate ischemic stress within the heart by modulating the supply of blood, the demand for perfusion, or a combination of both. MAIN
resultsTo achieve these goals we designed comprehensive system that includes (1) custom electrode arrays (2) signal acquisition and multiplexing units, (3) a surgical technique to place electrical recording and myocardial ischemic control equipment, and (4) an image based modeling pipeline to acquire, process, and visualize the results. With this setup, we are uniquely able to capture simultaneously and continuously the electrical signatures of acute myocardial ischemia within the heart, on the heart surface, and on the body surface. SIGNIFICANCE: This novel experimental preparation enables investigation of the complex and dynamic nature of acute myocardial ischemia that should lead to new, clinically translatable results.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.