Novel experimental model for studying the spatiotemporal electrical signature of acute myocardial ischemia: a translational platform

Berzuuist

et al. 2020

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Acute myocardial ischemia compromises the ordered electrical activation of the heart, however, because of sampling limitations, volumetric changes in activation have not been measured. We used a large-animal experimental model and high-resolution volumetric mapping to study the effects of ischemia on conduction speeds (CS) throughout the myocardium. We estimated CS and electrocardiographic changes (ST segments) and evaluated the spatial and temporal correlations between them across 11 controlled episodes. We found that ischemia induces significant conduction slowing, reducing the global median speed by 25 cm/s. Furthermore, there was a high temporal correlation between the development of ischemic severity and CS (corr. = 0.93) through each episode. The spatial correlations between ST-segment changes and CS slowing were more spatially complex than expected with substantial slowing at the periphery of the zones that showed ST-segment changes. This is the first study that has documented in an experimental model volumetric changes of CS during acute myocardial ischemia and explored the relationships between ischemia development in space and time. We showed that conduction speed changes are spatiotemporally correlated to ischemic severity and illustrated the biphasic response long proposed from cellular studies.

Section: Introductionmentioning

confidence: 95%

Quantifying the Spatiotemporal Influence of Acute Myocardial Ischemia on Volumetric Conduction Velocity

Berzuuist

et al. 2020

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“…Experimental Dataset: The measured electrograms were acquired using a method described previously. [8]. Briefly, an in situ pig heart was instrumented with 20 intramural plunge needle recording arrays, each with ten electrodes spaced 1.8 mm apart along the shaft of the needle.…”

Section: Methodsmentioning

confidence: 99%

Experimental Validation of a Novel Extracellular-Based Source Representation of Acute Myocardial Ischemia

Bergquist

et al. 2020

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Electrocardiographic imaging (ECGI) based detection of myocardial ischemia requires an accurate formulation of the source model, which includes a relationship between extracellular and transmembrane potentials (TMPs). In this study, we used high-resolution intramural experimental recordings and forward modeling to examine the relationship between extracellular potentials and TMPs during myocardial ischemia. We measured extracellular electrograms from intramural plunge needle arrays during seven controlled ischemia episodes in an animal model. We used three TMP source representations: (1) parameterized and distance-based (defined previously), (2) extracellularbased linear transform, and (3) extracellular-based sigmoidal transform. TMPs for each source formulation were then used to compute extracellular potentials by calculating the passive bidomain forward solution throughout the myocardium. We compared measured and computed potentials. Linear and sigmoidal approaches produced improved results compared to the parameterized method. The RMSE, SC, and TC of linear, sigmoidal, and parameterized methods were 0.85 mV, 1.21 mV, and 3.37 mV; 0.91, 0.88, and 0.47; 0.90, 0.77, and 0.33 respectively. We found extracellular-based calculations of TMPs produced superior forward computations compared to parameterized zones.

“…We tested our novel cardiac mapping system by recording intramyocardial, epicardial, and torso cardiac signals of an experiment model described previously. [5] The example experimental recording in figure 3 shows 530 individual electrograms from all three domains. The peak-topeak amplitude ranges were 25 mV, 18 mV, and 1 mV, for the intramural, epicardial, and torso domains, respectively.…”

Section: Recorded Signalsmentioning

confidence: 99%

“…First, the inputs must be flexible enough to use with a wide variety of recording arrays, each of which samples a different region of the heart and thorax, resulting in a range of signal amplitudes from microvolts to millivolts. [5] Second, the system must employ carefully tuned analog signal filtering, amplifier gains, and flexible referencing, and also protect against defibrillation pulses that can arise during an experiment. Third, the system must convert analog electrical potentials to digital signals with high fidelity, minimal noise, and adequate sampling and time resolutions for subsequent processing and analysis.…”

Section: Introductionmentioning

confidence: 99%

High-Capacity Cardiac Signal Acquisition System for Flexible, Simultaneous, Multidomain Acquisition

Bergquist

et al. 2020

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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.