Acute detection of optical tissue changes in real-time during pulsed field ablation (PFA)
Bibliographic record
Abstract
Abstract Background It has been established in previous animal and human studies that it is possible to assess lesion formation in real-time using optical means during the application of radiofrequency (RF) energy in cardiac ablation procedures. The optical interrogation was accomplished using a novel catheter and instrument system whereby the catheter has embedded optical fibers that transmit and receive light from the instrument. Purpose The aim of this study was to see if there are similar indications of lesion formation, detected by the same optical means, during the application of pulsed field ablation (PFA) energy to cause lesions through electroporation. Methods A series of 3 anesthetized pigs underwent PFA in the right atrium. An 8-electrode circular catheter was placed high in the right atrium, near the superior vena cava, to simulate pulmonary vein isolation as part of an AF ablation procedure. The optical catheter was placed adjacent to the circular catheter between stimulation electrode pairs. A bolus of adenosine was administered to create a window of asystole to avoid stimulation on the T-wave. Bipolar PFA was delivered immediately post drug infusion and the optical signature from the catheter was recorded and displayed in real-time. Electrograms were recorded and the mapping of the lesion was performed with the optical catheter at the following time intervals post PFA delivery: 0 min, 15 min, 1 hour, and 3 hours. Necropsy and histology followed the procedure. Results The optical signal is distinctly higher in intensity during the PFA pulse train. The optical signal showed an immediate significant decrease and a slow but steady decay over the mapping interval. Electrogram reduction accompanied PFA application and also showed a marked reduction over the mapping interval. The optical signal amplitudes were markedly lower when on the lesion compared to healthy non-ablated myocardium as predicted. Conclusions Preliminary results indicate that optical mapping detects immediate tissue changes during PFA at these energy levels and hence could be is a viable method of evaluating lesion formation during and after PFA energy application. The optical signal indicates that cell damage occurs immediately at these energy levels and continues to progress slowly in lesions made by PFA energy compared to those made by RF energy. The findings also suggest that optical mapping can identify acute lesions made with PFA energy in real-time implying that optical mapping could evolve as a PFA gap detector. Funding Acknowledgement Type of funding source: None
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".