Thermal Profiles for Focal Pulsed Electric Field Ablation
Bibliographic record
Abstract
BACKGROUND: Pulsed electrical field (PEF) ablation may cause tissue heating. These changes are reportedly small, but each PEF system and waveform will have a different behavior, and data are lacking. OBJECTIVES: This study sought to compare the temperature profile of focal point, monopolar biphasic PEF ablation versus radiofrequency (RF). METHODS: Ablation lesions were performed on perfused thigh muscle of swine. PEF lesions were performed with 3 compatible ablation catheters at the highest (25 amp) energy, and 1 catheter (Tacticath SE) was also used at the 22- and 19-amp levels. Temperature changes in the tissue were measured using fluoroptic temperature probes inserted at the muscle surface, as well as 3 mm and 7 mm below the surface. Temperatures were recorded continuously at baseline, during delivery, and after ablation. Muscle temperatures were compared with those of RF lesions performed with 1 catheter (Tacticath SE) at 30 W for 30 seconds. RESULTS: PEF ablation with 3energy settings produced small temperature changes. Maximum average temperature rise for PEF for the maximum (25-amp) energy setting (32 lesions) was 7.6 °C, 2.8 °C, and 0.9 °C at the surface, 3-mm depth, and 7-mm depth, respectively. The temperature rise was dose dependent, with lower energy settings yielding less temperature rise. RF ablations (10 lesions) produced temperature increases of 16.6 °C, 39.8 °C, and 9.5 °C at the surface, 3-mm depth, and 7-mm depth, respectively. CONCLUSIONS: PEF caused detectable temperature changes in muscle tissue, which never exceeded 2.8 °C at the 3-mm depth versus baseline. By contrast, RF produced substantial temperature rises. These data support that focal monopolar biphasic energy delivered by this PEF technology retains a favorable thermal safety profile.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".