Abstract
Background
The role of catheter tip shape on the safety and efficacy of radiofrequency (RF) ablation has been overlooked, although differences have been observed in clinical and research fields.
Objective
The purpose of this study was to analyze the role of electrode tip shape in RF ablation using a computational model.
Methods
We simulated 108 RF ablations through a realistic 3-dimensional computational model considering 2 clinically used, open-irrigated catheters (spherical and cylindrical tip), varying contact force (CF), blood flow, and irrigation. Lesions are defined by the 50°C isotherm contour and evaluated by means of width, depth, depth at maximum width, and volume. Ablations are deemed as safe, critical (tissue temperature >90°C), and pop (tissue temperature >100°C).
Results
Tissue–electrode contact is less for the spherical tip at low CF but the relationship is inverted at high CF. At low CF, the cylindrical tip generates deeper and wider lesions and a 4-fold larger volume. With increasing CF, the lesions generated by the spherical tip become comparable to those generated by the cylindrical tip. The 2 tips feature different safety profiles: CF and power are the main determinants of pops for the spherical tip; power is the main factor for the cylindrical tip; and CF has a marginal effect. The cylindrical tip is more prone to pop generation at higher powers. Saline irrigation and blood flow effect do not depend on tip shape.
Conclusion
Tip shape determines the performance of ablation catheters and has a major impact on their safety profile. The cylindrical tip shows more predictable behavior in a wide range of CF values.
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 699-705 |
| Seitenumfang | 7 |
| Fachzeitschrift | Heart Rhythm O2 |
| Volume | 3 |
| Ausgabenummer | 6 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - Aug. 2022 |
Wissenschaftszweige
- 101 Mathematik
- 101013 Mathematische Logik
- 101024 Wahrscheinlichkeitstheorie
- 102001 Artificial Intelligence
- 102003 Bildverarbeitung
- 102019 Machine Learning
- 102035 Data Science
- 603109 Logik
- 202027 Mechatronik
JKU-Schwerpunkte
- Digital Transformation
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