In Vitro Assay Development to Study Pulse Field Ablation Outcome Using Solanum Tuberosum.
Akshay NarkarAbouzar KaboudianYasaman ArdershirpourMaura CasciolaTromondae K FeasterKsenia BlinovaPublished in: International journal of molecular sciences (2024)
Exposing cells to intense and brief electric field pulses can modulate cell permeability, a phenomenon termed electroporation. When applied in medical treatments of diseases like cancer and cardiac arrhythmias, depending on level of cellular destruction, it is also referred to as irreversible electroporation (IRE) or Pulsed Field Ablation (PFA). For ablation device testing, several pulse parameters need to be characterized in a comprehensive manner to assess lesion boundary and efficacy. Overly aggressive voltages and application numbers increase animal burden. The potato tuber is a widely used initial model for the early testing of electroporation. The aim of this study is to characterize and refine bench testing for the ablation outcomes of PFA in this simplistic vegetal model. For in vitro assays, several pulse parameters like voltage, duration, and frequency were modulated to study effects not only on 2D ablation area but also 3D depth and volume. As PFA is a relatively new technology with minimal thermal effects, we also measured temperature changes before, during, and after ablation. Data from experiments were supplemented with in silico modeling to examine E-field distribution. We have estimated the irreversible electroporation threshold in Solanum Tuberosum to be at 240 V/cm. This bench testing platform can screen several pulse recipes at early stages of PFA device development in a rapid and high-throughput manner before proceeding to laborious trials for IRE medical devices.
Keyphrases
- high throughput
- blood pressure
- radiofrequency ablation
- healthcare
- type diabetes
- single cell
- left ventricular
- metabolic syndrome
- squamous cell carcinoma
- stem cells
- bone marrow
- endothelial cells
- catheter ablation
- electronic health record
- molecular docking
- cell cycle arrest
- papillary thyroid
- lymph node metastasis
- cell proliferation
- data analysis
- deep learning
- childhood cancer