Research and parameter optimization of boundary temperature-controlled regional radiofrequency ablation algorithm in...

Area of Science:

• Hepatobiliary Surgery
• Oncology
• Medical Engineering

Background:

• Hepatocellular carcinoma (HCC) treatment often utilizes radiofrequency ablation (RFA).
• Current RFA methods face challenges like incomplete ablation, tumor recurrence, and damage to surrounding healthy tissues.
• Improving RFA precision is crucial for better patient outcomes.

Purpose of the Study:

• To compare the ablation efficacy of traditional constant-power RFA (TCP-RFA) and boundary temperature-controlled RFA (BTC-RFA).
• To optimize BTC-RFA parameters for enhanced ablation precision.
• To evaluate the impact on both tumor and non-targeted tissue damage.

Main Methods:

• Ex vivo bovine liver model utilized for experimentation.
• Water-cooling equipment employed during ablation procedures.
• ImageJ software used to quantify the proportion of damage area (PDA).
• Statistical analysis performed on experimental data.

Main Results:

• BTC-RFA mode demonstrated a significant reduction in PDA compared to TCP-RFA.
• Optimal BTC-RFA parameters identified: 45W initial power, 55°C-65°C temperature control range, and 10°C step.
• BTC-RFA achieved precise ablation with reduced damage to non-targeted tissues.

Conclusions:

• BTC-RFA algorithm proves effective in achieving complete tumor ablation.
• BTC-RFA significantly minimizes collateral damage to healthy liver tissue.
• This technique shows promise for more precise and safer hepatocellular carcinoma treatment.