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Artificial Intelligence in Thermal Ablation: Current Applications and Future Directions in Microwave Technologies
Kealan Westby1, Daniel Westby2, Kevin McKevitt2
1Blackrock Health Galway Clinic, H91 HHT0 Galway, Ireland.
Biomimetics (Basel, Switzerland)
|December 24, 2025
Summary
Artificial intelligence (AI) is revolutionizing thermal ablation in oncology, especially microwave ablation (MWA). AI optimizes patient selection, image analysis, and real-time guidance for personalized cancer treatment.
Area of Science:
- Interventional oncology
- Medical imaging
- Artificial intelligence
Background:
- Thermal ablation modalities (RFA, cryoablation, HIFU, MWA) are key in interventional oncology.
- Artificial intelligence (AI) shows growing potential to enhance these treatments.
- Microwave ablation (MWA) presents unique opportunities for AI integration.
Purpose of the Study:
- To review the current landscape of AI-enhanced thermal ablation.
- To highlight emerging AI applications specifically within microwave ablation (MWA).
- To provide comparative insights across different ablation modalities.
Main Methods:
- Review of AI-driven methods including convolutional neural networks, radiomics, and reinforcement learning.
- Analysis of AI applications in patient selection, image segmentation, treatment response prediction, and procedural guidance.
- Comparative assessment of AI integration challenges and opportunities across RFA, cryoablation, HIFU, and MWA.
Main Results:
- AI methods are being applied to optimize various aspects of thermal ablation procedures.
- MWA technologies offer specific advantages for AI implementation.
- Existing AI applications are largely investigational but show significant promise.
Conclusions:
- The convergence of AI, advanced imaging, and energy delivery promises advancements in precision oncology.
- Integrating AI into clinical workflows requires focus on safety, consistency, and personalized therapy.
- Future research needs prospective validation, regulatory clarity, and interdisciplinary collaboration for AI-enabled thermal ablation adoption.
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