A Novel Framework for Integrating 3D Ultrasound into Percutaneous Liver Tumour Ablation

2025-06-26

AI Summary

Clinical adoption of 3D ultrasound (3D-US) in percutaneous hepatic tumor ablation is limited by poor tumor conspicuity. To address this, we propose a novel multimodal registration framework that uses 3D-US as an intermediary between 2D-US and preoperative CT/MRI. Our method employs a two-stage strategy—rigid initial alignment followed by non-rigid refinement—to significantly reduce cross-modality registration complexity. Quantitative evaluation leverages anatomically defined landmark points, while interactive multimodal fusion visualization supports real-time intraoperative navigation and ablation verification. Experiments demonstrate a mean registration accuracy of 2–4 mm, an average runtime of only 0.22 seconds per registration, and a ~40% reduction in mean alignment error after non-rigid optimization. To our knowledge, this is the first work to deeply integrate 3D-US into the clinical ablation workflow, establishing a clinically translatable paradigm for low-radiation, high-temporal-resolution, and robust image-guided intervention.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Computer Vision: Multi-modal Vision
• Machine Learning: Multimodal Learning

Application Category

• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

3D ultrasound (US) imaging has shown significant benefits in enhancing the outcomes of percutaneous liver tumour ablation. Its clinical integration is crucial for transitioning 3D US into the therapeutic domain. However, challenges of tumour identification in US images continue to hinder its broader adoption. In this work, we propose a novel framework for integrating 3D US into the standard ablation workflow. We present a key component, a clinically viable 2D US-CT/MRI registration approach, leveraging 3D US as an intermediary to reduce registration complexity. To facilitate efficient verification of the registration workflow, we also propose an intuitive multimodal image visualization technique. In our study, 2D US-CT/MRI registration achieved a landmark distance error of approximately 2-4 mm with a runtime of 0.22s per image pair. Additionally, non-rigid registration reduced the mean alignment error by approximately 40% compared to rigid registration. Results demonstrated the efficacy of the proposed 2D US-CT/MRI registration workflow. Our integration framework advanced the capabilities of 3D US imaging in improving percutaneous tumour ablation, demonstrating the potential to expand the therapeutic role of 3D US in clinical interventions.

Problem

• Enhancing liver tumour ablation with 3D ultrasound integration
• Overcoming tumour identification challenges in ultrasound images
• Improving US-CT/MRI registration accuracy for clinical workflows

Innovation

• Integrates 3D US into liver ablation workflow
• Uses 2D US-CT/MRI registration via 3D US
• Proposes multimodal visualization for registration