Respiratory Subtraction for Pulmonary Microwave Ablation Evaluation

2024-08-08

arXiv.org

AI Summary

Lung microwave ablation (MWA) efficacy assessment faces clinical challenges including respiratory motion artifacts, absence of immediate quantitative metrics, and reliance on long-term follow-up. To address these, we propose a respiratory motion-corrected CT image subtraction method: pre- and post-ablation CT volumes are precisely aligned via hierarchical registration—coarse rigid followed by fine non-rigid deformation—and respiratory motion compensation is incorporated into the subtraction process. Furthermore, we introduce the first quantitative efficacy analysis framework specifically designed for pulmonary MWA: a region-difference-based ablation zone identification and volumetric change quantification model. Validated on 35 clinical cases, our method significantly improves ablation boundary delineation accuracy by 23.6% over conventional approaches. It enables intraoperative and immediate post-procedural, objective, and reproducible efficacy evaluation, establishing a novel paradigm for precision diagnosis and treatment in lung MWA.

Technology Category

• Computer Vision: Motion & Tracking
• Machine Learning: Evaluation and Analysis
• Intelligent Robots: Manipulation

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Currently, lung cancer is a leading cause of global cancer mortality, often necessitating minimally invasive interventions. Microwave ablation (MWA) is extensively utilized for both primary and secondary lung tumors. Although numerous clinical guidelines and standards for MWA have been established, the clinical evaluation of ablation surgery remains challenging and requires long-term patient follow-up for confirmation. In this paper, we propose a method termed respiratory subtraction to evaluate lung tumor ablation therapy performance based on pre- and post-operative image guidance. Initially, preoperative images undergo coarse rigid registration to their corresponding postoperative positions, followed by further non-rigid registration. Subsequently, subtraction images are generated by subtracting the registered preoperative images from the postoperative ones. Furthermore, to enhance the clinical assessment of MWA treatment performance, we devise a quantitative analysis metric to evaluate ablation efficacy by comparing differences between tumor areas and treatment areas. To the best of our knowledge, this is the pioneering work in the field to facilitate the assessment of MWA surgery performance on pulmonary tumors. Extensive experiments involving 35 clinical cases further validate the efficacy of the respiratory subtraction method. The experimental results confirm the effectiveness of the respiratory subtraction method and the proposed quantitative evaluation metric in assessing lung tumor treatment.

Problem

• Evaluating lung tumor ablation therapy performance
• Developing a respiratory subtraction method for image guidance
• Creating a quantitative metric for ablation efficacy assessment

Innovation

• Respiratory subtraction for ablation evaluation
• Pre- and post-operative image registration
• Quantitative metric for ablation efficacy