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Image-Free Tumor Segmentation of Soft Tissue Using a Minimally Invasive Robotic Palpation System
Abstract:
Tumor segmentation is crucial for surgical planning and precise tumor resection for effective treatment. Traditionally, tumor localization has been performed using medical imaging techniques such as CT and MRI or through direct palpation by surgeons. However, in minimally invasive robotic surgery (MIS), these methods have limitations, including registration errors with imaging and inaccuracies caused by the subjectivity of palpation by surgeons. In this study, we introduce a robotic palpation system and an image-free process for MIS tumor segmentation using a robot. Our proposed system enables precise tumor shape differentiation through direct robotic palpation. For this, the robotic palpation system collects surface shape information through the proposed process, allowing tissue palpation at specific depths according to surface curvature. Additionally, it visualizes stiffness maps, enabling image-free tumor segmentation. In experiments using this system, evaluation of planar and curved phantom models demonstrates precise segmentation at targeted sites, with sensitivities of 0.9634 and 0.9729, and specificities of 0.9646 and 0.9878, respectively. Validation on ex-vivo porcine liver models further confirms the efficacy of our approach.
Insights
This study introduces a robotic palpation system for image-free tumor segmentation in minimally invasive robotic surgery (MIS). The system precisely differentiates tumor shapes and stiffness, improving surgical planning and resection accuracy.
Area of Science:
- Robotics
- Surgical Technology
- Medical Imaging
Background:
- Tumor segmentation is vital for surgical planning and effective cancer treatment.
- Traditional methods like CT, MRI, and surgeon palpation have limitations in minimally invasive robotic surgery (MIS), including registration errors and subjectivity.
- Accurate tumor localization is essential for precise tumor resection.
Purpose of the Study:
- To introduce a novel robotic palpation system for image-free tumor segmentation in MIS.
- To enable precise tumor shape differentiation and stiffness mapping through robotic palpation.
- To overcome the limitations of traditional imaging and palpation methods in MIS.
Main Methods:
- Development of a robotic palpation system capable of collecting surface shape information.
- Implementation of a process for tissue palpation at specific depths based on surface curvature.
- Visualization of tissue stiffness maps for image-free tumor segmentation.
- Validation using planar and curved phantom models and ex-vivo porcine liver models.
Main Results:
- The robotic system achieved precise tumor shape differentiation and stiffness mapping.
- Evaluation on phantom models demonstrated high sensitivity (0.9634-0.9729) and specificity (0.9646-0.9878) for tumor segmentation.
- Ex-vivo validation confirmed the system's efficacy in real biological tissues.
Conclusions:
- The proposed robotic palpation system offers a precise and image-free solution for tumor segmentation in MIS.
- This technology has the potential to enhance surgical planning and improve tumor resection outcomes.
- Robotic palpation represents a significant advancement in overcoming current challenges in MIS tumor localization.
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