Suturing Guidance Using 3D Tissue Modeling and Needle Path Planning
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Solution Overview
Problem
Surgical suturing in robotic-assisted surgery is cognitively challenging due to difficulties in envisioning needle trajectories and tool kinematics, particularly with curved or flexible tools, leading to sub-optimal suturing outcomes.
Innovation Solution
A tissue suturing guidance system utilizing a stereo-endoscope for three-dimensional surface reconstruction, multi-spectral imaging, and biomechanical modeling to generate a suturing configuration, which includes real-time feedback and adjustment of suture placement, tension, and pathway, guided by geometric and biomechanical tissue representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robotic-assisted suturing is performed manually by the clinician, then the clinician has full control over the suturing process, but the cognitive load increases and suturing outcomes become sub-optimal due to difficulty in envisioning needle trajectories and tool kinematics
Solution Approach 1:
The system creates a virtual copy of the physical surgical scene using stereo-endoscope imaging and 3D surface reconstruction. This virtual model allows the clinician to visualize needle trajectories and tool kinematics without adding physical complexity to the actual suturing instrument, thereby reducing cognitive load while maintaining control.
Solution Approach 2:
The guidance system acts as an intermediary between the clinician's intent and the physical suturing action. It provides real-time visual feedback and simulation of needle paths, serving as a mediator that translates complex tool kinematics into understandable visual representations, improving reliability without increasing operational difficulty.
2Manufacturing precision
If automated needle trajectory execution is implemented, then cognitive load is reduced and suturing precision is improved, but the system complexity increases
Solution Approach 1:
The robotic surgical system performs multiple functions: it executes automated needle trajectories, provides real-time visual guidance, and allows manual override when needed. This multi-functionality justifies the increased system complexity by delivering precise needle placement while maintaining operational flexibility.
Solution Approach 2:
The system implements real-time feedback through stereo-endoscope imaging and biomechanical tissue representation. This feedback loop allows the system to automatically adjust needle trajectories while providing visual confirmation to the clinician, improving precision without requiring overly complex automated systems.
3Reliability
If biomechanical tissue representation and simulation are used to determine optimal suture placement, then tissue contact pressure is optimized for tissue regrowth, but the time required for suturing configuration increases
Solution Approach 1:
The system performs preliminary biomechanical analysis and simulation to determine optimal suture placement before the actual suturing begins. By pre-calculating the ideal configuration based on tissue properties, the system optimizes tissue contact pressure for regrowth while reducing the time required during the actual suturing procedure.
Solution Approach 2:
The biomechanical tissue representation is dynamically updated based on real-time imaging and tissue properties. This allows the system to adapt the suture configuration as the procedure progresses, optimizing tissue regrowth effectiveness without requiring complete re-planning at each step, thereby reducing overall time loss.
Data Source
AI summary
A tissue suturing guidance system includes an image capturing device, a display, and a processor in communication with the image capturing device and the display. The image capturing device is configured to capture a suture site. The display is configured to display an image of the suture site. The processor is configured to: determine, based on the image of the suture site, a geometric tissue representation of the suture site; access measured properties of the suture site; determine, based on the measured properties of the suture site, a biomechanical tissue representation of the suture site; and generate, based on the geometric tissue representation and biomechanical tissue representation of the suture site, a suturing configuration for the suture site.