Real-Time Tissue Volume Estimation During Surgery
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Solution Overview
Problem
Current surgical procedures lack an efficient method to determine the volume of resected tissue during the procedure, which can lead to incomplete tissue removal and potential complications, such as metastasis, as existing methods require post-resection measurement.
Innovation Solution
A system and method utilizing a processor to generate a 3D occupancy map from depth datasets captured as different portions of the resected tissue are presented to an imaging device, allowing for real-time estimation of the tissue volume and comparison to preoperative expectations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If post-resection measurement methods are used, then measurement simplicity is maintained, but tissue removal adequacy cannot be confirmed during surgery
Solution Approach 1:
The system performs preliminary 3D mapping and volume calculation of the resected tissue immediately after resection, before the surgical procedure concludes. This allows the surgical team to confirm adequate tissue removal during the same surgical session, avoiding the need for separate post-operative measurement sessions and potential additional procedures.
Solution Approach 2:
The invention replaces traditional manual post-resection measurement methods with an automated optical imaging system that captures depth datasets, generates 3D occupancy maps, and calculates tissue volume automatically. This substitution enables real-time volume assessment during surgery without requiring manual measurement procedures.
2Reliability
If real-time volume measurement is implemented during surgery, then tissue removal adequacy is confirmed immediately, but system complexity increases
Solution Approach 1:
The imaging device is designed to perform multiple functions: capturing depth datasets, generating 3D occupancy maps, calculating tissue volume, and providing real-time feedback to the surgical team. This multi-functionality consolidates what could be separate complex systems into a single integrated device, reducing overall system complexity while maintaining real-time measurement capabilities.
Solution Approach 2:
The system automatically processes the captured depth datasets to generate 3D occupancy maps and calculate tissue volume without requiring manual intervention. The processor autonomously performs the complex computational tasks, eliminating the need for additional manual measurement tools or procedures and simplifying the operational workflow.
3Reliability
If traditional post-resection measurement is used, then equipment requirements are minimized, but incomplete resection risks remain
Solution Approach 1:
The system provides immediate feedback to the surgical team by comparing the measured tissue volume against the preoperative treatment plan. This feedback loop allows the surgical team to verify that the resected tissue volume meets the planned targets, enabling informed decisions about whether additional resection is needed while the patient is still under anesthesia and the surgical field is accessible.
Data Source
AI summary
An illustrative system is configured to access, during a surgical procedure that involves resecting a piece of tissue from a body, a plurality of depth datasets for the resected piece of tissue; determine, during the surgical procedure and based on the plurality of depth datasets, an estimated volume of the resected piece of tissue; and indicate, during the surgical procedure, whether the estimated volume of the resected piece of tissue is within a predetermined threshold of an expected volume of the resected piece of tissue.