3D Lung Model Displacement Calculation for Thoracoscopic Surgery
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
During thoracoscopic surgery, the deflation of lungs leads to a shift in the lung geometry, making preoperative three-dimensional reconstructions inaccurate, which can result in sub-optimal surgical outcomes due to the need for clinicians to compensate for the altered geometry during the procedure.
Innovation Solution
A system and method for modeling a collapsed lung using CT data, involving tissue differentiation, generation of a 3-D model, application of material properties, calculation of lung displacement, and display of a collapsed lung model to accurately depict the lung's geometry in a deflated state, incorporating features like gravity effects and curvature of the spine for precise surgical navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If preoperative three-dimensional reconstruction of the lung is performed using CT data, then accurate identification of lesion location and surgical planning is enabled, but the accuracy deteriorates when the lung is deflated during surgery due to geometry shift
Solution Approach 1:
The system performs preliminary actions by creating a preoperative 3D model of the inflated lung and then pre-calculating the displacement field that occurs during lung deflation. This allows the geometry transformation to be predicted and compensated for before surgery begins, maintaining accuracy from preoperative planning through intraoperative execution without requiring real-time geometric updates.
Solution Approach 2:
The system creates a virtual copy of the lung geometry in 3D space that can be transformed independently of the actual physical lung. By modeling the displaced geometry of the deflated lung based on the inflated preoperative scan, the system provides an accurate virtual representation that guides surgery without requiring repeated imaging or physical models.
2Ease of operation
If the lung is deflated during thoracoscopic procedure to provide surgical space, then access to the lesion is improved, but the preoperative three-dimensional model becomes inaccurate due to geometry change
Solution Approach 1:
The system performs preliminary calculations of the displacement field and transformed geometry before surgery begins. By pre-computing how the lung geometry will change during deflation based on material properties and boundary conditions, the system provides an accurate intraoperative guide without requiring the lung to remain inflated for modeling purposes.
Solution Approach 2:
The system introduces a computational model of lung tissue mechanics as an intermediary between the preoperative inflated geometry and the intraoperative deflated state. This virtual model acts as a mediator that translates the known preoperative geometry into an accurate prediction of the deflated geometry, eliminating the need to maintain the lung in either extreme state for modeling accuracy.
3Measurement precision
If clinicians compensate for altered lung geometry during surgery, then accurate lesion targeting is maintained, but procedural time increases and error probability increases
Solution Approach 1:
The system performs all necessary geometric transformations and displacement calculations before surgery begins. The complete transformed 3D model accounting for lung deflation is prepared in advance, eliminating the need for intraoperative geometric corrections or real-time image registration, thereby reducing procedural time and potential for human error.
Solution Approach 2:
The system provides real-time visual feedback by overlaying the pre-calculated displaced 3D model and surgical pathway directly onto the intraoperative video feed. This continuous visual guidance allows clinicians to proceed confidently without manual compensation, maintaining accuracy while reducing procedural complexity and time.
Data Source
AI summary
A method of modeling lungs of a patient includes acquiring computed tomography data of a patient's lungs, storing a software application within a memory associated with a computer, the computer having a processor configured to execute the software application, executing the software application to differentiate tissue located within the patient's lung using the acquired CT data, generate a 3-D model of the patient's lungs based on the acquired CT data and the differentiated tissue, apply a material property to each tissue of the differentiated tissue within the generated 3-D model, generate a mesh of the 3-D model of the patient's lungs, calculate a displacement of the patient's lungs in a collapsed state based on the material property applied to the differentiated tissue and the generated mesh of the generated 3-D model, and display a collapsed lung model of the patient's lungs based on the calculated displacement of the patient's lungs.