Adaptive Catheter Navigation via Dynamic 3D Model Registration
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Solution Overview
Problem
Current navigation systems for catheter tips in tortuous channels, such as pulmonary airways, face accuracy issues due to the rigidity of CT digital maps and the flexibility of lung structures, leading to inaccuracies as the distance from registration points increases, causing the locatable guide to appear outside the airways and providing inadequate guidance.
Innovation Solution
A method is developed to generate a three-dimensional virtual bronchial tree skeleton using automatic seed point detection, Region Growing Algorithm, and adaptive threshold detection, which creates an anatomically valid virtual model of airways, and continuously adapts the locatable guide's path to this skeleton for improved navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If a rigid CT digital map is used as the navigation reference, then the digital map structure is stable and easy to process, but the map accuracy deteriorates as distance from registration points increases due to lung flexibility
Solution Approach 1:
The patent transforms the static rigid CT map into a dynamic adaptive model by continuously adjusting the digital map to match the actual locatable guide path in real-time. The system recalculates and realigns the digital representation of airways based on observed LG positions, allowing the map to adapt to lung flexibility and movement during the procedure, thereby maintaining navigation accuracy throughout the entire airway tree.
2Ease of operation
If registration points are placed only in central lung areas, then the registration process is simple and quick, but navigation accuracy deteriorates in peripheral airways where it is most needed
Solution Approach 1:
The patent implements a feedback mechanism where the actual locatable guide path is continuously monitored and used to correct and refine the digital map representation. The system compares the observed LG positions with the predicted positions from the digital map, identifies deviations, and automatically adjusts the map to reduce errors. This feedback loop progressively improves navigation accuracy throughout the airway tree, including peripheral regions, without requiring additional manual registration points.
3Ease of operation
If the locatable guide is manually advanced without adaptive path adjustment, then the operation is simple, but the LG appears to drift outside airways and guidance becomes inadequate
Solution Approach 1:
The patent enables the navigation system to self-correct and self-adjust by automatically detecting deviations of the locatable guide from the expected path and dynamically updating the digital map accordingly. The system performs self-validation by checking whether the LG remains within airway boundaries and self-corrects by adjusting the digital representation to match actual anatomical conditions, thereby maintaining reliable guidance throughout the procedure without requiring constant manual intervention.
Data Source
AI summary
A method for using an assembled three-dimensional image to construct a three-dimensional model for determining a path through a lumen network to a target. The three-dimensional model is automatically registered to an actual location of a probe by tracking and recording the positions of the probe and continually adjusting the registration between the model and a display of the probe position. The registration algorithm becomes dynamic (elastic) as the probe approaches smaller lumens in the periphery of the network where movement has a bigger impact on the registration between the model and the probe display.