Lung Navigation Data Fusion for Respiratory-Aware 3D Localization
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Solution Overview
Problem
Existing lung treatment systems fail to account for changes in lung structure and respiratory cycle during procedures, relying on pre-operative data that may be outdated and not reflective of real-time conditions.
Innovation Solution
A method that integrates pre-operative image data with real-time CBCT scans during procedures to generate and update a 3D model of the patient's lungs, tracking tools and targets in real-time, and adjusting for respiratory cycle changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-operative CT scan data is used for navigation, then the system complexity is reduced and ease of operation is improved, but the measurement precision and reliability deteriorate due to outdated anatomical information
Solution Approach 1:
The system performs preliminary actions by acquiring pre-operative CT scan data to create an initial 3D model and plan the navigation pathway. This preliminary preparation establishes the baseline navigation plan before the actual procedure, allowing surgeons to plan ahead while still enabling real-time updates during the procedure to maintain precision.
Solution Approach 2:
The navigation system transitions from a static pre-operative model to a dynamic system that continuously updates anatomical information during the procedure. Real-time imaging and tracking systems dynamically adjust the 3D model to reflect actual anatomical positions and respiratory movements, maintaining measurement precision while preserving ease of operation through automated updates.
2Reliability
If real-time CBCT scanning is performed during the procedure, then the reliability and measurement precision are improved, but the loss of time and productivity deteriorate due to additional scanning and processing
Solution Approach 1:
The system maintains continuity of useful action by performing real-time CBCT scanning and automated image processing throughout the procedure without significant interruptions. The continuous acquisition and processing of anatomical data ensure that the navigation system always has current information, improving reliability while minimizing time loss through seamless integration into the surgical workflow.
Solution Approach 2:
The system implements feedback mechanisms where real-time CBCT scan results are automatically processed and fed back into the navigation system to update the 3D model and adjust the navigation pathway. This closed-loop feedback ensures that anatomical changes are immediately accounted for, maintaining reliability while reducing manual intervention time through automated processing.
3Measurement precision
If multiple data sources are integrated into the navigation system, then the reliability and measurement precision are improved, but the device complexity increases
Solution Approach 1:
The system merges multiple data sources including pre-operative CT scans, real-time CBCT imaging, electromagnetic tracking data, and respiratory monitoring into a unified navigation platform. By combining these diverse data streams into a single integrated system, the patent achieves high measurement precision while managing complexity through centralized data fusion and a unified user interface that presents consolidated information to the surgeon.
Solution Approach 2:
The navigation system acts as an intermediary that receives, processes, and harmonizes data from multiple independent sources. The system includes intermediate processing layers that standardize and integrate data from different modalities (CT, CBCT, electromagnetic sensors, respiratory monitors) into a common coordinate system and format, reducing the complexity burden of multi-source integration while maintaining high measurement precision.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Provides accurate and dynamic visualization of tools and targets within the lungs, ensuring precise navigation and treatment by aligning pre-procedural data with real-time anatomical changes.
Implementation Method 1
determine a location of a tool based on an electromagnetic (EM) sensor included in the tool as the tool is navigated within the patient's chest
Implementation Method 2
receiving cone beam computed tomography (CBCT) image data of a portion of the patient's chest based on an intra-procedural CBCT scan
Data Source
AI summary
Disclosed are systems, devices, and methods for navigating a tool inside a luminal network. An exemplary method includes receiving image data of a patient's chest, identifying the patient's lungs, determining locations of a luminal network in the patient's lungs, identifying a target location in the patient's lungs, generating a pathway to the target location, generating a three-dimensional (3D) model of the patient's lungs, the 3D model showing the luminal network in the patient's lungs and the pathway to the target location, determining a location of a tool based on an electromagnetic (EM) sensor included in the tool as the tool is navigated within the patient's chest, displaying a view of the 3D model showing the determined location of the tool, receiving cone beam computed tomography (CBCT) image data of the patient's chest, updating the 3D model based on the CBCT image data, and displaying a view of the updated 3D model.