Sensor-Guided Medical Navigation for Anatomical Divergence Alerts
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Solution Overview
Problem
Existing minimally invasive medical procedures face challenges in accurately mapping and navigating medical tools due to divergence between pre-operative images and real-time anatomical structures, particularly in pulmonary airways, leading to difficulties in locating target anatomical structures.
Innovation Solution
Systems and methods for determining and mitigating divergence by generating alerts and predicting the actual location of anatomical structures using sensor data and anatomic models, comparing real-time positional data with planned paths, and updating navigation based on divergence detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Force
If pre-operative images are used to guide medical device navigation, then the procedure can be planned in advance, but the anatomical structures may diverge from their expected locations during the procedure
Solution Approach 1:
The system continuously compares real-time sensor data from the medical device with the pre-operative anatomical model, detects divergence between expected and actual anatomical structures, and provides feedback to update the navigation plan. This closed-loop feedback mechanism resolves the contradiction by maintaining planning capability while adapting to actual anatomical variations.
Solution Approach 2:
The navigation system transitions from a static pre-operative plan to a dynamic adaptive plan that updates in real-time based on sensor data. The system dynamically adjusts the virtual path and anatomical model to reflect actual anatomical conditions, resolving the contradiction between advance planning and real-time accuracy.
2Ease of operation
If the medical device follows the pre-planned virtual path, then the procedure can proceed systematically, but the device may miss the actual anatomical target due to anatomical variation
Solution Approach 1:
The system provides continuous feedback by comparing device position on the virtual path with real-time sensor data, detecting when anatomical structures diverge from expected locations, and alerting the operator to adjust the path. This maintains systematic procedure progression while ensuring reliable target acquisition.
Solution Approach 2:
The system introduces an intermediary computational layer that processes sensor data and updates the virtual path accordingly. This intermediary layer acts as a mediator between the pre-planned path and actual anatomy, resolving the contradiction by systematically adapting the path to match real anatomical conditions.
3Measurement precision
If real-time sensor data is continuously monitored and compared with the anatomical model, then divergence can be detected, but the system complexity increases
Solution Approach 1:
The system performs self-service by automatically comparing sensor data with the anatomical model, computing divergence, and updating the virtual path without requiring manual intervention. This automation reduces operational complexity while maintaining high measurement precision for anatomical structure location.
Solution Approach 2:
The anatomical model and virtual path are prepared in advance from pre-operative images, establishing a baseline for comparison. This preliminary action reduces real-time computational complexity by having the reference framework ready before the procedure begins, while still enabling precise real-time divergence detection.
Data Source
AI summary
A system for determining divergence of an anatomic region from an anatomic model of the anatomic region may comprise a medical device and a computing device that causes the system to perform operations comprising receiving sensor data acquired while the medical device is inserted within an anatomic region of the patient and after the medical device has been registered to an anatomic model of the anatomic region. The anatomic model may include a model anatomic passageway and a target anatomic structure. The operations may include comparing the sensor data from the medical device to the model anatomic passageway, producing a divergence classifier for a divergence of the anatomic region from the anatomic model, and updating a virtual location of the target anatomic structure when the divergence classifier exceeds a threshold. The updated virtual location may be based on the sensor data corresponding to a distal portion of the medical device.