Flexible Catheter Motion Mapping for Distal End Deviation Alerts
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Solution Overview
Problem
In minimally invasive medical procedures, tools often experience unexpected motion due to factors like tool characteristics, patient anatomy, and curvature, which can lead to adverse contacts with tissues such as vessel dissection or perforation, especially when live medical imaging fails to detect these motions.
Innovation Solution
The implementation of predictive motion mapping for flexible devices, which uses a system comprising a control system with a medical imaging system, motion detector, workstation, robot, and artificial intelligence controller to predict the motion of interventional medical devices at the distal end based on motion at the proximal end, and alert for unintended behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If fluoroscopy imaging is used to guide the procedure, then real-time visualization is provided, but motion of the tool outside the field of view cannot be detected
Solution Approach 1:
The system transitions from two-dimensional fluoroscopy imaging to three-dimensional motion tracking by incorporating shape sensing technology that measures spatial coordinates along the entire length of the catheter, enabling detection of motion in dimensions outside the fluoroscopy field of view
Solution Approach 2:
A predictive motion mapping model acts as an intermediary between the limited fluoroscopy field of view and the complete tool motion, using machine learning to infer and predict tool behavior in regions not directly visible to the imaging system
2Length of moving object
If the tool is made long and thin to access distant anatomy, then reach is improved, but unexpected motion and buckling increase
Solution Approach 1:
The system implements continuous feedback by monitoring the actual three-dimensional shape and position of the catheter along its entire length, comparing predicted motion with actual motion, and providing real-time alerts when unexpected deviations occur, enabling corrective action before adverse events
Solution Approach 2:
The patent replaces reliance on mechanical tool stiffness with an intelligent monitoring and prediction system that uses shape sensing and machine learning to compensate for the inherent flexibility and motion variability of long, thin catheters
3Ease of operation
If motion at the proximal end is increased to improve操控性, then control authority is improved, but unintended motion at the distal end increases
Solution Approach 1:
The predictive motion mapping system provides real-time feedback by comparing the actual distal end position with the predicted position based on proximal end motion, alerting operators when unintended motion occurs, thereby enabling precise control despite increased manipulation at the proximal end
Data Source
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AI summary
A controller (150) for interventional medical devices includes a memory (151) and a processor (152). The memory (151) stores instructions that the processor (152) executes. When the instructions are executed, the instructions cause the controller (150) to obtain at least one location of a distal end of the interventional medical device (101), identify motion at a proximal end of an interventional medical device (101), apply a first trained artificial intelligence to the motion at the proximal end of the interventional medical device (101) and to the at least one location of the distal end of the interventional medical device (101), and predict motion along the interventional medical device (101) towards a distal end of the interventional medical device (101) during the interventional medical procedure. The controller (150) also obtains images of the distal end of the interventional medical device (101) from a medical imaging system (120) to determine when the actual motion deviates from the predicted motion.