Dynamic Needle Trajectory Planning for Respiratory Motion
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Solution Overview
Problem
Current needle insertion planning methods do not account for cyclical patient motion, such as breathing, leading to the need for continuous fluoroscopic imaging and significant radiation exposure during procedures.
Innovation Solution
A dynamic planning method that determines the expected patient motion on preoperative images and plans the needle trajectory to account for the movement of entry, target, and obstacle points throughout the motion cycle, allowing for reduced radiation exposure by limiting insertion to specific time frames with minimal curvature.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous fluoroscopic imaging is used during the procedure to account for patient motion, then the accuracy of needle insertion is improved, but radiation exposure to patient and medical staff increases significantly
Solution Approach 1:
The system performs preliminary action by acquiring multiple preoperative images at different time points during the breathing cycle before the procedure begins. These images are used to generate a 4D model that predicts patient motion throughout the cycle, allowing the trajectory to be planned in advance to account for expected motion without requiring continuous imaging during the procedure.
Solution Approach 2:
The system creates a computational model (4D model) that copies and represents the patient's breathing motion pattern based on preoperative imaging data. This model serves as a virtual representation of patient motion that can be used for trajectory planning and guidance without requiring actual continuous imaging during the procedure, thereby eliminating radiation exposure while maintaining accuracy.
2Stability of the object's composition
If patient respiration is stopped during image acquisition and needle insertion, then the position stability of target and obstacles is improved, but the procedure time increases and patient comfort decreases
Solution Approach 1:
The system applies dynamics by transitioning from static imaging to dynamic 4D imaging that captures patient motion throughout the breathing cycle. Multiple images are acquired at different time points during normal breathing, and these are combined to create a time-resolved model that accounts for motion without requiring the patient to hold their breath, thereby maintaining position stability while preserving natural respiratory function and reducing procedure time.
Solution Approach 2:
The system changes parameters by acquiring images at multiple time points throughout the breathing cycle rather than at a single static moment. This temporal parameter variation allows the system to capture the full range of motion and establish a predictive model of target and obstacle positions at any phase of the breathing cycle, eliminating the need for breath-holding while maintaining position stability.
3Device complexity
If a single static trajectory is planned based on initial image positions, then the planning complexity is reduced, but the trajectory may become unsafe or inaccurate due to patient motion during the procedure
Solution Approach 1:
The system performs preliminary action by acquiring multiple preoperative images at different time points during the breathing cycle before the procedure begins. These images are used to generate a 4D model that predicts patient motion throughout the cycle, allowing the trajectory to be planned in advance to account for expected motion without requiring continuous imaging during the procedure.
Solution Approach 2:
The system implements feedback by using the 4D model to continuously monitor and adjust the needle trajectory in real-time based on the patient's breathing phase. The system compares the actual breathing cycle phase with the predicted motion model and dynamically adjusts the trajectory to maintain safety and accuracy throughout the procedure.
Data Source
AI summary
A method of planning an image-guided interventional procedure to be performed on a patient, where expected motion of the patient, such as that of a breathing cycle, is determined on a sequence of preoperative images, and the procedure trajectory is planned accordingly. The method takes into account the initial positions of the interventional entry, the target region, and any obstructions or forbidden regions between the entry point and the target region, and uses object tracking methods of image processing on the preoperative images to determine how the positions of these three elements change relative to each other during the patient's motion cycle. The method may automatically search in at least some of the preoperative images taken at different temporal points of the motion cycle, for a path connecting the entry point with the target and avoiding the obstacles, which provides minimal lateral pressure on the patient's tissues.