Robotic CT-Guided Biopsy for Moving Lung Nodules
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Solution Overview
Problem
Current CT-guided needle biopsy systems face challenges in accurately targeting moving lung nodules due to respiratory motion, leading to decreased accuracy and increased procedure duration, particularly in patients who cannot hold their breath, resulting in higher complication rates and limited availability of skilled physicians.
Innovation Solution
An image-guided robotic needle biopsy system that acquires images of the moving target, generates a motion model, and determines an optimal needle advancing path based on the target's motion attributes, allowing for precise needle placement without requiring patients to hold their breath, using a combination of imaging units, processing units, and robotic manipulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If CT-guided needle biopsy is performed on moving lung nodules without motion compensation, then the procedure can be performed quickly, but the biopsy accuracy decreases due to respiratory motion
Solution Approach 1:
The system performs preliminary actions by acquiring multiple pre-operative CT images to generate a motion model of the lung nodule's respiratory movement pattern before the actual biopsy procedure. This motion model is then used to predict the nodule's position in real-time during the procedure, allowing the needle trajectory to be pre-planned to account for expected motion, thereby maintaining high biopsy accuracy without requiring prolonged procedure time.
Solution Approach 2:
The system implements feedback by continuously monitoring the patient's respiratory phase (through external markers or internal landmarks) and using this information to update the predicted nodule position in real-time. This feedback loop allows the system to adjust the needle targeting dynamically, compensating for respiratory motion and maintaining biopsy accuracy throughout the procedure without extending its duration.
2Measurement precision
If the patient is required to hold their breath during the procedure, then biopsy accuracy improves, but patient compliance becomes difficult and procedure complexity increases
Solution Approach 1:
The system applies self-service by using automatically acquired imaging data and computational algorithms to generate the motion model and predict nodule position without requiring active patient participation or breath-holding. The system independently processes the respiratory motion compensation, freeing the patient from the burden of maintaining specific breathing patterns while still achieving high needle placement accuracy.
Solution Approach 2:
The system embraces dynamics by modeling and adapting to the patient's natural respiratory motion patterns rather than attempting to freeze them. The motion model captures the dynamic characteristics of individual patient breathing, and the needle trajectory is dynamically adjusted based on real-time respiratory phase detection, allowing accurate biopsies to be performed during normal breathing without requiring patient compliance with breath-holding instructions.
3Reliability
If multiple needle passes are performed to ensure accurate sampling, then biopsy reliability improves, but the risk of complications such as pneumothorax and bleeding increases
Solution Approach 1:
The system performs preliminary action by generating a motion model from pre-operative CT images and using it to predict the lung nodule's position throughout the procedure. This allows for precise single-pass needle targeting, eliminating the need for multiple needle passes and thereby reducing complications while maintaining reliable tissue sampling.
Solution Approach 2:
The system replaces the mechanical trial-and-error approach of multiple needle passes with a computational approach using motion modeling and real-time position prediction. Instead of physically attempting multiple insertions to locate the moving target, the system uses algorithmic prediction to guide a single precise needle insertion, reducing mechanical trauma and complication risk while ensuring reliable sampling.
Data Source
AI summary
An image-guided system and method for performing needle biopsy on a moving lung nodule of a body is provided. CT images of the lung nodule are obtained to generate a motion model, based on which an optimal needle advancing path is determined. The motion of the lung nodule and the motion of a fiducial marker attached to the body are correlated. The motion of the fiducial marker is tracked and monitored by a camera to determine a position of the lung nodule based on the correlation. A time for advancing the needle is determined based on a motion attribute of the reference. The needle is advanced by a robotic needle manipulator at the predetermined time along the path to accomplish the needle placement.