CT-Guided Needle Insertion Path Planning With Breath Timing
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Solution Overview
Problem
Surgical procedures using CT images for visceral needle insertion face inaccuracies due to reliance on surgeon experience, leading to multiple image exposures and increased radiation risk, and are affected by patient breathing, increasing surgical risk.
Innovation Solution
A computer-assisted needle insertion method utilizing machine learning models to suggest a needle insertion path and period, guided by CT images and breath signals, ensuring accurate needle placement and synchronization with normal breathing cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If surgeon estimates needle insertion path based on experience, then surgical procedure can be performed, but needle insertion accuracy is insufficient and multiple CT images are required
Solution Approach 1:
The system performs preliminary planning of the needle insertion path using CT images before the actual surgery. The processing unit calculates the optimal insertion path, target coordinates, and insertion angle in advance, allowing the surgeon to follow a pre-determined accurate path rather than relying on experience during the procedure.
Solution Approach 2:
The patent introduces a computer-based processing unit and display device as intermediaries between the CT images and the surgeon's needle insertion action. The system processes CT image data to generate visual guidance (target coordinates, insertion paths, angles) that mediates the surgeon's decision-making, improving accuracy without requiring multiple manual CT scans.
2Measurement precision
If multiple CT images are taken for calibration, then needle insertion accuracy improves, but radiation dose to patient increases
Solution Approach 1:
The system performs comprehensive path planning using CT images taken before surgery. By calculating the optimal insertion path, target coordinates, and verification angles in advance, the system eliminates the need for additional calibration CT scans during the procedure, thereby reducing cumulative radiation exposure while maintaining accuracy.
Solution Approach 2:
The display device provides visual feedback to the surgeon showing the pre-calculated insertion path, target coordinates, and insertion angle. This feedback mechanism allows the surgeon to align the needle with the planned path without requiring additional CT images for verification, reducing radiation dose while ensuring accuracy through real-time visual guidance.
3Reliability
If surgeon performs needle insertion without breath synchronization, then procedure is simpler, but surgical risk increases due to breathing movement
Solution Approach 1:
The system performs preliminary calculation of the needle insertion path considering the patient's breath state. By determining the optimal insertion timing and path before the actual insertion, the system accounts for breathing movement in advance, allowing safe insertion during appropriate breath phases without requiring complex real-time intervention.
Solution Approach 2:
The display device provides periodic visual guidance to the surgeon regarding breath phases and insertion timing. The system monitors breath cycles and provides feedback at appropriate intervals, enabling the surgeon to synchronize needle insertion with safe breath periods, thereby improving safety through rhythm-based guidance rather than continuous complex control.
4Measurement precision
If computer-assisted path planning is implemented, then needle insertion accuracy improves, but system complexity increases
Solution Approach 1:
The processing unit performs multiple functions using a single integrated system: it processes CT image data, calculates the needle insertion path, determines target coordinates, computes insertion angles, and generates visual guidance for the display device. This multi-functionality reduces the need for separate specialized devices, managing system complexity while maintaining high accuracy.
Solution Approach 2:
The patent introduces a computer-based processing unit and display device as intermediaries between the CT images and the surgeon's needle insertion action. The system processes CT image data to generate visual guidance (target coordinates, insertion paths, angles) that mediates the surgeon's decision-making, improving accuracy without requiring multiple manual CT scans.
Data Source
AI summary
A computer-assisted needle insertion method is provided. The computer-assisted needle insertion method includes the following steps. A first machine learning model and a second machine learning model are obtained. A computed tomography image and a needle insertion path are obtained, a suggested needle insertion path is generated according to the first machine learning model, the computed tomography image, and the needle insertion path, and the needle is instructed to approach a needle insertion point on a skin of a target. The needle insertion point is located on the suggested needle insertion path. A breath signal of the target is obtained, and whether a future breath state of the target is normal is estimated according to the second machine learning model and the breath signal. A suggested needle insertion period is output according to the breath signal in response to determining that the future breath state is normal.