研究目的
To develop and evaluate a simple optical system for detecting and measuring patient external motion during radiotherapy treatments, aiming to improve accuracy in dose delivery by monitoring motion, alerting to out-of-tolerance movements, and recording trajectories for analysis.
研究成果
The developed optical system is accurate (better than 0.3 mm for small displacements), sensitive to low-amplitude motions (<0.5 mm), and capable of tracking high-speed movements (up to 11.5 cm/s). It is simple, affordable, and non-invasive, making it suitable for routine clinical use in radiotherapy to monitor patient motion, with potential applications in gating systems and other motion detection scenarios. Future work includes extending to more degrees of freedom and other medical fields.
研究不足
The system is sensitive to camera position changes, requiring recalibration if moved; it may have reduced accuracy for very high-speed motions beyond 11.5 cm/s or with low frame rates; relies on external surrogates which may not perfectly correlate with internal motion; and sticker deformation due to surface curvature can affect accuracy if not placed on flat anatomical positions.
1:Experimental Design and Method Selection:
The system uses two cameras to capture 2D images of points (black dots on white stickers) on a moving object, applying a geometric algorithm based on Tsai's work to reconstruct 3D positions from 2D projections. Calibration involves solving equations using known points.
2:Sample Selection and Data Sources:
Tests were conducted with phantoms (linear displacements, circular trajectories, oscillations) and 23 volunteer patients (breast, lung, bladder tumors) with 461 point trajectories.
3:List of Experimental Equipment and Materials:
Cameras (Intellisense CC 2330P, MediaWave Varifocal 27X), digital video recorder (X-Motion Premium 4), calibration phantom with aluminum structure and stickers, linac couch (Siemens ZXT), micrometer screws (Parker Hannifin Daedal), respiratory phantom (Anzai AZ-733V), in-house phantoms for oscillations, frame grabber card (DGF/MC4/PCIe), workstation (HP Z420), light meter (HIBOK 30), software (MATLAB, Python).
4:Experimental Procedures and Operational Workflow:
Calibration with phantom points, recording videos at 25 fps, image processing to track points with subpixel accuracy, real-time tracking with alerts for motion tolerances, data analysis including FFT and smoothing for motion separation.
5:Data Analysis Methods:
Statistical analysis of deviations, fitting to sine functions using Levenberg-Marquardt algorithm, calculation of percentiles and variances for patient motion studies.
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linac couch
ZXT
Siemens
To perform linear displacements for testing
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frame grabber card
DGF/MC4/PCIe
The Imaging Source
To grab real-time images for tracking
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camera
CC 2330P
Intellisense
To capture 2D images of points for motion tracking
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camera
Varifocal 27X
MediaWave
To capture 2D images of points for motion tracking
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digital video recorder
X-Motion Premium 4
Presntco
To record videos from cameras
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micrometer screw
Parker Hannifin Daedal
To measure small displacements with high precision
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respiratory phantom
AZ-733V
Anzai Medical
To simulate respiratory motion for testing
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workstation
Z420
HP
To control the frame grabber and run tracking software
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light meter
HIBOK 30
Tecno y Medida
To measure room illumination
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software
MATLAB 2008b
MathWorks
To implement algorithms for image processing and motion analysis
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software
Python
To implement algorithms for data fitting
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