Deformable motion reconstruction for scanned proton beam therapy using on-line x-ray imaging

Area of Science:

• Medical Physics
• Radiotherapy
• Image-guided therapy

Background:

• Organ motion poses challenges for dynamic radiotherapy, especially proton therapy.
• Magnetic deflection in proton therapy allows for precise tumor motion tracking.
• Current imaging systems may not capture sufficient 3D motion data.

Purpose of the Study:

• To develop and validate a method for estimating 3D deformable motion from sparse surrogate data using a monoscopic imaging system.
• To assess the feasibility of on-line motion reconstruction for dynamic radiotherapy.
• To evaluate the predictive capability of diaphragm motion for liver motion.

Main Methods:

• Subject-specific motion models were built using principal component analysis (PCA) from 4D MRI data.
• Simulated 4D CT datasets were generated, and time-resolved digitally reconstructed radiographs (DRRs) were calculated.
• Surrogate motions (fiducial markers, diaphragm) were used to predict 3D liver motion.
• 4D dose calculations were performed to verify prediction accuracy.

Main Results:

• Median (max) prediction errors of 2.63 (5.67) mm were achieved using fiducial markers.
• Diaphragm motion proved to be a good predictor for respiratory liver motion.
• Dose differences exceeding 5% occurred in a small percentage of points (median 3.61%, max 15.13%).
• Prediction accuracy was similar for monoscopic and stereoscopic systems.

Conclusions:

• On-line deformable motion reconstruction from sparse surrogate motions is feasible with monoscopic imaging.
• Diaphragm motion is a viable surrogate for predicting liver motion, potentially reducing reliance on fiducial markers.
• The developed method shows promise for improving the accuracy and safety of dynamic radiotherapy.