3D Organ Motion Estimation for Radiotherapy through Material Point Method-Driven Extrapolation of Multiple Orthogonal...

Area of Science:

• Medical Imaging
• Radiotherapy Physics
• Computational Biomechanics

Background:

• Accurate tracking of organ motion during radiotherapy is essential for precise radiation delivery.
• Existing methods often struggle with motion estimation in all three dimensions, especially for complex or non-periodic movements.
• Real-time magnetic resonance imaging (MRI) offers potential for dynamic motion monitoring.

Purpose of the Study:

• To develop and validate a novel method for estimating 3D organ motion during radiotherapy using real-time MRI data.
• To improve the accuracy of motion estimation compared to conventional techniques.
• To assess the method's applicability for organs with complex motion, such as the pancreas.

Main Methods:

• Integration of real-time MRI data from axial, coronal, and sagittal planes.
• Application of vertical extrapolation techniques combined with material point method (MPM) simulations.
• Generation of comprehensive 3D displacement fields for organ motion estimation.

Main Results:

• Validation through phantom experiments and human participant trials.
• Achieved Dice scores up to 0.748 in human trials, indicating improved accuracy.
• Demonstrated a 22.6% reduction in estimated error (minimum 5.18 mm), approaching clinical acceptability.

Conclusions:

• The proposed method effectively estimates 3D organ motion from real-time MRI, outperforming conventional approaches.
• It shows particular promise for organs with complex, non-periodic motion patterns, enhancing radiotherapy precision.
• The findings suggest a significant step towards more accurate and effective image-guided radiotherapy.