A Smartphone-Based Motion Monitoring System for Surface Guided Radiation Therapy.

Area of Science:

• Medical Physics
• Radiation Oncology
• Biomedical Engineering

Background:

• Surface-guided radiation therapy (SGRT) enhances patient positioning and motion monitoring during radiation therapy, especially for deep-inspiratory breath-hold (DIBH) in left-sided breast cancer.
• High costs and complexity of current SGRT systems limit their adoption, particularly in resource-limited settings.

Purpose of the Study:

• To develop and validate a smartphone-based iOS SGRT application (iSGRT) utilizing Light-Detection-and-Ranging (LiDAR) for accurate, low-cost surface tracking in radiation therapy.

Main Methods:

• The iSGRT application was developed using Swift and Open3D on iOS, capturing 6-degrees-of-freedom (6DoF) motion for patient positioning and respiratory monitoring.
• Accuracy was assessed using static couch displacements on a Varian TrueBeam and dynamic motion with a QUASAR phantom. A healthy volunteer comparison with an SDX spirometry system during DIBH was also performed.

Main Results:

• iSGRT demonstrated high correlations (r² ≥ 0.995 translational, r² ≥ 0.975 rotational) with static couch movements and strong agreement (r² ≥ 0.963) with phantom motion.
• The system achieved a temporal resolution of 4-5 Hz, comparable to clinical SGRT. Breath-hold durations in a volunteer were nearly identical between iSGRT and SDX (0.03s difference).

Conclusions:

• The study demonstrates the feasibility of iSGRT as a viable, real-time respiratory motion monitoring system for radiation therapy.
• The iSGRT application offers accuracy comparable to clinical SGRT systems at a significantly reduced cost and complexity.
• This technology holds potential to increase SGRT accessibility, especially in underserved, resource-limited environments.