Evaluating the Accuracy of Varian Identify Surface-Guidance System for High Precision Treatment Delivery and Motion Management
Abstract
Purpose
Surface-guided radiation therapy (SGRT) is increasingly used for high-precision patient setup and intrafraction motion management in radiotherapy clinics, including DIBH workflows. Respiratory signals acquired at simulation may be generated using different technologies and software than those at treatment, which can complicate the transfer of breath-hold parameters. This study investigates the ability of IDENTIFY to accurately measure breath-hold amplitude using phantom-based experiments and evaluates the uncertainty introduced within a workflow designed to translate respiratory signals from simulation to treatment.
Methods
A gating phantom is programmed to deliver free-breathing signals (Amp = 7.5 mm) with intermittent 15-s breath-holds at clinically relevant amplitudes (1 - 2 cm). Signals are captured at simulation using Varian RGSC. Setup accuracy of IDENTIFY is evaluated through CBCT repositioning. Respiratory traces are captured on IDENTIFY and compared to absolute programmed amplitudes to assess accuracy and RGSC to assess discrepancies. Gating window accuracy is assessed using breath hold amplitudes at window thresholds.
Results
IDENTIFY setup accuracy is within 1 mm in any orthogonal axis and within 1° in any rotational plane. IDENTIFY-measured breath-hold amplitudes demonstrate excellent agreement with programmed values (Pearson r = 0.99), with mean amplitude differences within 0.2% (max 0.04 mm). In contrast, RGSC systematically underestimates programmed amplitudes by ~12%. Preliminary gating window tests demonstrate consistent triggering at defined amplitude thresholds.
Conclusion
These preliminary results indicate that IDENTIFY provides highly accurate and reproducible measurements of breath-hold amplitude under controlled conditions, while RGSC exhibits a predictable systematic bias. Quantified uncertainties in setup and signal measurement are on the order of millimeters and fractions of a percent, respectively. Ongoing work focuses on formal uncertainty propagation across the full cross-system workflow and validation under more complex motion scenarios. This study represents an initial step toward defining a robust and quantitatively characterized DIBH transfer framework between simulation and treatment platforms.