Abstract
OBJECTIVE: This study addresses challenges in delivering high radiation doses and managing organ motion in Stereotactic Body Radiation Therapy (SBRT) for thoracic and abdominal cancer. It evaluates Varian's Real Time Position Management (RPM) system's infrared camera sensitivity during crucial Four-Dimensional computed tomography (4D-CT) scans for planning and treatment. The analysis includes CT simulator, LINAC (Novalis Tx and TrueBeam STx). This research enhances SBRT precision by offering insights into RPM and RGSC system performance across machines, impacting treatment planning and delivery optimization. METHODS: The QUASAR™ Respiratory Motion Assembly phantom is aligned with precision using lasers. It is configured with either six-dot reflective or four-dot lens marker blocks featuring a retroreflective marker placed on the phantom's surface. Motion is induced by adjusting the amplitude, and the camera position is finely tuned to monitor the marker's movements. This investigation entails variations in seconds per breath (SPB) within the Quasar breath platform, specifically at intervals of 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, and 5.0 seconds while maintaining a 1cm amplitude camera setting. RESULT: For TrueBeam-STx: Ensure SPB values are kept above 1.8 seconds for accurate replication. For Novalis-Tx: Stay within an SPB range of up to 2.0 seconds for reliable reproducibility. For CT Simulator: Optimal replication up to an SPB of 2.2 seconds; avoid SPB values below 1.8 seconds for reliable detection. CONCLUSION: Data for TrueBeam-STx, Novalis-Tx, and the CT simulator shows discrepancies in replicating the breathing cycle as Seconds Per Breath (SPB) decreases. Effective Infrared (IR) sensitivity is observed until SPB thresholds: 1.8s (TrueBeam-STx), 2.2s (Novalis-Tx), and 2.2s (CT simulator). We should consider values equal to or greater than the mentioned breathing periods. Variations in replicating breathing cycles signal challenges in planning and delivering treatments, especially with lower SPB values. These insights guide clinicians to adapt treatments based on machine-specific capabilities for accurate and reproducible outcomes.