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Evaluation of Lung and Liver Tumor Dose Coverage Treated With the CyberKnife Synchrony System With Consideration of Measured Tracking Errors

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Abstract Background/Aim: Lung and liver tumor dose coverage was evaluated for the CyberKnife synchrony respiratory tracking system (SRTS) with consideration of the motion tracking accuracy measured for motion patterns of… Click to show full abstract

Abstract Background/Aim: Lung and liver tumor dose coverage was evaluated for the CyberKnife synchrony respiratory tracking system (SRTS) with consideration of the motion tracking accuracy measured for motion patterns of individual patients. Patients and Methods: Seven treatment plans of six cases treated with the SRTS were evaluated. The motion phantom was moved with the motion data derived from the treatment log files. A laser emitted from the linac head to the moving phantom block was recorded with a webcam, and the tracking accuracy was evaluated. The dose volume histogram (DVH) of planning target volume (PTV) and gross tumor volume (GTV) were calculated by a pencil beam algorithm with shifting the beams with Gaussian random numbers mimicking the measured tracking errors. Results: The tracking errors measured with the motion phantom in the lateral direction were within ±2 mm for 90% of beam-on time. The tracking errors in the longitudinal direction were within ±3.0 mm and ±1.1 mm for 90% and 50% of beam-on time, respectively. Although one case showed a decrease in the dose covering 95% of PTV (D95%) by 1.8%, the change in the dose covering 99% of GTV (D99%) was within 1%. Conclusion: This study evaluated the motion tracking errors of the SRTS by a motion phantom moved with the patients’ respiration signal, and the impact of the tracking errors on the target coverage was calculated. Even for respiratory patterns with large maximum tracking errors, sufficient GTV coverage is achievable if the beam is accurately delivered for high percentage of beam-on time.

Keywords: lung liver; beam; coverage; motion; tracking errors; tumor

Journal Title: AntiCancer Research
Year Published: 2022

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