An End-to-End Test for Adaptive Radiotherapy with Varian Hypersight CBCT Imaging System Using Radiochromic Film in a Rando Pelvis Phantom 📝

Author: Jameson T. Baker, Yijian Cao, Jenghwa Chang, Sean T Grace, Lyu Huang, Jian Liu, Echezona Simon Obi, Anurag Sharma 👨‍🔬

Affiliation: Northwell, Hofstra University Medical Physics Program 🌍

Abstract:

Purpose:
To validate the end-to-end dosimetrical accuracy of Varian HyperSight CBCT for adaptive radiotherapy (ART), from simulation to dose delivery, using radiochromic film dosimetry in a Rando pelvis phantom.
Methods:
The Advanced Electron Density Phantom (Sun Nuclear, Melbourne, FL), which provides a full scatter condition in CBCT scans, was scanned using all clinical CBCTp protocols available on HyperSight. CT number-to-electron density (CT-ED) curves were derived and compared with those from a Siemens Somatom Edge Plus CT simulator. A Rando pelvis phantom was scanned with both imaging systems, and identical treatment plans were calculated. Radiochromic EBT-4 films were placed between phantom slabs to measure dose profiles across the PTV and surrounding regions. The measurements were repeated with smaller films positioned centrally in the PTV to evaluate absolute dose accuracy. Dose distributions from HyperSight CBCT-based calculations were compared with CT simulator-based calculations and film measurements using gamma analysis.
Results:
The CT-ED curve from HyperSight CBCT images closely matched that from a CT simulator. A 3D gamma analysis comparing dose distributions calculated with HyperSight and CT simulator images yielded a 98.2% passing rate using 1mm/1% and 10% threshold criteria. Large-film measurements showed dose profiles consistent with planned distributions, with >95% passing rates at 2 mm/4% gamma criteria for two films and >95% at 2 mm/6% for the third in the 2D gamma analysis. Absolute doses measured with small films within the PTV differed from planned doses by no more than 3%.
Conclusion:
Varian HyperSight CBCT images were successfully validated for simulation and treatment planning, supporting its integration into clinical ART workflows .

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