Predictive gamma passing rate for three-dimensional dose verification with finite detector elements via improved dose...

Area of Science:

• Medical Physics
• Radiation Oncology
• Dosimetry

Background:

• Accurate prediction of gamma passing rate (GPR) is crucial for quality assurance in intensity-modulated radiation therapy (IMRT).
• Existing methods may face limitations in predicting GPR for complex 3D dose distributions.
• The dose uncertainty potential (DUP) accumulation model offers a potential avenue for improved prediction.

Purpose of the Study:

• To develop and validate a novel method for predicting the 3D GPR using the DUP accumulation model.
• To extend the DUP model to account for attenuation in 3D dose distributions measured by the Delta4 system.

Main Methods:

• Sixty head-and-neck IMRT plans were created and measured using the Delta4 system.
• Planar DUP (pDUP) was generated from aperture shapes and projected to 3D, considering attenuation.
• An analytical learning model (LM) was developed and optimized to predict GPR based on DUP, compensating for limited detector statistics.

Main Results:

• The DUP-based prediction method was successfully extended to 3D.
• The coefficient in the learning model was optimized based on tolerance levels.
• The standard deviation of predicted GPR was 2.3%, 4.1%, and 6.7% for 3%/3mm, 3%/2mm, and 2%/2mm tolerances, respectively.

Conclusions:

• The DUP-based method provides a viable approach for predicting 3D GPR in IMRT.
• Introducing DUP attenuation and an optimized analytical LM enhances prediction accuracy.
• Further improvements in the LM and inclusion of other metrics are expected to increase GPR prediction precision.