Convolution-based modified Clarkson integration (CMCI) for electron cutout factor calculation.

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Imaging

Background:

• Electron therapy utilizes sharp dose fall-off for shallow tumors.
• Custom cutouts are essential for shielding normal tissues during electron beam radiation.
• Accurate output factor determination is critical for monitor unit (MU) calculations in electron therapy, often requiring time-consuming manual measurements.

Purpose of the Study:

• To develop and validate an accurate and efficient computational model for predicting cutout output factors in electron therapy.
• To replace laborious and error-prone patient-specific output factor measurements.
• To improve the quality assurance process for electron beam treatments.

Main Methods:

• Developed a convolution-based modified Clarkson integration (CMCI) model using annular sectors for output factor estimation.
• Generated a 2D fluence distribution for calculating output factors at any point.
• Applied the CMCI model to 10 irregular cutouts for breast cancer patients across 6E, 9E, and 15E electron beams.

Main Results:

• The CMCI model demonstrated good agreement with chamber and film measurements, comparable to electron Monte Carlo (eMC) at nominal SSD.
• CMCI showed higher accuracy than eMC at extended SSDs, with significantly lower mean absolute errors.
• eMC calculations exhibited larger deviations, up to -9.28%, compared to measurements for low-energy beams at extended SSDs.

Conclusions:

• The CMCI model provides an accurate and efficient method for predicting electron therapy cutout output factors.
• CMCI is more accurate than eMC, particularly for low-energy beams and extended source-to-surface distances.
• This model can be effectively used for MU calculations and as a quality assurance tool in electron therapy.