Direct reconstruction of the source intensity distribution of a clinical linear accelerator using a maximum...

Area of Science:

• Medical Physics
• Radiation Oncology
• Imaging and Simulation

Background:

• Accurate modeling of small radiation fields from clinical linear accelerators is crucial for precise dose delivery in radiation therapy.
• Current methods for determining source intensity distribution often require specialized equipment and complex clinical implementation.
• Direct source characterization is essential for improving the accuracy of beam modeling, especially in small fields used in advanced treatment techniques.

Purpose of the Study:

• To develop and validate a novel, clinically feasible method for direct determination of the source intensity distribution in clinical linear accelerators.
• To utilize a maximum-likelihood expectation-maximization (MLEM) algorithm with a simple experimental setup for source reconstruction.
• To assess the accuracy and reliability of the MLEM-based source reconstruction technique for small field beam modeling.

Main Methods:

• Employed a maximum-likelihood expectation-maximization (MLEM) algorithm for iterative source reconstruction.
• Utilized photon fluence profile measurements obtained from film dosimetry in air with a thin foil build-up.
• Minimized beam parameter variability and scatter by using the smallest field sizes and accounting for collimator jaw positions.

Main Results:

• The MLEM method accurately reconstructed electron source sizes with an accuracy better than 0.12 mm FWHM in simulations.
• Experimental validation on a Varian Novalis Tx showed excellent agreement with commissioned Monte Carlo models (0.03-0.11 mm FWHM accuracy).
• Evaluated uncertainties, identifying collimator jaw positioning as the dominant factor affecting reconstructed source distribution.

Conclusions:

• The MLEM-based approach provides a practical and accurate method for direct source intensity distribution determination in clinical linear accelerators.
• This technique simplifies experimental requirements, making it more accessible for routine clinical use and improving small field beam modeling.
• The findings contribute to enhanced accuracy in radiation therapy planning and delivery, particularly for treatments involving small radiation fields.