Do we need Monte Carlo treatment planning for linac based radiosurgery? A case study

Area of Science:

• Medical Physics
• Radiation Oncology
• Computational Dosimetry

Background:

• Conventional dose calculation algorithms in radiation therapy have limitations, particularly in accounting for lateral radiation transport.
• Accurate dosimetric data for small beams, crucial for stereotactic radiosurgery (SRS), are difficult to obtain, impacting conventional algorithm accuracy.
• Monte Carlo (MC) treatment planning offers a potentially more accurate alternative for SRS dose calculations.

Observation:

• This study investigated MC treatment planning using the OMEGA code system for SRS in two clinical cases with different collimator sizes and lesion locations.
• Dose distributions from MC plans were compared against a conventional algorithm based on Tissue Maximum Ratio (TMR)/Off Axis Ratio (OAR) formalism.
• The conventional algorithm showed accurate relative dose distributions compared to MC calculations, with minor absolute dose overestimations at the isocenter.

Findings:

• Without inhomogeneity correction, the conventional algorithm provided accurate relative dose distributions for SRS.
• Absolute dose overestimation by the conventional algorithm was 1.5% and 2.6% for the studied cases.
• Inhomogeneity correction using the ratio of TMRs significantly reduced overestimation without altering relative dose distributions.

Implications:

• Conventional dose algorithms are deemed sufficient for stereotactic radiosurgery treatment planning.
• Monte Carlo-based treatment planning for SRS may be unwarranted given the accuracy of conventional methods with appropriate corrections.
• Further validation of conventional algorithms with inhomogeneity corrections in SRS is supported by these findings.