PTV margin determination in conformal SRT of intracranial lesions

The planning target volume (PTV) includes the clinical target volume (CTV) to be irradiated and a margin to account for uncertainties in the treatment process. Uncertainties in miniature multileaf collimator (mMLC) leaf positioning, CT scanner spatial localization, CT‐MRI image fusion spatial localization, and Gill‐Thomas‐Cosman (GTC) relocatable head frame repositioning were quantified for the purpose of determining a minimum PTV margin that still delivers a satisfactory CTV dose. The measured uncertainties were then incorporated into a simple Monte Carlo calculation for evaluation of various margin and fraction combinations. Satisfactory CTV dosimetric criteria were selected to be a minimum CTV dose of 95% of the PTV dose and at least 95% of the CTV receiving 100% of the PTV dose. The measured uncertainties were assumed to be Gaussian distributions. Systematic errors were added linearly and random errors were added in quadrature assuming no correlation to arrive at the total combined error. The Monte Carlo simulation written for this work examined the distribution of cumulative dose volume histograms for a large patient population using various margin and fraction combinations to determine the smallest margin required to meet the established criteria. The program examined 5 and 30 fraction treatments, since those are the only fractionation schemes currently used at our institution. The fractionation schemes were evaluated using no margin, a margin of just the systematic component of the total uncertainty, and a margin of the systematic component plus one standard deviation of the total uncertainty. It was concluded that (i) a margin of the systematic error plus one standard deviation of the total uncertainty is the smallest PTV margin necessary to achieve the established CTV dose criteria, and (ii) it is necessary to determine the uncertainties introduced by the specific equipment and procedures used at each institution since the uncertainties may vary among locations. PACS number(s): 87.53.Kn, 87.53.Ly