Tumor-driven SRS VMAT planning: Regression models for intermediate and low dose spillage

Abstract

Purpose

Stereotactic radiosurgery (SRS) for brain metastases using volumetric modulated arc therapy (VMAT) is increasingly utilized. While high-dose conformity guidelines relative to tumor volume exist, recommendations for intermediate and low-dose regions remain undefined. This study explores tumor-specific characteristics and new dosimetric parameters to develop regression models for standardizing intracranial SRS planning.

Materials and Method

We introduce two dosimetric quantities: R_6Gy, the 6 Gy cloud volume ratio to the PTV, and %D_1cm, the maximum dose at 1 cm from the PTV relative to the prescribed dose. These, alongside R_50% and the volume of normal brain receiving 12 Gy (V_12Gy), were analyzed retrospectively in 290 VMAT SRS plans from 151 patients treated between January 2021 and September 2023. The data were stratified into single- and three- fraction arms. Statistical tests, including Spearman's rank correlation, and Normalized Mutual Information (NMI) evaluated relationships between dosimetric parameters, number of metastases (n), and total PTV volume, PTV_Total. Significant correlations were modeled using regression analysis.

Results

Strong correlations were found between PTV_Total and all dosimetric metrics in the single-fraction arm; weaker but significant correlations were noted in the three-fraction arm. Power-law regression best described R_50% and R_6Gy, while linear regressions best described %D_1cm and V_12Gy. Moderate monotonic correlations were observed between n and the dosimetric metrics.

Conclusion

This study proposes regression-based models for predicting dose spill based on tumor burden, total PTV volume and number of targets. These models provide a framework for model-based SRS planning, offering clinical physicists patient-specific guidance to improve consistency, optimize plan quality, and support future standardization efforts.