Strategies to optimize stereotactic radiosurgery plans for brain tumors with volumetric-modulated arc therapy

Prescription practice in SRS plans for brain tumors differs significantly for different modalities. In this retrospective study, the strategies to optimize SRS plans for brain tumors with volumetric arc therapy (VMAT) were presented.

Fifty clinically treated cases were stratified by the maximum target size into two groups (≥ 2 cm in 25 cases and <2 cm but ≥1 cm in 25 cases), which were optimized using traditional LINAC MLC-based approaches with the average prescription isodose line (P-IDL) of (91.4 ± 0.6)%. Four to five plans have been created for each case with variation of the P-IDL from 65% to 90%. The optimization strategies to select an optimal P-IDL, to use tuning structures within the target and beyond as well as to use NTO (normal tissue objectives), were applied to all new plans.

The optimal P-IDL was found to be around 75%. After applying the new optimization strategies with an average P-IDL of 74.8%, the mean modified gradient index (mGI) and V12 were reduced by 25% and 35%, respectively for both groups. The Paddick conformity index (PCI) was averagely improved by 8%. The average homogeneity index (HI) and focal index (FI) were increased by 22% and 50%, respectively. The mGI was inversely proportional to the PTV volumes. The shape of the dose distribution in target was also changed from concave to convex. The comparison of PCI with historical data from other institutes and modalities shows that the plans in this study have the best conformity near the target.

With the new optimization strategies for VMAT SRS plan of brain tumor more conformal plans in both high and intermediate dose region (~50% of the PD) were created, in which the dose in the core of the target was notably increased while V12 and mGI were significantly decreased, and PCI was improved. The mGI was inversely proportional to the PTV volumes. The optimal P-IDL is around 75%. The average PCI is the best in this study compared with the published historical data. These strategies are applicable to treatment planning for multiple brain and liver tumors where sparing the tissue peripheral to the target is critical.