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Plan Quality Comparison Between VMAT and DCA for Single Lesion Brain SRS

Q Shang*, K Koch , D Wiant , B Sintay , T Hayes , N Koch , H Liu , Cone Health Cancer Center, Greensboro, NC

Presentations

(Sunday, 7/14/2019)  

Room: ePoster Forums

Purpose: DCA is preferred for Linac-based single small lesion brain SRS due to its low MLC complexity and high delivery accuracy. But it usually involves a large amount of manual edition of MLC thus needs more planner intervention and longer planning time. This work investigates whether VMAT photon optimization (PO) algorithm could provide similar plan quality while reducing human planning effort.

Methods: 11 patients with a total of 14 brain lesions ranging from 14-30mm previously treated for 14-20Gy with single fraction SRS were studied retrospectively. Clinically all the plans were generated in iPlan (v4.5.5) using 3-4 non-coplanar dynamic conformal arcs (DCA). Each plan was optimized using VMAT in Eclipse (v15.5.11) with the same beam arrangement to achieve the same PTV coverage and similar dose conformity as the DCA plan. Optimization was performed using PO algorithm with high modulation control to minimize the MLC complexity. DCA plans were recalculated in Eclipse and both DCA and VMAT plans were normalized to 99.5% PTV coverage for a fair comparison. Plan quality was evaluated by modulation complexity score (MCS), Nakamura’s conformity index (NCI), MU, and normal tissue volume encompassed by 12Gy and 6Gy (V12 and V6).

Results: No significant changes were observed for NCI, V12 and V6 between VMAT and DCA plans. The maximum difference in NCI is 0.06. The maximum difference in V12 and V6 is 1.5cc and 3.0cc, respectively. The average MU is (3300+/-450) for DCA and (3464+/-548) for VMAT. The average MCS is (0.55+/-0.03) for DCA and (0.62+/-0.09) for VMAT.

Conclusion: VMAT optimization using PO algorithm with high modulation control offers comparable plan quality as the DCA technique for brain SRS while reducing planner intervention and planning time. More efficient treatment planning can be achieved when the VMAT delivery is streamlined with RapidPlan-based auto-planning.

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