SU-F-J-148: A Collapsed Cone Algorithm Can Be Used for Quality Assurance for Monaco Treatment Plans for the MR-Linac - Hackett, S; van Asselen, B; Feist, G; Pencea, S; Akhiat, H; Wolthaus, J; Kotte, A; Bol, G; Lagendijk, J; Raaymakers, B (Medical physics (Lancaster), 2016)
Purpose: Treatment plans for the MR-linac, calculated in Monaco v5.19, include direct simulation of the effects of the 1.5T B0-field. We tested the feasibility of using a collapsed-cone (CC) algorithm in Oncentra, which does not account for effects of the B0-field, as a fast online, independent 3D check of dose calculations. Methods: Treatment plans for six patients were generated in Monaco with a 6 MV FFF beam and the B0-field. All plans were recalculated with a CC model of the same beam. Plans for the same patients were also generated in Monaco without the B0-field. The mean dose (Dmean) and doses to 10% (D10%) and 90% (D90%) of the volume were determined, as percentages of the prescribed dose, for target volumes and OARs in each calculated dose distribution. Student’s t-tests between paired parameters from Monaco plans and corresponding CC calculations were performed. Results: Figure 1 shows an example of the difference between dose distributions calculated in Monaco, with the B0-field, and the CC algorithm. Figure 2 shows distributions of (absolute) difference between parameters for Monaco plans, with the B0-field, and CC calculations. The Dmean and D90% values for the CTVs and PTVs were significantly different, but differences in dose distributions arose predominantly at the edges of the target volumes. Inclusion of the B0-field had little effect on agreement of the Dmean values, as illustrated by Figure 3, nor on agreement of the D10% and D90% values. Conclusion: Dose distributions recalculated with a CC algorithm show good agreement with those calculated with Monaco, for plans both with and without the B0-field, indicating that the CC algorithm could be used to check online treatment planning for the MRlinac. Agreement for a wider range of treatment sites, and the feasibility of using the γ-test as a simple pass/fail criterion, will be investigated.