MO‐E‐BRA‐05: Clinical Issues Associated with the Use of Monte Carlo‐Based Prospective Planning for Lung SBRT and Spine SRS Patients

Purpose: To investigate the clinical issues associated with the use of Monte Carlo‐based prospective planning for lung SBRT and spine SRS patients. Methods: Experimental verification of the iPlan v.4.1 MC photon beam algorithm (BrainLab) was performed using film and ion‐chamber in water phantoms and solid‐water slabs containing bone and lung‐equivalent materials for a 6 MV photon beam from a Novalis linac. MC dose verification was performed for 5 spine and 7 lung patients using an anthropomorphic phantom. Treatment plans of prospectively treated patients were examined to investigate the influence of statistical uncertainties, MC‐based dose‐to‐water (Dw) and medium (Dm) and calculation speed. Results: Agreement between calculations and measurements in the water phantom verification tests was, on average, within 2%/1 mm (high dose/high gradient), and was within ±4%/2 mm in the heterogeneous slab geometries. For spine SRS, the agreement between PB and Dm calculations were within 4 % of IC measurements, however, the difference between MC_Dw and Dm was on average 9 %. For the lung SBRT tests the average difference between calculated PB doses and IC reading was 13%, and both MC calculations agreed within 1.5 % of measurements. The use of reduced uncertainty below 2% increases dose calculation time significantly but has an insignificant effect on the dose volume histograms (DVH). Conclusion: Prospective treatment planning with a well‐commissioned MC algorithm provides improved dose coverage and can be introduced for efficient calculations in the routine clinical setting. However, further investigation is warranted on issues such as dose‐to‐medium and water, the impact of statistical uncertainties on serial and parallel organs, and proper approaches for reliable dose measurements at small field sizes, under non‐equilibrium conditions. Acknowledgement: Supported in part by a grant from the NIH/NCI (R01CA106770). © 2010, American Association of Physicists in Medicine. All rights reserved.

Duke Scholars

Author Lei Ren Radiation Oncology