title: Monte Carlo based IMRT dose verification using MLC log files and R/V outputs.
abstract: Conventional IMRT dose verification using film and ion chamber measurements is useful but limited with respect to the actual dose distribution received by the patient. The Monte Carlo simulation has been introduced as an independent dose verification tool for IMRT using the patient CT data and MLC leaf sequence files, which validates the dose calculation accuracy but not the plan delivery accuracy. In this work, we propose a Monte Carlo based IMRT dose verification method that reconstructs the patient dose distribution using the patient CT, actual beam data based on the information from the record and verify system (R/V), and the MLC log files obtained during dose delivery that record the MLC leaf positions and MUs delivered. Comparing the Monte Carlo dose calculation with the original IMRT plan using these data simultaneously validates the accuracy of both the IMRT dose calculation and beam delivery. Such log file based Monte Carlo simulations are expected to be employed as a useful and efficient IMRT QA modality to validate the dose delivered to the patient. We have run Monte Carlo simulations for eight IMRT prostate plans using this method and the results for the target dose were consistent with the original CORVUS treatment plans to within 3.0% and 2.0% with and without heterogeneity corrections in the dose calculation. However, significant dose deviations in nearby critical structures have been observed. The results showed that up to 9.0% of the bladder dose and up to 38.0% of the rectum dose, to which leaf position errors were found to contribute <2%, were underestimated by the CORVUS treatment planning system. The concept of average leaf position error has been defined to analyze MLC leaf position errors for an IMRT plan. A linear correlation between the target dose error and the average position error has been found based on log file based Monte Carlo simulations, showing that an average position error of 0.2 mm can result in a target dose error of about 1.0%.
authors.affiliation: Department of Radiation Oncology, Fox Chase Cancer Center, Philadelphia, Pennsylvania 19111, USA. wei.luo@fccc.edu
authors.forename: Wei
authors.initials: W
authors.lastname: Luo
authors.forename: Jinsheng
authors.initials: J
authors.lastname: Li
authors.forename: Robert A
authors.initials: RA
authors.lastname: Price
authors.forename: Lili
authors.initials: L
authors.lastname: Chen
authors.forename: Jie
authors.initials: J
authors.lastname: Yang
authors.forename: Jiajin
authors.initials: J
authors.lastname: Fan
authors.forename: Zuoqun
authors.initials: Z
authors.lastname: Chen
authors.forename: Shawn
authors.initials: S
authors.lastname: McNeeley
authors.forename: Xiu
authors.initials: X
authors.lastname: Xu
authors.forename: Chang-Ming
authors.initials: CM
authors.lastname: Ma
mesh_terms: D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004307:Dose-Response Relationship, Radiation; D006801:Humans; D008297:Male; D009010:Monte Carlo Method; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011874:Radiometry / Q000379:methods*; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*; D015203:Reproducibility of Results; D012984:Software