AutoLock: a semiautomated system for radiotherapy treatment plan quality control.

A semiautomated system for radiotherapy treatment plan quality control (QC), named AutoLock, is presented. AutoLock is designed to augment treatment plan QC by automatically checking aspects of treatment plans that are well suited to computational evaluation, whilst summarizing more subjective aspects in the form of a checklist. The treatment plan must pass all automated checks and all checklist items must be acknowledged by the planner as correct before the plan is finalized. Thus AutoLock uniquely integrates automated treatment plan QC, an electronic checklist, and plan finalization. In addition to reducing the potential for the propagation of errors, the integration of AutoLock into the plan finalization workflow has improved efficiency at our center. Detailed audit data are presented, demonstrating that the treatment plan QC rejection rate fell by around a third following the clinical introduction of AutoLock.

Simulation of realistic linac motion improves the accuracy of a Monte Carlo based VMAT plan QA system.

PURPOSE: To investigate the use of a software-based pre-treatment QA system for VMAT, which incorporates realistic linac motion during delivery. METHODS: A beam model was produced using the GATE platform for GEANT4 Monte Carlo dose calculations. Initially validated against static measurements, the model was then integrated with a VMAT delivery emulator, which reads plan files and generates a set of dynamic delivery instructions analogous to the linac control system. Monte Carlo simulations were compared to measurements on dosimetric phantoms for prostate and head and neck VMAT plans. Comparisons were made between calculations using fixed control points, and simulations of continuous motion utilising the emulator. For routine use, the model was incorporated into an automated pre-treatment QA system. RESULTS: The model showed better agreement with measurements when incorporating linac motion: mean gamma pass (Γ<1) over 5 prostate plans was 100.0% at 3%/3mm and 97.4% at 2%/2mm when compared to measurement. For the head and neck plans, delivered to the anatomical phantom, gamma passes were 99.4% at 4%/4mm and 94.94% at 3%/3mm. For example simulations within patient CT data, gamma passes were observed which are within our centre's tolerance for pre-treatment QA. CONCLUSIONS: Through comparison to phantom measurements, it was found that the incorporation of a realistic linac motion improves the accuracy of the model compared to the simulation of fixed control points. The ability to accurately calculate dose as a second check of the planning system, and determine realistic delivery characteristics, may allow for the reduction of machine-based pre-treatment plan QA for VMAT.