Multivariate log file analysis for multi-leaf collimator failure prediction in radiotherapy delivery.

ABSTRACT:

Background and purpose

Motor failure in multi-leaf collimators (MLC) is a common reason for unscheduled accelerator maintenance, disrupting the workflow of a radiotherapy treatment centre. Predicting MLC replacement needs ahead of time would allow for proactive maintenance scheduling, reducing the impact MLC replacement has on treatment workflow. We propose a multivariate approach to analysis of trajectory log data, which can be used to predict upcoming MLC replacement needs.

Materials and methods

Trajectory log files from two accelerators, spanning six and seven months respectively, have been collected and analysed. The average error in each of the parameters for each log file was calculated and used for further analysis. A performance index (PI) was generated by applying m

SUBMITTER: Wojtasik AM 

PROVIDER: S-EPMC7807670 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature