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Operational Insights From the Longitudinal Analysis of a Linear Accelerator Machine Log
Jeremy D Hoisak1, Gwe-Ya G Kim1, Todd F Atwood1
1Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, USA.
Cureus
|July 9, 2021
Summary
This study analyzed linear accelerator (linac) faults over 30 months, finding the Varian Halcyon linac had fewer imaging and MLC faults than TrueBeam models. Insights will improve linac reliability and reduce clinical disruptions.
Area of Science:
- Medical Physics
- Radiation Oncology
- Health Systems Engineering
Background:
- Linear accelerators (linacs) are crucial for radiation therapy, but technical faults can disrupt clinical workflows.
- Cloud-based Machine Log systems offer a valuable tool for tracking linac performance and reliability.
- Understanding linac fault patterns is essential for optimizing quality assurance and minimizing downtime.
Purpose of the Study:
- To conduct a longitudinal analysis of technical faults in multiple linac models using a cloud-based Machine Log system.
- To derive operational insights into linac reliability, clinical utilization, and performance in a busy academic clinic.
- To identify trends in linac sub-system reliability based on age, design, clinical use, and operational demands.
Main Methods:
- Queried a cloud-based Machine Log system for linac type, fault counts, fault types, and downtime over 30 months.
- Obtained linac utilization data (fractions treated, monitor units delivered) from the record and verify system.
- Compared fault rates and types across two Varian TrueBeam, one Varian 21iX, and one Varian Halcyon linac.
Main Results:
- Over 30 months, 1234 faults were reported, including 153 "linac down" events.
- Varian TrueBeam linacs reported nearly twice as many imaging, MLC, and beam generation faults per fraction and MU compared to the Varian Halcyon.
- The Halcyon linac showed fewer beam generation/steering, accessory, and cooling faults but more computer/networking issues; it also reported fewer MLC faults despite its newer design.
Conclusions:
- Longitudinal analysis using a cloud-based Machine Log system provides valuable operational insights into linac performance and reliability.
- Identified trends in linac sub-system reliability are attributable to linac age, design, clinical application, or operational load.
- Results will inform the design of linac quality assurance schedules tailored to actual usage and observed reliability, aiming to reduce disruptions and enhance patient safety and efficiency.
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