Session Item

Poster discussion 2: CNS
Poster discussions
Clinical
SunCHECK Machine, an automated QA software solution: A centres 5 year experience evaluation
Greg Martin, United Kingdom
PO-1720

Abstract

SunCHECK Machine, an automated QA software solution: A centres 5 year experience evaluation
Authors:

Greg Martin1, Kevin Fogarty2,1, Daniel Egleston1, Laura Howard1, Martyn Gilmore1

1The Clatterbridge Cancer Centre, Medical Physics, Liverpool, United Kingdom; 2St. Lukes Radiation Oncology Network, Medical Physics, Dublin, Ireland

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Purpose or Objective

Evaluate the key stages of the SunCHECK Machine implementation, including; initial viability, sensitivity testing, commissioning, long term use with 9 linacs and time saving quantification.

Material and Methods

Initial viability: Qualitatively compare the results of automated and manual analysis for MLC based QA only.

Sensitivity testing: For a broader range of tests, performance was manually adjusted using independent methods to be outside of expected level/s. Tests included; picket fence (0.5mm leaf offset), VMAT QA – dose rate and gantry speed (DR+GS) first section 9.01% lower (all sections ideally equal) and leaf speed (LS) (first section 2.01% lower), Winston-Lutz (WL) (1mm X, Y and Z offset), flatness (1cm sheets of solid water introduced at G180), symmetry (beam symmetry steered 1%, 2% and 3% using StarcheckMAXI) and field size adjusted in 1mm increments from 26.7cm to 27.3cm.

Commissioning: QA patients were produced for each QA frequency, with a QA plan for each test (details of QA included in table attached), baselines acquired, SunCHECK analysis templates produced, baselines uploaded and automation tested.

Long term use: The software has been used on 9 linacs for 1 year and now evaluated.

Time saved: The time taken to complete QA measurements and analysis using legacy and SunCHECK Machine was compared (details in table).

Results

Initial viability: A qualitative comparison of automated and manually analysed results showed good agreement and demonstrated a time saving benefit.

Sensitivity testing: Picket fence leaf offset measured with SunCEHCK Machine 0.58mm (0.5mm expected). VMAT QA – DR+GS first section measured 10.6% lower (9.01% expected), LS measured 2.1% lower (expected 2.01%). Flatness (variance definition) 2.5% (0cm solid water), 2.8% (1cm), 3.0%(2cm), 3.3% (3cm). The measured mean change in symmetry (normalised point difference definition) 0.88% (expected 1%). Field size, mean difference from expected 0.03mm. WL mean measured offset in X, Y, Z 0.81mm (1mm expected).

Commissioning: The process described was successful, although bugs were identified and reported. QA templates cannot easily be secured once set up. Although templates can be copied, they lose association, meaning future changes need to be made to all templates.

Long Term use: For 12 months the platform has successfully completed all QA across 9 linacs, >95% without intervention. Troubleshooting guides were produced for routine issues e.g. smooth profiles, adjust image registration, etc. SunCHECK Machine has enabled quantitative analysis of imaging tests where previous qualitative analysis was used.

Time Saved: SunCHECK machine has saved 22hours and 43mins, per linac, per year. (Details in table)

Conclusion

The platform provided significant efficiency and quality benefits to the department. The simplifications allow technicians to acquire and manage the QA, rather than physicists.