Highlights
- •Optimal complexity metric for predicting plan deliverability with our equipment.
- •Effective PSQA workload reduction using complexity metric.
- •Further PSQA workload reduction after optimization of the MLC modelling.
Abstract
Introduction
Many complexity metrics characterize modulated plans. First, this study aimed at identify
the optimal complexity metrics to reduce workload associated to patient-specific quality
assurance (PSQA) for our equipment and processes. Second, it intended to optimize
our MLC modelling to improve measurement and calculation agreement with expectation
of further reducing PSQA workload.
Methods
Correlation and sensitivity at specificity equals to 1 were evaluated for PSQA results
and different complexity metrics. Thresholds to stop PSQA were determined. After validation
of the optimal complexity metric and threshold for our equipment and process, the
MLC modelling was reviewed with a recently published methodology. This method is based
on measurements with a Farmer-type ionization chamber of synchronous and asynchronous
sweeping gap plans. Effect on the PSQA results and the identified threshold was investigated.
Results
In our center, the most appropriate complexity metric for reducing our PSQA workload
was the Modulation Complexity Score for VMAT (MCSv). The optimization of the MLC modelling
significantly reduced the number of controlled plans, specifically for one of our
two Varian Clinac. Any plan with a MCSv >= 0.34 is treated without PSQA.
Conclusion
This study rationalized and reduced our PSQA workload by approximately 30%. It is
a continuing work with new TPS, machine or PSQA equipment. It encourages centers to
re-evaluate their MLC modelling as well as assess the benefit of complexity metrics
to streamline their PSQA workflow. An easier access, at least for reporting, at best
for optimizing plans, into the TPS would be beneficial for the community.
Keywords
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Article info
Publication history
Published online: February 24, 2023
Accepted:
February 13,
2023
Received in revised form:
January 16,
2023
Received:
September 15,
2022
Identification
Copyright
© 2023 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.
