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Dosimetric impact and detectability of multi-leaf collimator positioning errors on Varian Halcyon
Skylar S Gay1, Tucker J Netherton1,2, Carlos E Cardenas1
1Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Portal dosimetry effectively detects systematic multi-leaf collimator (MLC) errors in Varian Halcyon VMAT plans. Random MLC errors under ±5mm may go undetected, but portal dosimetry remains robust for quality assurance.
Area of Science:
- Medical Physics
- Radiation Oncology
- Radiotherapy Quality Assurance
Background:
- Accurate radiation delivery is crucial for effective cancer treatment.
- Multi-leaf collimator (MLC) positioning errors can compromise treatment plan integrity.
- Varian Halcyon linear accelerators are increasingly used for advanced radiotherapy techniques like VMAT.
Purpose of the Study:
- To assess the dosimetric impact of MLC positioning errors (random and systematic) on Varian Halcyon VMAT plans.
- To evaluate the efficacy of portal dosimetry in identifying clinically significant errors.
- To determine the correlation between portal dosimetry results and dose-volume histogram (DVH) metrics.
Main Methods:
- Introduced systematic and random MLC errors into 11 head and neck VMAT plans (99 total plans).
- Delivered plans on a Varian Halcyon and captured fluence using portal dosimetry.
- Compared DVH metrics of erroneous plans against baseline plans.
Main Results:
- Systematic MLC errors caused significant dosimetric changes, while random errors had a lesser impact.
- The magnitude of dosimetric changes correlated with the size of MLC errors.
- Portal dosimetry detected all systematic errors but struggled with random errors ≤±5mm.
- Following AAPM TG-218 recommendations optimized error detection.
- A moderate correlation was observed between normal tissue DVH metrics and portal dosimetry pass rates.
Conclusions:
- Portal dosimetry on the Varian Halcyon is a reliable tool for detecting MLC positioning errors in VMAT plans.
- Systematic MLC errors are more likely to cause clinically significant changes than random errors.
- Portal dosimetry QA can help prevent the delivery of inaccurate radiotherapy treatments.
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