Sensitivity evaluation of two commercial dosimeters in detecting Helical TomoTherapy treatment delivery errors.

Phys Med

Liverpool and Macarthur Cancer Therapy Centres and Ingham Institute, Sydney, NSW, Australia; Centre for Medical Radiation Physics, University of Wollongong, Wollongong, NSW, Australia; Institute of Medical Physics, School of Physics, University of Sydney, Sydney, NSW, Australia; South West Clinical School, University of New South Wales, Sydney, NSW, Australia. Electronic address:

Published: May 2017

Purpose: To assess the sensitivity of two commercial dosimetry systems in detecting Helical TomoTherapy (HT) delivery errors.

Method: Two commercial dosimeters i) MatriXX and ii) ArcCHECK® were considered. Ten retrospective nasopharynx HT patients were analysed. For each patient, error plans were created by independently introducing systematic offsets in: a) Jaw width error ±1, ±1.5 and ±2mm, b) Couch speed error ±2%, ±2.5, ±3% and ±4%, and c) MLC Leaf Open Time (MLCLOT) errors (3 separate MLC errors: either leaf 32 open or leaf 42 remains open during delivery, and 4% random reductions in MLCLOT). All error plans, along with the no error plan for each patient, were measured using both dosimeters in the same session. Gamma evaluation (3%/3mm) was applied to quantitatively compare the measured dose from each dosimeter to the treatment planning system. The error sensitivity was quantified as the rate of decrease in gamma pass rate.

Results: The gamma pass rate decreases with increase in error magnitude for both dosimeters. ArcCHECK was insensitive for couch speed error up to 2.5% and jaw width error up to -1.5mm while MatriXX was found to be insensitive to couch speed error up to 2% and couch speed up to -1mm. Both of the detectors show similar sensitivity to all the MLCLOT errors that were clinically relevant.

Conclusion: No statistically significant (p>0.05) differences exist in detecting the simulated delivery errors between MatriXX and ArcCHECK dosimeter systems for HT plans. Both dosimeters were able to pick up clinically relevant delivery errors.

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http://dx.doi.org/10.1016/j.ejmp.2017.04.011DOI Listing

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