51. Tomotherapy treatment site specific planning using statistical process control
- Author
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Jamie Trapp, Diana Binny, Craig M. Lancaster, Tanya Kairn, Mikel Byrne, and Scott Crowe
- Subjects
Quality Control ,medicine.medical_specialty ,medicine.medical_treatment ,Statistics as Topic ,Biophysics ,General Physics and Astronomy ,Tomotherapy ,030218 nuclear medicine & medical imaging ,03 medical and health sciences ,0302 clinical medicine ,Region specific ,Neoplasms ,Range (statistics) ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Medical physics ,Head and neck ,business.industry ,Radiotherapy Planning, Computer-Assisted ,General Medicine ,Statistical process control ,Modulation factor ,030220 oncology & carcinogenesis ,Cohort ,Radiotherapy, Intensity-Modulated ,business ,Quality assurance - Abstract
Background This study investigated planned MLC distribution and treatment region specific plan parameters to recommend optimal delivery parameters based on statistical process techniques. Methods A cohort of 28 head and neck, 19 pelvic and 23 brain pre-treatment plans were delivered on a helical tomotherapy system using 2.5 cm field width. Parameters such as gantry period, leaf open time (LOT), actual modulation factor, LOT sonogram, treatment duration and couch travel were investigated to derive optimal range for plans that passed acceptable delivery quality assurance. The results were compared against vendor recommendations and previous publications. Results No correlation was observed between vendor recommended gantry period and percentage of minimum leaf open times. The range of gantry period (min–max) observed was 16–21 s for head and neck, 15–22 s for pelvis and 13–18 s for brain plans respectively. It was also noted that the highest percentage (average ( X - ) ± SD) of leaf open times for a minimum time of 100 ms was seen for brain plans (53.9 ± 9.2%) compared to its corresponding head and neck (34.5 ± 4.2%) and pelvic (32.0 ± 9.4%) plans respectively. Conclusions We have proposed that treatment site specific delivery parameters be used during planning that are based on the treatment centre and have detailed recommendations and limitations for the studied cohort. This may enable to improve efficiency of treatment deliveries by reducing inaccuracies in MLC distribution.
- Published
- 2018