open access
Empirical estimation of beam-on time for prostate cancer patients treated on Tomotherapy
open access
Abstract
Background and aim
This study proposed a method to estimate the beam-on time for prostate cancer patients treated on Tomotherapy when FW (field width), PF (pitch factor), modulation factor (MF) and treatment length (TL) were given.
Material and methods
The study was divided into two parts: building and verifying the model. To build a model, 160 treatment plans were created for 10 patients. The plans differed in combination of FW, PF and MF. For all plans a graph of beam-on time as a function of TL was created and a linear trend function was fitted. Equation for each trend line was determined and used in a correlation model. Finally, 62 plans verified the treatment time computation model – the real execution time was compared with our estimation and irradiation time calculated based on the equation provided by the manufacturer.
Results
A linear trend function was drawn and the coefficient of determination R2 and the Pearson correlation coefficient r were calculated for each of the 8 trend lines corresponding to the adequate treatment plan. An equation to correct the model was determined to estimate more accurately the beam-on time for different MFs. From 62 verification treatment plans, only 5 disagreed by more than 60[[ce:hsp sp="0.25"/]]s with the real time from the HT software. Whereas, for the equation provided by the manufacturer the discrepancy was observed in 16 cases.
Conclusions
Our study showed that the model can well predict the treatment time for a given TL, MF, FW and it can be used in clinical practice.
Abstract
Background and aim
This study proposed a method to estimate the beam-on time for prostate cancer patients treated on Tomotherapy when FW (field width), PF (pitch factor), modulation factor (MF) and treatment length (TL) were given.
Material and methods
The study was divided into two parts: building and verifying the model. To build a model, 160 treatment plans were created for 10 patients. The plans differed in combination of FW, PF and MF. For all plans a graph of beam-on time as a function of TL was created and a linear trend function was fitted. Equation for each trend line was determined and used in a correlation model. Finally, 62 plans verified the treatment time computation model – the real execution time was compared with our estimation and irradiation time calculated based on the equation provided by the manufacturer.
Results
A linear trend function was drawn and the coefficient of determination R2 and the Pearson correlation coefficient r were calculated for each of the 8 trend lines corresponding to the adequate treatment plan. An equation to correct the model was determined to estimate more accurately the beam-on time for different MFs. From 62 verification treatment plans, only 5 disagreed by more than 60[[ce:hsp sp="0.25"/]]s with the real time from the HT software. Whereas, for the equation provided by the manufacturer the discrepancy was observed in 16 cases.
Conclusions
Our study showed that the model can well predict the treatment time for a given TL, MF, FW and it can be used in clinical practice.
Keywords
Tomotherapy; Treatment planning; Treatment time; Prostate cancer; Radiotherapy


Title
Empirical estimation of beam-on time for prostate cancer patients treated on Tomotherapy
Journal
Reports of Practical Oncology and Radiotherapy
Issue
Pages
201-208
Published online
2013-07-01
DOI
10.1016/j.rpor.2012.12.005
Bibliographic record
Rep Pract Oncol Radiother 2013;18(4):201-208.
Keywords
Tomotherapy
Treatment planning
Treatment time
Prostate cancer
Radiotherapy
Authors
Małgorzata Skórska
Tomasz Piotrowski