Intensity modulated radiation therapy has been shown to improve radiotherapy dose distributions when applied to lung treatments, especially if the delivery can be registered to the patient's breathing cycle. However, many technical issues associated with breathing-registered IMRT treatment planning have not yet been addressed, and comparisons between potential planning and delivery approaches are lacking. The primary goal of this project is to determine the tradeoffs between increased planning and delivery complexity vs. improvements in cumulative patient dose distributions and the expected impact on treatment outcomes. In an interdisciplinary collaboration, a shared cross-platform toolset, techniques, and test data sets will be developed and eventually publicly archived for use by other researchers. Within this framework, planning techniques to simulate a range of potential clinical options, from simple to complex, will be developed, including: simple margins, accounting for tumor motion in a statistical way, gating, and fully synchronizing IMRT delivery with breathing-phase. It is hypothesized that a significant fraction of simulated lung patients (who cannot achieve breath-hold techniques) will have a predicted outcome benefit from the use of breathing-registered planning and delivery.
In Specific Aim SA #1 (4-D optimization), temporo-spatial (""""""""4-D"""""""") IMRT planning and optimization methods for all relevant delivery techniques will be developed. In SA #2 (Management of uncertainties and daily variations), those methods will be generalized to explicitly account for uncertainties and day-to-day variations. In SA #3 (Clinical impact), the potential impact of the techniques in terms of likely dosimetric and outcome improvements will be estimated for a statistically significant cohort of simulated patient plans. This research will provide, firstly, guidance for understanding the potential outcomes impact of 4-D radiotherapy treatments; secondly, robust solutions to challenging 4-D treatment planning problems; and thirdly, shared data and software tools for other researchers in the area of 4-D planning. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA118200-01A2
Application #
7318498
Study Section
Radiation Therapeutics and Biology Study Section (RTB)
Program Officer
Deye, James
Project Start
2007-07-01
Project End
2012-05-31
Budget Start
2007-07-01
Budget End
2008-05-31
Support Year
1
Fiscal Year
2007
Total Cost
$333,640
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Salari, Ehsan; Unkelbach, Jan (2013) A column-generation-based method for multi-criteria direct aperture optimization. Phys Med Biol 58:621-39
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Yang, Deshan; Brame, Scott; El Naqa, Issam et al. (2011) Technical note: DIRART--A software suite for deformable image registration and adaptive radiotherapy research. Med Phys 38:67-77
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Nohadani, Omid; Seco, Joao; Bortfeld, Thomas (2010) Motion management with phase-adapted 4D-optimization. Phys Med Biol 55:5189-202
Bortfeld, Thomas (2010) The number of beams in IMRT--theoretical investigations and implications for single-arc IMRT. Phys Med Biol 55:83-97
Nohadani, Omid; Seco, Joao; Martin, Benjamin C et al. (2009) Dosimetry robustness with stochastic optimization. Phys Med Biol 54:3421-32
Vrancic, Christian; Trofimov, Alexei; Chan, Timothy C Y et al. (2009) Experimental evaluation of a robust optimization method for IMRT of moving targets. Phys Med Biol 54:2901-14
Unkelbach, Jan; Bortfeld, Thomas; Martin, Benjamin C et al. (2009) Reducing the sensitivity of IMPT treatment plans to setup errors and range uncertainties via probabilistic treatment planning. Med Phys 36:149-63
Bortfeld, Thomas; Webb, Steve (2009) Single-Arc IMRT? Phys Med Biol 54:N9-20

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