Among the various IMRT techniques that have been proposed or implemented, IMAT, or intensity-modulated arc therapy, is one of the most promising approaches for achieving superior dose conformity with a minimized treatment time. However, due to the many degrees of freedom in IMAT planning, optimizing an IMAT plan is computationally difficult, and an effective method for IMAT planning is not yet available. Moreover, methods for IMAT (and other rotational delivery schemes) to handle breathing induced target motion are also lacking. The goal of this proposal is to develop a clinically practical IMAT planning system that allows tumor tracking and image guidance through a bioengineering research partnership (NIH PAR-04- 023). We hypothesize that by using advanced graph algorithmic techniques in computer science, we can develop a robust and effective IMAT planning software for both static and moving targets. A breathing synchronized delivery technique will ensure optimal treatment for all breathing phases in a breathing cycle.
The specific aims of this proposal are:
Specific Aim I : To assess the advantages and disadvantages of IMAT over other IMRT methods using the current IMAT planning tool, and to integrate our Monte-Carlo based dose calculation engine with IMAT planning.
Specific Aim II : To develop a 4D IMAT planning system and a breathing synchronized delivery mechanism under image guidance.
Specific Aim III : Verify clinical feasibility of the planning and delivery scheme developed in Aim II using a 4D phantom to ensure that the IMAT plans with breathing motion compensation can be delivered accurately using motion synchronized IMAT delivery scheme. We believe that the full use of 4D CT images to make a plan that ensures optimality at all breathing phases is a significant advancement of the existing art of radiotherapy. Successful achievement of the aforementioned project aims will provide planning and practical image guidance for the safe and efficient delivery of IMAT, and significantly improve cancer treatments.
|Betzel, Gregory T; Yi, Byong Yong; Niu, Ying et al. (2012) Is RapidArc more susceptible to delivery uncertainties than dynamic IMRT? Med Phys 39:5882-90|
|Yu, Cedric X; Tang, Grace (2011) Intensity-modulated arc therapy: principles, technologies and clinical implementation. Phys Med Biol 56:R31-54|
|Gui, Minzhi; Feng, Yuanming; Yi, Byongyong et al. (2010) Four-dimensional intensity-modulated radiation therapy planning for dynamic tracking using a direct aperture deformation (DAD) method. Med Phys 37:1966-75|
|Zhou, Bo; Yu, Cedric X; Chen, Danny Z et al. (2010) GPU-accelerated Monte Carlo convolution/superposition implementation for dose calculation. Med Phys 37:5593-603|
|Tang, Grace; Earl, Matthew A; Luan, Shuang et al. (2010) Comparing radiation treatments using intensity-modulated beams, multiple arcs, and single arcs. Int J Radiat Oncol Biol Phys 76:1554-62|
|Zhang, Jin; Yi, Byongyong; Lasio, Giovanni et al. (2009) Tomographic image via background subtraction using an x-ray projection image and a priori computed tomography. Med Phys 36:4433-9|
|Luan, Shuang; Swanson, Nathan; Chen, Zhe et al. (2009) Dynamic gamma knife radiosurgery. Phys Med Biol 54:1579-91|
|Tang, Grace; Earl, Matthew A; Yu, Cedric X (2009) Variable dose rate single-arc IMAT delivered with a constant dose rate and variable angular spacing. Phys Med Biol 54:6439-56|
|Wang, Chao; Luan, Shuang; Tang, Grace et al. (2008) Arc-modulated radiation therapy (AMRT): a single-arc form of intensity-modulated arc therapy. Phys Med Biol 53:6291-303|
|Luan, Shuang; Wang, Chao; Cao, Daliang et al. (2008) Leaf-sequencing for intensity-modulated arc therapy using graph algorithms. Med Phys 35:61-9|
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