TH-A-9A-02: BEST IN PHYSICS (THERAPY) - 4D IMRT Planning Using Highly- Parallelizable Particle Swarm Optimization

Journal Article · Sun Jun 15 04:00:00 EDT 2014 · Medical Physics

DOI:https://doi.org/10.1118/1.4889572· OSTI ID:22409815

Modiri, A; Gu, X; Sawant, A ^[1]

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1. UT Southwestern Medical Center, Dallas, TX (United States)

Purpose: We present a particle swarm optimization (PSO)-based 4D IMRT planning technique designed for dynamic MLC tracking delivery to lung tumors. The key idea is to utilize the temporal dimension as an additional degree of freedom rather than a constraint in order to achieve improved sparing of organs at risk (OARs). Methods: The target and normal structures were manually contoured on each of the ten phases of a 4DCT scan acquired from a lung SBRT patient who exhibited 1.5cm tumor motion despite the use of abdominal compression. Corresponding ten IMRT plans were generated using the Eclipse treatment planning system. These plans served as initial guess solutions for the PSO algorithm. Fluence weights were optimized over the entire solution space i.e., 10 phases × 12 beams × 166 control points. The size of the solution space motivated our choice of PSO, which is a highly parallelizable stochastic global optimization technique that is well-suited for such large problems. A summed fluence map was created using an in-house B-spline deformable image registration. Each plan was compared with a corresponding, internal target volume (ITV)-based IMRT plan. Results: The PSO 4D IMRT plan yielded comparable PTV coverage and significantly higher dose—sparing for parallel and serial OARs compared to the ITV-based plan. The dose-sparing achieved via PSO-4DIMRT was: lung Dmean = 28%; lung V20 = 90%; spinal cord Dmax = 23%; esophagus Dmax = 31%; heart Dmax = 51%; heart Dmean = 64%. Conclusion: Truly 4D IMRT that uses the temporal dimension as an additional degree of freedom can achieve significant dose sparing of serial and parallel OARs. Given the large solution space, PSO represents an attractive, parallelizable tool to achieve globally optimal solutions for such problems. This work was supported through funding from the National Institutes of Health and Varian Medical Systems. Amit Sawant has research funding from Varian Medical Systems, VisionRT Ltd. and Elekta.

• OSTI ID: 22409815
• Journal Information: Medical Physics, Journal Name: Medical Physics Journal Issue: 6 Vol. 41; ISSN 0094-2405; ISSN MPHYA6
• Country of Publication: United States
• Language: English

Related Subjects

60 APPLIED LIFE SCIENCES
DEGREES OF FREEDOM
ESOPHAGUS
LUNGS
MATHEMATICAL SOLUTIONS
NEOPLASMS
OPTIMIZATION
PLANNING
RADIATION DOSES
RADIOTHERAPY
SPINAL CORD
STOCHASTIC PROCESSES