Improved swarm intelligence solution in large scale radiation therapy inverse planning

Arezoo Modiri; Xuejun Gu; Aaron Hagan; Amit Sawant

doi:10.1109/GLBC.2015.7158300

Improved swarm intelligence solution in large scale radiation therapy inverse planning

Arezoo Modiri, Xuejun Gu, Aaron Hagan, Amit Sawant

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

This study employs particle swarm optimization to solve the non-convex inverse problem of 4D stereotactic body radiation therapy planning, targeting toxicity reduction, for a right lower lobe lung tumor with motion range of 1.5cm. A novel approach is introduced to reduce the swarm search space. 90 aperture-weights are optimized using both conventional and improved PSO algorithms over 5 optimization runs per method. It is shown that, on average, the improved PSO-based plan reduces the maximum dose to heart, spinal cord and esophagus by 43%, as compared to the conventional PSO, while swarm population is cut to half.

Original language	English (US)
Title of host publication	2015 IEEE Great Lakes Biomedical Conference, GLBC 2015 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479917921
DOIs	https://doi.org/10.1109/GLBC.2015.7158300
State	Published - Jul 14 2015
Event	36th IEEE Great Lakes Biomedical Conference, GLBC 2015 - Milwaukee, United States Duration: May 14 2015 → May 17 2015

Publication series

Name	2015 IEEE Great Lakes Biomedical Conference, GLBC 2015 - Proceedings

Other

Other	36th IEEE Great Lakes Biomedical Conference, GLBC 2015
Country/Territory	United States
City	Milwaukee
Period	5/14/15 → 5/17/15

Keywords

Optimization
Radiation therapy
stochastic

ASJC Scopus subject areas

Biotechnology
Civil and Structural Engineering

Access to Document

10.1109/GLBC.2015.7158300

Cite this

Modiri, A., Gu, X., Hagan, A., & Sawant, A. (2015). Improved swarm intelligence solution in large scale radiation therapy inverse planning. In 2015 IEEE Great Lakes Biomedical Conference, GLBC 2015 - Proceedings Article 7158300 (2015 IEEE Great Lakes Biomedical Conference, GLBC 2015 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLBC.2015.7158300

Improved swarm intelligence solution in large scale radiation therapy inverse planning. / Modiri, Arezoo; Gu, Xuejun; Hagan, Aaron et al.
2015 IEEE Great Lakes Biomedical Conference, GLBC 2015 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. 7158300 (2015 IEEE Great Lakes Biomedical Conference, GLBC 2015 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Modiri, A, Gu, X, Hagan, A & Sawant, A 2015, Improved swarm intelligence solution in large scale radiation therapy inverse planning. in 2015 IEEE Great Lakes Biomedical Conference, GLBC 2015 - Proceedings., 7158300, 2015 IEEE Great Lakes Biomedical Conference, GLBC 2015 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 36th IEEE Great Lakes Biomedical Conference, GLBC 2015, Milwaukee, United States, 5/14/15. https://doi.org/10.1109/GLBC.2015.7158300

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title = "Improved swarm intelligence solution in large scale radiation therapy inverse planning",

abstract = "This study employs particle swarm optimization to solve the non-convex inverse problem of 4D stereotactic body radiation therapy planning, targeting toxicity reduction, for a right lower lobe lung tumor with motion range of 1.5cm. A novel approach is introduced to reduce the swarm search space. 90 aperture-weights are optimized using both conventional and improved PSO algorithms over 5 optimization runs per method. It is shown that, on average, the improved PSO-based plan reduces the maximum dose to heart, spinal cord and esophagus by 43%, as compared to the conventional PSO, while swarm population is cut to half.",

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N2 - This study employs particle swarm optimization to solve the non-convex inverse problem of 4D stereotactic body radiation therapy planning, targeting toxicity reduction, for a right lower lobe lung tumor with motion range of 1.5cm. A novel approach is introduced to reduce the swarm search space. 90 aperture-weights are optimized using both conventional and improved PSO algorithms over 5 optimization runs per method. It is shown that, on average, the improved PSO-based plan reduces the maximum dose to heart, spinal cord and esophagus by 43%, as compared to the conventional PSO, while swarm population is cut to half.

AB - This study employs particle swarm optimization to solve the non-convex inverse problem of 4D stereotactic body radiation therapy planning, targeting toxicity reduction, for a right lower lobe lung tumor with motion range of 1.5cm. A novel approach is introduced to reduce the swarm search space. 90 aperture-weights are optimized using both conventional and improved PSO algorithms over 5 optimization runs per method. It is shown that, on average, the improved PSO-based plan reduces the maximum dose to heart, spinal cord and esophagus by 43%, as compared to the conventional PSO, while swarm population is cut to half.

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Improved swarm intelligence solution in large scale radiation therapy inverse planning

Abstract

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Other

Keywords

ASJC Scopus subject areas

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