Highlights
- •We analyze the impact of different optimization methods in the charged particle therapy scanning paths.
- •We access the possibility to deflect the beam out of the extraction line during irradiation.
- •Beam deflection reduces the number of unnecessary particles delivered.
- •Beam deflections increases treatment time and number of wasted particles.
Abstract
Purpose
To compare different algorithms to optimize the scanning path in charged particle
therapy with quasidiscrete scanning. We implemented a Hybrid Genetic Algorithm with
Heuristics (HyGA) and combined it with clustering techniques. The performance was
compared to Simulated Annealing (SA) and to commercially available treatment planning
system (TPS).
Methods
Performance and clinical implications were assessed using data from 10 patients treated
at CNAO (Centro Nazionale di Adroterapia Oncologica). Clinical treatments are performed
relying on beam deflection, avoiding irradiation for transitions between adjacent
spots larger than 2 cm. A clustering method was implemented with HyGA (HyGA_Cl), which
assumes beam deflection during transition between clusters. Clinical performance was
determined as the total number of particles delivered during spot transitions and
the number of particles wasted due to beam deflection. Results were compared to scan
paths obtained with CNAO TPS.
Results
SA and HyGA produced on average shorter paths compared to the currently available
TPS. This did not result in a reduction of transit particles, due to the concomitant
effect of beam deflection out of the extraction line. HyGA_Cl achieved 2% average
reduction in transit particles when compared to CNAO TPS. As a drawback, wasted particles
increased, due to more frequent use of beam deflection. Both the SA and HyGA algorithms
reduced the number of wasted particles.
Conclusion
SA and HyGA proved to be the most cost-effective methods in reducing wasted particles,
with benefits in terms of shorter scan paths. A decrease in transit particles delivered
with beam deflection can be achieved using HyGA_Cl.
Keywords
Abbreviations:
CNAO (Centro Nazionale di Adroterapia Oncologica), HyGA (Hybrid Genetic Algorithm with Heuristics), HyGA_Cl (Hybrid Genetic Algorithm with Heuristics and Clustering), SA (Simulated Annealing), TPS (Treatment plan system), TSP (Traveling salesman problem)To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Physica Medica: European Journal of Medical PhysicsAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Radiological use of fast protons.Radiology. 1946; : 487-491
- Magnetic scanning system for heavy ion therapy.Nucl Instrum Methods Phys Res A. 1993; 330: 296-305
- Demonstration of scan path optimization in proton therapy.Med Phys. 2007; 34: 3457-3464
- Particle beam application: on the way to optimum dose conformity.Sci Part Ther Med Solution. 2005; : 80-83
- A study on repainting strategies for treating moderately moving targets with proton pencil beam scanning at the new gantry 2 at psi.Med Biol. 2010; 55: 5103-5121
- Particle radiosurgery: a new frontier of physics in medicine.Phys Med. 2014; 30: 535-538
- In the context of radiosurgery – pros and cons of rescanning as a solution for treating moving targets with scanned particle beams.Phys Med. 2014; 30: 551-554
- Heuristic optimization of the scanning path of particle therapy beams.Med Phys. 2009; 36: 2043-2051
- The status of CNAO.Eur Phys J Plus. 2011; 126
- Numerical recipes: the art of scientific computing.Cambridge University Press, 2007: 549-555
- A fast tsp solver using GA on JAVA.in: Information Processing Society of Japan 46th Natl Conv. 1993: 1-6
- The traveling salesman problem: a computational study.Princeton University Press, 2006: 104
- Matlab 2010b.(Natick)2000
- Optimization for fast-scanning irradiation in particle therapy.Med Phys. 2007; 34: 1653-1669
Article info
Publication history
Published online: January 20, 2015
Accepted:
January 3,
2015
Received in revised form:
January 2,
2015
Received:
May 20,
2014
Identification
Copyright
© 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Inc. All rights reserved.
