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Scan path optimization with/without clustering for active beam delivery in charged particle therapy.

Marta F Dias1, Marco Riboldi2, Joao Seco3

  • 1Department of Physics, Faculty of Sciences, University of Lisbon, Lisbon 1749, Portugal; Laboratório de Instrumentação e Física de Partículas, Lisbon 1749, Portugal; Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan 20133, Italy.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)
|January 25, 2015
PubMed
Summary

Optimizing scanning paths in charged particle therapy is crucial. Hybrid Genetic Algorithm with Heuristics (HyGA) and Simulated Annealing (SA) reduce wasted particles, while HyGA with clustering (HyGA_Cl) decreases transit particles.

Keywords:
Optimization algorithmsPath lengthScan pathTransit particlesWasted particles

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • Charged particle therapy offers precise dose delivery.
  • Optimizing scanning path is essential for treatment efficiency and minimizing radiation exposure.
  • Quasidiscrete scanning requires efficient algorithms to manage beam delivery and particle transitions.

Purpose of the Study:

  • To compare the efficacy of different algorithms for optimizing scanning paths in charged particle therapy.
  • To evaluate a Hybrid Genetic Algorithm with Heuristics (HyGA), including a clustering variant (HyGA_Cl), against Simulated Annealing (SA) and a commercial treatment planning system (TPS).

Main Methods:

  • Implemented HyGA and HyGA_Cl algorithms.
  • Assessed performance using clinical data from 10 patients treated at CNAO.
  • Compared scan paths, transit particles, and wasted particles with the CNAO TPS.
  • Analyzed clinical implications related to beam deflection during spot transitions.

Main Results:

  • SA and HyGA generated shorter scan paths than the TPS but did not reduce transit particles due to beam deflection.
  • HyGA_Cl achieved a 2% average reduction in transit particles compared to the CNAO TPS.
  • Both SA and HyGA algorithms successfully reduced the number of wasted particles, while HyGA_Cl increased them due to increased beam deflection.

Conclusions:

  • SA and HyGA are cost-effective for reducing wasted particles and shortening scan paths in charged particle therapy.
  • HyGA_Cl demonstrates potential for decreasing transit particles during beam deflection in quasidiscrete scanning.