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Related Experiment Video

Updated: Aug 6, 2025

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Optimization of isocenter position for multiple targets with nonuniform-margin expansion.

Junjie Miao1, Yingjie Xu1, Jianrong Dai1

  • 1Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Journal of Applied Clinical Medical Physics
|March 16, 2023
PubMed
Summary

Optimizing the isocenter position for the single isocenter for multiple-target (SIMT) technique minimizes total margin volume for brain metastases. The adaptive simulated annealing (ASA) algorithm significantly speeds up calculations and reduces treatment margins.

Keywords:
adaptive simulated annealingnonuniform marginsetup uncertaintysingle isocenter multiple targets

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Area of Science:

  • Radiation Oncology
  • Medical Physics
  • Image-Guided Therapy

Background:

  • The single isocenter for multiple-target (SIMT) technique is widely used for treating multiple brain metastases.
  • Determining the optimal isocenter position is crucial for minimizing radiation dose to healthy tissues.
  • Current methods may not fully account for complex target geometries and uncertainties.

Purpose of the Study:

  • To propose and evaluate a method for determining the optimal isocenter position in SIMT to minimize total expanded margin volume.
  • To investigate the impact of target size, translational error, and rotational error on optimal isocenter selection.
  • To assess the efficiency of the adaptive simulated annealing (ASA) algorithm for rapid isocenter determination.

Main Methods:

  • Developed a statistical model to establish the relationship between nonuniform margins, isocenter distance, uncertainties, and significance level.
  • Employed numerical simulations to analyze the nonlinear relationship between margin volume and isocenter position, considering rotational errors.
  • Utilized the adaptive simulated annealing (ASA) algorithm for efficient optimal isocenter identification and compared it with center-of-geometric (COG), center-of-volume (COV), and center-of-surface (COS) methods.
  • Evaluated the method in ten patients with multiple brain metastases treated with SIMT.

Main Results:

  • When target sizes are equal, the optimal isocenter determined by ASA coincides with COG, COV, and COS.
  • For targets of different sizes, the optimal isocenter is closer to larger tumors; COS is often a closer approximation than COV.
  • The ASA algorithm reduced calculation time from hours to seconds, enabling faster clinical implementation.
  • Optimized isocenter selection reduced margin volume by up to 27.7% compared to using COG.

Conclusions:

  • Optimal isocenter selection, particularly for targets with significant size differences, effectively reduces total margin volume in SIMT.
  • The ASA algorithm offers a substantial speed improvement for calculating optimal isocenter positions.
  • This approach provides a clinically viable method for isocenter selection, enhancing the protection of surrounding normal tissues.