CAD-based Monte Carlo dose calculation system for evaluating geometrical effect of inserted materials in carbon-ion
Min Cheol Han1, Yongdo Yun1, Taeho Kim1
1Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea.
Purpose:
Carbon-ion radiation therapy (CIRT) achieves potent tumor control by leveraging the unique physical and biological properties of carbon ions, such as the Bragg peak and high relative biological effectiveness. However, the presence of implanted markers or embolization coils can alter the beam range; therefore, clinical planning becomes complex. This study developed and validated a computer-aided design (CAD)-based Monte Carlo (MC) dose calculation system to accurately assess the geometric effects of materials inserted in CIRT.
Methods:
A gold fiducial marker, typically used for prostate CIRT, was evaluated in both experimental and simulation settings. Gafchromic™ EBT3 films, placed at multiple depths in a solid-water phantom, were used to measure the dose distributions. Simultaneously, a Tornado Embolization Microcoil™ (Cook Medical) for hepatic transcatheter arterial chemoembolization was modeled using CAD and simulated by considering different orientations. MC simulations were performed using TOol for PArticle Simulation, with the beam parameters obtained from the Heavy Ion Therapy Center used for validation.
Results:
The film-based and MC-based dose profiles showed a similar range shift for the fiducial marker, despite the linear energy-transfer dependence of the films. The orientation of the microcoil slightly affected the range shift (∼0.1 mm). Moreover, CAD-based modeling demonstrated a more accurate representation than using simplified geometries.
Conclusions:
The developed CAD-based MC simulation system is reliable and practical for evaluating the dosimetric impact of implanted materials on CIRT. Although MC simulations require extended computational time, the ability to incorporate absolute dose data and precisely model complex structures enhances the confidence in treatment planning.
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