Feasibility Study of Beam Angle Optimization for Proton Treatment Planning Using a Genetic Algorithm
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Feasibility Study of Beam Angle Optimization for Proton Treatment Planning Using a Genetic Algorithm Jaehyeon Seo, Yunhui Jo, Sunyoung Moon and Myonggeun Yoon∗ Department of Bio-convergence Engineering, Korea University, Seoul 02841, Korea
Sung Hwan Ahn, Boram Lee and Kwangzoo Chung† Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
Seonghoon Jeong Department of Proton Therapy Center, National Cancer Center, Goyang 10408, Korea (Received 6 April 2020; revised 2 June 2020; accepted 22 June 2020) This study describes a method that uses a genetic algorithm to select optimal beam angles in proton therapy and evaluates the effectiveness of the proposed algorithm in actual patients. In the use of the genetic algorithm to select the optimal angle, a gene represents the angle of each field and a chromosome represents the combination of beam angles. The fitness of the genetic algorithm, which represents the suitability of the chromosome to the solution, was quantified by using the dose distribution. The weighting factors of the organs used for fitness were obtained from clinical data through logistic regression, reflecting the dose characteristics of actual patients. Genetic operations, such as selection, crossover, mutation, and replacement, were used to modify the population and were repeated until an evaluation based on fitness reached the termination criterion. The proposed genetic algorithm was tested by assessing its ability to select optimal beam angles in three patients with liver cancer. The optimal results for fitness, planning target volume (PTV), normal liver, and skin in the population were compared with the clinical treatment plans, a process that took an average of 36.8 minutes. The dose-volume histograms (DVHs) and the fitness of the genetic algorithm plans did not differ significantly from the actual treatment plans. These findings indicate that the proposed genetic algorithm can automatically generate proton treatment plans with the same quality as actual clinical treatment plans. Keywords: Proton therapy, Treatment planning, Genetic algorithm, Beam angle optimization, Liver cancer DOI: 10.3938/jkps.77.312
I. INTRODUCTION Proton therapy is a type of radiation therapy in which tumors are treated with accelerated protons rather than with X-rays. A proton beam induces the maximum radiation dose near the end of beam range; this physical characteristic of protons has the advantage of maximizing radiation doses to cancer cells while minimizing damage to healthy tissue. Proton therapy has been used to treat many solid tumors, including prostate cancer, brain tumors, and lung cancer [1–4]. Proton therapy of liver cancer induces a lower degree of hepatic deterioration than other treatments, as well as showing good efficacy without increasing the side effects on the stomach and intestines [5–8]. ∗ E-mail: † E-mail:
[email protected] [email protected]
pISSN:0374-4884/eISSN:1976-8524
The purpose of radiation therapy is to deliver a therapeutic dos
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