@article{oai:repo.qst.go.jp:00048124,
 author = {松本, 真之介 and 古場, 裕介 and Kohno, Ryosuke and Lee, Choonsik and E., Bolch Wesley and Kai, Michiaki and 松本 真之介 and 古場 裕介},
 issue = {4},
 journal = {Health Physics},
 month = {Apr},
 note = {Proton therapy has the physical advantage of a Bragg peak that can provide a better dose distribution than conventional x-ray therapy. However, radiation exposure of normal tissues cannot be ignored because it is likely to increase the risk of secondary cancer. Evaluating secondary neutrons generated by the interaction of the proton beam with the treatment beam-line structure is necessary; thus, performing the optimization of radiation protection in proton therapy is required. In this research, the organ dose and energy spectrum were calculated from secondary neutrons using Monte Carlo simulations. The Monte Carlo code known as the Particle and Heavy Ion Transport code System (PHITS) was used to simulate the transport proton and its interaction with the treatment beam-line structure that modeled the double scattering body of the treatment nozzle at the National Cancer Center Hospital East. The doses of the organs in a hybrid computational phantom simulating a 5-y-old boy were calculated. In general, secondary neutron doses were found to decrease with increasing distance to the treatment field. Secondary neutron energy spectra were characterized by incident neutrons with three energy peaks: 1×10, 1, and 100 MeV. A block collimator and a patient collimator contributed significantly to organ doses. In particular, the secondary neutrons from the patient collimator were 30 times higher than those from the first scatter. These results suggested that proactive protection will be required in the design of the treatment beam-line structures and that organ doses from secondary neutrons may be able to be reduced.},
 pages = {380--386},
 title = {Secondary Neutron Doses to Pediatric Patients During Intracranial Proton Therapy: Monte Carlo Simulation of the Neutron Energy Spectrum and its Organ Doses},
 volume = {110},
 year = {2016}
}