Prediction of acute radiation mucositis using an oral mucosal dose surface model in carbon ion radiotherapy for head and neck tumors

Atsushi Musha, Hirofumi Shimada, Katsuyuki Shirai, Jun Ichi Saitoh, Satoshi Yokoo, Kazuaki Chikamatsu, Tatsuya Ohno, Takashi Nakano

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

Purpose To evaluate the dose-response relationship for development of acute radiation mucositis (ARM) using an oral mucosal dose surface model (OMDS-model) in carbon ion radiotherapy (C-ion RT) for head and neck tumors. Methods Thirty-nine patients receiving C-ion RT for head and neck cancer were evaluated for ARM (once per week for 6 weeks) according to the Common Terminology Criteria for Adverse Events (CTCAE), version 4.0, and the Radiation Therapy Oncology Group (RTOG) scoring systems. The irradiation schedule typically used was 64 Gy [relative biological effectiveness (RBE)] in 16 fractions for 4 weeks. Maximum point doses in the palate and tongue were compared with ARM in each patient. Results The location of the ARM coincided with the high-dose area in the OMDS-model. There was a clear dose-response relationship between maximum point dose and ARM grade assessed using the RTOG criteria but not the CTCAE. The threshold doses for grade 2-3 ARM in the palate and tongue were 43.0 Gy(RBE) and 54.3 Gy(RBE), respectively. Conclusions The OMDS-model was useful for predicting the location and severity of ARM. Maximum point doses in the model correlated well with grade 2-3 ARM.

Original languageEnglish
Article numbere0141734
JournalPLoS ONE
Volume10
Issue number10
DOIs
StatePublished - 2015/10/29

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences
  • General

Fingerprint

Dive into the research topics of 'Prediction of acute radiation mucositis using an oral mucosal dose surface model in carbon ion radiotherapy for head and neck tumors'. Together they form a unique fingerprint.

Cite this