Development of a novel prediction model for the dynamic tumor tracking toward the high-accurate four-dimensional image-guided radiotherapy

2017 Fiscal Year Final Research Report

• Project/Area Number: 15K21102
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Radiation science; Medical Physics and Radiological Technology
• Research Institution: Kyoto University
• Principal Investigator: Mukumoto Nobutaka 京都大学, 医学研究科, 特定職員 (50736618)
• Project Period (FY): 2015-04-01 – 2018-03-31
• Keywords: 医学物理学 / 呼吸性移動対策 / 動体追尾 / 品質保証 / 精度検証 / 動体ファントム

Outline of Final Research Achievements

Patient's respiratory motion will be changed due to the baseline drift. The accuracy of a prediction model for the dynamic tumor tracking will be decreased as the treatment time elapsed. We have developed four-axis moving phantom which enables to reproduce the patient’s respiratory motion including the baseline drift with high accuracy. The novel prediction model for the dynamic tumor tracking improved the prediction accuracy by updating the model using the real tumor position during beam delivery. However, the sampling interval greater than 2 seconds have a risk for creating the low-accurate prediction model.

Free Research Field

医学物理学・放射線技術学