Development of optimization system for high-precision radiotherapy using by structure data of planning and image of multi-modality

2018 Fiscal Year Final Research Report

• Project/Area Number: 16K19233
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Medical Physics and Radiological Technology
• Research Institution: Kyushu University
• Principal Investigator: Yoshidome Satoshi 九州大学, 大学病院, 診療放射線技師 (70419612)
• Research Collaborator: ARIMURA Hidetaka
• Project Period (FY): 2016-04-01 – 2019-03-31
• Keywords: 高精度放射線治療 / 画像誘導放射線治療 / kV-CBCT画像 / 体幹部定位放射線治療 / テンプレートマッチング技術

Outline of Final Research Achievements

Author developed the automated estimation method of the location of tumor in kV-CBCT images. In the results, the proposed method could estimate the location of tumor less than 2 mm in kV-CBCT images. These results were reported in the magazine of medical imaging and information sciences.
Author examined that the proposed method apply to tumor region with rotation and form change. In addition, author considered that the proposed method was supported by machine learning algorithm for applying to organ at risk.

Free Research Field

放射線治療

Academic Significance and Societal Importance of the Research Achievements

本研究における提案手法を用いて，実際に放射線治療を行っている際の腫瘍位置を自動的に推定することは，その放射線治療の精度を確認することに繋がり，放射線治療の適切な対象に十分な放射線を投与する一助となる．また，提案手法を基礎として，治療時の腫瘍の位置や状態によって日々の放射線治療を最適化できる可能性が示され，それが実現することで局所腫瘍制御率の向上や正常組織障害の低減につながると考えられる．