• Search Research Projects
  • Search Researchers
  • How to Use
  1. Back to project page

2023 Fiscal Year Final Research Report

Reconstruction of dose distributions using PET images in heavy ion therapy

Research Project

  • PDF
Project/Area Number 20K08066
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 52040:Radiological sciences-related
Research InstitutionNational Institutes for Quantum Science and Technology

Principal Investigator

Mohammadi Akram  国立研究開発法人量子科学技術研究開発機構, 量子医科学研究所 先進核医学基盤研究部, 主任研究員 (10554735)

Project Period (FY) 2020-04-01 – 2024-03-31
KeywordsDose reconstruction / PET image / heavy ion therapy
Outline of Final Research Achievements

It is desirable to verify the treatment during ion therapy. For this purpose, we developed a method for predicting the dose distributions from positron emission tomography (PET) images in ion therapy and demonstrated the validity of the method for 11C and 15O ion beams. The depth doses and PET images were measured in polymethyl methacrylate (PMMA) phantoms for both ion beams under the same conditions in the carbon therapy facility of the Heavy Ion Medical Accelerator in Chiba (HIMAC). The mono-energetic beams were used to reproduce the measured PET activity of the poly-energetic beams and then the depth doses were calculated using the proposed method. The predicted dose profiles were in overall good agreement with the measured ones and the distal fall-off positions at 80% of the Bragg peaks were also predicted within 0.2 mm for both 11C and 15O ion beams.

Free Research Field

放射線科学関連

Academic Significance and Societal Importance of the Research Achievements

Treatment verification is highly desirable in ion therapy to cover tumors with maximum dose and to spare normal tissues or organs at risk near the tumors. We developed a method to predict dose distribution from positron emission tomography (PET) images in ion therapy for treatment verification.

URL: 

Published: 2025-01-30  

Information User Guide FAQ News Terms of Use Attribution of KAKENHI

Powered by NII kakenhi