Impact of PET Image Reconstruction Algorithm on Fractal Dimension

• Project/Area Number: 17K09066
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Medical Physics and Radiological Technology
• Research Institution: Kagawa University
• Principal Investigator: Maeda Yukito 香川大学, 医学部附属病院, 技術職員 (10763336)
• Project Period (FY): 2017-04-01 – 2022-03-31
• Project Status: Completed (Fiscal Year 2021)
• Budget Amount: ¥3,900,000 (Direct Cost: ¥3,000,000、Indirect Cost: ¥900,000); Fiscal Year 2019: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000); Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000); Fiscal Year 2017: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
• Keywords: フラクタル解析 / 神経膠腫 / PET / メチオニン / 画像再構成アルゴリズム / グリオーマ / 11C-メチオニンPET / 濃度フラクタル / フラクタル次元 / 画像再構成 / 脳腫瘍 / 悪性度 / ピクセルカウンティング法 / 放射線

Outline of Final Research Achievements

The purpose of this study was to clarify the effects of four image reconstruction algorithms OSEM, OSEM + PSF, OSEM + TOF and OSEM + PSF + TOF on fractal analysis in brain tumor PET examination. In all algorithms the higher the malignancy of brain tumors, the smaller the fractal dimension in brain methionine PET. This result suggests the usefulness of classification using fractal analysis in brain methionine PET. Next, we also evaluated the usefulness of fractal analysis in comparison with conventionally quantitative values such as SUVs for the differentiation of IDH1 mutation glioma. Fractal analysis may be able to differentiate gliomas for IDH1 mutations that were not possible with conventional quantitative parameters.

Academic Significance and Societal Importance of the Research Achievements

画像解析の一つであるフラクタル解析と従来からPET検査で使用されている評価値を組み合わせることにより，脳腫瘍の治療方針決定や予後予測などをより高い精度で行う可能性が示唆された．本研究により，フラクタル解析は脳腫瘍患者およびその家族に対し，有用な情報を提供できる指標になりうる可能性があると考えている．

Research Products

• [Journal Article] Fractal analysis of 11C-methionine PET in patients with newly diagnosed glioma (2021)
  • Author(s): Maeda Yukito、Yamamoto Yuka、Norikane Takashi、Mitamura Katsuya、Hatakeyama Tetsuhiro、Miyake Keisuke、Nishiyama Yoshihiro、Kudomi Nobuyuki
  • Journal Title: EJNMMI Physics Volume: 8 Issue: 1 Pages: 1-9
  • DOI: 10.1186/s40658-021-00418-y
  • Peer Reviewed / Open Access
• [Presentation] フラクタル解析を用いた脳腫瘍悪性度分類の試み (2019)
  • Author(s): 前田幸人
  • Organizer: 日本核医学技術学会第31回中国四国地方会
• [Presentation] フラクタル解析を用いた脳腫瘍悪性度評価 ‐画像再構成アルゴリズムによる診断能の違い‐ (2019)
  • Author(s): 前田幸人
  • Organizer: CSFRT2019
• [Presentation] Impact of reconstruction algorithm with PSF and TOF and reconstruction parameter in fractal analysis: Evaluation by changed the number of updates (2018)
  • Author(s): 前田幸人
  • Organizer: SNMMI 2018 Annual Meeting
• [Presentation] Impact of reconstruction algorithm with PSF and TOF and reconstruction parameter in fractal analysis: Evaluation by changed the Gaussian filter size (2018)
  • Author(s): 前田幸人
  • Organizer: SNMMI 2018 Annual Meeting
• [Presentation] 脳腫瘍PETにおけるフラクタル解析 (2018)
  • Author(s): 前田幸人
  • Organizer: 香川県核医学談話会
• [Presentation] 11C-MET PETにおける フラクタル解析 (2018)
  • Author(s): 前田幸人
  • Organizer: 分子イメージング夏季集中セミナー
• [Presentation] 11C-メチオニンを用いた脳腫瘍PETにおけるフラクタル解析 (2018)
  • Author(s): 前田幸人
  • Organizer: CSFRT2018
• [Presentation] Impact of reconstruction algorithm with PSF and TOF and reconstruction parameter in fractal analysis: Evaluation by changed the number of updates (2018)
  • Author(s): 前田幸人
  • Organizer: SNMMI2018
  • Int'l Joint Research
• [Presentation] Impact of reconstruction algorithm with PSF and TOF and reconstruction parameter in fractal analysis: Evaluation by changed the Gaussian filter size (2018)
  • Author(s): 前田幸人
  • Organizer: SNMMI2018
  • Int'l Joint Research