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Establishment of coronary artery calcium scoring in low-dose CT using model-based iterative reconstruction

Research Project

Project/Area Number 16K10279
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Radiation science
Research InstitutionHiroshima University

Principal Investigator

Tatsugami Fuminari  広島大学, 病院(医), 講師 (90411355)

Co-Investigator(Kenkyū-buntansha) 粟井 和夫  広島大学, 医系科学研究科(医), 教授 (30294573)
檜垣 徹  広島大学, 医系科学研究科(医), 共同研究講座准教授 (80611334)
Project Period (FY) 2016-04-01 – 2021-03-31
Project Status Completed (Fiscal Year 2020)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2017: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2016: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Keywords冠動脈石灰化 / 逐次近似再構成法 / CT / 低線量CT / 逐次近似画像再構成法 / 心臓CT / 石灰化スコア
Outline of Final Research Achievements

We investigated the accuracy of volume measurement for coronary artery calcium using various image reconstruction methods. A phantom containing simulated calcification with various size and density were scanned with 320 slice CT and high-resolution CT. Images were generated with thin-slice thickness (0.5mm) and reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (hybrid IR), and model-based IR (MBIR). MBIR had the highest accuracy of calcium volume measurement. For calcium of 3 mm or more, it was considered possible to reduce the radiation dose by 67-84% by using MBIR. However, the accurate assessments of small calcifications (1-2 mm or less) or calcifications in low density (200 HU or less) were difficult even with the use of MBIR. Also, the error rate became larger with a lower radiation dose. Therefore, it was difficult to reduce radiation exposure in clinical practice, and we could not establish a calcium score using low-dose CT.

Academic Significance and Societal Importance of the Research Achievements

冠動脈石灰化スコアは通常3mm厚の画像を用いて定量評価を行うため、それ以下の小さな石灰化は背景組織と平均化され検出困難となる。今回は、0.5mm厚の薄い画像を作成し、小さな石灰化を正確に定量できるかを検討したが、1-2mm程度の石灰化や200HU以下の石灰化は、逐次近似画像再構成法を用いても真値との間に大きな誤差が生じた。また線量低減によりその差はさらに増大した。今後、薄い厚さの画像を用いて石灰化の有無を確認することは重要ではあるが、現状のCT装置の空間分解能では被ばく低減にはリスクがあると考えられる。低線量撮影を実現するには、新たな画像再構成法やCT装置のさらなる発展が必要と考えられた。

Report

(6 results)
  • 2020 Annual Research Report   Final Research Report ( PDF )
  • 2019 Research-status Report
  • 2018 Research-status Report
  • 2017 Research-status Report
  • 2016 Research-status Report
  • Research Products

    (24 results)

All 2021 2020 2019 2018 2017 2016

All Journal Article (9 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 5 results) Presentation (14 results) (of which Int'l Joint Research: 5 results,  Invited: 10 results) Book (1 results)

  • [Journal Article] Measurement of coronary artery calcium volume using ultra-high-resolution computed tomography: A preliminary phantom and cadaver study.2020

    • Author(s)
      Fukumoto W, Nagaoka M, Higaki T, Tatsugami F, Nakamura Y, Oostveen L, Klein W, Prokop M, Awai K.
    • Journal Title

      Eur J Radiol Open.

      Volume: 7 Pages: 100253-100253

    • DOI

      10.1016/j.ejro.2020.100253

    • NAID

      120007169785

    • Related Report
      2020 Annual Research Report
    • Peer Reviewed
  • [Journal Article] 心臓CT領域におけるdeep learning画像再構成法2020

    • Author(s)
      檜垣 徹, 立神史稔, 福本 航, 中村優子, 粟井和夫.
    • Journal Title

      Rad Fan.

      Volume: 18 Pages: 27-9

    • Related Report
      2020 Annual Research Report
  • [Journal Article] Deep learning reconstruction at CT: Phantom study of the image characteristics.2020

    • Author(s)
      Higaki T, Nakamura Y, Zhou J, Yu Z, Nemoto T, Tatsugami F, Awai K.
    • Journal Title

      Acad Radiol.

      Volume: 27 Issue: 1 Pages: 82-7

    • DOI

      10.1016/j.acra.2019.09.008

    • Related Report
      2019 Research-status Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Possibility of deep learning in medical imaging focusing improvement of computed tomography image quality.2020

    • Author(s)
      Nakamura Y, Higaki T, Tatsugami F, Honda Y, Narita K, Akagi M, Awai K.
    • Journal Title

      J Comput Assist Tomogr.

      Volume: 44 Issue: 2 Pages: 161-7

    • DOI

      10.1097/rct.0000000000000928

    • Related Report
      2019 Research-status Report
    • Peer Reviewed
  • [Journal Article] Deep learningを応用した画像再構成-CT・MRIの画質向上への活用-.2020

    • Author(s)
      檜垣 徹, 中村優子, 立神史稔, 粟井和夫.
    • Journal Title

      Medical Science Digest.

      Volume: 46 Pages: 18-21

    • Related Report
      2019 Research-status Report
  • [Journal Article] Improvement of image quality at CT and MRI using deep learning.2019

    • Author(s)
      Higaki T, Nakamura Y, Tatsugami F, Nakaura T, Awai K.
    • Journal Title

      Jpn J Radiol.

      Volume: 37 Issue: 1 Pages: 73-80

    • DOI

      10.1007/s11604-018-0796-2

    • NAID

      210000187271

    • Related Report
      2019 Research-status Report
    • Peer Reviewed
  • [Journal Article] Deep learning-based image restoration algorithm for coronary CT angiography.2019

    • Author(s)
      Tatsugami F, Higaki T, Nakamura Y, Yu Z, Zhou J, Lu Y, Fujioka C, Kitagawa T, Kihara Y, Iida M, Awai K.
    • Journal Title

      Eur Radiol.

      Volume: 29 Issue: 10 Pages: 5322-9

    • DOI

      10.1007/s00330-019-06183-y

    • Related Report
      2019 Research-status Report
    • Peer Reviewed / Int'l Joint Research
  • [Journal Article] Dual Energy CTのUpdateとディープラーニング画像再構成(TrueFidelity)の使用経験.2019

    • Author(s)
      立神史稔
    • Journal Title

      INNERVISION

      Volume: 34 Pages: 74-5

    • Related Report
      2019 Research-status Report
  • [Journal Article] 2019年のCTはこうなる.2019

    • Author(s)
      檜垣 徹, 中村優子, 立神史稔, 粟井和夫.
    • Journal Title

      Rad Fan.

      Volume: 4 Pages: 51-4

    • Related Report
      2019 Research-status Report
  • [Presentation] Deep Learningを用いたCT画像再構成―循環器領域での活用法―2021

    • Author(s)
      立神史稔
    • Organizer
      日本心血管画像動態学会
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] CT撮影法/再構成法の最近の話題 - AI再構成を含めて -2020

    • Author(s)
      立神史稔
    • Organizer
      三重MDCTセミナー
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] AIを用いたCT画像再構成ー臨床での活用法ー2020

    • Author(s)
      立神史稔
    • Organizer
      日本CT技術学会学術大会
    • Related Report
      2020 Annual Research Report
    • Invited
  • [Presentation] CT領域における最先端技術2019

    • Author(s)
      立神史稔
    • Organizer
      第40回 関西CT技術シンポジウム
    • Related Report
      2019 Research-status Report
    • Invited
  • [Presentation] Dual Energy CTの Updateとディープラーニング画像再構成(TrueFidelity)の使用経験2019

    • Author(s)
      立神史稔
    • Organizer
      GE Healthcare Japan Edison Seminar 2019
    • Related Report
      2019 Research-status Report
    • Invited
  • [Presentation] 心血管領域における新たなCT画像再構成2019

    • Author(s)
      立神史稔
    • Organizer
      第30回日本心血管画像動態学会
    • Related Report
      2019 Research-status Report
    • Invited
  • [Presentation] Radiation dose reduction in calcium volume measurement at cardiac CT using model-based iterative reconstruction: A phantom study2019

    • Author(s)
      Tatsugami F, Higaki T, Nakamura Y, Iida M, Fujioka C, Awai K.
    • Organizer
      European Congress of Radiology
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] Accuracy of volume measurements of coronary calcification at CT using model-based iterative reconstruction: a phantom study2018

    • Author(s)
      Higaki T, Tatsugami T, Fujioka C, Yokomachi K, Nakamura Y, Awai K.
    • Organizer
      The Radiological Society of North America
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] Easy understanding of theory and image characteristics of the model-based iterative reconstruction at CT for radiologists: how does it work?2018

    • Author(s)
      Higaki T, Tatsugami F, Nakamura Y, Fujioka C, Tsushima S, Awai K.
    • Organizer
      The Radiological Society of North America
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research
  • [Presentation] CT領域における最先端技術-MBIRからDeep Learning based Reconstruction-2018

    • Author(s)
      立神史稔
    • Organizer
      第54回 日本医学放射線学会秋季臨床大会
    • Related Report
      2018 Research-status Report
    • Invited
  • [Presentation] CT領域における最先端技術-画像再構成技術の発展とDual Energy Imaging-2018

    • Author(s)
      立神史稔
    • Organizer
      放射線診断セミナー山形
    • Related Report
      2018 Research-status Report
    • Invited
  • [Presentation] 逐次近似再構成法の概要と臨床評価2017

    • Author(s)
      立神史稔
    • Organizer
      第53回 日本医学放射線学会秋季臨床大会
    • Related Report
      2017 Research-status Report
    • Invited
  • [Presentation] Coronary CT angiography -Improvement in image quality-2017

    • Author(s)
      立神史稔
    • Organizer
      The 11th Congress of Asian Society of Cardiovascular Imaging
    • Related Report
      2017 Research-status Report
    • Int'l Joint Research / Invited
  • [Presentation] Radiation dose reduction for coronary artery calcium scoring at 320-detector CT with full iterative reconstruction: A Phantom Study2016

    • Author(s)
      Fuminari Tatsugami, Toru Higaki, Chikako Fujioka, Masao Kiguchi, Makoto Iida, Kazuo Awai
    • Organizer
      Congress of Asian Society of Cardiovascular Imaging(ASCI)
    • Place of Presentation
      シンガポール
    • Year and Date
      2016-08-05
    • Related Report
      2016 Research-status Report
    • Int'l Joint Research
  • [Book] 最新Body CT診断2018

    • Author(s)
      粟井 和夫、陣崎 雅弘
    • Total Pages
      380
    • Publisher
      メディカル・サイエンス・インターナショナル
    • ISBN
      9784895929073
    • Related Report
      2017 Research-status Report

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Published: 2016-04-21   Modified: 2022-01-27  

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