Literature DB >> 27423675

Comparative evaluation of newly developed model-based and commercially available hybrid-type iterative reconstruction methods and filter back projection method in terms of accuracy of computer-aided volumetry (CADv) for low-dose CT protocols in phantom study.

Yoshiharu Ohno1, Atsushi Yaguchi2, Tomoya Okazaki2, Kota Aoyagi3, Hitoshi Yamagata3, Naoki Sugihara3, Hisanobu Koyama4, Takeshi Yoshikawa5, Kazuro Sugimura4.   

Abstract

PURPOSE: To directly compare the capability of three reconstruction methods using, respectively, forward projected model-based iterative reconstruction (FIRST), adaptive iterative dose reduction using three dimensional processing (AIDR 3D) and filter back projection (FBP) for radiation dose reduction and accuracy of computer-aided volumetry (CADv) measurements on chest CT examination in a phantom study.
MATERIALS AND METHODS: An anthropomorphic thoracic phantom with 30 simulated nodules of three density types (100, -630, and -800 HU) and five different diameters was scanned with an area-detector CT at tube currents of 270, 200, 120, 80, 40, 20, and 10mA. Each scanned data set was reconstructed as thin-section CT with three methods, and all simulated nodules were measured with CADv software. For comparison of the capability for CADv at each tube current, Tukey's HSD test was used to compare the percentage of absolute measurement errors for all three reconstruction methods. Absolute percentage measurement errors were then compared by means of Dunett's test for each tube current at 270mA (standard tube current).
RESULTS: Mean absolute measurement errors of AIDR 3D and FIRST methods for each nodule type were significantly lower than those of the FBP method at 20mA and 10mA (p<0.05). In addition, absolute measurement errors of the FBP method at 20mA and 10mA was significantly higher than that at 270mA for all nodule types (p<0.05).
CONCLUSION: The FIRST and AIDR 3D methods are more effective than the FBP method for radiation dose reduction, while yielding better measurement accuracy of CADv for chest CT examination.
Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  CT; Computer-aided volumetry; Lung; Nodule; Radiation dose; Reconstruction algorithm

Mesh:

Year:  2016        PMID: 27423675     DOI: 10.1016/j.ejrad.2016.05.001

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  11 in total

1.  The usefulness of full-iterative reconstruction algorithm for the visualization of cystic artery on CT angiography.

Authors:  Toshihiko Hamamura; Yoshiko Hayashida; Yohei Takeshita; Koichiro Sugimoto; Issei Ueda; Koichiro Futatsuya; Shingo Kakeda; Takatoshi Aoki; Yukunori Korogi
Journal:  Jpn J Radiol       Date:  2019-04-30       Impact factor: 2.374

2.  Full model-based iterative reconstruction (MBIR) in abdominal CT increases objective image quality, but decreases subjective acceptance.

Authors:  Gautier Laurent; Nicolas Villani; Gabriela Hossu; Aymeric Rauch; Alain Noël; Alain Blum; Pedro Augusto Gondim Teixeira
Journal:  Eur Radiol       Date:  2019-01-30       Impact factor: 5.315

Review 3.  Regularization strategies in statistical image reconstruction of low-dose x-ray CT: A review.

Authors:  Hao Zhang; Jing Wang; Dong Zeng; Xi Tao; Jianhua Ma
Journal:  Med Phys       Date:  2018-09-10       Impact factor: 4.071

4.  Usefulness of model-based iterative reconstruction in semi-automatic volumetry for ground-glass nodules at ultra-low-dose CT: a phantom study.

Authors:  Shuki Maruyama; Yasuhiro Fukushima; Yuta Miyamae; Koji Koizumi
Journal:  Radiol Phys Technol       Date:  2018-02-10

5.  Deep-learning reconstruction for ultra-low-dose lung CT: Volumetric measurement accuracy and reproducibility of artificial ground-glass nodules in a phantom study.

Authors:  Ryoji Mikayama; Takashi Shirasaka; Tsukasa Kojima; Yuki Sakai; Hidetake Yabuuchi; Masatoshi Kondo; Toyoyuki Kato
Journal:  Br J Radiol       Date:  2021-12-15       Impact factor: 3.039

6.  Novel Intraoperative Navigation Using Ultra-High-Resolution CT in Robot-Assisted Partial Nephrectomy.

Authors:  Kiyoshi Takahara; Yoshiharu Ohno; Kosuke Fukaya; Ryo Matsukiyo; Takuhisa Nukaya; Masashi Takenaka; Kenji Zennami; Manabu Ichino; Naohiko Fukami; Hitomi Sasaki; Mamoru Kusaka; Hiroshi Toyama; Makoto Sumitomo; Ryoichi Shiroki
Journal:  Cancers (Basel)       Date:  2022-04-18       Impact factor: 6.639

7.  Low-Radiation-Dose Stress Myocardial Perfusion Measurement Using First-Pass Analysis Dynamic Computed Tomography: A Preliminary Investigation in a Swine Model.

Authors:  Logan Hubbard; Shant Malkasian; Yixiao Zhao; Pablo Abbona; Jungnam Kwon; Sabee Molloi
Journal:  Invest Radiol       Date:  2019-12       Impact factor: 6.016

8.  Tradeoff between noise reduction and inartificial visualization in a model-based iterative reconstruction algorithm on coronary computed tomography angiography.

Authors:  Kenichiro Hirata; Daisuke Utsunomiya; Masafumi Kidoh; Yoshinori Funama; Seitaro Oda; Hideaki Yuki; Yasunori Nagayama; Yuji Iyama; Takeshi Nakaura; Daisuke Sakabe; Kenichi Tsujita; Yasuyuki Yamashita
Journal:  Medicine (Baltimore)       Date:  2018-05       Impact factor: 1.889

9.  Ultra-high-resolution subtraction CT angiography in the follow-up of treated intracranial aneurysms.

Authors:  Frederick J A Meijer; Joanne D Schuijf; Joost de Vries; Hieronymus D Boogaarts; Willem-Jan van der Woude; Mathias Prokop
Journal:  Insights Imaging       Date:  2019-01-28

Review 10.  Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence.

Authors:  Akifumi Hagiwara; Shohei Fujita; Yoshiharu Ohno; Shigeki Aoki
Journal:  Invest Radiol       Date:  2020-09       Impact factor: 10.065

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