Literature DB >> 28214228

Coronary Artery Stent Evaluation with Model-based Iterative Reconstruction at Coronary CT Angiography.

Fuminari Tatsugami1, Toru Higaki2, Hiroaki Sakane2, Wataru Fukumoto2, Yoko Kaichi2, Makoto Iida2, Yasutaka Baba2, Masao Kiguchi3, Yasuki Kihara4, So Tsushima5, Kazuo Awai2.   

Abstract

RATIONALE AND
OBJECTIVES: This study aims to compare the image quality of coronary artery stent scans on computed tomography images reconstructed with forward projected model-based iterative reconstruction solution (FIRST) and adaptive iterative dose reduction 3D (AIDR 3D).
MATERIALS AND METHODS: Coronary computed tomography angiography scans of 23 patients with 32 coronary stents were used. The images were reconstructed with AIDR 3D and FIRST. We generated computed tomography attenuation profiles across the stents and measured the width of the edge rise distance and the edge rise slope (ERS). We also calculated the stent lumen attenuation increase ratio (SAIR) and measured visible stent lumen diameters. Two radiologists visually evaluated the image quality of the stents using a 4-point scale (1 = poor, 4 = excellent).
RESULTS: There was no significant difference in the edge rise distance between the two reconstruction methods (P = 0.36). The ERS on FIRST images was greater than the ERS on AIDR 3D images (325.2 HU/mm vs 224.4 HU/mm; P <0.01). The rate of the visible stent lumen diameter compared to the true diameter on FIRST images was higher than that on AIDR 3D images (51.4% vs 47.3%, P <0.01). The SAIR on FIRST images was lower than the SAIR on AIDR 3D images (0.19 vs 0.30, P <0.01). The mean image quality scores for AIDR 3D and FIRST images were 3.18 and 3.63, respectively; the difference was also significant (P <0.01).
CONCLUSION: The image quality of coronary artery stent scans is better on FIRST than on AIDR 3D images.
Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Coronary CT angiography; coronary stents; image quality; model-based iterative reconstruction

Mesh:

Year:  2017        PMID: 28214228     DOI: 10.1016/j.acra.2016.12.020

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  11 in total

1.  Deep learning-based image restoration algorithm for coronary CT angiography.

Authors:  Fuminari Tatsugami; Toru Higaki; Yuko Nakamura; Zhou Yu; Jian Zhou; Yujie Lu; Chikako Fujioka; Toshiro Kitagawa; Yasuki Kihara; Makoto Iida; Kazuo Awai
Journal:  Eur Radiol       Date:  2019-04-08       Impact factor: 5.315

2.  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

3.  Neointimal formation after carotid artery stenting: phantom and clinical evaluation of model-based iterative reconstruction (MBIR).

Authors:  Kazushi Yokomachi; Fuminari Tatsugami; Toru Higaki; Shinji Kume; Shigeyuki Sakamoto; Takahito Okazaki; Kaoru Kurisu; Yuko Nakamura; Yasutaka Baba; Makoto Iida; Kazuo Awai
Journal:  Eur Radiol       Date:  2018-06-22       Impact factor: 5.315

4.  The effect of heart rate on coronary plaque measurements in 320-row coronary CT angiography.

Authors:  Masafumi Kidoh; Daisuke Utsunomiya; Yoshinori Funama; Daisuke Sakabe; Seitaro Oda; Takeshi Nakaura; Hideaki Yuki; Yasunori Nagayama; Kenichiro Hirata; Yuji Iyama; Tomohiro Namimoto; Yasuyuki Yamashita
Journal:  Int J Cardiovasc Imaging       Date:  2018-07-20       Impact factor: 2.357

5.  Diagnostic accuracy of in-stent restenosis using model-based iterative reconstruction at coronary CT angiography: initial experience.

Authors:  Fuminari Tatsugami; Toru Higaki; Hiroaki Sakane; Yuko Nakamura; Makoto Iida; Yasutaka Baba; Chikako Fujioka; Atsuhiro Senoo; Toshiro Kitagawa; Hideya Yamamoto; Yasuki Kihara; Kazuo Awai
Journal:  Br J Radiol       Date:  2017-10-27       Impact factor: 3.039

6.  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

7.  Cervical spinal computed tomography utilizing model-based iterative reconstruction reduces radiation to an equivalent of three cervical X-rays.

Authors:  Kazutaka Masamoto; Shunsuke Fujibayashi; Bungo Otsuki; Yasuhiro Fukushima; Koji Koizumi; Takayoshi Shimizu; Yu Shimizu; Koichi Murata; Norimasa Ikeda; Shuichi Matsuda
Journal:  Eur Spine J       Date:  2020-05-09       Impact factor: 3.134

8.  Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT.

Authors:  Wookon Son; MinWoo Kim; Jae-Yeon Hwang; Yong-Woo Kim; Chankue Park; Ki Seok Choo; Tae Un Kim; Joo Yeon Jang
Journal:  Korean J Radiol       Date:  2022-05-27       Impact factor: 7.109

9.  Importance of the heart rate in ultra-high-resolution coronary CT angiography with 0.35 s gantry rotation time.

Authors:  Tsukasa Kojima; Takashi Shirasaka; Yuzo Yamasaki; Masatoshi Kondo; Hiroshi Hamasaki; Ryoji Mikayama; Yuki Sakai; Toyoyuki Kato; Akihiro Nishie; Kousei Ishigami; Hidetake Yabuuchi
Journal:  Jpn J Radiol       Date:  2022-04-09       Impact factor: 2.701

10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.