Literature DB >> 29944085

Phantom Study of In-Stent Restenosis at High-Spatial-Resolution CT.

Hiromitsu Onishi1, Masatoshi Hori1, Takashi Ota1, Atsushi Nakamoto1, Keigo Osuga1, Mitsuaki Tatsumi1, Hideyuki Fukui1, Shinsuke Tsukagoshi1, Ayumi Uranishi1, Yasuo Saito1, Akira Taniguchi1, Yukihiro Enchi1, Kazuhiko Sato1, Noriyuki Tomiyama1.   

Abstract

Purpose To examine the diagnostic performance of high-spatial-resolution (HSR) CT with 0.25-mm section thickness for evaluating renal artery in-stent restenosis. Materials and Methods A 0.05-mm wire phantom and vessel phantoms with renal stents with in-stent stenotic sections of varying diameters were scanned with both an HSR CT scanner equipped with 160-section multi-detector rows (0.25-mm section thickness) and a conventional CT scanner. The wire phantom was used to analyze modulation transfer function (MTF). With the vessel phantoms, the error rates were calculated as the absolute difference between the measured diameters and true diameters divided by the true diameters at the narrowing sections. For qualitative evaluation, overall image quality and diagnostic accuracy for evaluating stenosis in three stages were assessed by two radiologists. Statistical analyses included the paired t test, Wilcoxon signed-rank test, and McNemar test. Results HSR CT achieved 24.3 line pairs per centimeter ± 0.5 (standard deviation) and 29.1 line pairs per centimeter ± 0.4 at 10% and 2% MTF, respectively; and conventional CT was 12.5 line pairs per centimeter ± 0.1 and 14.3 line pairs per centimeter ± 0.1 at 10% and 2% MTF, respectively. The mean error rate of the measured diameter at HSR CT (8.0% ± 5.8) was significantly lower than that at at conventional CT (16.9% ± 9.3; P < .001). Image quality at HSR CT was significantly better than that at conventional CT (P < .001), but HSR CT was not significantly superior to conventional CT in terms of diagnostic accuracy. Conclusion Compared with conventional CT, high-spatial-resolution CT achieved spatial resolutions of up to 29 line pairs per centimeter at 2% modulation transfer function and yielded improved measurement accuracy for the evaluation of in-stent restenosis in a phantom study of renal artery stents. Published under a CC BY 4.0 license.

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Year:  2018        PMID: 29944085     DOI: 10.1148/radiol.2018180188

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  11 in total

1.  Dedicated convolutional neural network for noise reduction in ultra-high-resolution photon-counting detector computed tomography.

Authors:  Nathan R Huber; Andrea Ferrero; Kishore Rajendran; Francis Baffour; Katrina N Glazebrook; Felix E Diehn; Akitoshi Inoue; Joel G Fletcher; Lifeng Yu; Shuai Leng; Cynthia H McCollough
Journal:  Phys Med Biol       Date:  2022-09-02       Impact factor: 4.174

2.  Photon Counting CT: Clinical Applications and Future Developments.

Authors:  Scott S Hsieh; Shuai Leng; Kishore Rajendran; Shengzhen Tao; Cynthia H McCollough
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2020-08-28

3.  Synchrotron radiation computed tomography assessment of calcified plaques and coronary stenosis with different slice thicknesses and beam energies on 3D printed coronary models.

Authors:  Zhonghua Sun; Curtise K C Ng; Andrew Squelch
Journal:  Quant Imaging Med Surg       Date:  2019-01

4.  Synchrotron radiation computed tomography versus conventional computed tomography for assessment of four types of stent grafts used for endovascular treatment of thoracic and abdominal aortic aneurysms.

Authors:  Zhonghua Sun; Curtise K C Ng; Cláudia Sá Dos Reis
Journal:  Quant Imaging Med Surg       Date:  2018-07

Review 5.  Photon-counting detectors in computed tomography: from quantum physics to clinical practice.

Authors:  E Wehrse; L Klein; L T Rotkopf; W L Wagner; M Uhrig; C P Heußel; C H Ziener; S Delorme; S Heinze; M Kachelrieß; H-P Schlemmer; S Sawall
Journal:  Radiologe       Date:  2021-02-17       Impact factor: 0.635

6.  Comparative observer effects in 2D and 3D localization tasks.

Authors:  Craig K Abbey; Miguel A Lago; Miguel P Eckstein
Journal:  J Med Imaging (Bellingham)       Date:  2021-03-18

7.  Image quality improvement with deep learning-based reconstruction on abdominal ultrahigh-resolution CT: A phantom study.

Authors:  Takashi Shirasaka; Tsukasa Kojima; Yoshinori Funama; Yuki Sakai; Masatoshi Kondo; Ryoji Mikayama; Hiroshi Hamasaki; Toyoyuki Kato; Yasuhiro Ushijima; Yoshiki Asayama; Akihiro Nishie
Journal:  J Appl Clin Med Phys       Date:  2021-06-23       Impact factor: 2.102

8.  Physical evaluation of an ultra-high-resolution CT scanner.

Authors:  Luuk J Oostveen; Kirsten L Boedeker; Monique Brink; Mathias Prokop; Frank de Lange; Ioannis Sechopoulos
Journal:  Eur Radiol       Date:  2020-02-10       Impact factor: 5.315

9.  Reduction in Irradiation Dose in Aperture Coded Enhanced Computed Tomography Imager Using Super-Resolution Techniques.

Authors:  Yossef Danan; Doron Avraham; Zeev Zalevsky
Journal:  Sensors (Basel)       Date:  2020-11-16       Impact factor: 3.576

10.  Quantitative dual contrast photon-counting computed tomography for assessment of articular cartilage health.

Authors:  Petri Paakkari; Satu I Inkinen; Miitu K M Honkanen; Mithilesh Prakash; Rubina Shaikh; Miika T Nieminen; Mark W Grinstaff; Janne T A Mäkelä; Juha Töyräs; Juuso T J Honkanen
Journal:  Sci Rep       Date:  2021-03-10       Impact factor: 4.379

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