Literature DB >> 25838452

Chest CT at a dose below 0.3 mSv: impact of iterative reconstruction on image quality and lung analysis.

Chiaki Nakajo1, Susanne Heinzer2, Stéphane Montandon3, Vincent Dunet4, Pierre Bize4, Andrei Feldman5, Catherine Beigelman-Aubry4.   

Abstract

BACKGROUND: In chest computed tomography (CT), iterative reconstruction (IR) algorithms maintain diagnostic image quality (IQ) while significantly reducing the dose.
PURPOSE: To evaluate the impact of IR on IQ of chest CT at effective doses below 0.3 mSv.
MATERIAL AND METHODS: Twenty chest CT scans performed at effective dose below 0.3 mSv (CT1) were reconstructed varying three parameters: filtered back-projection and IR iDose(4) algorithms; 512 × 512 and 768 × 768 matrices; and sharp and soft kernels, thus generating eight series per patient. The qualitative evaluation of the IQ was performed by ranking series from 1 to 8 (8 corresponding to the highest rank) which was subsequently compared to quantitative assessment of IQ by using an appropriated merit formula. Intra- and inter-reader IQ ranking reliability was also evaluated using Cohen's kappa. Analysis of lung findings was finally compared between the best CT1 series and the reference CT (CT0).
RESULTS: The best series in terms of qualitative and quantitative IQ was obtained using IR, 512(2) matrix and soft kernel. The best CT1 series detected nodules greater than 4 mm with an almost perfect match with CT0.
CONCLUSION: Chest CT performed at effective doses below 0.3 mSv may be used to confidently diagnose lesions greater than 4 mm using iDose(4), soft kernel and 512 × 512 matrix. © The Foundation Acta Radiologica 2015.

Entities:  

Keywords:  Reduced dose chest computed tomography; image quality; iterative reconstruction; pulmonary nodules

Mesh:

Year:  2015        PMID: 25838452     DOI: 10.1177/0284185115578469

Source DB:  PubMed          Journal:  Acta Radiol        ISSN: 0284-1851            Impact factor:   1.990


  4 in total

1.  Lung cancer screening with ultra-low dose CT using full iterative reconstruction.

Authors:  Masayo Fujita; Toru Higaki; Yoshikazu Awaya; Toshio Nakanishi; Yuko Nakamura; Fuminari Tatsugami; Yasutaka Baba; Makoto Iida; Kazuo Awai
Journal:  Jpn J Radiol       Date:  2017-02-14       Impact factor: 2.374

2.  Influence of model based iterative reconstruction algorithm on image quality of multiplanar reformations in reduced dose chest CT.

Authors:  Heloise Barras; Vincent Dunet; Anne-Lise Hachulla; Jochen Grimm; Catherine Beigelman-Aubry
Journal:  Acta Radiol Open       Date:  2016-08-24

3.  Task-Based Model Observer Assessment of A Partial Model-Based Iterative Reconstruction Algorithm in Thoracic Oncologic Multidetector CT.

Authors:  David C Rotzinger; Damien Racine; Catherine Beigelman-Aubry; Khalid M Alfudhili; Nathalie Keller; Pascal Monnin; Francis R Verdun; Fabio Becce
Journal:  Sci Rep       Date:  2018-12-07       Impact factor: 4.379

4.  Comparison of Filtered Back Projection, Hybrid Iterative Reconstruction, Model-Based Iterative Reconstruction, and Virtual Monoenergetic Reconstruction Images at Both Low- and Standard-Dose Settings in Measurement of Emphysema Volume and Airway Wall Thickness: A CT Phantom Study.

Authors:  Cherry Kim; Ki Yeol Lee; Chol Shin; Eun-Young Kang; Yu-Whan Oh; Moin Ha; Chang Sub Ko; Jaehyung Cha
Journal:  Korean J Radiol       Date:  2018-06-14       Impact factor: 3.500

  4 in total

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