Literature DB >> 23727376

CT volumetry of artificial pulmonary nodules using an ex vivo lung phantom: influence of exposure parameters and iterative reconstruction on reproducibility.

Mark O Wielpütz1, Mathieu Lederlin, Jacek Wroblewski, Julien Dinkel, Monika Eichinger, Jürgen Biederer, Hans-Ulrich Kauczor, Michael Puderbach.   

Abstract

OBJECTIVES: To evaluate the influence of exposure parameters and raw-data based iterative reconstruction (IR) on the measurement variability of computer-aided nodule volumetry on chest multidetector computed tomography (MDCT).
MATERIALS AND METHODS: N=7 porcine lung explants were inflated in a dedicated ex vivo phantom and prepared with n=162 artificial nodules. MDCT was performed eight consecutive times (combinations of 120 and 80 kV with 120, 60, 30 and 12 mAs), and reconstructed with filtered back projection (FBP) and IR. Nodule volume and diameter were measured semi-automatically with dedicated software. The absolute percentage measurement error (APE) was computed in relation to the 120 kV 120 mAs acquisition. Noise was recorded for each nodule in every dataset.
RESULTS: Mean nodule volume and diameter were 0.32 ± 0.15 ml and 12.0 ± 2.6mm, respectively. Although IR reduced noise by 24.9% on average compared to FBP (p<0.007), APE with IR was equal to or slightly higher than with FBP. Mean APE for volume increased significantly below a volume computed tomography dose index (CTDI) of 1.0 mGy: for 120 kV 12 mAs APE was 3.8 ± 6.2% (FBP) vs. 4.0 ± 5.2% (IR) (p<0.007); for 80 kV 12 mAs APE was 8.0 ± 13.0% vs. 9.3 ± 15.8% (n.s.), respectively. Correlating APE with image noise revealed that at identical noise APE was higher with IR than with FBP (p<0.05).
CONCLUSIONS: Computer-aided volumetry is robust in a wide range of exposure settings, and reproducibility is reduced at a CTDI below 1.0 mGy only, but the error rate remains clinically irrelevant. Noise reduction by IR is not detrimental for measurement error in the setting of semi-automatic nodule volumetry on chest MDCT.
Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Keywords:  Computer-aided diagnosis; Lung cancer; Screening

Mesh:

Year:  2013        PMID: 23727376     DOI: 10.1016/j.ejrad.2013.04.035

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


  7 in total

1.  Computer-assisted solid lung nodule 3D volumetry on CT: influence of scan mode and iterative reconstruction: a CT phantom study.

Authors:  Adriaan Coenen; Osamu Honda; Eric J van der Jagt; Noriyuki Tomiyama
Journal:  Jpn J Radiol       Date:  2013-08-18       Impact factor: 2.374

2.  Variability in CT lung-nodule volumetry: Effects of dose reduction and reconstruction methods.

Authors:  Stefano Young; Hyun J Grace Kim; Moe Moe Ko; War War Ko; Carlos Flores; Michael F McNitt-Gray
Journal:  Med Phys       Date:  2015-05       Impact factor: 4.071

Review 3.  Quality assurance and quantitative imaging biomarkers in low-dose CT lung cancer screening.

Authors:  Chara E Rydzak; Samuel G Armato; Ricardo S Avila; James L Mulshine; David F Yankelevitz; David S Gierada
Journal:  Br J Radiol       Date:  2017-10-27       Impact factor: 3.039

Review 4.  Low-Dose CT Screening for Lung Cancer: Evidence from 2 Decades of Study.

Authors:  David S Gierada; William C Black; Caroline Chiles; Paul F Pinsky; David F Yankelevitz
Journal:  Radiol Imaging Cancer       Date:  2020-03-27

5.  Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability.

Authors:  Hyungjin Kim; Chang Min Park; Myunghee Lee; Sang Joon Park; Yong Sub Song; Jong Hyuk Lee; Eui Jin Hwang; Jin Mo Goo
Journal:  PLoS One       Date:  2016-10-14       Impact factor: 3.240

6.  Detection of artificial pulmonary lung nodules in ultralow-dose CT using an ex vivo lung phantom.

Authors:  Caroline Alexandra Burgard; Thomas Gaass; Madeleine Bonert; David Bondesson; Natalie Thaens; Maximilian Ferdinand Reiser; Julien Dinkel
Journal:  PLoS One       Date:  2018-01-03       Impact factor: 3.240

7.  Influence of exposure parameters and iterative reconstruction on automatic airway segmentation and analysis on MDCT-An ex vivo phantom study.

Authors:  Patricia Leutz-Schmidt; Oliver Weinheimer; Bertram J Jobst; Julien Dinkel; Jürgen Biederer; Hans-Ulrich Kauczor; Michael U Puderbach; Mark O Wielpütz
Journal:  PLoS One       Date:  2017-08-02       Impact factor: 3.240

  7 in total

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