Literature DB >> 17433595

Interobserver-variability of lung nodule volumetry considering different segmentation algorithms and observer training levels.

H Bolte1, T Jahnke, F K W Schäfer, R Wenke, B Hoffmann, S Freitag-Wolf, V Dicken, J M Kuhnigk, J Lohmann, S Voss, N Knöss, M Heller, J Biederer.   

Abstract

OBJECTIVE: The aim of this study was to investigate the interobserver variability of CT based diameter and volumetric measurements of artificial pulmonary nodules. A special interest was the consideration of different measurement methods, observer experience and training levels.
MATERIALS AND METHODS: For this purpose 46 artificial small solid nodules were examined in a dedicated ex-vivo chest phantom with multislice-spiral CT (20 mAs, 120 kV, collimation 16 mm x 0.75 mm, table feed 15 mm, reconstructed slice thickness 1mm, reconstruction increment 0.7 mm, intermediate reconstruction kernel). Two observer groups of different radiologic experience (0 and more than 5 years of training, 3 observers each) analysed all lesions with digital callipers and 2 volumetry software packages (click-point depending and robust volumetry) in a semi-automatic and manually corrected mode. For data analysis the variation coefficient (VC) was calculated in per cent for each group and a Wilcoxon test was used for analytic statistics.
RESULTS: Click-point robust volumetry showed with a VC of <0.01% in both groups the smallest interobserver variability. Between experienced and un-experienced observers interobserver variability was significantly different for diameter measurements (p=0.023) but not for semi-automatic and manual corrected volumetry. A significant training effect was revealed for diameter measurements (p=0.003) and semi-automatic measurements of click-point depending volumetry (p=0.007) in the un-experienced observer group.
CONCLUSIONS: Compared to diameter measurements volumetry achieves a significantly smaller interobserver variance and advanced volumetry algorithms are independent of observer experience.

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Year:  2007        PMID: 17433595     DOI: 10.1016/j.ejrad.2007.02.031

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


  11 in total

1.  The influence of initial outlines on manual segmentation.

Authors:  William F Sensakovic; Adam Starkey; Rachael Roberts; Christopher Straus; Philip Caligiuri; Masha Kocherginsky; Samuel G Armato
Journal:  Med Phys       Date:  2010-05       Impact factor: 4.071

2.  Accuracy of MRI volume measurements of breast lesions: comparison between automated, semiautomated and manual assessment.

Authors:  Marga B Rominger; Daphne Fournell; Beenarose Thanka Nadar; Sarah N M Behrens; Jens H Figiel; Boris Keil; Johannes T Heverhagen
Journal:  Eur Radiol       Date:  2009-01-22       Impact factor: 5.315

3.  Variability of semiautomated lung nodule volumetry on ultralow-dose CT: comparison with nodule volumetry on standard-dose CT.

Authors:  Patrick A Hein; Valentina C Romano; Patrik Rogalla; Christian Klessen; Alexander Lembcke; Lars Bornemann; Volker Dicken; Bernd Hamm; Hans-Christian Bauknecht
Journal:  J Digit Imaging       Date:  2008-09-05       Impact factor: 4.056

4.  Computer-aided diagnosis systems for lung cancer: challenges and methodologies.

Authors:  Ayman El-Baz; Garth M Beache; Georgy Gimel'farb; Kenji Suzuki; Kazunori Okada; Ahmed Elnakib; Ahmed Soliman; Behnoush Abdollahi
Journal:  Int J Biomed Imaging       Date:  2013-01-29

5.  Measurement of tumor volumes improves RECIST-based response assessments in advanced lung cancer.

Authors:  P David Mozley; Claus Bendtsen; Binsheng Zhao; Lawrence H Schwartz; Matthias Thorn; Yuanxin Rong; Luduan Zhang; Andrea Perrone; René Korn; Andrew J Buckler
Journal:  Transl Oncol       Date:  2012-02-01       Impact factor: 4.243

Review 6.  Recent technological and application developments in computed tomography and magnetic resonance imaging for improved pulmonary nodule detection and lung cancer staging.

Authors:  Jessica C Sieren; Yoshiharu Ohno; Hisanobu Koyama; Kazuro Sugimura; Geoffrey McLennan
Journal:  J Magn Reson Imaging       Date:  2010-12       Impact factor: 4.813

7.  Liver volume measurement: reason of the difference between in vivo CT-volumetry and intraoperative ex vivo determination and how to cope it.

Authors:  Stefan M Niehues; J K Unger; M Malinowski; J Neymeyer; B Hamm; M Stockmann
Journal:  Eur J Med Res       Date:  2010-08-20       Impact factor: 2.175

Review 8.  Meta-analysis of the technical performance of an imaging procedure: guidelines and statistical methodology.

Authors:  Erich P Huang; Xiao-Feng Wang; Kingshuk Roy Choudhury; Lisa M McShane; Mithat Gönen; Jingjing Ye; Andrew J Buckler; Paul E Kinahan; Anthony P Reeves; Edward F Jackson; Alexander R Guimaraes; Gudrun Zahlmann
Journal:  Stat Methods Med Res       Date:  2014-05-28       Impact factor: 3.021

9.  PET-based delineation of tumour volumes in lung cancer: comparison with pathological findings.

Authors:  Andrea Schaefer; Yoo Jin Kim; Stephanie Kremp; Sebastian Mai; Jochen Fleckenstein; Hendrik Bohnenberger; Hans-Joachim Schäfers; Jan-Martin Kuhnigk; Rainer M Bohle; Christian Rübe; Carl-Martin Kirsch; Aleksandar Grgic
Journal:  Eur J Nucl Med Mol Imaging       Date:  2013-04-30       Impact factor: 9.236

10.  Repeatability and intra- and inter-observer agreement of cervical vertebral sagittal diameter ratios in horses with neurological disease.

Authors:  K J Hughes; E H Laidlaw; S M Reed; J Keen; J B Abbott; T Trevail; G Hammond; T D H Parkin; S Love
Journal:  J Vet Intern Med       Date:  2014 Nov-Dec       Impact factor: 3.333

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