Literature DB >> 18641255

Effect of nodule characteristics on variability of semiautomated volume measurements in pulmonary nodules detected in a lung cancer screening program.

Ying Wang1, Rob J van Klaveren, Hester J van der Zaag-Loonen, Geertruida H de Bock, Hester A Gietema, Dong Ming Xu, Anne L M Leusveld, Harry J de Koning, Ernst T Scholten, Johny Verschakelen, Mathias Prokop, Matthijs Oudkerk.   

Abstract

PURPOSE: To retrospectively assess volume measurement variability in solid pulmonary nodules (volume, 15-500 mm(3)) detected at lung cancer screening and to quantify the independent effects of nodule morphology, size, and location.
MATERIALS AND METHODS: This retrospective study was a substudy of the screening program that was approved by the Dutch Ministry of Health, and all participants provided written informed consent. Two independent readers used semiautomated software to measure the volume of pulmonary nodules detected in 6774 participants aged 50-75 years (5917 men). Nodules were classified according to their location (purely intraparenchymal, pleural based, juxtavascular, or fissure attached), morphology (smooth, polylobulated, spiculated, or irregular), and size (<or=50 mm(3) or >50 mm(3)). The level of agreement was expressed by using the absolute values of the relative volume differences (RVDs). Multivariate logistic regression analysis was performed, and odds ratios (ORs) were computed to quantify the independent effects of morphology, location, and size on RVD categories.
RESULTS: Altogether, 4225 nodules in 2239 participants were included. Complete agreement in volume was obtained for 3646 (86%) of the nodules. Disagreement was small (absolute value of RVD < 5%) for 173 (4%) nodules, moderate (absolute value of RVD >or= 5% but < 15%) for 232 (6%), and large (absolute value of RVD >or= 15%) for 174 (4%). Multivariate analysis showed that the ORs of volume disagreement were 15.7, 3.1, and 1.9 for irregular, spiculated, and polylobulated nodules, respectively; 3.5, 2.6, and 2.1 for juxtavascular, pleural-based, and fissure-attached nodules, respectively; and 1.3 for large nodules compared with smooth, purely intraparenchymal, and small reference nodules.
CONCLUSION: Nodule morphology, location, and size influence volume measurement variability, particularly for juxtavascular and irregular nodules.

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Year:  2008        PMID: 18641255     DOI: 10.1148/radiol.2482070957

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


  24 in total

1.  The impact of radiologists' expertise on screen results decisions in a CT lung cancer screening trial.

Authors:  Marjolein A Heuvelmans; Matthijs Oudkerk; Pim A de Jong; Willem P Mali; Harry J M Groen; Rozemarijn Vliegenthart
Journal:  Eur Radiol       Date:  2014-11-04       Impact factor: 5.315

2.  Zone of transition: a potential source of error in tumor volume estimation.

Authors:  Lijuan Zhang; David F Yankelevitz; Claudia I Henschke; Artit C Jirapatnakul; Anthony P Reeves; Darryl Carter
Journal:  Radiology       Date:  2010-08       Impact factor: 11.105

3.  CT tumor volume measurement in advanced non-small-cell lung cancer: Performance characteristics of an emerging clinical tool.

Authors:  Mizuki Nishino; Mengye Guo; David M Jackman; Pamela J DiPiro; Jeffrey T Yap; Tak K Ho; Hiroto Hatabu; Pasi A Jänne; Annick D Van den Abbeele; Bruce E Johnson
Journal:  Acad Radiol       Date:  2010-10-30       Impact factor: 3.173

4.  Imaging-based observational databases for clinical problem solving: the role of informatics.

Authors:  Alex A T Bui; William Hsu; Corey Arnold; Suzie El-Saden; Denise R Aberle; Ricky K Taira
Journal:  J Am Med Inform Assoc       Date:  2013-06-17       Impact factor: 4.497

5.  Inter- and intrascanner variability of pulmonary nodule volumetry on low-dose 64-row CT: an anthropomorphic phantom study.

Authors:  X Xie; M J Willemink; Y Zhao; P A de Jong; P M A van Ooijen; M Oudkerk; M J W Greuter; R Vliegenthart
Journal:  Br J Radiol       Date:  2013-07-24       Impact factor: 3.039

6.  Three-dimensional analysis of pulmonary nodules: variability of semiautomated volume measurements between different versions of the same software.

Authors:  M F Rinaldi; T Bartalena; L Braccaioli; N Sverzellati; S Mattioli; E Rimondi; G Rossi; M Zompatori; G Battista; R Canini
Journal:  Radiol Med       Date:  2010-01-15       Impact factor: 3.469

7.  National lung screening trial: variability in nodule detection rates in chest CT studies.

Authors:  Paul F Pinsky; David S Gierada; P Hrudaya Nath; Ella Kazerooni; Judith Amorosa
Journal:  Radiology       Date:  2013-04-16       Impact factor: 11.105

Review 8.  Decision making in patients with pulmonary nodules.

Authors:  David E Ost; Michael K Gould
Journal:  Am J Respir Crit Care Med       Date:  2011-10-06       Impact factor: 21.405

9.  Lung nodule volumetry: segmentation algorithms within the same software package cannot be used interchangeably.

Authors:  H Ashraf; B de Hoop; S B Shaker; A Dirksen; K S Bach; H Hansen; M Prokop; J H Pedersen
Journal:  Eur Radiol       Date:  2010-03-20       Impact factor: 5.315

10.  Volumetric measurement of pulmonary nodules at low-dose chest CT: effect of reconstruction setting on measurement variability.

Authors:  Ying Wang; Geertruida H de Bock; Rob J van Klaveren; Peter van Ooyen; Wim Tukker; Yingru Zhao; Monique D Dorrius; Rozemarijn Vliegenthart Proença; Wendy J Post; Matthijs Oudkerk
Journal:  Eur Radiol       Date:  2009-11-18       Impact factor: 5.315

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