Literature DB >> 19018537

A comparison of six software packages for evaluation of solid lung nodules using semi-automated volumetry: what is the minimum increase in size to detect growth in repeated CT examinations.

Bartjan de Hoop1, Hester Gietema, Bram van Ginneken, Pieter Zanen, Gerard Groenewegen, Mathias Prokop.   

Abstract

We compared interexamination variability of CT lung nodule volumetry with six currently available semi-automated software packages to determine the minimum change needed to detect the growth of solid lung nodules. We had ethics committee approval. To simulate a follow-up examination with zero growth, we performed two low-dose unenhanced CT scans in 20 patients referred for pulmonary metastases. Between examinations, patients got off and on the table. Volumes of all pulmonary nodules were determined on both examinations using six nodule evaluation software packages. Variability (upper limit of the 95% confidence interval of the Bland-Altman plot) was calculated for nodules for which segmentation was visually rated as adequate. We evaluated 214 nodules (mean diameter 10.9 mm, range 3.3 mm-30.0 mm). Software packages provided adequate segmentation in 71% to 86% of nodules (p < 0.001). In case of adequate segmentation, variability in volumetry between scans ranged from 16.4% to 22.3% for the various software packages. Variability with five to six software packages was significantly less for nodules >or=8 mm in diameter (range 12.9%-17.1%) than for nodules <8 mm (range 18.5%-25.6%). Segmented volumes of each package were compared to each of the other packages. Systematic volume differences were detected in 11/15 comparisons. This hampers comparison of nodule volumes between software packages.

Entities:  

Mesh:

Year:  2008        PMID: 19018537     DOI: 10.1007/s00330-008-1229-x

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  16 in total

1.  Small pulmonary nodules: volumetrically determined growth rates based on CT evaluation.

Authors:  D F Yankelevitz; A P Reeves; W J Kostis; B Zhao; C I Henschke
Journal:  Radiology       Date:  2000-10       Impact factor: 11.105

2.  New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada.

Authors:  P Therasse; S G Arbuck; E A Eisenhauer; J Wanders; R S Kaplan; L Rubinstein; J Verweij; M Van Glabbeke; A T van Oosterom; M C Christian; S G Gwyther
Journal:  J Natl Cancer Inst       Date:  2000-02-02       Impact factor: 13.506

3.  Small pulmonary nodules: volume measurement at chest CT--phantom study.

Authors:  Jane P Ko; Henry Rusinek; Erika L Jacobs; James S Babb; Margrit Betke; Georgeann McGuinness; David P Naidich
Journal:  Radiology       Date:  2003-09       Impact factor: 11.105

4.  Volumetric measurements of pulmonary nodules at multi-row detector CT: in vivo reproducibility.

Authors:  Dag Wormanns; Gerhard Kohl; Ernst Klotz; Anke Marheine; Florian Beyer; Walter Heindel; Stefan Diederich
Journal:  Eur Radiol       Date:  2003-11-13       Impact factor: 5.315

5.  Guidelines for management of small pulmonary nodules detected on CT scans: a statement from the Fleischner Society.

Authors:  Heber MacMahon; John H M Austin; Gordon Gamsu; Christian J Herold; James R Jett; David P Naidich; Edward F Patz; Stephen J Swensen
Journal:  Radiology       Date:  2005-11       Impact factor: 11.105

6.  Automated volumetry of solid pulmonary nodules in a phantom: accuracy across different CT scanner technologies.

Authors:  Marco Das; Georg Mühlenbruch; Markus Katoh; Annemarie Bakai; Marcos Salganicoff; Sven Stanzel; Andreas H Mahnken; Rolf W Günther; Joachim E Wildberger
Journal:  Invest Radiol       Date:  2007-05       Impact factor: 6.016

7.  Pulmonary nodule volume: effects of reconstruction parameters on automated measurements--a phantom study.

Authors:  James G Ravenel; William M Leue; Paul J Nietert; James V Miller; Katherine K Taylor; Gerard A Silvestri
Journal:  Radiology       Date:  2008-05       Impact factor: 11.105

Review 8.  Computer-aided detection and automated CT volumetry of pulmonary nodules.

Authors:  Katharina Marten; Christoph Engelke
Journal:  Eur Radiol       Date:  2006-09-20       Impact factor: 5.315

9.  Statistical methods for assessing agreement between two methods of clinical measurement.

Authors:  J M Bland; D G Altman
Journal:  Lancet       Date:  1986-02-08       Impact factor: 79.321

10.  Small pulmonary nodules: evaluation with repeat CT--preliminary experience.

Authors:  D F Yankelevitz; R Gupta; B Zhao; C I Henschke
Journal:  Radiology       Date:  1999-08       Impact factor: 11.105

View more
  44 in total

1.  Evaluating the growth of pulmonary nodular ground-glass opacity on CT: comparison of volume rendering and thin slice images.

Authors:  Mingzhu Liang; Xueguo Liu; Weidong Li; Kunwei Li; Xiangmeng Chen; Guojie Wang; Kai Chen; Jinxin Zhang
Journal:  J Huazhong Univ Sci Technolog Med Sci       Date:  2011-12-16

2.  Adrenal gland volume measurement in septic shock and control patients: a pilot study.

Authors:  Stephanie Nougaret; B Jung; S Aufort; G Chanques; S Jaber; B Gallix
Journal:  Eur Radiol       Date:  2010-06-04       Impact factor: 5.315

3.  Return of the pulmonary nodule: the radiologist's key role in implementing the 2015 BTS guidelines on the investigation and management of pulmonary nodules.

Authors:  Richard N J Graham; David R Baldwin; Matthew E J Callister; Fergus V Gleeson
Journal:  Br J Radiol       Date:  2016-01-19       Impact factor: 3.039

4.  [Radiological evaluation of incidental pulmonary nodules].

Authors:  H Prosch; C Schaefer-Prokop
Journal:  Radiologe       Date:  2013-07       Impact factor: 0.635

5.  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

6.  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

7.  Volume estimation of low-contrast lesions with CT: a comparison of performances from a phantom study, simulations and theoretical analysis.

Authors:  Qin Li; Marios A Gavrielides; Rongping Zeng; Kyle J Myers; Berkman Sahiner; Nicholas Petrick
Journal:  Phys Med Biol       Date:  2015-01-02       Impact factor: 3.609

8.  Systematic analysis of bias and variability of texture measurements in computed tomography.

Authors:  Marthony Robins; Justin Solomon; Jocelyn Hoye; Ehsan Abadi; Daniele Marin; Ehsan Samei
Journal:  J Med Imaging (Bellingham)       Date:  2019-07-12

9.  Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases.

Authors:  Eui Jin Hwang; Jin Mo Goo; Jihye Kim; Sang Joon Park; Soyeon Ahn; Chang Min Park; Yeong-Gil Shin
Journal:  Eur Radiol       Date:  2017-01-03       Impact factor: 5.315

10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.