Literature DB >> 15578184

Computer-assisted detection of pulmonary nodules: evaluation of diagnostic performance using an expert knowledge-based detection system with variable reconstruction slice thickness settings.

Katharina Marten1, Andreas Grillhösl, Tobias Seyfarth, Silvia Obenauer, Ernst J Rummeny, Christoph Engelke.   

Abstract

The purpose of this study was to evaluate the performance of a computer-assisted diagnostic (CAD) tool using various reconstruction slice thicknesses (RST). Image data of 20 patients undergoing multislice CT for pulmonary metastasis were reconstructed at 4.0, 2.0 and 0.75 mm RST and assessed by two blinded radiologists (R1 and R2) and CAD. Data were compared against an independent reference standard. Nodule subgroups (diameter >10, 4-10, <4 mm) were assessed separately. Statistical methods were the ROC analysis and Mann-Whitney U test. CAD was outperformed by readers at 4.0 mm (Az = 0.18, 0.62 and 0.69 for CAD, R1 and R2, respectively; P<0.05), comparable at 2.0 mm (Az = 0.57, 0.70 and 0.69 for CAD, R1 and R2, respectively), and superior using 0.75 mm RST (Az = 0.80, 0.70 and 0.70 and sensitivity = 0.74, 0.53 and 0.53 for CAD, R1 and R2, respectively; P<0.05). Reader performances were significantly enhanced by CAD (Az = 0.93 and 0.95 for R1 + CAD and R2 + CAD, respectively, P<0.05). The CAD advantage was best for nodules <10 mm (detection rates = 93.3, 89.9, 47.9 and 47.9% for R1 + CAD, R2 + CAD, R1 and R2, respectively). CAD using 0.75 mm RST outperformed radiologists in nodules below 10 mm in diameter and should be used to replace a second radiologist. CAD is not recommended for 4.0 mm RST.

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Year:  2004        PMID: 15578184     DOI: 10.1007/s00330-004-2544-5

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


  29 in total

1.  Computerized detection of pulmonary nodules on CT scans.

Authors:  S G Armato; M L Giger; C J Moran; J T Blackburn; K Doi; H MacMahon
Journal:  Radiographics       Date:  1999 Sep-Oct       Impact factor: 5.333

2.  Automated detection of lung nodules in CT scans: preliminary results.

Authors:  S G Armato; M L Giger; H MacMahon
Journal:  Med Phys       Date:  2001-08       Impact factor: 4.071

3.  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

4.  Computer-assisted detection of pulmonary nodules: performance evaluation of an expert knowledge-based detection system in consensus reading with experienced and inexperienced chest radiologists.

Authors:  Katharina Marten; Tobias Seyfarth; Florian Auer; Edzard Wiener; Andreas Grillhösl; Silvia Obenauer; Ernst J Rummeny; Christoph Engelke
Journal:  Eur Radiol       Date:  2004-07-03       Impact factor: 5.315

5.  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

6.  Characteristics of small lung cancers invisible on conventional chest radiography and detected by population based screening using spiral CT.

Authors:  S Sone; F Li; Z G Yang; S Takashima; Y Maruyama; M Hasegawa; J C Wang; S Kawakami; T Honda
Journal:  Br J Radiol       Date:  2000-02       Impact factor: 3.039

7.  Screening for early lung cancer with low-dose spiral CT: prevalence in 817 asymptomatic smokers.

Authors:  Stefan Diederich; Dag Wormanns; Michael Semik; Michael Thomas; Horst Lenzen; Nikolaus Roos; Walter Heindel
Journal:  Radiology       Date:  2002-03       Impact factor: 11.105

8.  Lung cancer screening with CT: Mayo Clinic experience.

Authors:  Stephen J Swensen; James R Jett; Thomas E Hartman; David E Midthun; Jeff A Sloan; Anne-Marie Sykes; Gregory L Aughenbaugh; Medy A Clemens
Journal:  Radiology       Date:  2003-01-24       Impact factor: 11.105

9.  Peripheral lung cancer: screening and detection with low-dose spiral CT versus radiography.

Authors:  M Kaneko; K Eguchi; H Ohmatsu; R Kakinuma; T Naruke; K Suemasu; N Moriyama
Journal:  Radiology       Date:  1996-12       Impact factor: 11.105

10.  How good is intercenter agreement in the identification of embolic signals in carotid artery disease?

Authors:  H Markus; J M Bland; G Rose; M Sitzer; M Siebler
Journal:  Stroke       Date:  1996-07       Impact factor: 7.914

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  17 in total

1.  Consensus versus disagreement in imaging research: a case study using the LIDC database.

Authors:  Dmitriy Zinovev; Yujie Duo; Daniela S Raicu; Jacob Furst; Samuel G Armato
Journal:  J Digit Imaging       Date:  2012-06       Impact factor: 4.056

2.  Value of axial and coronal maximum intensity projection (MIP) images in the detection of pulmonary nodules by multislice spiral CT: comparison with axial 1-mm and 5-mm slices.

Authors:  Ray Valencia; Timm Denecke; Lukas Lehmkuhl; Frank Fischbach; Roland Felix; Friedrich Knollmann
Journal:  Eur Radiol       Date:  2005-08-16       Impact factor: 5.315

3.  Insertion of virtual pulmonary nodules in CT data of the chest: development of a software tool.

Authors:  Hoen-oh Shin; Matthias Blietz; Bernd Frericks; Stefan Baus; Dagmar Savellano; Michael Galanski
Journal:  Eur Radiol       Date:  2006-07-04       Impact factor: 5.315

4.  Automated volumetry of pulmonary nodules on multidetector CT: influence of slice thickness, reconstruction algorithm and tube current. Preliminary results.

Authors:  A R Larici; M L Storto; M Torge; M Mereu; F Molinari; F Maggi; L Bonomo
Journal:  Radiol Med       Date:  2008-02-25       Impact factor: 3.469

5.  Pulmonary nodule detection on MDCT images: evaluation of diagnostic performance using thin axial images, maximum intensity projections, and computer-assisted detection.

Authors:  A Jankowski; T Martinelli; J F Timsit; C Brambilla; F Thony; M Coulomb; G Ferretti
Journal:  Eur Radiol       Date:  2007-09-01       Impact factor: 5.315

Review 6.  Computer-aided diagnosis of lung cancer and pulmonary embolism in computed tomography-a review.

Authors:  Heang-Ping Chan; Lubomir Hadjiiski; Chuan Zhou; Berkman Sahiner
Journal:  Acad Radiol       Date:  2008-05       Impact factor: 3.173

Review 7.  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

8.  A cloud-based computer-aided detection system improves identification of lung nodules on computed tomography scans of patients with extra-thoracic malignancies.

Authors:  Lorenzo Vassallo; Alberto Traverso; Michelangelo Agnello; Christian Bracco; Delia Campanella; Gabriele Chiara; Maria Evelina Fantacci; Ernesto Lopez Torres; Antonio Manca; Marco Saletta; Valentina Giannini; Simone Mazzetti; Michele Stasi; Piergiorgio Cerello; Daniele Regge
Journal:  Eur Radiol       Date:  2018-06-15       Impact factor: 5.315

9.  Inadequacy of manual measurements compared to automated CT volumetry in assessment of treatment response of pulmonary metastases using RECIST criteria.

Authors:  Katharina Marten; Florian Auer; Stefan Schmidt; Gerhard Kohl; Ernst J Rummeny; Christoph Engelke
Journal:  Eur Radiol       Date:  2005-12-06       Impact factor: 5.315

10.  Significance of pulmonary nodules in patients with colorectal cancer.

Authors:  Fabio Pomerri; Salvatore Pucciarelli; Isacco Maretto; Ernesta Perrone; Giovanna Pintacuda; Sara Lonardi; Donato Nitti; Pier Carlo Muzzio
Journal:  Eur Radiol       Date:  2012-04-01       Impact factor: 5.315

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