Literature DB >> 17929026

Comparison of sensitivity and reading time for the use of computer-aided detection (CAD) of pulmonary nodules at MDCT as concurrent or second reader.

F Beyer1, L Zierott, E M Fallenberg, K U Juergens, J Stoeckel, W Heindel, D Wormanns.   

Abstract

The purpose of this study was to compare sensitivity for detection of pulmonary nodules in MDCT scans and reading time of radiologists when using CAD as the second reader (SR) respectively concurrent reader (CR). Four radiologists analyzed 50 chest MDCT scans chosen from clinical routine two times and marked all detected pulmonary nodules: first with CAD as CR (display of CAD results immediately in the reading session) and later (median 14 weeks) with CAD as SR (display of CAD markers after completion of first reading without CAD). A Siemens LungCAD prototype was used. Sensitivities for detection of nodules and reading times were recorded. Sensitivity of reading with CAD as SR was significantly higher than reading without CAD (p < 0.001) and CAD as CR (p < 0.001). For nodule size of 1.75 mm or above no significant sensitivity difference between CAD as CR and reading without CAD was observed; e.g., for nodules above 4 mm sensitivity was 68% without CAD, 68% with CAD as CR (p = 0.45) and 75% with CAD as SR (p < 0.001). Reading time was significantly shorter for CR (274 s) compared to reading without CAD (294 s; p = 0.04) and SR (337 s; p < 0.001). In our study CAD could either speed up reading of chest CT cases for pulmonary nodules without relevant loss of sensitivity when used as CR, or it increased sensitivity at the cost of longer reading times when used as SR.

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Mesh:

Year:  2007        PMID: 17929026     DOI: 10.1007/s00330-007-0667-1

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


  14 in total

1.  Automatic detection of pulmonary nodules at spiral CT: clinical application of a computer-aided diagnosis system.

Authors:  Dag Wormanns; Martin Fiebich; Mustafa Saidi; Stefan Diederich; Walter Heindel
Journal:  Eur Radiol       Date:  2001-09-29       Impact factor: 5.315

2.  Lung cancer: performance of automated lung nodule detection applied to cancers missed in a CT screening program.

Authors:  Samuel G Armato; Feng Li; Maryellen L Giger; Heber MacMahon; Shusuke Sone; Kunio Doi
Journal:  Radiology       Date:  2002-12       Impact factor: 11.105

3.  Pulmonary nodules at chest CT: effect of computer-aided diagnosis on radiologists' detection performance.

Authors:  Kazuo Awai; Kohei Murao; Akio Ozawa; Masanori Komi; Haruo Hayakawa; Shinichi Hori; Yasumasa Nishimura
Journal:  Radiology       Date:  2004-02       Impact factor: 11.105

4.  Lung micronodules: automated method for detection at thin-section CT--initial experience.

Authors:  Matthew S Brown; Jonathan G Goldin; Robert D Suh; Michael F McNitt-Gray; James W Sayre; Denise R Aberle
Journal:  Radiology       Date:  2003-01       Impact factor: 11.105

5.  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

Review 6.  [Computer-aided diagnosis and volumetry of pulmonary nodules: current concepts and future perspectives].

Authors:  K Marten; E J Rummeny; C Engelke
Journal:  Rofo       Date:  2005-02

7.  The potential contribution of a computer-aided detection system for lung nodule detection in multidetector row computed tomography.

Authors:  Jeong Won Lee; Jin Mo Goo; Hyun Ju Lee; Jong Hyo Kim; Seunghwan Kim; Youn Tae Kim
Journal:  Invest Radiol       Date:  2004-11       Impact factor: 6.016

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.  Indeterminate solitary pulmonary nodules revealed at population-based CT screening of the lung: using first follow-up diagnostic CT to differentiate benign and malignant lesions.

Authors:  Shodayu Takashima; Shusuke Sone; Feng Li; Yuichiro Maruyama; Minoru Hasegawa; Masumi Kadoya
Journal:  AJR Am J Roentgenol       Date:  2003-05       Impact factor: 3.959

10.  Patient-specific models for lung nodule detection and surveillance in CT images.

Authors:  M S Brown; M F McNitt-Gray; J G Goldin; R D Suh; J W Sayre; D R Aberle
Journal:  IEEE Trans Med Imaging       Date:  2001-12       Impact factor: 10.048

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  24 in total

1.  Detection of noncalcified pulmonary nodules on low-dose MDCT: comparison of the sensitivity of two CAD systems by using a double reference standard.

Authors:  A R Larici; M Amato; P Ordóñez; F Maggi; L Menchini; A Caulo; L Calandriello; G Vallati; S Giunta; M Crecco; L Bonomo
Journal:  Radiol Med       Date:  2012-02-10       Impact factor: 3.469

2.  Assessing operating characteristics of CAD algorithms in the absence of a gold standard.

Authors:  Kingshuk Roy Choudhury; David S Paik; Chin A Yi; Sandy Napel; Justus Roos; Geoffrey D Rubin
Journal:  Med Phys       Date:  2010-04       Impact factor: 4.071

3.  Evaluation of a method of computer-aided detection (CAD) of pulmonary nodules with computed tomography.

Authors:  G Foti; N Faccioli; M D'Onofrio; A Contro; T Milazzo; R Pozzi Mucelli
Journal:  Radiol Med       Date:  2010-06-23       Impact factor: 3.469

4.  High performance lung nodule detection schemes in CT using local and global information.

Authors:  Wei Guo; Qiang Li
Journal:  Med Phys       Date:  2012-08       Impact factor: 4.071

Review 5.  CAD (computed-aided detection) and CADx (computer aided diagnosis) systems in identifying and characterising lung nodules on chest CT: overview of research, developments and new prospects.

Authors:  F Fraioli; G Serra; R Passariello
Journal:  Radiol Med       Date:  2010-01-15       Impact factor: 3.469

6.  Computer aided detection and diagnosis in radiology.

Authors:  E Kotter; M Langer
Journal:  Eur Radiol       Date:  2011-01-11       Impact factor: 5.315

7.  Integration of fully automated computer-aided pulmonary nodule detection into CT pulmonary angiography studies in the emergency department: effect on workflow and diagnostic accuracy.

Authors:  Amirhossein Mozaffary; Tugce Agirlar Trabzonlu; Pamela Lombardi; Adeel R Seyal; Rishi Agrawal; Vahid Yaghmai
Journal:  Emerg Radiol       Date:  2019-07-27

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

Review 9.  Pulmonary quantitative CT imaging in focal and diffuse disease: current research and clinical applications.

Authors:  Mario Silva; Gianluca Milanese; Valeria Seletti; Alarico Ariani; Nicola Sverzellati
Journal:  Br J Radiol       Date:  2018-01-12       Impact factor: 3.039

10.  Computer-aided detection (CAD) of lung nodules in CT scans: radiologist performance and reading time with incremental CAD assistance.

Authors:  Justus E Roos; David Paik; David Olsen; Emily G Liu; Lawrence C Chow; Ann N Leung; Robert Mindelzun; Kingshuk R Choudhury; David P Naidich; Sandy Napel; Geoffrey D Rubin
Journal:  Eur Radiol       Date:  2009-09-16       Impact factor: 5.315

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