Literature DB >> 20574707

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

G Foti1, N Faccioli, M D'Onofrio, A Contro, T Milazzo, R Pozzi Mucelli.   

Abstract

PURPOSE: The authors sought to compare the sensitivity and reading time obtained using computer-aided detection (CAD) software as second reader (SR) or concurrent reader (CR) in the identification of pulmonary nodules.
MATERIALS AND METHODS: Unenhanced CT scans of 100 consecutive cancer patients were retrospectively reviewed by four readers to identify all solid, noncalcified pulmonary nodules ranging from 3 to 30 mm in diameter. The sensitivity and reading time of each reader and of CAD alone were calculated at 3-mm and 5-mm thresholds with respect to the reference standard, consisting of a consensus reading by the four radiologists involved in the study. The McNemar test was used to compare the sensitivities obtained by reading without CAD (readers 1 and 2), with CAD as SR (readers 1 and 2 with a 2-month delay), and with CAD as CR (readers 3 and 4). The paired Student's t test was used to compare reading times. A value of p<0.05 was considered statistically significant.
RESULTS: A total of 258 and 224 nodules were identified at 3-mm and 5-mm thresholds, respectively. The sensitivity of CAD alone was 62.79% and 67.41% at the 3-mm and 5-mm threshold values respectively, with 4.15 and 2.96 false-positive findings per examination. CAD as SR produced a significant increase in sensitivity (p<0.001) in nodule detection with respect to reading without CAD both at 3 mm (12.01%) and 5 mm (10.04%); the average increase in sensitivity obtained when comparing CAD as SR to CAD as CR was statistically significant (p<0.025) both at the 3-mm (5.35%) and 5-mm (4.68%) thresholds. CAD as CR produced a nonsignificant increase in sensitivity compared with reading without CAD (p>0.05). Mean reading time using CAD as SR (330 s) was significantly longer than reading without CAD (135 s, p<0.001) and reading with CAD as CR (195 s, p<0.025).
CONCLUSIONS: The use of CAD as CR, without any significant increase in reading time, produces no significant increase in sensitivity in pulmonary nodule detection when compared with reading without CAD (p>0.05); CAD as SR, at the cost of longer reading times, increases sensitivity when compared with reading without CAD (p<0.001) or with CAD as CR (p<0.025).

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Year:  2010        PMID: 20574707     DOI: 10.1007/s11547-010-0556-6

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


  36 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.  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

3.  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

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

Review 5.  Current status and future potential of computer-aided diagnosis in medical imaging.

Authors:  K Doi
Journal:  Br J Radiol       Date:  2005       Impact factor: 3.039

6.  Performance evaluation of a computer-aided detection algorithm for solid pulmonary nodules in low-dose and standard-dose MDCT chest examinations and its influence on radiologists.

Authors:  M Das; G Mühlenbruch; S Heinen; A H Mahnken; M Salganicoff; S Stanzel; R W Günther; J E Wildberger
Journal:  Br J Radiol       Date:  2008-11       Impact factor: 3.039

Review 7.  Image-based evaluation of tumor response to treatment: where is radiology today?

Authors:  S Kharuzhyk; M Fabel; H von Tengg-Kobligk; H U Kauczor
Journal:  Exp Oncol       Date:  2008-09

8.  Evaluation of tumor measurements in oncology: use of film-based and electronic techniques.

Authors:  L H Schwartz; M S Ginsberg; D DeCorato; L N Rothenberg; S Einstein; P Kijewski; D M Panicek
Journal:  J Clin Oncol       Date:  2000-05       Impact factor: 44.544

Review 9.  Radiologic measurements of tumor response to treatment: practical approaches and limitations.

Authors:  Chikako Suzuki; Hans Jacobsson; Thomas Hatschek; Michael R Torkzad; Katarina Bodén; Yvonne Eriksson-Alm; Elisabeth Berg; Hirofumi Fujii; Atsushi Kubo; Lennart Blomqvist
Journal:  Radiographics       Date:  2008 Mar-Apr       Impact factor: 5.333

10.  Automated CT volumetry of pulmonary metastases: the effect of a reduced growth threshold and target lesion number on the reliability of therapy response assessment using RECIST criteria.

Authors:  Katharina Marten; Florian Auer; Stefan Schmidt; Ernst J Rummeny; Christoph Engelke
Journal:  Eur Radiol       Date:  2007-05-10       Impact factor: 7.034

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  3 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

Review 2.  Missed lung cancer: when, where, and why?

Authors:  Annemilia Del Ciello; Paola Franchi; Andrea Contegiacomo; Giuseppe Cicchetti; Lorenzo Bonomo; Anna Rita Larici
Journal:  Diagn Interv Radiol       Date:  2017 Mar-Apr       Impact factor: 2.630

3.  The impact of trained radiographers as concurrent readers on performance and reading time of experienced radiologists in the UK Lung Cancer Screening (UKLS) trial.

Authors:  Arjun Nair; Nicholas J Screaton; John A Holemans; Diane Jones; Leigh Clements; Bruce Barton; Natalie Gartland; Stephen W Duffy; David R Baldwin; John K Field; David M Hansell; Anand Devaraj
Journal:  Eur Radiol       Date:  2017-06-22       Impact factor: 5.315

  3 in total

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