Literature DB >> 16763934

Computer-aided nodule detection on digital chest radiography: validation test on consecutive T1 cases of resectable lung cancer.

Shuji Sakai1, Hiroyasu Soeda, Naoki Takahashi, Takashi Okafuji, Tadamasa Yoshitake, Hidetake Yabuuchi, Ichiro Yoshino, Keiji Yamamoto, Hiroshi Honda, Kunio Doi.   

Abstract

PURPOSE: To evaluate the usefulness of a commercially available computer-assisted diagnosis (CAD) system on operable T1 cases of lung cancer by use of digital chest radiography equipment.
MATERIALS AND METHODS: Fifty consecutive patients underwent surgery for primary lung cancer, and 50 normal cases were selected. All cancer cases were histopathologically confirmed T1 cases. All normal individuals were selected on the basis of chest computed tomography (CT) confirmation and were matched with cancer cases in terms of age and gender distributions. All chest radiographs were obtained with one computed radiography or two flat-panel detector systems. Eight radiologists (four chest radiologists and four residents) participated in observer tests and interpreted soft copy images by using an exclusive display system without and with CAD output. When radiologists diagnosed cases as positives, the locations of lesions were recorded on hard copies. The observers' performance was evaluated by receiver operating characteristic analysis.
RESULTS: The overall detectability of lung cancer cases with CAD system was 74% (37/50), and the false-positive rate was 2.28 (114/50) false positives per case for normal cases. The mean A(z) value increased significantly from 0.896 without CAD output to 0.923 with CAD output (P = 0.018). The main cause of the improvement in performance is attributable to changes from false negatives without CAD to true positives with CAD (19/31, 61%). Moreover, improvement in the location of the tumor was observed in 1.5 cases, on average, for radiology residents.
CONCLUSION: This CAD system for digital chest radiographs is useful in assisting radiologists in the detection of early resectable lung cancer.

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Year:  2006        PMID: 16763934      PMCID: PMC3045164          DOI: 10.1007/s10278-006-0626-4

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  26 in total

1.  Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists' detection of pulmonary nodules.

Authors:  J Shiraishi; S Katsuragawa; J Ikezoe; T Matsumoto; T Kobayashi; K Komatsu; M Matsui; H Fujita; Y Kodera; K Doi
Journal:  AJR Am J Roentgenol       Date:  2000-01       Impact factor: 3.959

2.  Digital chest radiography: practical issues.

Authors:  Heber MacMahon
Journal:  J Thorac Imaging       Date:  2003-07       Impact factor: 3.000

3.  A comparison of conventional film, CR hard copy and PACS soft copy images of the chest: analyses of ROC curves and inter-observer agreement.

Authors:  Gwyneth C Weatherburn; Deborah Ridout; Nicola H Strickland; Peter Robins; Christine M Glastonbury; Walter Curati; Chris Harvey; Clair Shadbolt
Journal:  Eur J Radiol       Date:  2003-09       Impact factor: 3.528

Review 4.  Radiologic evaluation of the solitary pulmonary nodule.

Authors:  W R Webb
Journal:  AJR Am J Roentgenol       Date:  1990-04       Impact factor: 3.959

5.  Missed bronchogenic carcinoma: radiographic findings in 27 patients with a potentially resectable lesion evident in retrospect.

Authors:  J H Austin; B M Romney; L S Goldsmith
Journal:  Radiology       Date:  1992-01       Impact factor: 11.105

6.  CT screening for lung cancer: five-year prospective experience.

Authors:  Stephen J Swensen; James R Jett; Thomas E Hartman; David E Midthun; Sumithra J Mandrekar; Shauna L Hillman; Anne-Marie Sykes; Gregory L Aughenbaugh; Aaron O Bungum; Katie L Allen
Journal:  Radiology       Date:  2005-02-04       Impact factor: 11.105

7.  Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system.

Authors:  Shingo Kakeda; Junji Moriya; Hiromi Sato; Takatoshi Aoki; Hideyuki Watanabe; Hajime Nakata; Nobuhiro Oda; Shigehiko Katsuragawa; Keiji Yamamoto; Kunio Doi
Journal:  AJR Am J Roentgenol       Date:  2004-02       Impact factor: 3.959

Review 8.  What is early lung cancer? A review of the literature.

Authors:  Arifa Pasic; Pieter E Postmus; Thomas G Sutedja
Journal:  Lung Cancer       Date:  2004-09       Impact factor: 5.705

9.  Disparities in surgical resection of early-stage non-small cell lung cancer.

Authors:  Abdul R Jazieh; Mohammad J Kyasa; Goplan Sethuraman; John Howington
Journal:  J Thorac Cardiovasc Surg       Date:  2002-06       Impact factor: 5.209

Review 10.  Screening for lung cancer. A critique of the Mayo Lung Project.

Authors:  R S Fontana; D R Sanderson; L B Woolner; W F Taylor; W E Miller; J R Muhm; P E Bernatz; W S Payne; P C Pairolero; E J Bergstralh
Journal:  Cancer       Date:  1991-02-15       Impact factor: 6.860

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  11 in total

1.  Impact of a computer-aided detection (CAD) system integrated into a picture archiving and communication system (PACS) on reader sensitivity and efficiency for the detection of lung nodules in thoracic CT exams.

Authors:  Luca Bogoni; Jane P Ko; Jeffrey Alpert; Vikram Anand; John Fantauzzi; Charles H Florin; Chi Wan Koo; Derek Mason; William Rom; Maria Shiau; Marcos Salganicoff; David P Naidich
Journal:  J Digit Imaging       Date:  2012-12       Impact factor: 4.056

2.  Computer-aided diagnosis for improved detection of lung nodules by use of posterior-anterior and lateral chest radiographs.

Authors:  Junji Shiraishi; Feng Li; Kunio Doi
Journal:  Acad Radiol       Date:  2007-01       Impact factor: 3.173

3.  Integration of temporal subtraction and nodule detection system for digital chest radiographs into picture archiving and communication system (PACS): four-year experience.

Authors:  Shuji Sakai; Hidetake Yabuuchi; Yoshio Matsuo; Takashi Okafuji; Takeshi Kamitani; Hiroshi Honda; Keiji Yamamoto; Keiichi Fujiwara; Naoki Sugiyama; Kunio Doi
Journal:  J Digit Imaging       Date:  2007-03-01       Impact factor: 4.056

4.  Effect of multiscale processing in digital chest radiography on automated detection of lung nodule with a computer assistance system.

Authors:  Qian He; Wen He; Keyang Wang; Daqing Ma
Journal:  J Digit Imaging       Date:  2008-02-01       Impact factor: 4.056

5.  Does computer-aided diagnosis for lung tumors change satisfaction of search in chest radiography?

Authors:  Kevin S Berbaum; Robert T Caldwell; Kevin M Schartz; Brad H Thompson; E A Franken
Journal:  Acad Radiol       Date:  2007-09       Impact factor: 3.173

Review 6.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

Review 7.  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

8.  [Detection of lung nodules. New opportunities in chest radiography].

Authors:  S Pötter-Lang; S Schalekamp; C Schaefer-Prokop; M Uffmann
Journal:  Radiologe       Date:  2014-05       Impact factor: 0.635

Review 9.  Recent technological and application developments in computed tomography and magnetic resonance imaging for improved pulmonary nodule detection and lung cancer staging.

Authors:  Jessica C Sieren; Yoshiharu Ohno; Hisanobu Koyama; Kazuro Sugimura; Geoffrey McLennan
Journal:  J Magn Reson Imaging       Date:  2010-12       Impact factor: 4.813

10.  Edge map analysis in chest X-rays for automatic pulmonary abnormality screening.

Authors:  K C Santosh; Szilárd Vajda; Sameer Antani; George R Thoma
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-03-19       Impact factor: 2.924

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