Literature DB >> 21512042

Improved detection of subtle lung nodules by use of chest radiographs with bone suppression imaging: receiver operating characteristic analysis with and without localization.

Feng Li1, Takeshi Hara, Junji Shiraishi, Roger Engelmann, Heber MacMahon, Kunio Doi.   

Abstract

OBJECTIVE: The purpose of this article is to evaluate radiologists' ability to detect subtle nodules by use of standard chest radiographs alone compared with bone suppression imaging used together with standard radiographs.
MATERIALS AND METHODS: The cases used in this observer study comprised radiographs of 72 patients with a subtle nodule and 79 patients without nodules taken from the Japanese Society of Radiological Technology nodule database. A new image-processing system was applied to the 151 radiographs to create corresponding bone suppression images. Two image reading sets were used with an independent test method. The first reading included half of the patients (a randomly selected subset A) showing only the standard image and the remaining half (subset B) showing the standard image plus bone suppression images. The second reading entailed the same subsets; however, subset A was accompanied by bone suppression images, whereas subset B was shown with only the standard image. The two image sets were read by three experienced radiologists, with an interval of more than 2 weeks between the sessions. Receiver operating characteristic (ROC) curves, with and without localization, were obtained to evaluate the observers' performance.
RESULTS: The mean value of the area under the ROC curve for the three observers was significantly improved, from 0.840 with standard radiographs alone to 0.863 with additional bone suppression images (p = 0.01). The area under the localization ROC curve was also improved with bone suppression imaging.
CONCLUSION: The use of bone suppression images improved radiologists' performance in the detection of subtle nodules on chest radiographs.

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Year:  2011        PMID: 21512042     DOI: 10.2214/AJR.10.4816

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  15 in total

1.  Improved detection of focal pneumonia by chest radiography with bone suppression imaging.

Authors:  Feng Li; Roger Engelmann; Lorenzo Pesce; Samuel G Armato; Heber Macmahon
Journal:  Eur Radiol       Date:  2012-07-05       Impact factor: 5.315

Review 2.  Potential clinical impact of advanced imaging and computer-aided diagnosis in chest radiology: importance of radiologist's role and successful observer study.

Authors:  Feng Li
Journal:  Radiol Phys Technol       Date:  2015-05-17

3.  Quantitative analysis of rib kinematics based on dynamic chest bone images: preliminary results.

Authors:  Rie Tanaka; Shigeru Sanada; Keita Sakuta; Hiroki Kawashima
Journal:  J Med Imaging (Bellingham)       Date:  2015-05-07

4.  [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

5.  Dose reduction and image quality improvement of chest radiography by using bone-suppression technique and low tube voltage: a phantom study.

Authors:  Satoshi Takagi; Tatsuya Yaegashi; Masayori Ishikawa
Journal:  Eur Radiol       Date:  2019-08-05       Impact factor: 5.315

6.  Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings.

Authors:  Sohee Park; Sang Min Lee; Kyung Hee Lee; Kyu-Hwan Jung; Woong Bae; Jooae Choe; Joon Beom Seo
Journal:  Eur Radiol       Date:  2019-11-20       Impact factor: 5.315

7.  Improved detection of solitary pulmonary nodules on radiographs compared with deep bone suppression imaging.

Authors:  Jiefang Wu; Weiguo Chen; Fengxia Zeng; Le Ma; Weimin Xu; Wei Yang; Genggeng Qin
Journal:  Quant Imaging Med Surg       Date:  2021-10

8.  A comparison of computer-aided detection (CAD) effectiveness in pulmonary nodule identification using different methods of bone suppression in chest radiographs.

Authors:  Ronald D Novak; Nicholas J Novak; Robert Gilkeson; Bahar Mansoori; Gunhild E Aandal
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

Review 9.  Multi-reader multi-case studies using the area under the receiver operator characteristic curve as a measure of diagnostic accuracy: systematic review with a focus on quality of data reporting.

Authors:  Thaworn Dendumrongsup; Andrew A Plumb; Steve Halligan; Thomas R Fanshawe; Douglas G Altman; Susan Mallett
Journal:  PLoS One       Date:  2014-12-26       Impact factor: 3.240

10.  X-ray Dark-field Radiography - In-Vivo Diagnosis of Lung Cancer in Mice.

Authors:  Kai Scherer; Andre Yaroshenko; Deniz Ali Bölükbas; Lukas B Gromann; Katharina Hellbach; Felix G Meinel; Margarita Braunagel; Jens von Berg; Oliver Eickelberg; Maximilian F Reiser; Franz Pfeiffer; Silke Meiners; Julia Herzen
Journal:  Sci Rep       Date:  2017-03-24       Impact factor: 4.379

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