Literature DB >> 16538152

Detection of small pulmonary nodules using direct digital radiography and picture archiving and communication systems.

Ning Wu1, Gordon Gamsu, Julianna Czum, Barry Held, Ravi Thakur, Gregory Nicola.   

Abstract

PURPOSE: To evaluate the detection of small pulmonary nodules, in the diameter range of 5.4 to 15 mm, using direct digital chest imaging and soft copy interpretation on picture archiving and communication systems.
MATERIALS AND METHODS: The results of clinical computed tomography (CT) scans of the thorax were retrospectively reviewed from our radiology information system and picture archiving and communication systems archives. Patients with CT studies containing between 1 and 6 nodules, who also had a digital chest examination within 1 month of the CT scan were selected. Thirty patients with suitable nodules and 30 without nodules were included and form the data base for this study. The nodules were between 5.4 and 15 mm in average diameter. Four separate observers independently viewed the frontal and lateral chest studies of the 60 patients. The presence or absence of nodules was determined. Data were analyzed with Kappa, McNemar and Fischer exact tests for agreement and differences between observers, nodule size, and nodule zone.
RESULTS: A total of 42 nodules between 5.4 and 15 mm were present. The overall detection rate for the 4 observers was 41.7%. For nodules between 5.4 and 8 mm the detection rate was 26.2%. Agreement between observer's detection was poor to moderate. Differences between observers for both nodule size and zone were not significant. Only 1 observer had a relationship between nodule detection and nodule size.
CONCLUSIONS: Observer detection of pulmonary nodules in the range of 5 to 15 mm using current digital radiography systems is not reliable in the confusing environment of the lung. Additional modification of these systems is required to increase nodule conspicuity.

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Year:  2006        PMID: 16538152     DOI: 10.1097/01.rti.0000203638.28511.9b

Source DB:  PubMed          Journal:  J Thorac Imaging        ISSN: 0883-5993            Impact factor:   3.000


  6 in total

1.  Automatic detection of follicular regions in H&E images using iterative shape index.

Authors:  K Belkacem-Boussaid; S Samsi; G Lozanski; M N Gurcan
Journal:  Comput Med Imaging Graph       Date:  2011-04-20       Impact factor: 4.790

2.  Analysis of the impact of digital tomosynthesis on the radiological investigation of patients with suspected pulmonary lesions on chest radiography.

Authors:  Emilio Quaia; Elisa Baratella; Stefano Cernic; Arianna Lorusso; Federica Casagrande; Vincenzo Cioffi; Maria Assunta Cova
Journal:  Eur Radiol       Date:  2012-04-27       Impact factor: 5.315

Review 3.  Comparison of digital tomosynthesis and chest radiography for the detection of pulmonary nodules: systematic review and meta-analysis.

Authors:  Jun H Kim; Kyung H Lee; Kyoung-Tae Kim; Hyun J Kim; Hyeong S Ahn; Yeo J Kim; Ha Y Lee; Yong S Jeon
Journal:  Br J Radiol       Date:  2016-10-19       Impact factor: 3.039

4.  Extraction of color features in the spectral domain to recognize centroblasts in histopathology.

Authors:  Kamel Belkacem-Boussaid; Olcay Sertel; Gerard Lozanski; Arwa Shana'aah; Metin Gurcan
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

5.  Histopathological image analysis for centroblasts classification through dimensionality reduction approaches.

Authors:  Evgenios N Kornaropoulos; M Khalid Khan Niazi; Gerard Lozanski; Metin N Gurcan
Journal:  Cytometry A       Date:  2013-12-26       Impact factor: 4.355

6.  Diagnostic imaging costs before and after digital tomosynthesis implementation in patient management after detection of suspected thoracic lesions on chest radiography.

Authors:  Emilio Quaia; Guido Grisi; Elisa Baratella; Roberto Cuttin; Gabriele Poillucci; Sara Kus; Maria Assunta Cova
Journal:  Insights Imaging       Date:  2014-01-14
  6 in total

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