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Observer training for computer-aided detection of pulmonary nodules in chest radiography
OBJECTIVES: To assess whether short-term feedback helps readers to increase their performance using computer-aided detection (CAD) for nodule detection in chest radiography. METHODS: The 140 CXRs (56 with a solitary CT-proven nodules and 84 negative controls) were divided into four subsets of 35; ea...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3387360/ https://www.ncbi.nlm.nih.gov/pubmed/22447377 http://dx.doi.org/10.1007/s00330-012-2412-7 |
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author | De Boo, Diederick W. van Hoorn, François van Schuppen, Joost Schijf, Laura Scheerder, Maeke J. Freling, Nicole J. Mets, Onno Weber, Michael Schaefer-Prokop, Cornelia M. |
author_facet | De Boo, Diederick W. van Hoorn, François van Schuppen, Joost Schijf, Laura Scheerder, Maeke J. Freling, Nicole J. Mets, Onno Weber, Michael Schaefer-Prokop, Cornelia M. |
author_sort | De Boo, Diederick W. |
collection | PubMed |
description | OBJECTIVES: To assess whether short-term feedback helps readers to increase their performance using computer-aided detection (CAD) for nodule detection in chest radiography. METHODS: The 140 CXRs (56 with a solitary CT-proven nodules and 84 negative controls) were divided into four subsets of 35; each were read in a different order by six readers. Lesion presence, location and diagnostic confidence were scored without and with CAD (IQQA-Chest, EDDA Technology) as second reader. Readers received individual feedback after each subset. Sensitivity, specificity and area under the receiver-operating characteristics curve (AUC) were calculated for readings with and without CAD with respect to change over time and impact of CAD. RESULTS: CAD stand-alone sensitivity was 59 % with 1.9 false-positives per image. Mean AUC slightly increased over time with and without CAD (0.78 vs. 0.84 with and 0.76 vs. 0.82 without CAD) but differences did not reach significance. The sensitivity increased (65 % vs. 70 % and 66 % vs. 70 %) and specificity decreased over time (79 % vs. 74 % and 80 % vs. 77 %) but no significant impact of CAD was found. CONCLUSION: Short-term feedback does not increase the ability of readers to differentiate true- from false-positive candidate lesions and to use CAD more effectively. KEY POINTS: • Computer-aided detection (CAD) is increasingly used as an adjunct for many radiological techniques. • Short-term feedback does not improve reader performance with CAD in chest radiography. • Differentiation between true- and false-positive CAD for low conspicious possible lesions proves difficult. • CAD can potentially increase reader performance for nodule detection in chest radiography. |
format | Online Article Text |
id | pubmed-3387360 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-33873602012-07-11 Observer training for computer-aided detection of pulmonary nodules in chest radiography De Boo, Diederick W. van Hoorn, François van Schuppen, Joost Schijf, Laura Scheerder, Maeke J. Freling, Nicole J. Mets, Onno Weber, Michael Schaefer-Prokop, Cornelia M. Eur Radiol Chest OBJECTIVES: To assess whether short-term feedback helps readers to increase their performance using computer-aided detection (CAD) for nodule detection in chest radiography. METHODS: The 140 CXRs (56 with a solitary CT-proven nodules and 84 negative controls) were divided into four subsets of 35; each were read in a different order by six readers. Lesion presence, location and diagnostic confidence were scored without and with CAD (IQQA-Chest, EDDA Technology) as second reader. Readers received individual feedback after each subset. Sensitivity, specificity and area under the receiver-operating characteristics curve (AUC) were calculated for readings with and without CAD with respect to change over time and impact of CAD. RESULTS: CAD stand-alone sensitivity was 59 % with 1.9 false-positives per image. Mean AUC slightly increased over time with and without CAD (0.78 vs. 0.84 with and 0.76 vs. 0.82 without CAD) but differences did not reach significance. The sensitivity increased (65 % vs. 70 % and 66 % vs. 70 %) and specificity decreased over time (79 % vs. 74 % and 80 % vs. 77 %) but no significant impact of CAD was found. CONCLUSION: Short-term feedback does not increase the ability of readers to differentiate true- from false-positive candidate lesions and to use CAD more effectively. KEY POINTS: • Computer-aided detection (CAD) is increasingly used as an adjunct for many radiological techniques. • Short-term feedback does not improve reader performance with CAD in chest radiography. • Differentiation between true- and false-positive CAD for low conspicious possible lesions proves difficult. • CAD can potentially increase reader performance for nodule detection in chest radiography. Springer-Verlag 2012-03-25 2012 /pmc/articles/PMC3387360/ /pubmed/22447377 http://dx.doi.org/10.1007/s00330-012-2412-7 Text en © The Author(s) 2012 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Chest De Boo, Diederick W. van Hoorn, François van Schuppen, Joost Schijf, Laura Scheerder, Maeke J. Freling, Nicole J. Mets, Onno Weber, Michael Schaefer-Prokop, Cornelia M. Observer training for computer-aided detection of pulmonary nodules in chest radiography |
title | Observer training for computer-aided detection of pulmonary nodules in chest radiography |
title_full | Observer training for computer-aided detection of pulmonary nodules in chest radiography |
title_fullStr | Observer training for computer-aided detection of pulmonary nodules in chest radiography |
title_full_unstemmed | Observer training for computer-aided detection of pulmonary nodules in chest radiography |
title_short | Observer training for computer-aided detection of pulmonary nodules in chest radiography |
title_sort | observer training for computer-aided detection of pulmonary nodules in chest radiography |
topic | Chest |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3387360/ https://www.ncbi.nlm.nih.gov/pubmed/22447377 http://dx.doi.org/10.1007/s00330-012-2412-7 |
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