Solid, part-solid, or non-solid? : classification of pulmonary nodules in low-dose chest computed tomography by a computer-aided diagnosis system
OBJECTIVES: The purpose of this study was to develop and validate a computer-aided diagnosis (CAD) tool for automatic classification of pulmonary nodules seen on low-dose computed tomography into solid, part-solid, and non-solid.
MATERIALS AND METHODS: Study lesions were randomly selected from 2 sites participating in the Dutch-Belgian NELSON lung cancer screening trial. On the basis of the annotations made by the screening radiologists, 50 part-solid and 50 non-solid pulmonary nodules with a diameter between 5 and 30 mm were randomly selected from the 2 sites. For each unique nodule, 1 low-dose chest computed tomographic scan was randomly selected, in which the nodule was visible. In addition, 50 solid nodules in the same size range were randomly selected. A completely automatic 3-dimensional segmentation-based classification system was developed, which analyzes the pulmonary nodule, extracting intensity-, texture-, and segmentation-based features to perform a statistical classification. In addition to the nodule classification by the screening radiologists, an independent rating of all nodules by 3 experienced thoracic radiologists was performed. Performance of CAD was evaluated by comparing the agreement between CAD and human experts and among human experts using the Cohen κ statistics.
RESULTS: Pairwise agreement for the differentiation between solid, part-solid, and non-solid nodules between CAD and each of the human experts had a κ range between 0.54 and 0.72. The interobserver agreement among the human experts was in the same range (κ range, 0.56-0.81).
CONCLUSIONS: A novel automated classification tool for pulmonary nodules achieved good agreement with the human experts, yielding κ values in the same range as the interobserver agreement. Computer-aided diagnosis may aid radiologists in selecting the appropriate workup for pulmonary nodules.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2015 |
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| Erschienen: |
2015 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:50 |
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| Enthalten in: |
Investigative radiology - 50(2015), 3 vom: 21. März, Seite 168-73 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Jacobs, Colin [VerfasserIn] |
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| Links: |
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| Themen: |
Clinical Trial |
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| Anmerkungen: |
Date Completed 21.10.2015 Date Revised 08.04.2022 published: Print Citation Status MEDLINE |
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| doi: |
10.1097/RLI.0000000000000121 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM244319561 |
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| 100 | 1 | |a Jacobs, Colin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Solid, part-solid, or non-solid? |b classification of pulmonary nodules in low-dose chest computed tomography by a computer-aided diagnosis system |
| 264 | 1 | |c 2015 | |
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| 500 | |a Date Completed 21.10.2015 | ||
| 500 | |a Date Revised 08.04.2022 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a OBJECTIVES: The purpose of this study was to develop and validate a computer-aided diagnosis (CAD) tool for automatic classification of pulmonary nodules seen on low-dose computed tomography into solid, part-solid, and non-solid | ||
| 520 | |a MATERIALS AND METHODS: Study lesions were randomly selected from 2 sites participating in the Dutch-Belgian NELSON lung cancer screening trial. On the basis of the annotations made by the screening radiologists, 50 part-solid and 50 non-solid pulmonary nodules with a diameter between 5 and 30 mm were randomly selected from the 2 sites. For each unique nodule, 1 low-dose chest computed tomographic scan was randomly selected, in which the nodule was visible. In addition, 50 solid nodules in the same size range were randomly selected. A completely automatic 3-dimensional segmentation-based classification system was developed, which analyzes the pulmonary nodule, extracting intensity-, texture-, and segmentation-based features to perform a statistical classification. In addition to the nodule classification by the screening radiologists, an independent rating of all nodules by 3 experienced thoracic radiologists was performed. Performance of CAD was evaluated by comparing the agreement between CAD and human experts and among human experts using the Cohen κ statistics | ||
| 520 | |a RESULTS: Pairwise agreement for the differentiation between solid, part-solid, and non-solid nodules between CAD and each of the human experts had a κ range between 0.54 and 0.72. The interobserver agreement among the human experts was in the same range (κ range, 0.56-0.81) | ||
| 520 | |a CONCLUSIONS: A novel automated classification tool for pulmonary nodules achieved good agreement with the human experts, yielding κ values in the same range as the interobserver agreement. Computer-aided diagnosis may aid radiologists in selecting the appropriate workup for pulmonary nodules | ||
| 650 | 4 | |a Clinical Trial | |
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Multicenter Study | |
| 650 | 4 | |a Randomized Controlled Trial | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 700 | 1 | |a van Rikxoort, Eva M |e verfasserin |4 aut | |
| 700 | 1 | |a Scholten, Ernst Th |e verfasserin |4 aut | |
| 700 | 1 | |a de Jong, Pim A |e verfasserin |4 aut | |
| 700 | 1 | |a Prokop, Mathias |e verfasserin |4 aut | |
| 700 | 1 | |a Schaefer-Prokop, Cornelia |e verfasserin |4 aut | |
| 700 | 1 | |a van Ginneken, Bram |e verfasserin |4 aut | |
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