ArticleJournal of digital imaging2013
A comparison of computer-aided detection (CAD) effectiveness in pulmonary nodule identification using different methods of bone suppression in chest radiographs.
Article in Journal of digital imaging, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 26 citations in OpenAlex.
- A novel bone suppression algorithm in intensity-based 2D/3D image registration for real-time tumor motion monitoring: Development and phantom-based validation.Medical physics · 2022Article
- Article
- Improved detection of solitary pulmonary nodules on radiographs compared with deep bone suppression imaging.Quantitative imaging in medicine and surgery · 2021Article
- Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings.European radiology · 2020Article
- Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists.PLoS medicine · 2018Article
- Computer-aided Detection Fidelity of Pulmonary Nodules in Chest Radiograph.Journal of clinical imaging science · 2017Article
- A novel bone suppression method that improves lung nodule detection : Suppressing dedicated bone shadows in radiographs while preserving the remaining signal.International journal of computer assisted radiology and surgery · 2016Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aimed to compare the diagnostic effectiveness of computer-aided detection (CAD) software (OnGuard™ 5.2) in combination with hardware-based bone suppression (dual-energy subtraction radiography (DESR)), software-based bone suppression (SoftView™, version 2.4), and standard posteroanterior images with no bone suppression. A retrospective pilot study compared the diagnostic performance of two commercially available methods of bone suppression when used with commercially available CAD software. Chest images from 27 patients with computed tomography (CT) and pathology-proven malignant pulmonary nodules (8-34 mm) and 25 CT-negative patient controls were used for analysis. The Friedman, McNemar, and chi-square tests were used to compare diagnostic performance and the kappa statistic was used to evaluate method agreement. The average number of regions of interest and false-positives per image identified by CAD were not found to be significantly different regardless of the bone suppression methods evaluated. Similarly, the sensitivity, specificity, and test efficiency were not found to be significantly different. Agreement between the methods was between poor and excellent. The accuracy of CAD (OnGuard™, version 5.2) is not statistically different with either DESR or SoftView™ (version 2.4) bone suppression technology in digital chest images for pulmonary nodule identification. Low values for sensitivity (<80 %) and specificity (<50 %) may limit their utility for clinical radiology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.