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. 2025 Nov 4.
doi: 10.1007/s10278-025-01731-z. Online ahead of print.

Performance Comparison Between Two Versions of a Commercial Artificial Intelligence System for Chest Radiograph Interpretation: A Multicenter Study

Carolina Diaz Angulo  1 , Teodoro Martín-Noguerol  2 , Felix Paulano-Godino  2 , Laura Alonso De Caso García  2 , Antonio Luna  2
Affiliations

Performance Comparison Between Two Versions of a Commercial Artificial Intelligence System for Chest Radiograph Interpretation: A Multicenter Study

Carolina Diaz Angulo et al. J Imaging Inform Med. .

Abstract

The purpose of the study was to compare the diagnostic performance of version 1.5.0 and version 1.5.4 of Gleamer ChestView, a deep learning-based artificial intelligence system for chest X-ray analysis, across multiple thoracic findings. A retrospective multicenter study including 187 chest radiographs from six centers using equipment from four manufacturers (Agfa-Gevaert N.V., Mortsel, Belgium; IRay Technology Co., Ltd., Shanghai, China; LG Electronics Inc., Seoul, South Korea; Siemens Healthineers, Erlangen, Germany) was conducted. Inclusion criteria were chest radiographs acquired during the month following the implementation of version 1.5.0 of Gleamer ChestView. Each radiograph was analyzed by both versions. Ground truth was established through chest CT performed within a week of the radiograph when available (49 cases) and consensus by three board-certified general radiologists in the remaining 138 cases. Standard reference included 57 positive cases (pleural effusion, alveolar disease, mediastinal mass, pneumothorax, pulmonary nodule) and 130 normal studies. Performance metrics (sensitivity, specificity, precision, F1 score) were calculated for each version. A total of 187 chest radiographs were analyzed (101 females, 86 males; mean age 59.2 ± 19.7 years; range 15-95). Overall performance improved from version 1.5.0 to 1.5.4, with higher accuracy (87.7% vs 92.5%), precision (75.0% vs 85.2%), specificity (86.9% vs 93.1%), and F1 score (0.816 vs 0.881). For nodule detection, version 1.5.4 showed increased precision (47.8% to 73.3%) while maintaining sensitivity. Gleamer ChestView version 1.5.4 demonstrated improved lesion-specific performance compared to version 1.5.0, with fewer false positives and higher diagnostic confidence. These findings support the implementation of updated AI systems following systematic version-to-version validation.

Keywords: Artificial intelligence; Chest radiography; Computer-aided detection; Version comparison.

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Conflict of interest statement

Declarations. Ethics Approval: This study was conducted following the Declaration of Helsinki, and Institutional Review Board approval was obtained from all participating centers. Consent to Participate: Written informed consent was obtained from all participants for the use of clinical and imaging data for research purposes. Consent for Publication: The authors consent to the publication of the submitted article named “Performance Comparison Between Two Versions of a Commercial AI Tool for Chest Radiograph Interpretation: A Multicenter Study.” No human images have been added to the manuscript. Competing interests: The authors declare no competing interests.

References

    1. Akhter Y, Singh R, Vatsa M. AI-based radiodiagnosis using chest X-rays: A review. Front Big Data. 2023;6:1120989. https://doi.org/10.3389/fdata.2023.1120989 - DOI - PubMed - PMC
    1. Bennani S, Regnard NE, Ventre J, et al. Using AI to Improve Radiologist Performance in Detection of Abnormalities on Chest Radiographs. Radiology. 2023;309(3):e230860. https://doi.org/10.1148/radiol.230860 - DOI - PubMed
    1. Putha P, Tadepalli M, Reddy B, et al. Can Artificial Intelligence Reliably Report Chest X-Rays?: Radiologist Validation of an Algorithm trained on 2.3 Million X-Rays. Published online June 4, 2019. https://doi.org/10.48550/arXiv.1807.07455
    1. 510(k) Premarket Notification. Accessed May 1, 2025. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K241620
    1. Gleamer Receives FDA Clearance for ChestView - Gleamer. Accessed May 1, 2025. https://www.gleamer.ai/insights/gleamer-receives-fda-clearance-for-chest...