| K-number | K241620 |
| Device name | ChestView US |
| Applicant | Gleamer Sas |
| Product code | MYN |
| Device class | Class II |
| Decision date | Feb 27, 2025 |
| Decision | Substantially Equivalent |
| Regulation | 892.2070 |
ChestView US is a radiological computer-assisted detection (CADe) software device that analyzes frontal and lateral chest X-rays to identify and mark suspicious regions of interest (ROIs) in four categories: Nodule, Pleural Space Abnormality, Mediastinum/Hila Abnormality, and Consolidation. It is intended for use as a concurrent reading aid for radiologists and emergency medicine physicians interpreting chest radiographs in adults, and does not replace clinical judgment or other diagnostic testing.
ChestView US uses supervised deep learning deployed on secure cloud-based infrastructure to process digital chest X-rays received from DICOM sources. Like its predicate Aorta-CAD, it analyzes chest radiographs using machine learning, displays results on PACS systems with bounding boxes around detected ROIs, and operates as a concurrent reading aid. The key difference is that ChestView US detects four ROI categories versus Aorta-CAD's two categories, but both share identical underlying technology, deployment platform, image source, and workflow integration.
Not stated in this summary. The document references FDA guidance on software documentation (Basic Documentation Level) and describes performance metrics (AUC, ROC curves, sensitivity, specificity) but does not cite specific ISO, IEC, ASTM, or other consensus standards.
Both ChestView US and Aorta-CAD are Class II medical image analyzers under 21 CFR 892.2070 that use supervised deep learning to detect and categorize ROIs on chest radiographs and present results as concurrent reading aids to physicians. Although ChestView US identifies four ROI types versus Aorta-CAD's two, the primary intended purpose of both devices is identical: to assist physicians by identifying and marking suspicious regions for further consideration. The technological characteristics—including imaging modality (X-ray), deployment platform (cloud-based), intended users (physicians), and workflow integration (PACS display)—are substantially similar. The difference in specific ROI categories does not constitute a new intended use or raise different safety and effectiveness questions, as both devices perform the same assistive function within chest radiograph interpretation.
View the full FDA submission: accessdata.fda.gov