(166 days)
eUnity is a software application that displays medical image data and associated clinical reports. eUnity performs operations relating to the transfer, storage, display, and measurement of image data.
eUnity allows users to perform image manipulations, including window/level, rotation, measurement and markup. eUnity displays both lossy compressed images. For lossy images, the medical professional user must determine if the level of loss is acceptable for their purposes.
Display monitors used for reading medical images for diagnostic purposes must comply with applicable regulatory approvals and with quality control requirements for their use and maintenance.
eUnity is a software application that displays medical image data and associated clinical reports. eUnity performs operations relating to the transfer, storage, display, and measurement of image data.
eUnity allows users to perform image manipulations, including window/level, rotation, measurement and markup. eUnity displays both lossy compressed images. For lossy images, the medical professional user must determine if the level of loss is acceptable for their purposes.
This document is an FDA 510(k) clearance letter for a Picture Archiving and Communications System (PACS) software application called eUnity. It primarily focuses on the regulatory aspects of the device, declaring it substantially equivalent to a predicate device.
Crucially, this document does not contain information about the acceptance criteria and the study that proves the device meets those criteria, as typically required for AI/ML-driven medical devices.
The product, eUnity, is described as a software application that displays medical image data, performs operations related to transfer, storage, display, and measurement of image data, and allows for image manipulations. This description indicates it is a standard PACS viewer, not an AI/ML diagnostic or assistive device that would undergo rigorous performance testing against specific acceptance criteria.
Therefore, I cannot provide the requested information based on the provided text. The document does not discuss:
- Acceptance Criteria Table: No performance metrics or thresholds are mentioned.
- Study Details: No studies demonstrating performance against specific criteria are described.
- Sample Size: No information on test or training set sizes.
- Data Provenance: No details on the origin of data used for testing or training.
- Experts/Ground Truth: No mention of experts, ground truth establishment, or adjudication.
- MRMC Studies: No comparative effectiveness studies with human readers.
- Standalone Performance: No standalone performance metrics for an algorithm.
- Ground Truth Type: Not applicable, as this is a PACS viewer, not a diagnostic algorithm.
- Training Set Details: Not applicable.
The FDA's review for this device (a PACS viewer) likely focused on its ability to accurately display images, handle data, and ensure basic functionality equivalent to existing devices, rather than on the diagnostic performance of an AI algorithm.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).