(97 days)
Centricity Universal Viewer is a device that displays medical images and data from various imaging sources, and from other healthcare information sources. Medical images and data can be displayed, communicated, stored, and processed.
Typical users of this system are authorized healthcare professionals.
Centricity Universal Viewer is intended to assist in the viewing, analysis, diagnostic interpretation, and sharing of images and other information.
Mammography images may only be interpreted using a monitor compliant with requirements of local regulations and must meet other technical specifications reviewed and accepted by the local regulatory agencies.
Contraindications:
Centricity Universal Viewer is contraindicated for the use of lossy compressed mammographic images. Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations.
Centricity Universal Viewer is an Internet based medical image display and interpretation software product that is part of a picture archiving and communications system that assists radiologists and cardiologists in their diagnostic workflows. It provides users with capabilities relating to the acceptance, transfer, display, storage, and digital processing of medical images (including digital mammograms).
Centricity Universal Viewer provides APIs (Application Program Interfaces) to integrate with third-party medical devices and non-medical devices, which include integration with Tomtec-Arena™(K132544) for advanced cardiology applications.
Centricity Universal Viewer supports DICOM SOP classes to access and manage medical imaging studies from , Computed Tomography (CT), Magnetic Resonance (MR), Ultrasound (US), Nuclear Medicine (NM), Computerized Radiography (CR), Digital mammography (MG), Digital X-ray (DX), Positron Emission Tomography (PET/PT), X-Ray Angioaraphy (XA), Diaital Intra-oral X-Ray (IO), Radiofluoroscopic X-ray (RF), Secondary Capture Images (SC), Visible Light (VL) Endoscopic, Microscopic and Photographic Image Storage, Slide Coordinates Microscopic Image Storage, Presentation States (PS), Key Image Notes (KIN), and other DICOM imaging modalities.
Centricity Universal Viewer is not intended for the diagnosis of digital pathology images.
Centricity Universal Viewer is designed to be deployed over conventional TCP/IP networking infrastructure available in most healthcare organizations and utilizes commercially available computer platforms and operating systems.
The system does not produce any original medical images. All images located on the Centricity Universal Viewer have been received from DICOM compliant modalities and/or image acquisition systems.
The provided text is a 510(k) Summary for the GE Healthcare Centricity Universal Viewer. This document demonstrates substantial equivalence to a predicate device, rather than proving that the device meets specific acceptance criteria through a clinical study.
Therefore, many of the requested sections about acceptance criteria, study details, ground truth, and expert involvement are not applicable or cannot be extracted from this type of regulatory submission.
However, I can provide information based on what is available in the document:
1. A table of acceptance criteria and the reported device performance
This document does not describe specific numerical acceptance criteria or performance metrics for the Centricity Universal Viewer in the way one would find in a clinical performance study for an AI algorithm. Instead, it focuses on software verification and validation activities to ensure functional equivalence to a predicate device.
| Acceptance Criteria Category | Reported Device Performance (as described in the document) |
|---|---|
| Functional Equivalence | Demonstrated functional equivalence to predicate device (Centricity PACS-IW with Universal Viewer K123174) with specified modifications. |
| Software Quality Assurance | Complies with voluntary standards; applied quality assurance measures including Risk Analysis, Requirements Reviews, Design Reviews, Usability Analysis, Testing (unit, integration, performance, regression, system), and Simulated use testing (Validation). |
| Safety and Effectiveness | Information provided supports the device to be as safe, as effective and substantially equivalent to its predicate device. |
| Compliance | Software documentation provided at a moderate level of concern following FDA guidance. |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document does not specify a "test set" in the context of a clinical performance study with patient data. The testing mentioned (unit, integration, system, simulated use) refers to software engineering verification and validation activities. Therefore, details about sample size, data provenance, or retrospective/prospective nature are not available.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
Not applicable. The document describes software verification and validation, not a clinical study where ground truth would be established by experts.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. The document describes software verification and validation, not a clinical study requiring ground truth adjudication.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
No MRMC comparative effectiveness study is mentioned in this document. The device is a Picture Archiving and Communication System (PACS) viewer, not an AI-assisted diagnostic tool in the sense of providing specific interpretive recommendations. Its purpose is to display and process images for human interpretation.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This is not an AI algorithm acting in a standalone capacity. It is an image display and processing system intended for human-in-the-loop diagnostic interpretation.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable. Ground truth in the context of clinical performance evaluation is not discussed. Software validation focused on ensuring the system performs as designed and intended.
8. The sample size for the training set
Not applicable. This document describes a PACS viewer, not a machine learning or AI algorithm that requires a "training set" of data in the common sense.
9. How the ground truth for the training set was established
Not applicable, as there is no "training set" referenced for an AI/ML algorithm within this document.
§ 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).