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510(k) Data Aggregation
(196 days)
OMNI-VUE 2 SYSTEM
Omni-Vue 2™ System is a software device that receives digital images and data from various sources (e.g. CT scanners, MR scanners, ultrasound systems, R/F Units, computed & direct radiographic devices, secondary capture devices, scanners, imaging gateways or other imaging sources). Images and data can be stored, communicated, processed and displayed within the system and or across computer networks at distributed locations. Device options make possible reading (including mammography), telecommunications; fast demonstration; etc .; and teleconferencing.
Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretation. Mammographic images may only be interpreted using an FDA cleared monitor that meets technical specifications reviewed and accepted by FDA
Omni-Vue 2™ System makes possible the capturing, storage, distribution, manipulation, and networking of medical images at distributed locations. In cases where DICOM images are not directly available, the System can acquire medical images using a DICOM gateway, which generates DICOM-type files. For example, film digitizers obtain images from old film and convert them to meet DICOM standards and stored files are transmitted using a network and can be viewed or manipulated from an imaging workstation.
The provided K130374 510(k) summary for the Omni-Vue 2™ System details the device's characteristics and its substantial equivalence to a predicate device. However, it does not contain specific acceptance criteria, a detailed study proving the device meets these criteria, or information regarding sample sizes for test/training sets, ground truth establishment, or expert involvement as requested.
The document primarily focuses on establishing substantial equivalence by comparing the features of the Omni-Vue 2™ System to its predicate device, OmniVue, and demonstrating that any differences do not impact safety or efficacy. The "Nonclinical Testing" section mentions that "predetermined acceptance criteria were met" but does not specify what those criteria were or detail the studies performed to meet them.
Therefore, most of the requested information cannot be extracted from this document.
Here's what can be inferred or stated based on the provided text, with explicit notes where information is missing:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Not explicitly stated in the document) | Reported Device Performance (Implied from substantial equivalence claim) |
|---|---|
| Functionality equivalent to predicate device | Omni-Vue 2™ provides core PACS functionalities (DICOM Storage SCU/SCP, Q/R SCU/SCP, image manipulation, reporting, etc.) |
| Safety equivalent to predicate device | "The modification to the subject device does not raise any new potential safety risks." |
| Efficacy equivalent to predicate device | "The new device does not raise any new potential safety risks and is equivalent in performance to existing legally marketed devices." |
| Predetermined acceptance criteria for internal testing (details not provided) | "The complete system configuration has been assessed and tested at the factory and has passed all in-house testing criteria. ... Validation testing indicated that ... the predetermined acceptance criteria were met." |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: Not specified. The document mentions "nonclinical testing results" but does not provide details on the number of images or cases used in the testing.
- Data Provenance: Not specified. It doesn't mention country of origin or whether the data was retrospective or prospective.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified. The document generally states that "A physician, providing ample opportunity for competent human intervention interprets images and information being displayed and printed," but this refers to the intended use of the device, not the ground truth establishment for testing.
4. Adjudication Method for the Test Set
- Adjudication Method: Not specified.
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. This device is a PACS system, not an AI-assisted diagnostic tool, so such a study would not be applicable in this context.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) Was Done
- No standalone performance study is mentioned or applicable, as this is a software system intended for human interaction and interpretation.
7. The Type of Ground Truth Used
- Not specified. The document refers to "nonclinical testing results" and meeting "predetermined acceptance criteria" but does not elaborate on the nature of the ground truth used for these internal tests.
8. The Sample Size for the Training Set
- Not applicable. This document describes a Picture Archiving Communications System (PACS), which is a software device for managing and viewing medical images. It does not involve a machine learning algorithm that requires a training set.
9. How the Ground Truth for the Training Set Was Established
- Not applicable, as there is no training set for this type of device.
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