Search Results
Found 3 results
510(k) Data Aggregation
(173 days)
Client Outlook Inc.
eUnity is a software application that displays medical image data and associated clinical reports to aid in diagnosis for healthcare professionals. It 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 provides 2D display, Multi-Planar Reformating and 3D visualization of medical image data, and mobile access to images.
eUnity displays both lossless and lossy compressed images. For lossy images, the medical professional user must determine if the level of loss is acceptable for their purposes. Display monitors or mobile devices used for reading medical images for diagnostic purposes must comply with applicable regulatory approvals and with quality control requirements for their use and maintenance. For mobile diagnostic usage when a full workstation is not available.
Mobile usage for mammography is for reference and referral only.
Client Outlook has developed eUnity to load, display and manipulate medical (DICOM) images within a web-browser without installing client software. eUnity is a server-based software solution that extends common web-browsers on the most popular operating systems into medical review stations; removing a technical barrier that had long been a key contributor to poor medical image access.
eUnity is an enterprise medical image viewer that provides access to full quality images from anywhere using nothing more than a standard web browser. Combined with a calibrated monitor, it can be used to make diagnostic decisions. Secure, fast, immediate access to information means less time spent searching for specialized workstations and supports greater efficiency for care, greater collaboration, and faster turnaround times.
This device is the successor to eUnity predicate (K161515) and adds the following functionality: MIP/MPR/3D and Mobile Diagnostic Use.
Here's a breakdown of the acceptance criteria and study information for the eUnity device based on the provided text, structured to answer your specific questions.
1. Table of Acceptance Criteria and Reported Device Performance
The provided document (K172490) is a 510(k) summary for a medical image processing software (eUnity). It's primarily a comparison document to demonstrate substantial equivalence to predicate devices rather than a detailed report of a performance study with numerical acceptance criteria. The "acceptance criteria" here are implied by the comparison to already cleared predicate devices and the statement that the device "meets its design requirements and intended use, and that it is safe and effective."
The capabilities added to the new eUnity version (K172490) are:
- MIP/MPR/3D functionality
- Mobile Diagnostic Use
The reported performance is qualitative and based on clinical validation:
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Functional Equivalence to Predicate for Existing Features: Demonstrates the same or similar essential features for visualization of radiological data. | The eUnity device (K172490) offers the same functionality as the K161515 eUnity device for existing features (e.g., Window Level, Rotate/Pan/Zoom, Multi-Study viewing, Measurement tools, Metadata display, etc.) (See Comparison Chart in the document). |
| Successful Implementation of New Features (MIP/MPR/3D): New 3D viewing capabilities are functionally similar to those in reference predicate devices. | The device adds MIP/MPR/3D functionality, which is compared to the Resolution MD (K133508) and Vue Motion (K151774) reference predicate devices, both of which have these features. The documentation does not provide a specific performance metric for these new features but implies their functionality is equivalent to the predicates. |
| Successful Implementation of Mobile Diagnostic Use: Enables diagnostic quality viewing on mobile devices. | "Additional Clinical Validation testing based on typical clinical workflows was performed by trained radiologists in comparison with an existing device and on several different hardware devices. ... There was consensus among all the Radiologists that the same diagnosis would be made on the mobile device with eUnity as on the predicate device in various lighting conditions." This suggests the mobile diagnostic capability was deemed diagnostically equivalent. The validated mobile devices include: iPhone 6 and higher, iPad Mini and higher, iPad Pro and higher, Samsung Galaxy Note 5 and higher, and Samsung Galaxy Tab E and higher. Additionally, a "Mobile Luminance Check" is implemented, requiring the user to determine lighting conditions prior to diagnosis. |
| Meets Design Requirements and Intended Use, Safe and Effective: Overall regulatory compliance and performance. | "designated individuals performed all verification and validation activities and results demonstrated that the device meets its design requirements and intended use, and that it is safe and effective." This is a general statement affirming the successful completion of internal V&V activities. The substantial equivalence argument itself serves as the primary "proof" of safety and effectiveness for a 510(k) device. |
2. Sample Size Used for the Test Set and the Data Provenance
- Test Set Sample Size: The document does not specify a numerical sample size (e.g., number of images, number of cases) for the "Additional Clinical Validation testing." It mentions "several different hardware devices" and testing "on several different hardware devices."
- Data Provenance: Not explicitly stated whether the data used for clinical validation was retrospective or prospective, nor its country of origin.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
- Number of Experts: The document states "multiple team members" performed verification and validation activities, and "trained radiologists" performed the clinical validation. It also notes "consensus among all the Radiologists." The exact number of radiologists involved is not specified, but it implies more than one.
- Qualifications of Experts: The experts are identified as "trained radiologists." No further details on their years of experience or specific subspecialties are provided.
4. Adjudication Method for the Test Set
- The document states, "There was consensus among all the Radiologists that the same diagnosis would be made on the mobile device with eUnity as on the predicate device in various lighting conditions." This indicates a consensus-based adjudication method, but the specific process (e.g., initial independent reads followed by a consensus meeting, voting, etc.) is not detailed. It implies that agreement was reached among the radiologists.
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, an MRMC comparative effectiveness study, particularly one measuring the improvement of human readers with AI assistance, was not conducted or reported. This device is a medical image viewing and processing software, not an AI-powered diagnostic aid. The clinical validation was a comparison of diagnostic capability on different platforms (mobile with eUnity vs. predicate device).
6. If a Standalone (i.e. algorithm only without human-in-the loop performance) Was Done
- No, a standalone (algorithm-only) performance study was not conducted as this device is a viewing platform and requires human interpretation for diagnosis. Its intended use states "a licensed medical practitioner reviews the output, providing ample opportunity for competent human intervention for the interpretation of images and information being displayed."
7. The Type of Ground Truth Used
- The ground truth for the clinical validation appears to be the diagnosis made using an existing predicate device/workstation. The test aimed to determine if "the same diagnosis would be made on the mobile device with eUnity as on the predicate device." This suggests the predicate's output served as the reference.
8. The Sample Size for the Training Set
- This document describes a 510(k) submission for a software that displays and manipulates medical images. It is not an AI/ML device in the sense of requiring a "training set" to learn diagnostic patterns. Therefore, there is no mention of a training set or its sample size. The software's functionality is based on established imaging principles and display technologies, not learned algorithms from a dataset.
9. How the Ground Truth for the Training Set Was Established
- Not applicable, as there is no "training set" for this type of medical device software.
Ask a specific question about this device
(166 days)
Client Outlook Inc.
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.
Ask a specific question about this device
(10 days)
CLIENT OUTLOOK INC
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, zoom, measurement and markup.
eUnity displays both lossless and 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.
Mammographic images and digitized film screen images must not be reviewed for primary image interpretations.
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, zoom, measurement and markup.
eUnity displays both lossless and lossy compressed images.
This looks like a 510(k) clearance letter for the device "eUnity," which is a Picture Archiving and Communications System (PACS). The provided document is primarily an FDA clearance letter and an Indications for Use form. It does not contain the detailed study information, acceptance criteria, or performance data that you are requesting.
Therefore, I cannot fulfill your request to describe the acceptance criteria and the study that proves the device meets them based only on the provided text. This information would typically be found in the 510(k) summary or the full premarket notification submission to the FDA, which is not included here.
The document states that the device is "substantially equivalent" to a legally marketed predicate device. This substantial equivalence determination often means that the device's technical characteristics and intended use are similar enough to an existing device that extensive new clinical studies to prove effectiveness and safety might not have been required, or that engineering bench tests and demonstrations of equivalence were sufficient.
To answer your questions, I would need access to the actual 510(k) submission document or a summary from the FDA's database that includes the performance data and study details.
Ask a specific question about this device
Page 1 of 1