(54 days)
UDE software is intended to display images from CT, MR, CR, US, XA and SC for the trained physician 's diagnosis or referring purpose. UDE provides wireless and portable access to medical images. It is not intended to be used as, or to replace, a full diagnostic workstation or system and should be used only when there is no access to a workstation. This device is not to be used for mammography diagnosis.
UDE is a software device that can be installed on Apple iPad Pro. Through wireless network, user can login, query and display the images which are stored in heir existing UDE server. The device can be installed in iOS 9, 11, 12 and 13 version platform such as iPad /iPhone, but can't be installed in platforms other than iOS 9, 11, 12 and 13 version . The image display quality on iPad /iPhone will be almost the same as on iPad Pro when it is used for diagnosis purpose of CT, MR, US, XA and SC. However, if it is used for CR diagnosis purpose, we will strongly suggest that users should adopt iPad Pro. because the screen size of iPad Pro is larger than those of Apple® iPad/iPhone.
Main features of UDE are listed below
- Receive, Store, Retrieve, Display, and Process Digital Images(CT, MR, US, CR, Full- Field . Mammography, XA,SC etc.)
- · The displayed CT, MR, CR,, US,XA and SC images can be diagnosed by the trained physicians.
- . The displayed CT, MR, CR, Full- Field Mammography, US, XA and SC images can be referred by the trained physicians. Mammography images are not for diagnostic use
- · Communication log file
- · Auto delete old images (FIFO)
- · Overlay labels
- · User Authentication
- Display of Clinical Patient Data .
- Distance Calculation
- · layout adjustment (1×1, 2×1, 1×2, 2×2)
- · Pan
- Zoom
- Window Level
- · Cine Loop
- Mammography hanging protocol
Below is an analysis of the provided information, structured to address your request for acceptance criteria and study details.
Please note: The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device. As such, it often contains less detailed information about performance studies compared to a full clinical study report. The analysis below extracts all available information and explicitly states when information is not present in the provided text.
Acceptance Criteria and Study Details for UDE
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly state formal acceptance criteria with numerical targets for device performance based on a specific study. Instead, it refers to the device meeting "the acceptance criteria referred to medical image software quality request" and passing "all tests successfully" based on the AAPM Assessment of Display Performance for Medical Imaging Devices (2005) document.
| Performance Metric/Characteristic | Acceptance Criteria (Implicit/Referenced Standard) | Reported Device Performance |
|---|---|---|
| Software Quality | "Medical image software quality request" | Met and passed |
| Display Performance | AAPM Assessment of Display Performance for Medical Imaging Devices (2005) | All tests passed successfully |
| Substantial Equivalence | Equivalence to predicate device (EBM iDO Viewer K140399) in terms of safety and effectiveness, despite extended functionalities and different hardware. | Achieved (FDA clearance indicates this was met) |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: Not specified for either the software verification/validation or the display performance testing.
- Data Provenance:
- Software Verification/Validation: Unspecified, likely internal testing by the manufacturer (EBM Technologies Incorporated) in Taiwan (Republic of China).
- Display Performance: Unspecified, conducted by "a third party." No country of origin is specified for this third party.
- Retrospective or Prospective: Not specified. Given the nature of verification and validation testing, it would generally be considered prospective testing against design specifications.
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.
4. Adjudication Method for the Test Set
- No adjudication method is described. The document states that software verification and validation tests "had all met and passed" and display performance tests "had passed successfully." This suggests a direct comparison against established criteria or metrics rather than an expert adjudication process to establish ground truth.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- No, an MRMC comparative effectiveness study was not explicitly described or conducted for UDE to demonstrate improvement with AI vs. without AI assistance.
- Effect Size: Not applicable as no such study was performed or reported.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study
- Yes, for the referenced performance testing, the device was assessed on its own capabilities. The "display performance" testing evaluates the device's ability to render images according to a standard (AAPM document), which is a standalone evaluation of the device's display component. Similarly, "software verification testing and validation testing" are standalone evaluations of the software's functionality and adherence to quality requests.
- The device itself, UDE, is a display and PACS (Picture Archiving and Communications System) software. Its primary function is to display images for a physician's diagnosis or reference. It is not an AI algorithm designed to interpret images or generate diagnoses automatically. Therefore, the "standalone" performance here refers to its ability to display medical images accurately, comply with software quality standards, and perform its stated functions.
7. Type of Ground Truth Used
- Software Verification/Validation: The ground truth would be the pre-defined software requirements and design specifications that the software is intended to meet, and potentially expected outputs for given inputs.
- Display Performance: The ground truth would be the criteria and metrics defined in the "AAPM Assessment of Display Performance for Medical Imaging Devices (2005)" document, which specify the expected performance characteristics of a medical imaging display.
8. Sample Size for the Training Set
- Not applicable. UDE is a medical image display and PACS software, not a machine learning or AI model that requires a "training set" in the conventional sense of supervised learning. The software is developed based on engineering principles and tested against specifications.
9. How the Ground Truth for the Training Set Was Established
- Not applicable. As stated in point 8, there is no "training set" for this type of software.
§ 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).