(41 days)
Seno Advantage is a medical image review station that allows easy selection, processing, filming and media interchange of multi-modality images from a variety of diagnosis imaging systems. When interpreted by a trained physician, mammographic images displayed on the high-resolution monitors may be used as an element for diagnosis. Furthermore filmed images from all modalities may also be used as an element for diagnosis.
The Seno Advantage Workstation is a multi-modality review workstation. It includes a color flat panel for the multi-modality image review and two specific B&W high resolution monitors for the mammographic images review. Moreover, a dedicated keypad is provided to increase productivity. The Seno Advantage is positioned to be the system of choice for all users of Modality: CT, MR, XR, RF, XA, CR, DX, MG, NM, PET, US, SC. The Hardware configuration of Seno Advantage is the following: HP XW8000 Workstation, Monitors specifications (NEC Flat Panel 18.1" LCD, 2 Grayscale 5 Mpixels CRT), Seno Advantage supports the following image networking: Standard 10/100/1000 Base-T Ethernet Protocols supported: DICOM 3.0 Storage SCU/SCP and Query/Retrieve SCU/SCP, InSite, TCP/IP network layer, SdCNet supported to query/retrieve from AW 3.1 and AW 4.0.
This document is a 510(k) summary for the Seno Advantage, a medical image review workstation. The document primarily focuses on demonstrating substantial equivalence to a predicate device (Advantage Workstation 4.1, K020483). It describes the device's hardware, software, indications for use, and comparison with the predicate.
Here's an analysis of the provided text in relation to your questions regarding acceptance criteria and study information:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly state specific acceptance criteria or report device performance in a quantitative manner comparable to what might be expected for a diagnostic or AI device study. Instead, the "Conclusion" section states: "Seno Advantage provides images comparable to the predicate device." This implies an acceptance criterion of image comparability.
The submission is for a medical image review workstation, which is a viewing and processing device, not a diagnostic algorithm that generates a specific output that can be measured against ground truth in terms of sensitivity, specificity, etc. Therefore, performance a device that displays images is typically evaluated by demonstrating that the displayed images meet certain technical specifications (e.g., resolution, brightness, contrast) and are diagnostically acceptable for a trained physician. The document refers to the use of "high-resolution monitors" for mammographic images.
Reported Device Performance (Implicit):
- Image Comparability: "Seno Advantage provides images comparable to the predicate device." (This is the primary performance claim).
- Workflow Integration: "Seno Advantage brings additional features in order to integrate seamlessly into the Radiology Department Workflow."
- Risk Management: "The entire potential new hazards has been studied and controlled by a Risk Management Plan: A hazard analysis/ Risk Management Summary A software development and validation process A software verification plan." (This relates to safety and quality, not clinical performance metrics).
Table (Reconstructed based on implied criteria):
| Acceptance Criteria (Implied) | Reported Device Performance (Implied) |
|---|---|
| Images are diagnostically acceptable. | Provides images "comparable to the predicate device." |
| Image quality meets technical specifications. | Uses "high-resolution monitors" for mammographic images (2560x2048 pixels via 5 Mpixels CRT). |
| Device functions as a multi-modality review station. | Supports review of CT, MR, XR, RF, XA, CR, DX, MG, NM, PET, US, SC images. |
| Device integrates into workflow. | "brings additional features in order to integrate seamlessly into the Radiology Department Workflow." |
| Device is safe and effective. | Risk Management Plan, software development, and validation processes were followed. |
2. Sample size used for the test set and the data provenance
The document does not mention a specific test set, sample size of images, or data provenance (country of origin, retrospective/prospective) for evaluating image comparability or clinical performance. This type of detail is typical for devices that include diagnostic algorithms, which this workstation does not appear to be. The evaluation seems to be based on technical specifications and functional equivalence to the predicate.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. As no specific test set or clinical performance evaluation is described, there's no mention of experts or their qualifications for establishing ground truth. The device is a viewing workstation, and its primary claim is image comparability to a legally marketed predicate. The "indications for use" state that images are to be "interpreted by a trained physician," which implies that the human expert is the ultimate interpreter, not the device itself providing automated diagnoses.
4. Adjudication method for the test set
Not applicable. Without a test set and ground truth establishment process, there is no mention of an adjudication method.
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
Not applicable. This device is a viewing workstation, not an AI-assisted diagnostic tool. Therefore, an MRMC study comparing human readers with and without AI assistance was not performed and is not mentioned.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This device does not feature a standalone diagnostic algorithm. It is a workstation for human review of images.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not applicable. As this device is a workstation for viewing images and demonstrates substantial equivalence based on technical specifications and functionality, there is no discussion of ground truth derived from expert consensus, pathology, or outcomes data. The "ground truth" related to its function would be whether the images are displayed correctly and are diagnostically interpretable by a trained physician, which is implicitly covered by the claim of image comparability to the predicate.
8. The sample size for the training set
Not applicable. The document does not describe a training set as it is not a machine learning or AI-driven diagnostic device.
9. How the ground truth for the training set was established
Not applicable. As there is no described training set, there is no mention of how ground truth for such a set would be established.
§ 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).