(91 days)
MammoWorkstation is designed to assist radiologists in conducting primary diagnostic review for diagnostic and screening mammography through flexible and interactive manipulation of multi-modality softcopy images.
It provides image review, manipulation, analysis, post-processing and printing capabilities that support image management display needs in the medical environment.
Mammo Workstation is designed to give easy and economic access to and display of multimodality softcopy images, structured reports, and CAD results through interfaces to various image storage devices using DICOM or similar interface standards. It supports creation of structured reports according to the DICOM breast imaging report templates.
Mammo Workstation supports teleradiology and teleconferencing providing access to multimodality softcopy images and structured reports in multiple locations within and outside the hospital.
Lossy compressed mammographic images must not be used for primary diagnostic interpretation unless approved for use in digital mammography.
Display monitors used for primary diagnostic interpretation of mammographic images must be approved for use in digital mammography.
All images sent to or imported in the Mammoworkstation must conform to regulatory requirements. Image quality must conform with applicable quality guidelines. All modalities must be certified for soft-copy reading.
The Mammo Workstation is a medical image review workstation software for diagnostic and screening mammography.
Mammoworkstation has the capability to review Digital Breast Tomosynthesis (DBT) images that are compatible with DICOM Breast Tomosynthesis Image Storage.
It is a software product.
The provided document is a 510(k) Premarket Notification Submission for the GE Healthcare MammoWorkstation. It describes the device's intended use and substantial equivalence to predicate devices. However, the document explicitly states that "The subject of this premarket submission, MammoWorkstation, did not require clinical studies to support substantial equivalence."
Therefore, the information required to populate the acceptance criteria and study details for device performance is not available in the provided text. The submission relies on non-clinical tests (risk analysis, requirements reviews, design reviews, various levels of testing like unit, integration, performance, safety, and simulated use testing) to demonstrate substantial equivalence to its predicate devices.
Here's a summary of what can be extracted based on the prompt's requirements, with explicit notation of what is not provided:
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Safety and Effectiveness through Substantial Equivalence | |
| (Implied criteria: Device attributes and performance are similar to legally marketed predicate devices) | "GE Healthcare considers the Mammo Workstation to be as safe, as effective, and performance is substantially equivalent to the predicate device(s)." |
| Compliance with Voluntary Standards | |
| (Implied criteria: Adherence to relevant industry and regulatory standards) | "The Mammo Workstation and its applications comply with voluntary standards as detailed in Section 9, 11 and 17 of this premarket submission." |
| Quality Assurance Measures Applied | |
| (Process-based criteria for development and testing) | Demonstrated through: Risk Analysis, Requirements Reviews, Design Reviews, Testing on unit level (Module verification), Integration testing (System verification), Performance testing (Verification), Safety testing (Verification), Simulated use testing (Validation). |
| Image Compatibility for Digital Breast Tomosynthesis (DBT) | |
| (Criteria: Ability to review and process DBT images) | "Mammoworkstation has the capability to review Digital Breast Tomosynthesis (DBT) images that are compatible with DICOM Breast Tomosynthesis Image Storage." |
| Image Quality Conformance | |
| (Criteria: All images conform to regulatory and quality guidelines) | "All images sent to or imported in the Mammoworkstation must conform to regulatory requirements. Image quality must conform with applicable quality guidelines." |
| Modalities Certification for Soft-copy Reading | |
| (Criteria: Hardware supporting the workstation is certified for diagnostic reading) | "All modalities must be certified for soft-copy reading." |
| Display Monitor Approval for Digital Mammography | |
| (Criteria: Monitors used for primary diagnosis must be approved) | "Display monitors used for primary diagnostic interpretation of mammographic images must be approved for use in digital mammography." |
2. Sample size used for the test set and the data provenance:
- Not provided. The document states that "MammoWorkstation, did not require clinical studies." Therefore, there is no test set with clinical data to report. Non-clinical testing was performed (e.g., unit, integration, performance, safety, simulated use testing) but details on specific test sets (e.g., number of images, type of data) are not included.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable/Not provided. As no clinical studies were performed requiring a test set with ground truth established by experts.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not applicable/Not provided. No clinical studies or test sets requiring expert adjudication were performed.
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 done. The document explicitly states "did not require clinical studies." This type of study would be a clinical study. The device is a "Medical imaging software" that is a "workstation" for review and analysis, not an AI CAD system claiming to improve human reader performance directly.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
- Not applicable/Not provided. Since this is a workstation software and not an AI algorithm for autonomous detection/diagnosis, a standalone performance study in that context would not be relevant. The submission focuses on the functionality and safety of the workstation itself.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
- Not applicable/Not provided. No clinical ground truth was established as no clinical studies were deemed necessary.
8. The sample size for the training set:
- Not applicable/Not provided. As no AI/CAD algorithm (that would require a training set) is the primary subject of clinical evaluation here. The device is a workstation.
9. How the ground truth for the training set was established:
- Not applicable/Not provided. No training set for an AI algorithm was used for clinical evaluation.
§ 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).