(15 days)
ETIAM PACS Components™ is intended to be used by healthcare personnel to import, review, edit and send medical images.
ETIAM PACS Components™ is not labeled for diagnostic use.
ETIAM PACS Components™ is a device that receives medical images (including mammograms) and data from various imaging sources. Images and data can be stored, communicated, processed and displayed within the system or across computer networks at distributed locations.
Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that meets other technical specifications reviewed and accepted by FDA.
Typical users of this system are trained professionals, e.g. physicians, radiologists, nurses, medical technicians, and assistants.
ETIAM PACS Components™ are software applications that make possible the capturing, storage, distribution, and networking of medical images at distributed locations. In cases where DICOM images are not directly available to ETIAM PACS Components™, 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 in an archive. Stored files are transmitted using a network and can be viewed or manipulated from an imaging workstation.
The ETIAM PACS Components™ device did not undergo a clinical study as the manufacturer deemed it unnecessary to evaluate the safety or effectiveness. This determination was made because the device "only utilizes standard lossy (irreversible) compression techniques defined and supported by DICOM Standard" and the compression function must be activated by an administrator. Therefore, the information typically derived from such studies (like acceptance criteria, sample sizes, expert qualifications, etc.) is not available in the provided text.
The primary method for demonstrating safety and effectiveness was through non-clinical performance evaluations and a comparison to predicate devices, showing substantial equivalence in technological characteristics.
1. Table of Acceptance Criteria and Reported Device Performance
| Specification (Acceptance Criteria implied by comparison) | ETIAM PACS Components™ Performance |
|---|---|
| Comparison of multiple studies | YES |
| Measurements | YES |
| Annotation of images | YES |
| DICOM Query/Retrieve, DICOM Print Client | YES |
| JPEG lossy/lossless compression | YES |
| TWAIN interface | YES |
| Image file import | YES |
| Patient CD/DVD import | YES |
| Create Patient CD, DVD | YES |
| Export to memory stick | YES |
| Windows print | YES |
| Image export to image file or AVI video file | YES |
| Integration of direct interface to an automatic publisher for patient CD/DVD creation | YES |
| Review report (SR formats) | YES |
| Manipulating images | YES |
| Interface to RIS worklist or DICOM Archive | YES |
| Video capture interface | YES |
| Digitize film | YES |
| Edit patient demographics | YES |
2. Sample size used for the test set and the data provenance: Not applicable, as no clinical test set was used for performance validation. Non-clinical performance was validated through "test bench" activities.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as no clinical test set was used for performance validation.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable, as no clinical test set was used for performance validation.
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. The device is a PACS component, not an AI-assisted diagnostic tool. No MRMC study was performed.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: The device itself is a standalone software product for managing medical images. Its performance was assessed through non-clinical bench testing.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable for the clinical performance, as none was conducted scientifically. For non-clinical performance, the "ground truth" would be the expected functionality and output based on design specifications and DICOM standards.
8. The sample size for the training set: Not applicable, as no AI/machine learning component is described that would require a training set.
9. How the ground truth for the training set was established: Not applicable, as no AI/machine learning component is described.
§ 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).