(39 days)
Image Medical Acquisition Station (IMAS) is a PACS and teleradiology software application used to acquire digitized film images, add and modify patient and study demographics, and transmit the results to DICOM PACS systems, archives and workstations. IMAS is for hospitals, imaging centers, radiologist reading practices and any user who requires and is granted access to patient image, demographic and report information.
Image Medical Acquisition Station (IMAS) is for use in hospitals, imaging centers, radiologist reading practices and any user who requires and is granted access to patient image, demographic and report information.
Lossy compressed mammography images and digitized film screen mammography images must not be reviewed for primary image interpretations. Mammography images may only be interpreted using an FDA approved monitor that offers at least 5 Mpixel resolution and meets other technical specifications reviewed and accepted by FDA.
IMAS is a software application used to acquire image data from film digitizers and send it to DICOM-compliant devices. IMAS executes on a Microsoft Windows NT, 2000 and XP workstation that is connected to a film digitizer via a SCSI cable. When IMAS initializes, it obtains some settings information from the film digitizer, and displays a user interface. From the user interface, a user logs onto IMAS using an account ID and password. Once logged into IMAS, the user has the ability to create patient and study information, instruct the film digitizer to scan one or more sheets of film and download the image data, group the data from one or more films into a folder, and send the resulting information to one or more configured destinations via DICOM.
When IMAS receives the image data from the film digitizer, it appears on the workstation monitor for review. At this point, the user can reorient the image by flipping and rotating it, adjust the window and level setting, or apply a zoom factor to it. If the digitized image is of a sheet of film containing multiple images, the user can separate the image into one or more images by defining the area of each image and creating a new image from the data in the selected area.
The provided 510(k) summary for the eRAD/ImageMedical Corp., Image Medical Acquisition Station (IMAS) does not contain the detailed study information typically requested regarding acceptance criteria and performance validation.
The document primarily focuses on demonstrating substantial equivalence to predicate devices (iCRco's Xscan32 (K002911) and Merge/eFilm's eFilm Scan (K020995)) for the purpose of regulatory clearance. It states that "Extensive testing of the software package has been performed by programmers, by non-programmers, quality control staff, and by potential customers," but it does not elaborate on the specifics of this testing in a way that would allow for the completion of the requested table and study details.
Here's an attempt to answer the questions based only on the provided text, highlighting what is missing:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria (Implied) | Reported Device Performance (Implied) |
|---|---|
| Functionality similar to predicate devices: acquisition of image data from film digitizers, sending to DICOM-compliant devices, user interface for patient/study info, film scanning, grouping data, sending to destinations, image review functions (flip, rotate, adjust window/level, zoom, separate multi-image films). | "All of the functions IMAS performs are available in at least one of the listed substantially equivalent devices. In most cases, the function is available in all of them." |
| Software designed, developed, tested, and validated according to written procedures. | "ERAD/ImageMedical Corp., certifies that the Image Medical Acquisition Station (IMAS) software is designed, developed, tested and validated according to written procedures." |
| Production of diagnostic quality images and associated information. | "The software developed for this product is used to provide diagnostic quality images and associated information to the indented users." |
| No significant differences compared to predicate devices. | "There are no significant differences between IMAS and the collective functions of all the predicate devices." |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size: Not specified. The document only mentions "Extensive testing."
- Data Provenance: Not specified.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
- Not specified. The document mentions "programmers, non-programmers, quality control staff, and potential customers" performing testing, but does not identify them as "experts" establishing ground truth in a clinical sense, nor their qualifications.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not specified.
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 is not mentioned. This device is an acquisition station, not an AI-assisted diagnostic tool.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- This device is a software application for acquiring and transmitting images. Its performance is inherent in its ability to correctly perform these functions. The concept of "standalone performance" as it applies to an AI diagnostic algorithm does not directly translate here. The document implies its standalone functionality by stating it "acquires image data" and "sends it to DICOM-compliant devices."
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Not specified in a clinical sense. For this type of device (an image acquisition and transmission system), the "ground truth" would likely relate to the integrity and accuracy of the digital image representation compared to the original film, correct DICOM formatting, and successful transmission. The document does not detail how these aspects were validated.
8. The sample size for the training set
- Not applicable. This device is an image acquisition and communication software, not a machine learning or AI model that requires a training set.
9. How the ground truth for the training set was established
- Not applicable (as it's not an AI/ML device requiring a training set).
Conclusion based on the provided text:
The 510(k) summary for the IMAS device provides a high-level overview of its function and claims of substantial equivalence. It does not contain the detailed validation study information, specific acceptance criteria with quantitative metrics, sample sizes, or expert involvement typically found in submissions for diagnostic AI or more complex medical image analysis devices. The "validation and effectiveness" section merely states "extensive testing" was performed by various internal and external groups, without detailing the methodology or results of this testing. The focus is entirely on functional equivalence to existing cleared devices rather than a detailed performance study against a clinical ground truth.
§ 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).