(14 days)
Beyondlmage Workstation is a software application that is used for viewing medical images, BeyondImage Workstation receives digital images and data from various sources (including but not limited to CT, MR, US, RF units, computed and digital radiographic devices). Images are stored, communicated, processed and displayed on the local disc of a workstation and/or across computer networks at distributed locations. Tasks that users may perform when viewing images include, but are not limited to adjustment of window width and center; image stacking; annotation and measurement of regions of interest; and inversion, rotation, and flips of images. It also provides standard Multi-Planar Reformation (MPR) views and 3D views of Volume Rendering for digital images from CT, MR, and PET unit. In addition, using BeyondImage Workstation, users can edit and print report. Beyondlmage Workstation cannot display and process mammograms.
Typical users of Beyondlmage Workstation are trained medical professionals, including but not limited to radiologists, clinicians, technologists, and others.
Beyondlmage Workstation is a software application that provides image viewing and manipulation in a diagnostic imaging setting. The functions of this application are applied to medical images that are acquired and stored on an image server in DICOM format. Beyondlmage Workstation can also transfer images in DICOM 3.0 format over a medical imaging network, as well as exporting images to applications in other proprietary formats.
BeyondImage Workstation cannot receive, display and process the images with non-DICOM3.0 format.
Beyondlmage Workstation cannot display and process mammograms.
The provided 510(k) summary (K092235) for the Neusoft BeyondImage Workstation does not contain any information about acceptance criteria or a study that proves the device meets specific performance criteria.
This 510(k) is a Traditional 510(k), which aims to demonstrate substantial equivalence to a legally marketed predicate device. In such cases, the primary focus is on comparing the new device's intended use, technological characteristics, and performance data (if any) to those of the predicate device(s). The document explicitly states: "We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent... to legally marketed predicate devices."
Therefore, I cannot provide the requested information. The document focuses on demonstrating substantial equivalence to existing PACS workstations (eFilm Workstation K012211 and Omni-Vue System K073062) rather than presenting a performance study with specific acceptance criteria for the BeyondImage Workstation itself.
To directly answer your questions based only on the provided text, the response would be as follows:
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A table of acceptance criteria and the reported device performance:
- Not found in the provided document. The document does not specify quantitative acceptance criteria or report specific performance metrics for the BeyondImage Workstation. It focuses on functional equivalence to predicate devices.
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Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
- Not applicable/Not found. The document does not describe a performance study with a test set.
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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 applicable/Not found. The document does not describe a performance study with a test set where ground truth was established by experts.
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Adjudication method (e.g. 2+1, 3+1, none) for the test set:
- Not applicable/Not found. The document does not describe a performance study with a test set.
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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. This device is a PACS workstation for viewing and manipulating images, not an AI-assisted diagnostic tool. No MRMC study is mentioned or relevant for this type of device.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not applicable/Not found. This is a workstation software, not an autonomous algorithm.
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The type of ground truth used (expert concensus, pathology, outcomes data, etc):
- Not applicable/Not found. The document does not describe a performance study requiring ground truth.
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The sample size for the training set:
- Not applicable/Not found. This device is a PACS workstation for displaying and manipulating images. It is not an AI/ML device that requires a training set in the typical sense for clinical performance.
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How the ground truth for the training set was established:
- Not applicable/Not found. As above, no training set or ground truth establishment is described.
In summary, the provided 510(k) documentation focuses entirely on demonstrating substantial equivalence through a comparison of intended use and technological characteristics with predicate devices, as is common for PACS systems. It does not include information on specific performance acceptance criteria or a dedicated study to meet such criteria.
§ 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).