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The Sectra Workstation is intended for the manipulation and displaying of medical images, including mammograms. It can show images from different modalities and interfaces to various image storage and printing devices using DICOM or similar interface standards.

Device options make possible mammography reading, telecommunications; fast demonstration; prosthesis CAD; 3-D and angiography, etc.; and teleconferencing.

Lossy compressed mammographic images are not intended for diagnostic review. Mammographic images should only be viewed with a monitor approved by FDA for viewing mammographic images.

For primary diagnosis, post process DICOM "for presentation" images must be used.

The Sectra Workstation is mainly a software product. It is used for visualization and processing of digital medical images. The Sectra Workstation is used as a client together with a Sectra provided server (Class I Exempt). The system runs on PCs under the Windows operating systems. Most notably two or more monitors are used.

The Sectra Workstation is a family of devices, including several workstations or types of workstations.

| Workstation

To handle specific user needs it is also possible to activate Sectra developed add-ons for the Sectra Workstation. An add-on is thus an additional feature set that can be used on the Sectra Workstation. There are add-ons on Sectra Workstation IDS5 but are included as ordinary features for IDS7. Examples:

The provided 510(k) summary for K063093, "Sectra Workstation," does not contain detailed information regarding acceptance criteria or a specific study proving device performance in the way described in your request.

This submission focuses primarily on demonstrating substantial equivalence to a predicate device (K051315, Sectra IDS5 Workstation) rather than presenting a detailed performance study with quantitative acceptance criteria. The document states that the device is "similar to the predicate device" and that "the device and the predicate device share the same certification or conformance to performance standards and both function as Image Processing System (LLZ)."

Therefore, most of the specific information requested cannot be extracted from this 510(k) document. Here's what can be inferred or explicitly stated:

1. A table of acceptance criteria and the reported device performance

The document does not provide a table of acceptance criteria or specific reported device performance metrics like sensitivity, specificity, accuracy, etc. for the software's image processing or display capabilities. It assumes equivalence based on its technological characteristics and intended use.

However, the general "acceptance criteria" can be inferred as meeting regulatory and technical standards, which are mentioned:

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

Not applicable. No specific test set or performance data related to clinical or diagnostic accuracy is presented. This 510(k) does not describe a clinical study.

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 applicable. No ground truth establishment is described as there is no clinical performance study presented. The device is a Picture Archiving and Communications System (PACS) workstation, primarily a display and manipulation tool for medical images, rather than an AI-driven diagnostic aid with its own independent diagnostic performance to be evaluated against ground truth.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

Not applicable. No adjudication method is described as there is no clinical performance study presented.

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 document describes a PACS workstation, not an AI-assisted diagnostic tool. No MRMC study or AI assistance is mentioned.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

Not applicable. This is a workstation for human users, not a standalone diagnostic algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

Not applicable. No ground truth is discussed as no clinical performance study is presented. The device serves to display images, and its "performance" is primarily defined by its ability to correctly handle and render these images according to DICOM and other technical standards, which are typically verified through engineering and software testing rather than clinical ground truth comparisons.

8. The sample size for the training set

Not applicable. Given this is a PACS workstation and not an AI/machine learning device, there is no concept of a "training set" in the context of this 510(k) submission.

9. How the ground truth for the training set was established

Not applicable. As there's no training set, there's no ground truth for a training set to be established.

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