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syngo.via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options. syngo.via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S.

syngo.via is a software solution intended to be used for viewing, manipulation, communication, and storage of medical images. It can be used as a stand-alone device or together with a variety of cleared and unmodified syngo based software options. syngo.via supports interpretation and evaluation of examinations within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments. The system is not intended for the displaying of digital mammography images for diagnosis in the U.S. The system is a software only medical device. It defines minimum requirements to the hardware it runs on. The hardware itself is not seen as a medical device and not in the scope of this 510(k) submission. It supports the physician in diagnosis and treatment planning. syngo.via also supports storage of Structured DICOM Reports. In a comprehensive imaging suite syngo.via integrates Radiology Information Systems (RIS) to enable customer specific workflows. The predicate device, syngo.via allows for the use of a variety of advanced applications (clinical applications) These applications are medical devices on their own rights and filed separately. They are not part of this 510(k) submission and not part of the syngo.via medical device. syngo.via has a universal component called generic reader application which is part of this medical device and it allows no newly introduced imaging and post processing algorithms compared to the above mentioned predicate devices. syngo.via is based on Windows. Due to special customer requirements and the clinical focus syngo.via can be configured in the same way as the predicate device with different combinations of syngo- or Windows based software options and clinical applications which are intended to assist the physician in diagnosis and/or treatment planning. This includes commercially available post-processing software packages.

Here's an analysis of the provided 510(k) summary regarding acceptance criteria and supporting studies:

This 510(k) pertains to "syngo.via," a PACS system. Based on the document, this 510(k) is for enhanced functionalities of syngo.via, making it an update or extension of a previously cleared device (K123375). The key here is that it's not a new AI algorithm designed for a
specific diagnostic task with associated performance metrics. Instead, it seems to be primarily a software platform update that integrates functionalities already present in other cleared Siemens products.

Therefore, the typical structure for reporting AI/CADe/CADx device performance (sensitivity, specificity, AUROC, etc.) involving a test set, ground truth, and expert readers is not applicable in this submission. The "acceptance criteria" discussed are likely related to software verification and validation, adherence to standards, and demonstrating substantial equivalence to existing devices with similar functionalities.

1. Table of Acceptance Criteria and Reported Device Performance

As mentioned above, this 510(k) is for an enhanced PACS system and does not present specific diagnostic performance metrics. The "performance" is primarily demonstrated through compliance with standards and equivalence to predicate devices. There are no explicit quantitative acceptance criteria for diagnostic performance in terms of sensitivity, specificity, etc., as it's not a new diagnostic algorithm.

The "performance" described is in terms of:

• Software Functionality: Viewing, manipulation, communication, and storage of medical images.
• Integration: HL7-/DICOM-compatible RIS workflow.
• Technological Characteristics: Runs on Windows OS, supports DICOM images, image data compression (lossless and lossy).
• Imaging Algorithms (inherited/similar to predicates): MPR, MIP, MinIP, VRT, SSD, Digitally Reconstructed Radiograph, Editor functionality, Registration, Region Growing, Quantitative measurements.
• Automatic Spine Labeling (inherited/similar to predicates): Anatomy Labeling of Vertebra bodies, automatically suggested labels with manual override.

2. Sample size used for the test set and the data provenance

The document does not describe a "test set" in the context of diagnostic performance evaluation (e.g., a set of medical images used to evaluate an algorithm's diagnostic accuracy). The testing performed was software verification and validation testing at Unit, Integration, and System levels, as per IEC 62304. This type of testing uses various software inputs and configurations to ensure functional correctness, rather than a diagnostic image dataset. No specific sample size of images or data provenance (country, retrospective/prospective) is provided because it's not relevant for this type of submission.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

Not applicable. There was no diagnostic "test set" requiring expert ground truth for diagnostic accuracy evaluation.

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

Not applicable. There was no diagnostic "test set" requiring expert ground truth or adjudication.

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 510(k) does not present an MRMC study comparing human reader performance with and without AI assistance, as it is a PACS system enhancement, not a new AI-powered diagnostic tool.

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

Not applicable. This is not a standalone diagnostic algorithm. syngo.via is a platform for viewing, manipulation, communication, and storage of medical images, intended to "support the physician in diagnosis and treatment planning." The functionalities described (like automatic spine labeling) are features within this broader platform, and their performance is indicated as being similar to those from previously cleared predicate devices.

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

Not applicable. As there was no diagnostic test set in the traditional sense, there was no ground truth for diagnostic accuracy established through expert consensus, pathology, or outcomes data. The "ground truth" for the software's functional performance would be defined by the software requirements and design specifications, verified through testing procedures.

8. The sample size for the training set

Not applicable. This 510(k) does not describe a new AI algorithm that requires a training set. The enhanced functionalities are stated to have "similar technological characteristics as the predicate device" and incorporate "imaging and post processing algorithms compared to the above mentioned predicate devices." This implies that any underlying algorithms for features like "Automatic Spine Labeling" are either existing, well-established, or derived from components previously cleared, rather than newly developed and trained models.

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

Not applicable, as there is no mention of a training set for a new algorithm in this 510(k) submission.

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