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syngo.via MI Workflows are medical diagnostic applications for viewing, manipulation, 3D- visualization and comparison of medical images from multiple imaging modalities and/or multiple time-points. The apports functional data, such as PET or SPECT as well as anatomical datasets, such as CT or MR.

syngo.via MI Workflows enable visualization of information that would otherwise have to be visually compared disjointedly. syngo.via MI Workflows provide analytical tools to help the user assess, and document changes in morphological or functional activity at diagnostic and therapy follow-up examinations. syngo via MI Workflows can perform harmonization of SUV (PET) across different PET systems or different reconstruction methods.

syngo.via MI workflows support the interpretation of examinations and follow up documentation of findings within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology environments.

Note: The clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard practices and visual comparison of the separate unregistered images. syngo.via MI Workflows are a complement to these standard procedures.

The Scenium display and analysis software has been developed to aid the Clinician in the assessment and quantification of pathologies taken from PET and SPECT scans.

The software is deployed via medical imaging workplaces and is organized as a series of workflows which are specific to use with particular drug and disease combinations.

The software aids in the assessment of human brain scans enabling automated analysis through quantification of mean pixel values located within standard regions of interest. It facilitates comparison with existing scans derived from FDGPET, amyloid-PET, and SPECT studies, calculation of uptake ratios between regions of interest, and subtraction between two functional scans.

syngo.via MI Workflows is a software-only medical device which will be delivered on CD-ROM / DVD to be installed onto the commercially available Siemens syngo.via software platform (K191040) by trained service personnel.

syngo.via MI Workflows is a medical diagnostic application for viewing, manipulation, 3Dvisualization and comparison of medical images from multiple imaqinq modalities and/or multiple time-points. The application supports functional data, such as PET or SPECT as well as anatomical datasets, such as CT or MR. The images can be viewed in a number of output formats including MIP and volume rendering.

syngo.via MI Workflows enable visualization of information that would otherwise have to be visually compared disjointedly. syngo.via MI Workflows provide analytical tools to help the user assess, and document changes in morphological or functional activity at diagnostic and therapy follow-up examinations. They additionally support the interpretation and evaluation of examinations and follow up documentation of findings within healthcare institutions, for example, in Radiology (Oncology), Nuclear Medicine and Cardiology environments.

Scenium display and analysis software sits within the MI Neurology workflow within syngo.via MI Workflows. This software enables visualization and appropriate rendering of multimodality data, providing a number of features which enable the user to process acquired image data.

Scenium consists of four workflows:

• -Database Comparison
• -Striatal Analysis
• Cortical Analysis -
• -Subtraction

These workflows are used to assist the clinician with the visual evaluation, assessment and quantification of pathologies, such as dementia (i.e., Alzheimer's), movement disorders (i.e., Parkinson's) and seizure analysis (i.e., Epilepsy).

The modifications to the syngo.via MI Workflows and Scenium (MI Neurology) software (K173897 and K173597) include the following new features:

The provided text does not contain detailed information about specific acceptance criteria or a dedicated study proving the device meets those criteria. The document is a 510(k) summary for the syngo.via MI Workflows VB40A, Scenium device, primarily focusing on demonstrating substantial equivalence to a predicate device.

However, it does mention that "Verification and Validation activities have been successfully performed on the software package, including assurance that functions work as designed, performance requirements and specifications have been met, and that all hazard mitigations have been fully implemented. All testing has met the predetermined acceptance values." This generally indicates that internal testing was conducted against defined acceptance criteria, but these criteria and the detailed results are not explicitly stated.

Therefore, many of the requested details cannot be extracted from the provided text.

Here's what can be gathered, with limitations:

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

• Not explicitly provided. The document states "All testing has met the predetermined acceptance values," but does not list specific acceptance criteria or the quantitative performance metrics achieved.

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

• Not provided. The document does not discuss the sample size or provenance of data used for any performance testing.

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 provided. This information is absent from the text.

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

• Not provided. The document does not describe any adjudication methods.

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 provided. The document does not mention any MRMC comparative effectiveness studies or the impact of the device on human reader performance. The device is described as a diagnostic application for viewing, manipulation, 3D-visualization, and comparison, and its role is to "complement these standard procedures," but no specific reader studies are detailed.

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

• Not explicitly stated as a standalone study in the context of clinical performance. The device itself is software-only, meaning its "standalone" functionality is its core operation. However, the document does not present specific performance metrics that would be associated with a standalone algorithm performance study (e.g., sensitivity, specificity for a particular pathology detection). It focuses on the software's ability to view, manipulate, and analyze images, and that "All testing has met the predetermined acceptance values," implying functional and performance testing, but not necessarily a clinical standalone performance study in the way AI algorithms are often evaluated for diagnostic accuracy.

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

• Not provided. The document does not specify how ground truth was established for any testing.

8. The sample size for the training set

• Not provided. The document does not discuss any training sets, suggesting that this device might not involve a machine learning model that requires a distinct training phase in the traditional sense, or at least that information is not part of this 510(k) summary. Given the device's description as an "Image Processing Software" that provides "analytical tools," it's more likely rule-based or using established algorithms rather than a deep learning model requiring extensive training data.

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

• Not applicable / Not provided. As no training set information is given, this question cannot be answered.

In summary, the provided FDA 510(k) summary focuses on demonstrating substantial equivalence to predicate devices and adherence to quality systems and standards (ISO 14971, IEC 62304), rather than detailing specific clinical performance studies with acceptance criteria, ground truth, or reader study results. The statement about "All testing has met the predetermined acceptance values" is a general confirmation of internal verification and validation.

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syngo.via MI Workflows are medical diagnostic applications for viewing, manipulation, 3D- visualization and comparison of medical images from multiple imaging modalities and/or multiple time-points. The application supports functional data, such as PET or SPECT as well as anatomical datasets, such as CT or MR.

syngo.via MI Workflows enable visualization of information that would otherwise have to be visually compared disjointedly. syngo.via MI Workflows provide analytical tools to help the user assess, and document changes in morphological or functional activity at diagnostic and therapy follow-up examinations. syngo.via MI Workflows can perform harmonization of SUV (PET) across different PET systems or different reconstruction methods.

syngo.via MI workflows support the interpretation of examinations and follow up documentation of findings within healthcare institutions, for example, in Radiology, Nuclear Medicine and Cardiology envirents.

Note: The clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard practices and visual comparison of the separate unregistered images. syngo.via MI Workflows are a complement to these standard procedures.

The syngo.via MI Workflows are software only medical devices which will be delivered on CD-ROM / DVD to be installed onto the commercially available Siemens syngo.via software platform by trained service personnel.

syngo.via MI Workflows is a medical diagnostic application for viewing, manipulation, 3Dvisualization and comparison of medical images from multiple imaqinq modalities and/or multiple time-points. The application supports functional data, such as PET or SPECT as well as anatomical datasets, such as CT or MR. The images can be viewed in a number of output formats including MIP and volume rendering.

syngo.via MI Workflows enable visualization of information that would otherwise have to be visually compared disjointedly. synqo.via MI Workflows provide analytical tools to help the user assess, and document changes in morphological or functional activity at diagnostic and therapy follow-up examinations. They additionally support the interpretation and evaluation of examinations and follow up documentation of findings within healthcare institutions, for example, in Radiology (Oncology), Nuclear Medicine and Cardiology environments.

The provided text primarily focuses on the submission of a 510(k) premarket notification for syngo.via MI Workflows VB30A and its substantial equivalence to a predicate device (syngo.via MI Workflows VB20). It outlines the device's intended use, technological characteristics, and compliance with various regulatory standards.

However, the document does not contain the detailed information necessary to fully answer all parts of your request regarding acceptance criteria and a specific study proving the device meets those criteria. The text mentions that "Verification and Validation activities have been successfully performed on the software package," and "All testing has met the predetermined acceptance values," but it does not provide specific numerical acceptance criteria, reported performance values, sample sizes, ground truth establishment, or details of any comparative effectiveness studies.

Therefore, I cannot populate all sections of the table or provide detailed answers to items 2-9.

Here's what can be extracted and what is missing:

1. Table of acceptance criteria and the reported device performance

Missing Information: Specific numerical or qualitative acceptance criteria for particular features (e.g., accuracy of 3D visualization, quantification precision, speed of processing) and the actual reported performance values are not detailed in this document.

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

• Missing Information: The document states "Verification and Validation activities have been successfully performed," but does not provide any specifics about the sample size of the test set, the provenance of the data used for testing, or whether it was retrospective or prospective.

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)

• Missing Information: This information is not present in the provided text.

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

• Missing Information: This information is not present in the provided text.

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

• Missing Information: The document outlines the device as a "medical diagnostic application for viewing, manipulation, 3D-visualization and comparison of medical images" and explicitly states it is a "complement to these standard procedures." It does not describe any MRMC comparative effectiveness study, nor does it provide any effect size for human reader improvement with or without AI assistance. The device is software for image manipulation and viewing, not an AI for interpretation in the sense of directly assisting reader decisions, but rather providing tools.

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

• Missing Information: This document does not detail any standalone performance studies. The device is described as an application for viewing and manipulation, implying human interaction.

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

• Missing Information: This information is not present in the provided text.

8. The sample size for the training set

• Missing Information: The document describes the device as a software platform with new features added to a predicate device. It does not mention any "training set" in the context of machine learning, suggesting this is not a machine learning device that requires a training set in the typical sense.

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

• Missing Information: As no training set is mentioned in the context of machine learning, there is no information on how its ground truth would be established.

Summary of what the document does convey:

• The device (syngo.via MI Workflows VB30A) is a software-only medical device for medical image viewing, manipulation, 3D-visualization, and comparison from multiple modalities and time-points.
• It is an updated version of a predicate device (syngo.via MI Workflows VB20) with new features in specific workflows (MM Oncology, MI Neurology, MI Cardiology, MI Reading / SPECT Processing).
• It is intended to run on the Siemens syngo.via software platform.
• Siemens claims substantial equivalence to the predicate device and states that "no changes that raise any new issues of safety and effectiveness."
• Verification and validation activities were successfully performed, and all testing met predetermined acceptance values.
• The device complies with various recognized industry standards (ISO 14971, IEC 62304, NEMA PS 3.1 - 3.20, IEC 62366, ISO 15223-1).

Ask a specific question about this device