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syngo.CT Single Source Dual Energy is designed to operate with CT images which have been acquired with Siemens Dual Spiral Single Source scanners. The various materials of an anatomical region of interest have different attenuation coefficients, which depend on the used energy. These differences provide information on the chemical composition of the scanned body materials. syngo.CT Single Source Dual Energy combines images acquired with low and high energy spectra to visualize this information. Depending on the region of interest, contrast agents may be used.

The functionality of the syngo.CT Single Source Dual Energy applications is as follows:

• · Monoenergetic
• · Monoenergetic Plus
• · Brain Hemorrhage
• · Liver VNC
• · Gout Evaluation
• Bone Marrow
• Rho/Z
• · Kidney Stones*)

*) Kidney Stones is designed to support the chemical composition of kidney stones and especially the differentiation between uric acid and non-uric acid stones. For full identification of the kidney stone additional clinical information should be considered such as patient history and urine testing. Only a well-trained radiologist can make the final diagnosis under consideration of all available information. The accuracy of identification is decreased in obese patients.

syngo.CT Single Source Dual Energy Software Package is a post processing application package consisting of several post processing application classes that can be used to improve visualization of various energy dependent materials in the human body. Different body regions require specific tools that allow for the correct evaluation of data sets. syngo.CT Single Source Dual Energy provides a range of application classes that meet the requirements of each evaluation type. The different application classes for the subject device can be combined into one workflow. A listing of device modifications is as follows:

• 1. New software version syngo.via VB10 (SOMARIS/8 VB10A) for the syngo.CT Single Source Dual Energy post processing application package to support the following features:
  • Addition of new application class Rho/Z .
  • Visualization of fat content (fat map) for application class Liver . VNC
  • 2. Modified Indication for Use to include features Rho/Z
  • 3. Modified Indication for Use to include reference to Dual Spiral Single Source Scanners

The subject device syngo.CT Single Source Dual Energy also supports the following unmodified post-processing application classes:

• . Monoenergetic
• Brain Hemorrhage ●
• o Gout Evaluation
• . Monoenergetic Plus
• o Bone Marrow
• o Kidney Stones

syngo.CT Single Source Dual Energy is designed to operate on the most recent version syngo.via client server platform which supports preprocessing and loading of datasets by syngo.via depending on configurable rules.

The provided text describes a 510(k) premarket notification for the "syngo.CT Single Source Dual Energy" device. The document focuses on establishing substantial equivalence to previously cleared predicate devices, rather than detailing a specific clinical study with acceptance criteria for device performance. As such, much of the requested information about acceptance criteria, detailed study design, and performance metrics is not explicitly present in the provided text.

However, based on the non-clinical testing summary, here's what can be extracted and inferred:

1. Table of Acceptance Criteria and Reported Device Performance

The document states:

• "The testing results support that all the software specifications have met the acceptance criteria."
• "The results of these tests demonstrate that the subject device performs as intended."
• "The result of all conducted testing was found acceptable to support the claim of substantial equivalence."

While these statements confirm that acceptance criteria were met, the specific quantitative criteria and detailed performance metrics are not provided in the given text. The tests were aimed at verifying the functionality of new features (Rho/Z, visualization of fat content for Liver VNC).

2. Sample Size Used for the Test Set and Data Provenance

The text states:

• "Phantom bench testing and retrospective analysis of available patient data was conducted for application classes Rho/Z and feature Fat Map."

• Sample Size for Test Set: Not specified.

• Data Provenance: Retrospective analysis of available patient data. No specific country of origin is mentioned, but the manufacturer is Siemens Medical Solutions USA, Inc. with a manufacturing facility in Germany, suggesting a likely European or US data source.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of those Experts

The document mentions for Kidney Stones evaluation: "Only a well-trained radiologist can make the final diagnosis under consideration of all available information." This suggests that clinical interpretation by radiologists is part of the diagnostic process, but it doesn't specify the number or specific qualifications of experts used to establish ground truth for the test set of this particular device functionality study.

4. Adjudication Method for the Test Set

Not specified in the provided text.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

The provided text does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done. The focus is on non-clinical testing and verification/validation, not human reader performance improvement with or without AI assistance.

6. Standalone Performance Study

The testing conducted was for "algorithm only without human-in-the loop performance" in the sense that the software's functionality was evaluated on phantoms and retrospective data. However, it's a post-processing application, meaning its output is intended for human interpretation. The study primarily confirmed the technical functionality of the new features (e.g., ability to calculate Rho/Z or visualize fat content), rather than a clinical outcome or diagnostic accuracy in isolation.

7. Type of Ground Truth Used

• For phantom bench testing: The ground truth would typically be known physical properties of the phantom materials.
• For retrospective analysis of available patient data: The ground truth would likely be established from existing clinical records, potentially including patient history, other imaging modalities, or pathology reports for conditions like kidney stones or liver fat. The exact method for establishing ground truth for the retrospective data is not explicitly stated.

8. Sample Size for the Training Set

The document does not mention a training set or its sample size. This suggests the nature of the evaluation was more focused on verifying the implementation and performance of the software's algorithms for specific analyses (like Rho/Z or fat mapping) rather than training a machine learning model.

9. How the Ground Truth for the Training Set Was Established

As no training set is mentioned, this information is not applicable/provided.

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