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

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

• Monoenergetic
• Brain Hemorrhage
• Gout Evaluation
• Lung Vessels
• Heart PBV
• Bone Removal
• Lung Perfusion
• Liver VNC
• Monoenergetic Plus
• Virtual Unenhanced
• Bone Marrow
• Kidney Stones

*) Kidney Stones is designed to support the visualization of 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.

Dual energy offers functions for qualitative and quantitative evaluations. Dual energy CT can be used to improve the visualization of the chemical composition of various energy dependent materials in the human body when compared to single energy CT.

Depending on the organ of interest, the user can select and modify different application classes or parameters and algorithms. syngo.CT 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.

syngo.CT Dual Energy is a post processing software package 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. Similar to the predicate device (K083524, clearance date April 01, 2009), syngo.CT Dual Energy allows the evaluation of CT data acquired via spiral or sequence scans at two sufficiently different energy spectra (for example 80 kV and 140 kV) achieved with dual source CT scanners.

Here's a summary of the acceptance criteria and study information for the syngo.CT Dual Energy Software Package, based on the provided 510(k) summary:

Acceptance Criteria and Device Performance:

The provided 510(k) summary does not explicitly state quantitative acceptance criteria or detailed device performance metrics (e.g., accuracy, sensitivity, specificity) in a table format. It states that "The testing results supports that all the software specifications have met the acceptance criteria." and that "Testing for verification and validation of the device was found acceptable to support the claims of substantial equivalence."

The focus of the submission is on demonstrating substantial equivalence to predicate devices, rather than achieving specific performance targets for novel functionality.

Study Information:

1. Table of Acceptance Criteria and Reported Device Performance:

   Feature/Application	Acceptance Criteria	Reported Device Performance
   Overall Software Specifications	Met all specifications (implied)	All software specifications met, verification and validation acceptable.

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

   • Sample Size: Not explicitly stated. The document mentions "retrospective analysis of available patient data from several hospitals for all three new application classes (Monoenergetic Plus, Virtual Unenhanced, Bone Marrow)." It does not provide the number of patients or cases.
   • Data Provenance: Retrospective analysis from "several hospitals." The specific countries of origin are not mentioned.

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

   • Not specified. The document indicates that for Kidney Stones, "Only a well-trained radiologist can make the final diagnosis under consideration of all available information." This suggests expert involvement in clinical interpretations, but not the specific number or qualifications for establishing ground truth for the test set of the device's general functionality.

4. Adjudication Method for the Test Set:

   • Not specified.

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

   • No MRMC comparative effectiveness study is mentioned as having been performed. The submission focuses on substantial equivalence based on technical characteristics and functionality.

6. Standalone (Algorithm-Only) Performance Study:

   • Yes, implicitly. The document states that "Phantom bench tests have been conducted in the case of Monoenergetic Plus as well as a retrospective analysis of available patient data from several hospitals for all three new application classes." This testing of the software's performance on phantom data and retrospective patient data suggests a standalone evaluation of the algorithm's capabilities.

7. Type of Ground Truth Used:

   • For the "Monoenergetic Plus" application, phantom bench tests were used, suggesting a controlled physical model with known properties as ground truth.
   • For the three new application classes (Monoenergetic Plus, Virtual Unenhanced, Bone Marrow), retrospective analysis of available patient data was used. The specific nature of the ground truth for this patient data is not detailed (e.g., expert consensus, pathology, or clinical outcomes), but it would likely involve established clinical diagnoses or reference standards from the hospital records.
   • For "Kidney Stones," the indication for use specifies that "Only a well-trained radiologist can make the final diagnosis under consideration of all available information," implying that clinical judgment of experts serves as the ultimate ground truth for this specific application in practice.

8. Sample Size for the Training Set:

   • Not specified. The submission describes post-processing software and does not detail a separate training set or machine learning model development process that would typically involve a distinct training set size. The "retrospective analysis" mentioned primarily refers to testing/validation rather than training.

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

   • Not applicable, as a distinct training set for a machine learning model is not explicitly mentioned as part of the software's development or validation in this context. The document emphasizes technical characteristics and functionality compared to a predicate device.

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