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syngo.CT Dual Energy is designed to operate with CT images based on two different X-ray spectra.

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 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 general functionality of the syngo.CT Dual Energy application is as follows:

• · Monoenergetic 1)
• · Brain Hemorrhage
• · Gout Evaluation
• · Lung Vessels
• · Heart PBV
• · Bone Removal
• · Lung Perfusion
• · Liver VNC
• · Monoenergetic Plus 1)
• · Virtual Unenhanced 1)
• Bone Marrow
• · Hard Plaques
• Rho/Z
• · Kidney Stones 2)
• · SPR (Stopping Power Ratio)
• · SPP (Spectral Post-Processing Format) 1)
• · Optimum Contrast 1)

The availability of each feature depends on the Dual Energy scan mode.

1. This functionality supports data from Photon-Counting CT scanners.

2. Kidney Stones is designed to support the visualization of the chemical composition of kidney stones and especially the differentiation between 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 upon consideration of all available information. The accuracy of identification is decreased in obese patients.

Dual energy offers functions for qualitative and quantitative post-processing evaluations. syngo.CT Dual Energy is a post-processing application consisting of several post-processing application classes that 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.

Different body regions require specific tools that allow the correct evaluation of data sets. syngo.CT 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.

Based on the provided text, the acceptance criteria and the study proving the device meets these criteria can be summarized as follows:

The document describes software verification and validation, non-clinical testing, and an evaluation of specific application classes for Photon Counting Data. However, it does not provide a quantitative table of acceptance criteria for specific performance metrics (e.g., sensitivity, specificity, accuracy) or detailed clinical study results with human readers (MRMC study). The testing described focuses on technical performance and consistency with expected phantom values and visual comparison with clinical data, rather than diagnostic accuracy or clinical effectiveness in a human-in-the-loop setting.

Here's a breakdown of the available information:

1. Acceptance Criteria and Reported Device Performance

The document states that "all software specifications have met the acceptance criteria" and "The testing results support that all the software specifications have met the acceptance criteria." However, the document does not explicitly list the specific acceptance criteria in a table format with corresponding reported device performance values for metrics like accuracy, sensitivity, or specificity.

Instead, the performance data provided focuses on:

• Software Verification and Validation: Conformance with "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices," risk analysis completion, and mitigation of identified hazards.
• Non-Clinical Testing: Integration and functional tests were conducted to demonstrate the ability of included features. "The results of these tests demonstrate that the subject device performs as intended."
• Evaluation of application classes for Photon Counting Data:
  • Monoenergetic Plus application class: "calculated values from phantom scans agreed well with the expected ones. Clinical data showed no artifacts. The iodine contrast clearly increased with lower keV settings and decreased with higher ones."
  • Virtual Unenhanced application class: "demonstrated that virtual non-contrast images and iodine concentration can be calculated from spectral data acquired at the NAEOTOM Alpha." In phantom scans, "the measured iodine concentration agrees well with the known iodine concentration. The VNC values are good approximations of the expected water value for all tested iodine concentrations." In clinical data, "the image impression of the virtual non-contrast images was compared with true non-contrast images. Measurements showed good agreement of CT values in the VNCs with the values in the TNCs."

No quantitative performance metrics (e.g., sensitivity, specificity, AUC) or a direct comparison to specific numerical acceptance criteria are provided in the document.

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

The document mentions "phantom scans" and "clinical data" for the evaluation of the Monoenergetic Plus and Virtual Unenhanced application classes.

• Phantom Scans: "Multi-Energy CT Phantom (Sun Nuclear Corporation, Melbourne, Florida, USA) was scanned at a NAETOM Alpha."
• Clinical Data: Used for visual comparison and measurement of CT values. The text refers to "clinical data" in general without specifying the sample size (number of patients/cases).
• Data Provenance: Not specified (e.g., country of origin). The data from the NAETOM Alpha appears to be prospectively acquired for testing purposes. It is not stated whether the clinical data used for comparison was retrospective or prospective.

3. Number of Experts Used to Establish Ground Truth and Qualifications

The document mentions that for the Kidney Stones feature, "Only a well-trained radiologist can make the final diagnosis upon consideration of all available information." However, it does not specify the number of experts used to establish ground truth for the test set or their specific qualifications (e.g., years of experience, subspecialty) for the evaluations described (phantom studies or clinical data comparisons).

4. Adjudication Method for the Test Set

The document does not describe any formal adjudication method (e.g., 2+1, 3+1 consensus) for establishing ground truth for the "clinical data" used. The evaluations seem to rely on technical comparisons for phantom data and general observation/measurement agreement for clinical data.

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

No MRMC comparative effectiveness study was conducted or reported. The submission focuses on technical validation and comparison of the device's outputs to expected values and impressions, rather than measuring human reader performance with and without AI assistance.

6. Standalone (Algorithm Only) Performance Study

The study appears to be an algorithm-only performance evaluation in terms of its ability to generate specific types of images/data (monoenergetic images, virtual non-contrast images, iodine concentrations) and the agreement of these outputs with expected or true values (for phantom data) and visual/measurement comparisons (for clinical data). However, no specific standalone diagnostic performance metrics (e.g., sensitivity, specificity for disease detection) are reported.

7. Type of Ground Truth Used

• Technical/Physical Ground Truth: For phantom studies, the "known iodine concentration" and "expected" values serve as ground truth.
• Reference Image Ground Truth: For the Virtual Unenhanced application, "true non-contrast images" are used as a reference for comparison.
• Expert Interpretive Ground Truth: While "well-trained radiologist" is mentioned in the Indications for Use for Kidney Stones, the actual methodology for establishing ground truth for the clinical data used in the evaluation is not detailed beyond "image impression" and "measurements." It's an implicit expert consensus by a "well-trained radiologist" who would interpret the images, but the methodology for establishing this is not formalized in the provided text.

8. Sample Size for the Training Set

The document does not specify the sample size for the training set used to develop the syngo.CT Dual Energy algorithms. The focus of this submission is on verification and validation of a device modification, not initial algorithm development.

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

The document does not describe how the ground truth for the training set was established, as it pertains to the validation of a device modification rather than the initial algorithm development.

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