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syngo. CT Single Source Dual Energy is designed to operate with CT images which have been acquired with Siemens Twin Beam 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 are as follows:

• · Monoenergetic
• · Bone Removal
• · Liver VNC
• · Lung Analysis
• · Gout Evaluation
• · Monoenergetic Plus
• · Virtual Unenhanced
• · Rho/Z
• · Hard Plaques
• · 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 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 (twin beam) 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. This software application 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.

After loading the two reconstructed image datasets acquired with two different X-ray spectra into syngo.CT Single Source Dual Energy (twin beam), a correction algorithm is used in order to minimize motion effects. They are then displayed using linear blending with selectable mixing ratio and color scale. Multiplanar reformations (MPR) of the volume are shown in 3 image segments, which are initialized as sagittal, coronal and axial view. After arriving at an initial diagnosis on the basis of the CT-images, the user can choose one of the following application classes:

• . Monoenergetic
• Bone Removal ●
• Liver VNC
• Lung Analysis
• Gout Evaluation ●
• Monoenergetic Plus ●
• Virtual Unenhanced .
• Rho/Z ●
• Hard Plaques .
• Kidney Stones .

These application classes are designed for specific clinical tasks, so that algorithms, additional tool buttons, the use of colored overlay images and image representation (for example MPR or maximum intensity projection) is optimized correspondingly.

The provided document is a 510(k) premarket notification for a medical device called "syngo.CT Single Source Dual Energy (twin beam)". It describes the device, its intended use, and a comparison with predicate devices. While it mentions "clinical validation" and "performance tests", it does not detail specific acceptance criteria or provide quantitative results in the format of a clinical study or performance study with the level of detail requested in the prompt.

The document states:

• "A clinical validation has been conducted to show that both application classes "Gout" and "Lung Analysis" operate as intended."
• "Furthermore, phantom bench testing and clinical validation in a retrospective study was conducted to test the functionality of the remaining application classes Rho/Z and Kidney Stones."
• "Retrospective clinically validated studies were conducted to test the performance for applications classes Monoenergetic Plus, Bone Removal, Liver VNC, and Hard Plaques, as well as the predicate device application classes."
• "These studies demonstrate that the subject device using twin beam datasets performs as well as the predicate device applications that were tested using the same methods."
• "The result of all conducted testing was found acceptable to support the claim of substantial equivalence."

However, it does not provide the specific "acceptance criteria" (e.g., minimum sensitivity, specificity, accuracy) nor the "reported device performance" (e.g., actual sensitivity, specificity, accuracy values) in a table format. It also does not explicitly state the details requested about sample size, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, or training set details.

Therefore, I cannot fully answer the prompt based on the provided text. The document acts as a summary for a 510(k) submission, confirming that studies were performed and found acceptable for substantial equivalence, but it does not present the detailed results expected from an clinical study report.

No information is provided in the document for the following points, so I cannot answer them:

• A table of acceptance criteria and the reported device performance: The document states that "clinical validation" and "performance tests" were conducted and found "acceptable," and that the device "performs as well as the predicate device applications." However, it does not specify the quantitative acceptance criteria (e.g., specific thresholds for sensitivity, specificity, or accuracy) or the actual reported device performance metrics in a table.
• Sample sized used for the test set and the data provenance: No specific sample sizes for test sets are mentioned. The provenance is implied to be "clinical validation" and "retrospective studies," but the country of origin is not specified.
• 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 specified.
• Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not specified.
• 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 mentioned. The studies described are for the device's performance, not comparative effectiveness with human readers.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The document describes "clinical validation" and "performance tests" for the application, implying standalone performance of the software, but does not explicitly label it as "standalone" or provide specific metrics to differentiate it from assisted performance.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not specified.
• The sample size for the training set: The document discusses performance and clinical validation, but does not describe the training set or its size, or the use of deep learning/AI models that would require a distinct training set.
• How the ground truth for the training set was established: Not applicable, as training set details are not provided.

The only specific information related to "proof" of meeting criteria is:

• "Performance tests were conducted to test the functionality of the syngo.CT Single Source Dual Energy (twin beam) post-processing application."
• "A clinical validation has been conducted to show that both application classes "Gout" and "Lung Analysis" operate as intended."
• "Furthermore, phantom bench testing and clinical validation in a retrospective study was conducted to test the functionality of the remaining application classes Rho/Z and Kidney Stones."
• "Retrospective clinically validated studies were conducted to test the performance for applications classes Monoenergetic Plus, Bone Removal, Liver VNC, and Hard Plaques, as well as the predicate device application classes."
• "These studies demonstrate that the subject device using twin beam datasets performs as well as the predicate device applications that were tested using the same methods."
• "The result of all conducted testing was found acceptable to support the claim of substantial equivalence."

This indicates that internal studies were performed and deemed sufficient by the manufacturer for the 510(k) submission, confirming the device operates as intended and is comparable to predicate devices. However, the specific quantitative details of these studies are not disclosed in this summary.

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syngo. CT Single Source Dual Energy is designed to operate with CT images which have been acquired with Siemens 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
• Gout Evaluation
• · Brain Hemorrhage
• · Liver VNC
• · Monoenergetic Plus
• 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 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 materials in the human body.

syngo.CT Single Source 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.

After loading the two reconstructed image datasets acquired with two different X-ray spectra into syngo.CT Single Source Dual Energy, a registration is performed in case the image data sets are not acquired simultaneously, to compensate for potential motion effects. They are then displayed using linear blending with selectable mixing ratio and color scale. Multiplanar reformations (MPR) of the volume are shown in 3 image segments, which are initialized as sagittal, coronal and axial view.

After arriving at an initial diagnosis on the basis of the CT-images, the user can choose one of the following application classes:

• Gout Evaluation
• . Monoenergetic
• Brain Haemorrhage
• LiverVNC
• Kidney Stones
• . Monoenergetic Plus
• Bone Marrow

These application classes are designed for specific clinical tasks, so that algorithms, additional tool buttons, the use of colored overlay images and image representation (for example MPR or maximum intensity projection) are optimized correspondingly.

The Siemens syngo.CT Single Source Dual Energy software package (K133677) has a broad indication for use, stating it can aid in the visualization of the chemical composition of various materials in the human body by combining CT images acquired with low and high energy spectra. It lists several specific applications: Monoenergetic, Gout Evaluation, Brain Hemorrhage, Liver VNC, Monoenergetic Plus, Bone Marrow, and Kidney Stones.

For the Kidney Stones application, the indication for use specifies it is "designed to support the visualization of the chemical composition of kidney stones and especially the differentiation between uric acid stones." It further states that "accuracy of identification is decreased in obese patients" and emphasizes that "Only a well-trained radiologist can make the final diagnosis under consideration of all available information."

Here's an analysis of the acceptance criteria and study information provided in the document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size (Test Set): For the Kidney Stones application, a "phantom study" was performed, but the specific number of phantoms or stone types tested is not provided. For the "other application classes," "clinical data" was used, but the sample size (number of patients/cases) and whether this data was retrospective or prospective is not specified.
• Data Provenance: Not explicitly stated for either the phantom study or the clinical data. The document does not mention the country of origin. The clinical data appears to be retrospective as it's used to demonstrate functionality rather than being part of a controlled prospective trial described in detail.

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

• This information is not provided in the document. While the indication for use mentions that "Only a well-trained radiologist can make the final diagnosis," it does not detail the number or qualifications of experts involved in establishing ground truth for the performance studies.

4. Adjudication Method for the Test Set

• The document does not specify any adjudication method for the test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done or reported in this document. The document focuses on the performance of the device itself rather than its impact on human reader performance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

• Yes, the performance studies described appear to be standalone (algorithm only). For the Kidney Stones application, a "phantom study was performed to test the ability of application kidney stones." For other applications, "clinical data have been used to demonstrate the functionality of the other application classes." These descriptions imply direct evaluation of the software's output rather than assessing human performance with or without the software.

7. The Type of Ground Truth Used

• For the Kidney Stones application, the ground truth was likely based on the known composition of the phantom stones ("phantom study... differentiate between uric acid and non-uric acid stones").
• For the "other application classes," the "clinical data" used to demonstrate functionality would have had an associated ground truth, but the specific type (e.g., pathology, expert consensus, outcomes data) is not specified.

8. The Sample Size for the Training Set

• The document does not provide any information regarding the sample size for a training set. The descriptions focus on verification and validation testing, not the development or training of the algorithms. Given that this is a 510(k) for an updated software package, it's possible that the core algorithms were developed using proprietary datasets not disclosed here, or that the system relies on physical principles rather than extensive machine learning requiring a distinct "training set" in the modern sense.

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

• As the document does not mention a training set, it also does not provide information on how its ground truth was established.

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