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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 1)
• · Gout Evaluation 1)
• · Lung Vessels 1)
• · Heart PBV
• · Bone Removal
• · Lung Perfusion 1)
• · Lung Mono 1 )
• · Liver VNC 1)
• · Monoenergetic Plus 1)
• · Virtual Unenhanced 1)
• Bone Marrow
• · Hard Plaques
• Rho/Z
• · Kidney Stones 1) 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 Siemens Healthineers Photon-Counting CT scanners acquired in QuantumPlus modes.

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.

Here's an analysis of the acceptance criteria and study details for the syngo.CT Dual Energy device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• DE Brain Hemorrhage (PCCT): 28 features (implicitly, from patient cases). Data provenance not specified (retrospective/prospective, country of origin).
• Lung Mono for Dual Source Dual Energy: 20 cases (of suspected pulmonary embolisms). Data provenance not specified.
• Lung Analysis (Lung PBV, Lung Mono, Lung Vessels) for PCCT: 33 cases (of suspected pulmonary embolisms). Data provenance not specified.

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

• DE Brain Hemorrhage (PCCT): Two readers. Qualifications not specified beyond "readers."
• Lung Mono for Dual Source Dual Energy: Not explicitly stated for ground truth, but a "two-reader study" was performed for testing. Implicitly, radiologists are involved in identifying obstructing clots.
• Lung Analysis (Lung PBV, Lung Mono, Lung Vessels) for PCCT: Not explicitly stated for ground truth, but a "two-reader study" was performed for testing. Implicitly, "trained radiologists" identify obstructing clots in conventional CT images.

4. Adjudication Method for the Test Set

Not specified. The studies mention "two-reader study," but whether there was an adjudication for discrepancies (e.g., 2+1, 3+1) is not provided.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

It appears standalone studies were performed for the "DE Brain Hemorrhage," "Lung Mono," and "Lung Analysis" features. There is no mention of a comparative effectiveness study evaluating the improvement of human readers with AI assistance versus without AI assistance. The studies assess the device's ability to provide information; they do not quantify a human reader's performance change with the device.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The performance data described are related to the device output's ability to visualize certain conditions effectively, implying a standalone (or heavily algorithm-driven) assessment of the generated images/maps. For example, for "DE Brain Hemorrhage," it "demonstrated complementary visualization." For "Lung Mono," it "demonstrated adequate agreement." However, the mention of "two-reader studies" suggests human interpretation of the images generated by the device, rather than a purely algorithmic output without any human involvement in the evaluation of the results. It's an assessment of the utility of the device's output.

7. The Type of Ground Truth Used

The ground truth implicitly relies on:

• Follow-up data: For DE Brain Hemorrhage, comparing reading results "with later follow-up data."
• Expert Consensus/Clinical Standard: For Lung Mono and Lung Analysis, the identification of obstructing clots in conventional CT images by "trained radiologists" serves as the reference, suggesting a clinical gold standard interpreted by experts.

8. The Sample Size for the Training Set

The document does not provide details regarding the training set size for any of the features. The performance data section focuses entirely on validation studies.

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

Since no information is provided on the training set, how its ground truth was established is also not detailed in this document.

Ask a specific question about this device

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 1)
• · Lung Vessels
• · Heart PBV
• · Bone Removal
• · Lung Perfusion
• · Liver VNC 1)
• · Monoenergetic Plus 1)
• · Virtual Unenhanced 1)
• Bone Marrow
• · Hard Plaques
• Rho/Z
• · Kidney Stones 1) 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.

The provided text is a 510(k) summary for the syngo.CT Dual Energy device, specifically addressing modifications that enable its application classes (Liver VNC, Kidney Stones, Gout Evaluation) to support Photon-Counting CT (PCCT) data. While it discusses performance evaluations, it does not present a formal study with acceptance criteria and detailed quantitative results in the format requested.

The document indicates that the acceptance criteria for these modifications were primarily based on ensuring the existing algorithms and functionality, when applied to PCCT data, yield comparable results to their performance with previously approved dual-source dual-energy (DSDE) data or true non-contrast images, as appropriate. The evaluation appears to be a consistency check rather than a comparative effectiveness study against human readers or a standalone performance study with strict statistical endpoints.

Based on the provided text, here's an attempt to answer the questions, highlighting what information is available and what is not:

Acceptance Criteria and Device Performance Study for syngo.CT Dual Energy (K232155 - PCCT data support)

The provided submission summarizes the non-clinical testing performed to demonstrate that the updated syngo.CT Dual Energy, with its new support for Photon-Counting CT (PCCT) data for Liver VNC, Kidney Stones, and Gout Evaluation, continues to perform as intended and is substantially equivalent to its predicate. The "acceptance criteria" are implied by the performance evaluation statements, focusing on agreement and similarity of results between PCCT data and established methods (DSDE data or true non-contrast images).

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

2. Sample size used for the test set and the data provenance

• Liver VNC: "four-phase liver scans"
• Kidney Stones: "phantom data" (unspecified quantity) and "clinical data" (unspecified quantity)
• Gout Evaluation: Unspecified quantity of data for direct comparison.

Data Provenance:
The data provenance is not explicitly stated in terms of country of origin or whether it was retrospective or prospective. However, the mention of "NAEOTOM Alpha" (a Siemens PCCT scanner) suggests it's likely proprietary or internal test data generated for validation purposes. The phrase "already approved" for DSDE data suggests existing, previously validated clinical data might have been used for comparison.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This information is not provided in the document. The evaluations described ("agreed well," "similar to," "were the same") imply a comparison method, but the human reference or "ground truth" establishment process for these specific tests is not detailed, nor are the number and qualifications of experts involved.

4. Adjudication method for the test set

This information is not provided in the document. Given the summary nature of the performance data, it's unlikely a formal adjudication process for establishing ground truth for these specific validation tests would be detailed here.

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

No, a MRMC comparative effectiveness study involving human readers assisting with AI assistance versus without AI assistance was not mentioned or described in this 510(k) summary. The study focuses on the device's performance with new data types (PCCT), not on its impact on human reader performance.

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

Yes, the described performance data appears to be standalone (algorithm only), focusing on the processing capabilities of the syngo.CT Dual Energy software with PCCT data and comparing its output to known values (phantoms) or established results (DSDE data, true non-contrast images). There is no mention of human interaction being part of the evaluation of the algorithm's performance in these specific tests.

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

• Liver VNC: "True non contrast images" served as the ground truth/reference.
• Kidney Stones:
  • For phantom data: "known size and composition of the stones in the phantoms" served as ground truth.
  • For clinical data: "already approved dual-source dual-energy (DSDE) data" likely served as the reference for "similar" performance.
• Gout Evaluation: "results from the already approved DSDE scan mode" served as the reference for comparison.

8. The sample size for the training set

The document does not provide any information about the training set size for the algorithms within syngo.CT Dual Energy. Given that the 510(k) is for modifications to support new data types (PCCT) for existing algorithms, it's implied that the core algorithms were developed and trained previously. This submission specifically addresses the validation of these existing algorithms on the new PCCT data.

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

The document does not provide any information on how the ground truth for the training set (from the original algorithm development) was established.

Ask a specific question about this device

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.

Ask a specific question about this device

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

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

*) 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.

syngo.CT Dual Energy is a post-processing application consisting of several postprocessing 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.

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 text describes the syngo.CT Dual Energy device and its substantial equivalence to predicate devices, but it does not contain a specific table of acceptance criteria with reported device performance for a multi-reader multi-case (MRMC) study or standalone AI performance.

The document primarily focuses on establishing substantial equivalence based on the device's technological characteristics, adherence to standards, and functionality being similar to existing cleared devices. It states that "the post-processing software functionality remains unchanged from the subject device and the predicate devices."

However, based on the information provided, I can infer some aspects and highlight what is missing.

Here's an analysis of the acceptance criteria and study information, addressing each of your points based only on the provided text:

Acceptance Criteria and Device Performance (Inferred/Missing)

The document does not explicitly present a table of quantitative acceptance criteria for clinical performance (e.g., sensitivity, specificity, accuracy for a specific disease detection task) or corresponding reported device performance values. The clearance is based on the device having "the same intended use and similar indication for use" and "technological characteristics such as image visualization, operating platform, and image manipulation are the same as the predicate devices."

The closest the document comes to performance assessment is for the new features (SPR and SPP) and the revalidation of existing features for the combined application:

• For SPR (Stopping Power Ratio): "the report shows that the SPR feature can reproduce the theoretical SPR values of the phantom inserts used from Dual Energy CT scans."
• For SPP (Spectral Post-Processing Format): "the combination of the SPP-generation process produces equivalent results to the reference method based on functionality available in the predicate device(s). This means also that the information in the SPP-format (including all hidden data) was correctly calculated."
• For other application classes (Rho/Z, Kidney Stones, Monoenergetic Plus, Bone Removal, Liver VNC, Hard Plaques): "These studies demonstrate that the subject device performs as well as the predicate device applications that were tested using the same methods."

Since no specific quantitative metrics or a defined Acceptance Criteria table with Reported Performance are present in the provided text, that section cannot be filled out as requested. The basis for acceptance is stated as "The result of all conducted testing was found acceptable to support the claim of substantial equivalence," implying that the performance matched the predicate devices or theoretical expectations for new features.

Detailed Study Information from the Text:

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

   • Not provided in the document. The document describes functional equivalence and performance "as well as" predicate devices or theoretical values for new features, but no specific quantitative acceptance criteria or reported values are presented in a table.

2. Sample sizes used for the test set and the data provenance:

   • Test Set Sample Size: The document mentions "phantom-based validation" for SPR and SPP, and "phantom bench testing and clinical validation in a retrospective study" for Rho/Z and Kidney Stones. "Retrospective clinically validated studies" were also conducted for Monoenergetic Plus, Bone Removal, Liver VNC, and Hard Plaques.
     • Specific numbers for phantom or clinical cases are NOT provided.
   • Data Provenance: "clinical validation in a retrospective study was conducted." The geographic origin of the data (country of origin) is NOT specified. The studies are explicitly stated as retrospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of Experts: The document states for Kidney Stones: "Only a well-trained radiologist can make the final diagnosis under consideration of all available information." This implies expert involvement for ground truth, but the specific number of experts used for ground truth establishment for any of the test sets is NOT provided.
   • Qualifications of Experts: For Kidney Stones, "a well-trained radiologist" is mentioned. Specific experience (e.g., 10 years) is NOT provided.

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

   • NOT specified.

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:

   • No MRMC comparative effectiveness study is explicitly mentioned or described. The device is a "post-processing application" that "improves visualization" and helps in "differentiation." The focus is on the device's performance per se and its equivalence to predicate devices, not on human reader improvement with or without AI assistance. The term "AI" is not used; it's described as software providing "visualization" and "evaluation tools."

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

   • The evaluations for SPR and SPP ("reproduce the theoretical SPR values," "produces equivalent results to the reference method") appear to be standalone algorithm performance tests using phantoms.
   • For the other clinical application classes, the description "demonstrate that the subject device performs as well as the predicate device applications" suggests an assessment of the algorithm's output, which would be standalone, but this is not explicitly delineated from a human-in-the-loop study. Given it's a post-processing application, the algorithm's output is what's being evaluated.

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

   • Theoretical values/Reference methods: For SPR (theoretical values) and SPP (reference method based on predicate device functionality).
   • Clinical validation: For Rho/Z, Kidney Stones, Monoenergetic Plus, Bone Removal, Liver VNC, and Hard Plaques, it states "clinical validation" and "clinically validated studies." For Kidney Stones, "Only a well-trained radiologist can make the final diagnosis," suggesting the ground truth is expert diagnosis/interpretation, potentially combined with "patient history and urine testing." It does not explicitly mention pathology or long-term outcomes data.

8. The sample size for the training set:

   • NOT provided. The document describes testing and validation (test set), but there is no information about a dedicated training set or its size, consistent with this being a 510(k) submission for a post-processing software update/combination, rather than a novel AI/machine learning device. The existing functionalities are described as unchanged.

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

   • NOT applicable/provided. As no training set information is present, the method for establishing its ground truth is also not mentioned.

Ask a specific question about this device

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
• o Lung Perfusion
• Liver VNC ●
• Monoenergetic Plus ●
• Virtual Unenhanced ●
• Bone Marrow ●
• Hard Plaques ●
• o Rho/Z
• 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.

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.

The provided text describes syngo.CT Dual Energy, a software package for post-processing CT images. While it mentions non-clinical testing and verification/validation, it does not provide specific acceptance criteria or details of a study that directly proves the device meets such criteria in terms of performance metrics like accuracy, sensitivity, or specificity for its various applications.

The document focuses on substantiating equivalence to predicate devices, primarily through software updates and new application classes (Rho/Z, Hard Plaques, Fat Map for Liver VNC). The testing described is more about demonstrating that the software functions as intended and meets safety standards, rather than providing performance metrics against specific acceptance thresholds for clinical utility.

Therefore, many of the requested details cannot be extracted directly from this document.

Here's an attempt to answer based on the provided text, highlighting where information is absent:

1. Table of acceptance criteria and the reported device performance

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

• Sample size for test set: Not specified. The document mentions "retrospective analysis of available patient data" but does not give a number of cases or patients.
• Data provenance: "retrospective analysis of available patient data". No country of origin is mentioned. Whether it was prospective or retrospective is stated as retrospective.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of experts: Not specified.
• Qualifications of experts: Not specified. However, for "Kidney Stones" application, it states, "Only a well-trained radiologist can make the final diagnosis under consideration of all available information," implying radiologists would be involved in ground truth establishment for that specific application.

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

• Adjudication method: Not specified.

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

• MRMC comparative effectiveness study: No, an MRMC comparative effectiveness study is not mentioned. The document describes a "verification/validation testing" and states that "supportive articles that demonstrate the usability" of certain application classes were provided, but it does not detail a study evaluating human reader improvement with AI assistance.

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

• Standalone performance study: The non-clinical testing included "phantom bench testing," which would be a form of standalone testing on controlled data. However, quantitative performance metrics for the algorithm's standalone performance (e.g., accuracy of material decomposition in phantoms) are not provided. The overall conclusion is that the device "performs as intended," but specific performance values are absent.

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

• Type of ground truth: Not explicitly stated. For "retrospective analysis of available patient data," the ground truth would likely be based on existing clinical reports or expert interpretation. For "phantom bench testing," the ground truth would be the known composition of the phantom materials.

8. The sample size for the training set

• Sample size for training set: Not applicable/Not specified. The document describes a software package with new and modified application classes, rather than a deep learning AI model that would typically have a distinct training set. The focus is on verifying improvements and new functionalities over existing predicate devices.

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

• How ground truth for training set was established: Not applicable/Not specified, as a distinct "training set" for an AI model is not described. The document pertains to updates to an existing software package for image post-processing.

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