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This computed tomography system is intended to generate and process cross-sectional images of patients by computer reconstruction of x-ray transmission data.

The images delivered by the system can be used by trained staff as an aid in diagnosis, treatment and radiation therapy planning as well as for diagnostic and therapeutic interventions.

This CT system can be used for low dose lung cancer screening in high risk populations*.

*As defined by professional medical societies. Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

The subject device SOMATOM CT Scanner Systems with SOMARIS/7 syngo CT VB30 are Computed Tomography X-ray Systems which feature one (single source) continuously rotating tube-detector system and function according to the fan beam principle. The SOMATOM CT Scanner Systems with Software SOMARIS/7 syngo CT VB30 produces CT images in DICOM format, which can be used by trained staff for post-processing applications commercially distributed by Siemens Healthcare and other vendors as an aid in diagnosis, treatment preparation and therapy planning support (including, but not limited to, Brachytherapy, Particle including Proton Therapy, External Beam Radiation Therapy, Surgery). The computer system delivered with the CT scanner is able to run optional post processing applications.

The platform software for the SOMATOM CT Scanner Systems, SOMARIS/7 syngo CT VB30, is a commandbased program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text.

1. Table of Acceptance Criteria and Reported Device Performance

The document primarily focuses on functional verification and validation testing rather than explicit, quantifiable acceptance criteria with corresponding performance metrics for each feature in a tabular format. Instead, it describes the objective of each test and then states that the results were found to be acceptable or passed.

However, we can extract the objectives and the documented outcomes for features where some quantifiable or descriptive performance is mentioned:

• Median difference between true and personalized delay 90% of patients.
• Higher overall and more uniform attenuation in individualized cohort vs. fixed.
• Higher contrast-to-noise ratio (CNR) and subjective image quality in individualized cohort.
• Able to adjust scan timing to altered protocols to reach diagnostic image quality despite slower injection rate and reduced iodine dose.
• Images with individualized post-trigger delay provided higher attenuation for all organs.
• Mean vessel enhancement significantly higher in individualized scan timing group. |
  | FAST 3D Camera (Adolescent support) | Achieve comparable or more accurate results than predicate for adults, while supporting adolescent patients (120 cm+) with comparable accuracy as adult patients. | Achieves the objective of the test. (Implies comparable or more accurate results). |
  | FAST Isocentering (Adolescent support) | Lateral isocenter accuracy of subject device comparable to predicate for adult patients, and similar accuracy for adolescent patients. | Comparable to predicate for adult patients; similar accuracy for adolescent patients. |
  | FAST Range (Adolescent support) | Robustness of groin landmark improved; other landmarks detected with comparable accuracy for adults; accuracy of landmark detection for adolescents similar to adults. | Robustness of groin landmark improved; other landmarks with comparable accuracy. For adolescents, similar accuracy to adults. |
  | FAST Direction | Comparable accuracy of pose detection to predicate device. | Comparable accuracy. |
  | FAST Planning | Fraction (percentage) of correct ranges that can be applied without change; calculation time meets interactive requirements. | For >90% of ranges, no editing action was necessary to cover standard ranges. For >95%, the speed of the algorithm was sufficient. |
  | Tin Filtration (New kV combinations) | Successful implementation of new voltage combinations (80/Sn140 kV and 100/Sn140 kV) verified; description of spectral properties given; improved CNR in spectral results (monoenergetic images). | Successful implementation verified via phantom scans and image quality criteria evaluation. All applied tests concerning image quality passed. Different spectral properties with and without Sn filter evident, and Sn filter improves spectral separation considerably. Results support claims related to improved CNR. |
  | General Non-Clinical Testing (Integration & Functional) | Verify and validate functionality of modifications. Ensure safe and effective integration. Conformance with special controls for software medical devices. Risk mitigation. | All software specifications met acceptance criteria. Testing supports claims of substantial equivalence. |

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

• FAST Bolus: The test describes using a "real contrast enhancement curve" determined by measurements with a dynamic scan mode. The subsequent supporting peer-reviewed studies provide more detail:

  • Korporaal et al. (2015): Not explicitly stated, but implies a cohort undergoing bolus tracking.
  • Hinzpeter et al. (2019): 108 patients received patient-specific trigger delay (subject), 108 patients received fixed trigger delay (reference). Prospective CT angiography scans of the aorta.
  • Gutjahr et al. (2019): 3 groups, 20, 20, and 40 patients respectively.
  • Yu et al. (2021): 104 patients (52 per group, implied) in abdominal multiphase CT, comparing individualized vs. fixed post-trigger delay.
  • Yuan et al. (2023): 204 consecutive participants randomly divided into two groups (102 patients each). A prospective study in coronary CT angiography (CCTA).
  • Schwartz et al. (2018): Not explicitly stated, but implied patient-specific data.
  • Data Provenance: The supporting studies imply a mix of retrospective analysis (e.g., Korporaal et al. simulating retrospectively differences) and prospective studies based on the descriptions provided. The locations of these studies are not explicitly mentioned in the excerpt, but given Siemens' global presence, it's likely multi-national.

• FAST 3D Camera, FAST Isocentering, FAST Range, FAST Direction, FAST Planning, Tin Filtration: For these features, the testing is described as "bench testing" using phantoms and internal validation. "Patient data" is mentioned for FAST Planning but without specific numbers.

  • Sample Size: Not specified for these internal bench tests; often involves phantom studies rather than patient-level data for performance metrics. For FAST Planning, it refers to "patient data" for validation, but the sample size is not indicated.
  • Data Provenance: Implied internal testing, likely at Siemens R&D facilities. No external patient data provenance details are given.

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

• For FAST Bolus, the "ground truth" for the internal bench test was defined as an "ideal post bolus delay" determined by measurements with a dynamic scan mode. This suggests an objective, data-driven approach rather than expert consensus on individual cases for the initial ground truth. However, the supporting studies mention:
  • Hinzpeter et al. (2019): Mentions subjective image quality and CNR, which would typically involve expert readers, but the number and qualifications are not provided.
  • Yuan et al. (2023): Mentions "Both readers rated better subjective image quality." suggesting at least two readers, but their qualifications are not provided.
• For other features (FAST 3D Camera, FAST Planning, etc.), the ground truth seems to be established through objective measurement against predefined targets (e.g., "calculated by FAST Planning algorithm that are correct and can be applied without change"). No specific expert involvement for ground truth establishment for these features is detailed.

4. Adjudication Method for the Test Set

• The document does not describe a formal adjudication method (e.g., 2+1, 3+1) for the establishment of ground truth or for reader studies. Where multiple readers are mentioned (e.g., Yuan et al. for FAST Bolus), it only states their findings without detailing an adjudication process. This suggests either independent readings or consensus where needed, but not a formal adjudication protocol.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, and Effect Size

• Yes, implicitly for FAST Bolus: The supporting publications function as comparative effectiveness studies where human assessment (e.g., subjective image quality, diagnostic confidence) is evaluated with or without the aid of the FAST Bolus prototype.
  • Hinzpeter et al. (2019): "higher overall and more uniform attenuation in the individualized cohort compared to the fixed cohort. No difference between the cohorts for image noise was found, but a higher contrast-to-noise ratio (CNR) and higher subjective image quality in the individualized cohort compared to the fixed cohort." This indicates improvement with the AI-assisted timing.
  • Yu et al. (2021): "In the arterial phase, the images of group A with the individualized post-trigger delay provided higher attenuation for all organs... Furthermore, the contrast-to-noise ratio (CNR) of liver, pancreas and portal vein were significantly higher in the group with the individualized scan timing compared to the fixed scan delay. The overall subjective image quality and diagnostic confidence between the two groups were similar." This indicates improved quantitative metrics, with subjective similar.
  • Yuan et al. (2023): "Both readers rated better subjective image quality for Group B with the individualized scan timing. Also, the mean vessel enhancement was significantly higher in Group B in all coronary vessels. After adjusting for the patient variation, the FAST Bolus prototype was associated with an average of 33.5 HU higher enhancement compared to the fixed PTD." This provides a direct effect size for enhancement.
• For the other features, the description is focused on the device's inherent performance (e.g., accuracy of landmark detection, successful implementation) rather than human reader improvements. So, no MRMC study for those.

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

• Yes, for multiple features. The "Bench Testing" descriptions primarily evaluate the algorithm's performance in a standalone manner against a defined ground truth or objective:
  • FAST Bolus: "the post bolus delay as calculated by FAST Bolus to an ideal post bolus delay... was calculated. The objectives of the test were to investigate the deviation from the post bolus delay as determined by FAST Bolus to an ideal/ground truth delay..." This is standalone.
  • FAST 3D Camera, FAST Isocentering, FAST Range, FAST Direction: The tests "demonstrate that the FAST 3D Camera feature... achieves comparable or more accurate results," "lateral isocenter accuracy... comparable," "robustness of the groin landmark is improved," "comparable accuracy of the pose detection." These are assessments of the algorithm's direct performance.
  • FAST Planning: "assess the fraction (percentage) of ranges calculated by the FAST Planning algorithm that are correct and can be applied without change." This is a direct measurement of the algorithm's output quality.
  • Tin Filtration: Verifies "successful implementation" and investigates "improved contrast-to-noise ratio (CNR) in spectral results." This is standalone performance of the image reconstruction/processing.

7. The Type of Ground Truth Used

• Objective/Measured Data:
  • FAST Bolus: "ideal post bolus delay" determined by "measurements with a dynamic scan mode" and "averaged dynamic scans."
  • FAST 3D Camera, FAST Isocentering, FAST Range, FAST Direction: Implied ground truth based on objective measurements of spatial accuracy relative to predefined targets or phantoms.
  • FAST Planning: "correct" ranges are the ground truth, implying comparison to a predefined standard or ideal plan.
  • Tin Filtration: Objective image quality criteria and spectral property measurements are used as ground truth indicators.
• Expert Consensus/Subjective Assessment (as secondary metric in supporting studies): Some of the supporting publications for FAST Bolus also incorporate subjective image quality ratings by human readers, which would likely involve some form of expert consensus or individual expert assessment.

8. The Sample Size for the Training Set

• The document does not provide information on the sample size used for the training set for any of the AI/algorithm features. This information is typically proprietary and not usually disclosed in a 510(k) summary unless specifically requested or deemed critical for demonstrating substantial equivalence.

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

• The document does not provide information on how the ground truth for the training set was established. Given the nature of these features (automated bolus timing, patient positioning, scan range planning), the training data would likely involve large datasets of CT scans annotated with physiological events, anatomical landmarks, and optimal scan parameters. These annotations would typically be established by highly qualified medical professionals (e.g., radiologists, technologists) or through automated processes validated against gold standards. However, the specific methodology is not detailed in this excerpt.

Ask a specific question about this device

This computed tomography system is intended to generate and process cross-sectional images of patients by computer reconstruction of x-ray transmission data.

The images delivered by the system can be used by a trained physician as an aid in diagnosis. The images delivered by the system can be used by trained staff as an aid in diagnosis, treatment preparation and radiation therapy planning.

This CT system can be used for low dose lung cancer screening in high risk populations *

• As defined by professional medical societies. Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

The subject device SOMATOM CT Scanner Systems with SOMARIS/7 syngo CT VB20 are Computed Tomography X-ray Systems which feature one (single source) or two (dual source) continuously rotating tubedetector system and function according to the fan beam principle. The SOMATOM CT Scanner Systems with Software SOMARIS/7 syngo CT VB20 produces CT images in DICOM format, which can be used by trained staff for post-processing applications commercially distributed by Siemens Healthcare and other vendors as an aid in diagnosis, treatment preparation and therapy planning support (including, but not limited to, Brachytherapy, Particle including Proton Therapy, External Beam Radiation Therapy, Surgery). The computer system delivered with the CT scanner is able to run optional post processing applications.

The platform software for the SOMATOM CT Scanner Systems, SOMARIS/7 syngo CT VB20, is a commandbased program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation.

Here's an analysis of the acceptance criteria and supporting study information based on the provided text, broken down by your requested points:

Acceptance Criteria and Study Information for SOMATOM CT Scanner Systems-Software Version SOMARIS/7 syngo CT VB20

The provided document (a 510(k) summary) describes an update to existing Computed Tomography (CT) scanner systems (SOMATOM Force, SOMATOM Definition Flash, SOMATOM Drive, SOMATOM Definition Edge, SOMATOM Definition AS Open, SOMATOM Definition AS/AS+, SOMATOM Confidence, and SOMATOM Edge Plus) with new software version SOMARIS/7 syngo CT VB20. The primary goal of the submission is to demonstrate substantial equivalence to previously cleared predicate devices (K173630 and K173607).

The document does not explicitly list specific numerical acceptance criteria for device performance beyond stating that "all software specifications have met the acceptance criteria" and "the SOMATOM CT Scanner Systems perform comparably to the predicate devices." It focuses on confirming the updated device maintains the safety and effectiveness of the predicate devices.

1. Table of Acceptance Criteria and Reported Device Performance

As specific numerical acceptance criteria are not presented in the document, I will infer the high-level acceptance criteria from the submission's focus on demonstrating substantial equivalence and list the general performance statements made.

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

The document states that "phantom tests were conducted" and refers to "dosimetry and imaging performance, and analysis of phantom images to assess device and feature performance." However, no specific sample size for the test set (number of phantom scans, patient data, etc.) is provided.

Data Provenance: The tests are described as "non-clinical test (integration and functional) including phantom tests... during product development." This indicates that the testing was conducted internally by the manufacturer,Siemens, likely on prototypes or production units, using phantoms. There is no mention of human subject data, country of origin, or whether the tests utilized retrospective or prospective data. The nature of phantom studies typically makes them prospective in this context.

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

The document does not provide information on the number of experts used to establish ground truth or their specific qualifications (e.g., number of radiologists, years of experience). Given the nature of this submission (software upgrade for a CT system, focusing on technical performance and substantial equivalence rather than a new diagnostic algorithm's clinical efficacy), it's less likely to involve extensive expert-driven ground truth establishment as would be seen for AI/CADe devices. The "ground truth" for technical performance is typically established via physical measurements and established phantom metrics.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method (e.g., 2+1, 3+1). As stated above, the testing appears to be primarily technical and phantom-based, where ground truth is often objectively measurable through physical properties or established methods, rather than subjective expert interpretation requiring adjudication.

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

No MRMC comparative effectiveness study was done or reported in this document. The submission focuses on demonstrating substantial equivalence of the updated CT system to its predicates through technical and non-clinical testing, not on measuring improvements in human reader performance with or without AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

While the document focuses on the performance of the CT system and its software, it does not specifically describe a standalone algorithm-only performance study in the context of an AI/CADe device. The SOMARIS/7 syngo CT VB20 is a platform software update for CT scanners, enhancing system functionality and image reconstruction capabilities (e.g., "Enhanced FAST DE Results," "Precision Matrix," "DirectDensity™"). The "performance" being evaluated is the system's ability to generate cross-sectional images and support diagnostic tasks, as opposed to a specific AI algorithm. The performance evaluation discussed would inherently be of the "algorithm" integrated into the system, contributing to the overall image quality and functional capabilities.

7. Type of Ground Truth Used

The ground truth for the non-clinical testing appears to be based on:

• Physical Measurements and Phantom Readings: "Non-clinical test (integration and functional) including phantom tests were conducted." This implies that phantoms with known properties or simulated pathologies were used, and the system's output (image quality, dose metrics, etc.) was measured against these known values.
• Engineering Specifications / Reference Data: For software functional tests ("all software specifications have met the acceptance criteria"), the ground truth would be the defined engineering and design specifications for the software's intended behavior.

There is no mention of pathology, outcomes data, or expert consensus (in the typical sense of clinical ground truth for diagnostic accuracy) for establishing the ground truth described in this submission.

8. Sample Size for the Training Set

The document does not mention a training set sample size or the use of a separate training set. This is consistent with the nature of the submission, which describes a software update for a CT system rather than a machine learning or AI algorithm submission where training data sets are explicitly separated from test data. The software updates described are enhancements to the system's core functionality, reconstruction, and workflow, which are typically developed and verified through engineering processes rather than large-scale machine learning training.

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

Since no training set is mentioned in the context of typical AI/ML development, this information is not applicable based on the provided document. The "training" for such system software updates primarily refers to the iterative development and internal testing processes by the engineers, where specifications serve as the "ground truth."

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This computed tomography system is intended to generate and process cross-sectional images of patients by computer reconstruction of x-ray transmission data.

The images delivered by the system can be used by a trained physician as an aid in diagnosis. The images delivered by the system can be used by trained staff as an aid in diagnosis, treatment preparation and radiation therapy planning.

This CT system can be used for low dose lung cancer screening in high risk populations *

• As defined by professional medical societies. Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

Siemens intends to market a new software version, SOMARIS/7 syngo CT VB10 for the following SOMATOM Computed Tomography (CT) Scanner Systems:

Dual Source CT Systems:

• SOMATOM Force
• SOMATOM Drive
• SOMATOM Flash

Single Source CT Systems:

• SOMATOM Definition AS/AS+
• SOMATOM Definition AS Open
• SOMATOM Definition Edge
• SOMATOM Confidence

The subject device SOMATOM CT Scanner Systems with SOMARIS/7 syngo CT VB10 are Computed Tomography X-ray Systems which feature one (single source) or two (dual source) continuously rotating tube-detector system and function according to the fan beam principle. The SOMATOM CT Scanner Systems with Software SOMARIS/7 syngo CT VB10 produces CT images in DICOM format, which can be used by trained staff for post-processing applications commercially distributed by Siemens Healthcare and other vendors as an aid in diagnosis, treatment preparation and therapy planning support (including, but not limited to, Brachytherapy, Particle including Proton Therapy, External Beam Radiation Therapy, Surgery). The computer system delivered with the CT scanner is able to run optional post processing applications.

The platform software for the SOMATOM CT Scanner Systems, SOMARIS/7 syngo CT VB10, is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation.

The provided document is a 510(k) premarket notification for Siemens SOMATOM CT Scanner Systems with software version SOMARIS/7 syngo CT VB10. It describes the device, its intended use, and a comparison with predicate devices to establish substantial equivalence.

However, the document does not contain specific details about acceptance criteria, reported device performance metrics (e.g., sensitivity, specificity, AUC), sample sizes for test sets, data provenance, number or qualifications of experts for ground truth, adjudication methods, multi-reader multi-case (MRMC) comparative effectiveness studies, standalone algorithm performance, or specific ground truth types for image-based diagnostic performance assessments.

The "Performance Data" section primarily focuses on non-clinical testing for system functionality, adherence to general medical device standards (ISO, NEMA, IEC), electrical safety, EMC, software verification and validation (including cybersecurity), and phantom tests to assess device and feature performance. It broadly states that "The test results show that all of the software specifications have met the acceptance criteria" and that "Verification and validation testing of the device was found acceptable to support the claim of substantial equivalence," but it does not quantify these acceptance criteria or the specific performance results in a table or detailed study findings.

The indications for use mention "aid in diagnosis, treatment preparation and radiation therapy planning" and "low dose lung cancer screening in high risk populations," which typically would involve performance metrics like sensitivity and specificity. However, these metrics are not presented. The reference to the National Lung Screening Trial (NLST) is for the clinical context of low-dose lung cancer screening, not for the performance validation of the Siemens CT system itself against a ground truth.

Therefore, I cannot populate a table with acceptance criteria and reported device performance, nor can I provide answers to the majority of the requested points, as that information is not present in the provided text.

Based on the provided text, here's what can be extracted regarding the study and performance claims:

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

The document does not provide specific quantitative acceptance criteria (e.g., sensitivity, specificity, reader performance metrics) or corresponding reported device performance values for diagnostic tasks. It broadly states that "all of the software specifications have met the acceptance criteria" and that testing demonstrates "comparability to the predicate devices in terms of technological characteristics and safety and effectiveness."

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

This information is not provided in the document. The testing mentioned is primarily "non-clinical test (integration and functional) including phantom tests."

3. 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)

This information is not provided in the document. The testing described does not involve expert-adjudicated ground truth as it pertains to diagnostic performance on patient data.

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

This information is not provided in the document.

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

This information is not provided in the document. The study described focuses on technical verification and validation, and comparability to predicate devices, not on human-AI comparative effectiveness.

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

The document mentions "phantom tests" to assess device and feature performance. However, it does not specify performance metrics for a standalone algorithm related to diagnostic accuracy on clinical cases. The device is a CT scanner, and the software updates are for image processing and system functionality, not a standalone diagnostic AI algorithm.

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

For the non-clinical and phantom tests conducted, the ground truth would be the known and controlled parameters of the phantoms and the expected technical performance outputs. There is no mention of ground truth types for clinical diagnostic accuracy related to patient data.

8. The sample size for the training set

Not applicable. The document describes a software update for a medical imaging device (CT scanner) validated through non-clinical testing and phantom studies, not an AI model trained on a dataset.

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

Not applicable, as this is not an AI model requiring a training set with established ground truth.

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This computed tomography system is intended to generate and process cross-sectional images of patients by computer reconstruction of x-ray transmission data. The images delivered by the system can be used by a trained physician as an aid in diagnosis. This CT system can be used for low dose lung cancer screening in high risk populations * * As defined by professional medical societies. Please refer to clinical literature, including the results of the National Lung Screening Trial (N Engl J Med 2011; 365:395-409) and subsequent literature, for further information.

Siemens SOMATOM Computed Tomography System family scanners are whole body X-ray computed tomography systems which feature a continuously rotating tube-detector system and functions according to the fan beam principle. The SOMATOM Computed Tomography System family scanners vary in configurations from 6 to 192 slices, and are intended to produce cross sectional images of the body by computer reconstruction of x-ray transmission data from either the same axial plane taken at different angles or spiral planes taken at different angles. The system software is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation. The systems described in this submission provide pre-defined low dose scan modes similar to the modes used for The National Lung Screening Trial (NLST), and the features as recommend by the study. This allows use of these systems for screening in the same way the CT systems were used for NLST. The computer system delivered with the CT scanner is able to run post processing applications optionally.

The provided text describes Siemens' application for expanded indications for use for their SOMATOM Computed Tomography (CT) System family scanners to include low-dose lung cancer screening in high-risk populations. The submission asserts that the devices are substantially equivalent to previously cleared versions and that the new indication does not constitute a new intended use.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not explicitly state specific quantitative acceptance criteria for performance metrics for the low-dose lung cancer screening indication. Instead, it states that the devices perform "comparably or better than" older devices which were used in the NLST study. The performance characteristics compared are standard CT image quality metrics.

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

The document explicitly states: "Non clinical tests (integration and functional) and phantom testing were conducted for the SOMATOM Computed Tomography System family during product development." It further mentions: "The test results demonstrate that the subject devices perform comparably or better than the older devices. Since the older devices have been identified as suitable for lung cancer screening within the NLST, the respective performance of the subject devices can be regarded as suitable for lung cancer screening as well."

• Sample Size for Test Set: Not specified for new testing. The reliance is on comparability to devices used in the NLST study. The NLST study itself included over 53,000 participants.
• Data Provenance: The new testing focuses on non-clinical phantom testing. The clinical basis for the indication relies on existing clinical literature, specifically referencing the National Lung Screening Trial (NLST) which was a prospective, randomized controlled trial conducted in the United States.

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

The document does not describe the use of human experts to establish ground truth for the non-clinical phantom testing performed for this submission. The "ground truth" for the acceptance of the lung cancer screening application is implicitly tied to the performance characteristics of the devices used in the NLST study and subsequent literature, as defined by professional medical societies.

4. Adjudication Method for the Test Set

Not applicable, as expert adjudication for performance metrics within this submission is not described.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not performed as part of this submission. The devices are CT scanners, not AI-powered diagnostic aids that directly assist human readers. The submission focuses on the performance of the CT system itself for low-dose lung cancer screening.

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

This is not applicable as the device in question is a CT scanner, not an algorithm, and it requires clinical interpretation by a trained physician.

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

The ground truth for the suitability of the CT systems for low-dose lung cancer screening relies on:

• Clinical Literature: Specifically, the results of the National Lung Screening Trial (NLST) which involved clinical outcomes data (lung cancer incidence, mortality).
• Professional Medical Society Definitions: The indications for use explicitly state "As defined by professional medical societies."
• Technical Guidelines: From organizations like the American College of Radiology (ACR) and National Comprehensive Cancer Network (NCCN).

For the non-clinical performance tests conducted for this submission, the ground truth would be based on physical phantom measurements and known parameters of the phantoms.

8. The Sample Size for the Training Set

The document does not describe a training set in the context of an AI/ML algorithm. The devices are CT scanners, and their development and validation involve engineering, physics, and clinical studies (like NLST, which is referenced as foundational for the indication).

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

Not applicable, as no training set for an AI/ML algorithm is described.

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The Siemens SOMATOM Definition Edge, SOMATOM Definition AS/ AS+ (Project P46) systems are intended to produce cross-sectional images of the body by computer reconstruction of xray transmission data from either the same axial plane taken at different angles or spiral planes* taken at different angles.

(*spiral planes: the axial planes resulted from the continuous rotation of detectors and x-ray tube, and the simultaneous translation of the patient.)

The Siemens SOMATOM Definition AS/AS* and SOMATOM Definition Edge equipped with syngo CT VA48 are Computed Tomography X- ray Systems. which feature a continuously rotating tube-detector system and functions according to the fan beam principle. The SOMATOM Definition AS/ AS* and SOMATOM Definition Edge produce CT images in DICOM format, which can be used by post-processing applications commercially distributed by Siemens and other vendors.

The system software is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation. The version of system software, syngo CT VA48, supports functionality such as Twin Beam scanning, Fast 3D Align, TrueD 4D Viewer, Fast DE evaluation and improved functionality with extended Field of View. The computer system delivered with the CT scanner is able to run optional post processing applications.

In addition to the previously supported software functionality, which was cleared for the FAST DE Result evaluation of Dual Source and Single Source (dual spiral) data, the subject device will support the FAST DE Result evaluation of data acquired with TwinBeam technology. FAST DE Results evaluation allows to use the optional post-processing features Monoenergetic Plus and Virtual Enhanced.

The Siemens SOMATOM Definition AS/AS+ and SOMATOM Definition Edge (with software version syngo CT VA48) is a Computed Tomography X-ray System. Its primary function is to produce cross-sectional images of the body by computer reconstruction of x-ray transmissions data. The device was evaluated to demonstrate continued conformance with special controls for medical devices containing software.

Here's a breakdown of the acceptance criteria and study information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Test Set Sample Size: Not explicitly stated as a number of cases/patients. The document mentions "retrospective analysis of available patient data" and "supportive articles that demonstrate the usability," but does not provide a specific numerical sample size for this patient data.
• Data Provenance: The document states "retrospective analysis of available patient data." The country of origin for the data is not specified.

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

• This information is not provided in the document. The document mentions "supportive articles that demonstrate the usability," which might imply expert review, but no details are given about the number or qualifications of experts for establishing ground truth on the test set.

4. Adjudication Method for the Test Set:

• This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and its effect size:

• A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done with human readers comparing performance with and without AI assistance. The study focuses on the device's technical performance and its equivalence to predicate devices, not on human reader improvement with AI.

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

• Yes, a standalone performance assessment was conducted for the device's software functionalities. The performance tests ("Phantom bench testing and retrospective analysis of available patient data was conducted for application classes Monoenergetic Plus and Virtual Unenhanced for the FAST DE Results for TwinBeam Data software module") evaluate the algorithm's output directly.

7. The Type of Ground Truth Used:

• The document mentions "phantom bench testing" and "retrospective analysis of available patient data." For phantom testing, the ground truth would be the known properties of the phantom. For retrospective patient data, the type of ground truth is not explicitly stated (e.g., expert consensus on original scans, pathology). However, the context of "supportive articles that demonstrate the usability" suggests comparison against accepted clinical interpretation or existing diagnostic standards, rather than pathology or long-term outcomes data primarily.

8. The Sample Size for the Training Set:

• The document does not specify a sample size for a training set. The descriptions focus on verification and validation testing, and on demonstrating functionality and equivalence. "Available patient data" is mentioned in the context of retrospective analysis for performance testing, not explicitly for training.

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

• As a training set is not explicitly mentioned and described, information on how its ground truth was established is not provided. The device in this submission is an update to a CT system's software functionality (specifically "FAST DE Results for TwinBeam Data"), rather than a new AI/CADx algorithm that requires extensive new training data in the context of this 510(k) summary. The focus is on demonstrating that the new software version performs as intended and is substantially equivalent to previous versions.

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The Siemens SOMATOM Definition Edge (Project P46F) systems are intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from either the same axial plane taken at different angles or spiral planes* taken at different angles.

(*spiral planes: the axial planes resulted from the continuous rotation of detectors and x-ray tube, and the simultaneous translation of the patient.)

Siemens intends to market a new software version, syngo® VA48 (SOMARIS/7 VA48) for its SOMATOM Definition Edge Computed Tomography X-ray systems. The subject device SOMATOM Definition Edge will be delivered with software version syngo® VA48 (SOMARIS/7 VA48). Additionally software version synqo® VA48 (SOMARIS/7 VA48 will be offered as an optional upgrade for existing SOMATOM Definition Edge systems. syngo® VA48 (SOMARIS/7 VA48) is a further development to the SOMARIS/7 operating software cleared as part of the predicate devices.

This document is a 510(k) summary for the Siemens SOMATOM Definition Edge Computed Tomography Systems with software version syngo® VA48. It demonstrates substantial equivalence to previously cleared predicate devices.

Here's an analysis based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with specific performance metrics for the SOMATOM Definition Edge with syngo® VA48. Instead, it states that the device is "designed to fulfill the requirements of the following standards" and that "The testing results supports that all the software specifications have met the acceptance criteria."

The listed standards include:

• IEC 60601-2-44: Medical electrical equipment Part 2-44: Particular requirements for the safety of X-ray equipment for computed tomography - Ed. 2.1
• IEC 61223-3-5: Evaluation and routine testing Evaluation and routine testing in medical imaging departments - Part 3-5: Acceptance tests - Imaging performance of computed tomography X-ray equipment CORRIGENDUM 1
• NEMA XR-25: Computed Tomography Dose Check
• IEC 61223-2-6: Evaluation and routine testing in medical imaging departments - Part 2-6: Constancy tests - Imaging performance of computed tomography X-ray equipment
• NEMA PS 3.1 3.18: Digital Imaging and Communications in Medicine (DICOM) Set
• IEC 62304 Ed. 1.0: Medical device software software life cycle processes
• IEC 60601-1: Medical electrical equipment - Part 1: General requirements for Safety, 1988, Amendment 1, 1991-11, Amendment 2, 1995
• ISO 14971: Medical devices Application of risk management to medical devices
• NEMA XR-29: Standard Attributes on CT Equipment Related to Dose Optimization and Management

The document generally states that "Performance tests were conducted to test the functionality of the SOMATOM Definition Edge configured with software version syngo® VA48. These tests have been performed to test the ability of the included features of the subject device. 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."

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

The document does not specify a sample size for a test set, nor does it detail the provenance (e.g., country of origin, retrospective/prospective) of any clinical data. The submission focuses on non-clinical testing and software validation. It mentions that "The predicate devices were cleared based on non-clinical supportive information and clinical images," but does not explicitly state that new clinical images were used for this particular submission's test set.

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. The testing described is non-clinical performance and software validation.

4. Adjudication Method for the Test Set

This information is not provided in the document.

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

No MRMC study is mentioned in this 510(k) summary. The document focuses on demonstrating substantial equivalence through non-clinical testing and software validation, not on comparative effectiveness with human readers.

6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study

The document describes non-clinical technical performance tests and software verification/validation, indicating a standalone evaluation of the device's functionality. It states: "Non clinical tests were conducted for the SOMATOM Definition Edge configured with software version syngo® VA48 during product development. The modifications described in this Premarket Notification were supported with verification/validation testing." However, this is for the CT system itself, not an AI algorithm in the contemporary sense. The "AI" components listed (ADMIRE Iterative Reconstruction, iMAR Improved Metal Artifact Correction, MARIS) are features of the CT imaging chain rather than separate diagnostic AI algorithms requiring individual standalone performance evaluation in this context.

7. Type of Ground Truth Used

For the non-clinical testing and software validation, the ground truth would be defined by the technical specifications and expected performance characteristics of the CT system and its software features, as outlined in the referenced IEC and NEMA standards. There is no mention of ground truth established by expert consensus, pathology, or outcomes data, as this submission is for a CT system update, not a diagnostic AI algorithm.

8. Sample Size for the Training Set

This information is not applicable and therefore not provided. The document describes an update to a CT imaging system's software version, not a machine learning model that undergoes a distinct training phase with a specific training set. The "features" like ADMIRE, iMAR, and MARIS are advanced image reconstruction and processing techniques, not typically "trained" on a dataset in the way a deep learning model is.

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

This information is not applicable and therefore not provided.

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