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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 Flash system is 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.)

New software version syngo® VA48 (SOMARIS/7 VA48) is a commandbased program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation that will be available on the SOMATOM Definition Flash CT system. syngo® VA48 (SOMARIS/7 VA48) is a further development to the SOMARIS/7 operating software cleared as part of the predicate devices.

syngo® VA48 is scanner platform software that supports the following device features:

1). New system scanner software version SOMARIS/7 VA48 which includes:

-Respiratory - Analysis of Respiratory Rate & Pitch Adjustment -FAST 3D Reconstruction (FAST 3D Align)

-Multiphase reconstruction with extended Field of View

-FAST DE Results (Dual Energy PACS-ready images) -FAST Contact

-Iterative Reconstruction with extended Field of View

-OEM Varian RGSC Online Mode

-Full 4D Lung Scan

-Applications at CT - syngo.via client

• -Temporal MIP (t-MIP)
• -TrueD 4D Viewer
• 2). ADMIRE Iterative Reconstruction (option)
• 3). iMAR Improved Metal Artifact Reduction (option)
• 4). MARIS (Metal Artifact Reduction in Image Space) Option
• 5). HandCARE Quantitative Dose Reduction Option
• 6). CARE Dose4D Dose Reduction Option

There are no modifications to the hardware of the SOMATMOM Definition Flash.

The provided text is a 510(k) premarket notification for the Siemens SOMATOM Definition Flash CT system. It describes the device, its intended use, and its equivalence to previously cleared predicate devices. However, it does not contain the specific details required to fully address your request regarding acceptance criteria and the study that proves the device meets them.

The document states:

• "The test results show that all of the software specifications have met the acceptance criteria. Verification and validation testing of the device was found acceptable to support the claims of substantial equivalence." (Page 6)
• "Performance tests were conducted to test the functionality of the SOMATOM Definition AS Open 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." (Page 7)

While it confirms that tests were conducted and acceptance criteria were met for software specifications and overall functionality, it does not explicitly list the acceptance criteria themselves, nor does it provide detailed study data, sample sizes, ground truth establishment methods, or specific performance metrics (like sensitivity, specificity, or AUC) that you'd expect from a clinical performance study.

Therefore, I cannot populate the table or answer most of your detailed questions based solely on the provided text. The document focuses on regulatory compliance (510(k) pathway for substantial equivalence) rather than a detailed clinical performance study report.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

• Cannot provide. The document states that acceptance criteria were met for software specifications and device functionality, but it does not specify what those criteria were (e.g., specific quantitative thresholds for image quality, diagnostic accuracy, or dose reduction) or the numerical 'reported device performance' against them.

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

• Cannot provide. The document mentions "non-clinical tests (integration and functional)" and "Performance tests" but does not detail the nature of these tests in terms of patient data (if any), sample sizes, or data provenance. The focus is on software and system functionality testing.

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):

• Cannot provide. The document does not describe any expert-reviewed test sets or ground truth establishment relevant to clinical performance.

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

• Cannot provide. Not applicable as no expert-reviewed test set is detailed.

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:

• Cannot provide. No mention of MRMC studies or AI assistance for human readers. The device is a CT scanner system with new software features, not an AI-assisted diagnostic tool in the sense of improving human reader performance.

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

• Cannot provide. While there were "Performance tests" and "software verification and validation," the document doesn't provide details to assess if these were purely standalone performance evaluations of an algorithm in a clinical context (e.g., detecting specific pathologies). The tests appear to be primarily functional and integration tests for a CT system's software update.

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

• Cannot provide. No information on ground truth for clinical performance.

8. The sample size for the training set:

• Cannot provide. The document describes software updates for a CT system, not an AI/machine learning model that would typically have a "training set."

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

• Cannot provide. See answer to point 8.

In summary: The provided document is a regulatory submission for a CT system upgrade, demonstrating substantial equivalence through non-clinical and functional testing against recognized standards. It does not contain the detailed clinical performance study information you are seeking.

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The Siemens SOMATOM Definition AS/ AS+ (Project P46) 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 simulaneous translation of the patient.)

Siemens intends to market a new software version, syngo ® VA48 (SOMARIS/7 VA48) for its SOMATOM Definition AS/AS+ Computed Tomography X-ray systems. The subject device SOMATOM Definition AS/AS+ 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 AS/AS+ systems. syngo® VA48 (SOMARIS/7 VA48) is a further development to the SOMARIS/7 operating software cleared as part of the predicate devices.

The provided text describes a 510(k) premarket notification for the Siemens SOMATOM Definition AS/AS+ Computed Tomography Systems with a new software version, syngo® VA48. The submission aims to demonstrate substantial equivalence to previously cleared predicate devices.

However, the document does not contain the specific acceptance criteria or details of a study that proves the device meets those criteria in the context of clinical performance or diagnostic accuracy.

The non-clinical testing section (Page 6 and 7) primarily focuses on:

• Adherence to recognized industry standards: IEC 60601-2-44, IEC 61223-3-5, NEMA XR-25, IEC 61223-2-6, NEMA PS 3.1-3.18, IEC 62304, IEC 60601-1, ISO 14971, NEMA XR-29.
• Software verification and validation: Stating that risk analysis was completed, risk control implemented, and testing results support that software specifications meet acceptance criteria, and that verification/validation was found acceptable.
• Performance tests: General statement that "Performance tests were conducted to test the functionality of... syngo® VA48... The results of these tests demonstrate that the subject device performs as intended."

Therefore, many of the requested details cannot be extracted from the provided text.

Here's an attempt to answer the questions based on the available information, with clear indications where the information is not present:

1. Table of Acceptance Criteria and Reported Device Performance

Not explicitly provided in the document. The document states that "all the software specifications have met the acceptance criteria" and "the subject device performs as intended" based on non-clinical performance and software verification/validation. However, the specific acceptance criteria (e.g., in terms of imaging performance metrics like spatial resolution, contrast-to-noise ratio, dose reduction effectiveness at specific levels, or diagnostic accuracy) are not detailed.

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

Not applicable/provided for clinical performance data. The document describes "non-clinical testing" and "software verification and validation." There is no mention of a clinical test set or patient data used for defining performance against specific acceptance criteria. The predicate devices were cleared "based on non-clinical supportive information and clinical images" (Page 7), but this refers to the previous clearances, not the current submission's testing.

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

Not applicable/provided. As there's no described clinical test set with ground truth establishment.

4. Adjudication Method for the Test Set

Not applicable/provided. As there's no described clinical test set with ground truth establishment.

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

No. The document does not describe an MRMC study or any study involving human readers with or without AI assistance.

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

Partially Yes, but not in the context of diagnostic accuracy. The "performance tests" mentioned are likely standalone tests of the software's functionality, adherence to standards, and system performance (e.g., image quality metrics, dose reduction functionality) without human interpretation in a diagnostic setting. However, the specific metrics and results are not detailed.

7. The Type of Ground Truth Used

Not applicable for clinical ground truth. The "ground truth" for the non-clinical and software testing would be the expected functional behavior, adherence to engineering specifications, and compliance with industry standards. No clinical ground truth (e.g., pathology, outcomes data, expert consensus on disease presence) is mentioned as part of this submission's testing.

8. The Sample Size for the Training Set

Not applicable/provided. This submission is for a CT system with updated software, not an AI/ML algorithm that requires a training set in the conventional sense. The software updates are described as "further development" of existing operating software (Page 4).

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

Not applicable/provided. As there is no mention of a training set.

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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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The Siemens SOMATOM Definition AS Open 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.)

New software version syngo® VA48 (SOMARIS/7 VA48) is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation that will be available on the SOMATOM Definition AS Open Computed Tomography systems. syngo® VA48 (SOMARIS/7 VA48) is a further development to the SOMARIS/7 operating software cleared as part of the predicate device.

syngo® VA48 is scanner platform software that supports the following device features:

• 1). New system scanner software version synqo® VA48 (SOMARIS/7 VA48) which includes:
  • -Respiratory Analysis of Respiratory Rate & Pitch Adjustment -FAST 3D Reconstruction (FAST 3D Align)
  • -Multiphase reconstruction with extended Field of View
  • -FAST DE Results (Dual Energy PACS-ready images)
  • -FAST contact
  • -Iterative Reconstruction with extended Field of View
  • -OEM Varian RGSC Online Mode
  • -Full 4D Lung Scan
  • -Applications at CT syngo.via client
  • -TrueD 4D Viewer
• 2). ADMIRE Iterative Reconstruction (Option)
• 3). iMAR Improved Metal Artifact Reduction (Option)

There are no modifications to the hardware of the device.

This document, a 510(k) Summary for the Siemens SOMATOM Definition AS Open CT system with software version syngo® VA48, primarily focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed clinical study demonstrating improved human reader performance with AI assistance. It describes software updates and their verification and validation against technical standards.

Therefore, many of the requested details, such as specific acceptance criteria for AI performance, clinical study design for improved human reader performance, sample sizes for test sets in an MRMC study, expert qualifications for ground truth in a clinical context, or the effect size of AI assistance on human reader performance, are not explicitly available within this document. This submission is for a computed tomography x-ray system, and the "AI" or "machine learning" components mentioned (e.g., ADMIRE Iterative Reconstruction, iMAR Improved Metal Artifact Reduction) are features of the imaging system and reconstruction algorithms, not typically standalone AI interpretation tools that would undergo an MRMC study in the way a diagnostic AI would.

Given the information provided, here's what can be extracted and inferred, with limitations noted:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't provide a table of performance acceptance criteria in the sense of a diagnostic AI's clinical metrics (e.g., sensitivity, specificity, AUC). Instead, it refers to acceptance criteria for software specifications and conformance to technical standards.

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

The document refers to "Performance tests" and "Non-clinical tests (integration and functional)" but does not specify a sample size for a clinical test set of patient data, nor its provenance (country, retrospective/prospective). This type of information would be expected for a diagnostic AI device, not typically for a CT system software update focusing on features like iterative reconstruction or metal artifact reduction.

3. Number of Experts and Qualifications for Ground Truth:

Not applicable to this type of submission. There is no mention of human experts establishing ground truth for a diagnostic test set in the context of this 510(k). The "ground truth" here likely refers to technical specifications and expected performance characteristics of the CT system and its software, validated through engineering and phantom testing, rather than clinical interpretation.

4. Adjudication Method for the Test Set:

Not applicable. No clinical adjudication process is described as there isn't a stated clinical test set requiring human interpretation for ground truth.

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

No, an MRMC study was explicitly not done or described in this document. This regulatory submission is for a computed tomography x-ray system, specifically a software update (syngo® VA48) that includes features like iterative reconstruction (ADMIRE) and metal artifact reduction (iMAR). These are image processing and acquisition technologies, not AI-driven diagnostic assistance tools designed to change human reader performance in a comparative effectiveness study.

6. Standalone Performance (Algorithm Only without Human-in-the-Loop Performance):

The document describes "Performance tests" to "test the functionality of the SOMATOM Definition AS Open configured with software version syngo VA48." While not using the term "standalone performance" in the context of a diagnostic AI, the testing described appears to be algorithm-only, focused on the technical performance and functional verification of the software features themselves (e.g., image reconstruction quality, artifact reduction effectiveness) against technical standards. "The results of these tests demonstrate that the subject device performs as intended."

7. Type of Ground Truth Used:

The ground truth for this submission appears to be based on:

• Technical specifications and engineering standards: Conformance to various IEC and NEMA standards (e.g., IEC 60601-2-44, IEC 61223-3-5, NEMA XR-25, DICOM).
• Internal software specifications and functional requirements: "The test results show that all the software specifications have met the acceptance criteria."
• Risk analysis and mitigation: "The Risk analysis was completed, and risk control implemented, to mitigate identified hazards." (The "ground truth" here is the identified hazards and their successful mitigation).

There is no mention of expert consensus, pathology, or outcomes data as a ground truth for clinical performance in this document.

8. Sample Size for the Training Set:

Not applicable. This document is not describing a machine learning model that was "trained" on a dataset in the way a diagnostic AI would be. The software updates described (like ADMIRE and iMAR) are based on algorithms and iterative processes, but the traditional concept of a "training set" for a deep learning model isn't presented here.

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

Not applicable, as there is no described training set for an AI model in this document.

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The Siemens SOMATOM Definition AS Open 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.)

The Siemens SOMATOM Definition AS Open is a whole body X-ray Computed Tomography System. The SOMATOM Definition AS Open produces 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 new version of system software, syngo® CT 2013B (SOMARIS/7 VA46A), supports the following features:

• MARIS (Metal Artifact Reduction in Image Space) A image . reconstruction mode designed to reduce image artifacts caused by metal
• HD FoV Pro (HD FoV 2.0) Designed to enable a more reliable . visualization of the skin line of human body parts located outside of the standard field of view
• t-MIP -- Image manipulation method for arithmetic operations which allows . the calculation of temporal Maximum or Minimum Intensity Projection (MIP) images from a set of series.

Here's a breakdown of the acceptance criteria and the study information for the SOMATOM Definition AS Open configured with software version syngo® CT 2013B (SOMARIS/7 VA46A), based on the provided text:

Important Note: The provided document is a 510(k) summary for a medical device which is largely about demonstrating "substantial equivalence" to a predicate device. This type of submission often focuses on verifying that new features don't introduce new safety or effectiveness concerns, rather than conducting a full-scale clinical trial to prove a specific level of diagnostic performance against a robust ground truth. As such, some of the requested information (especially about specific performance metrics tied to acceptance criteria, MRMC studies, and detailed ground truth establishment for clinical effect) might not be explicitly present or as detailed as in a typical in vitro diagnostic (IVD) or AI-only software submission.

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size (Clinical Tests): Not specified. The document states "Clinical tests were performed... to validate the performance of the MARIS algorithm" and "These tests include testing of the metal artifact reduction capabilities of MARIS in different clinical scenarios." However, the number of patients, scans, or images is not provided.
• Data Provenance: Not explicitly stated (e.g., country of origin). The tests were "clinical tests," implying real patient data. It is highly likely to be retrospective clinical data, as typical for 510(k) submissions focusing on software improvements, but this is not explicitly confirmed.

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

• The document mentions "clinical tests" for MARIS validation, but it does not specify how ground truth was established for these tests, nor does it mention the number or qualifications of experts involved in any ground truth assessment. In the context of metal artifact reduction, "ground truth" might be subjective visual assessment by radiologists if not compared to a gold standard imaging modality.

4. Adjudication Method for the Test Set:

• The document does not specify any adjudication method (e.g., 2+1, 3+1). Given the lack of detail on expert involvement, it's unlikely a formal adjudication process was described for the submission.

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

• No, an MRMC comparative effectiveness study was not done (or at least not described in this summary). The studies mentioned focus on validating the performance of features (MARIS, HD FoV Pro) in the device itself, not on comparing human reader performance with and without AI assistance from this specific device.

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

• The document describes "bench tests were performed to verify and validate the performance of the MARIS and HD FoV Pro (HD FoV 2.0) features," which are likely standalone algorithm evaluations using phantoms or controlled datasets.
• "Clinical tests" were also performed for the MARIS algorithm, which would involve the algorithm processing clinical data. While these involve physicians interpreting the output of the CT system, the focus of the "clinical tests" was on validating the algorithm's performance (e.g., artifact reduction), rather than a human reading study. So, in terms of the algorithm itself, yes, standalone performance was assessed.

7. The Type of Ground Truth Used:

• For the "bench tests" of MARIS and HD FoV Pro, the ground truth would likely be phantom-based measurements and technical specifications. Phantoms provide a known, controlled environment to assess image quality, artifact reduction, and field of view accuracy.
• For the "clinical tests" of MARIS, the document does not explicitly state the type of ground truth used. In the context of artifact reduction, it could involve visual assessment by clinicians comparing images with and without MARIS, or a comparison to an established 'gold standard' image if available (e.g., a non-metallic scan of the same area if feasible). However, no specifics are provided.

8. The Sample Size for the Training Set:

• The document does not specify the sample size for any training set. This is not uncommon for 510(k) submissions where the software updates are incremental and rely on established engineering practices, rather than a deep learning model requiring a distinct, large training dataset. The MARIS algorithm is described as an "image reconstruction mode," implying an algorithmic approach rather than a machine learning model that undergoes explicit "training" on a labeled dataset.

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

• As the document does not mention a training set in the context of machine learning, there is no information on how its ground truth was established. For algorithmic development, the "training" (design and tuning) is based on engineering principles, image science, and potentially smaller, internally-derived datasets with known properties or simulated artifacts.

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The SOMATOM P45 is 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 resulting from the continuous rotation of detectors and x-ray tube, and the simultaneous translation of the patient.)

The Siemens SOMATOM P45 is a whole body X-ray Computed Tomography System, which features two continuously rotating tube-detector systems and functions according to the fan beam principle. The SOMATOM P45 produces CT images in DICOM format, which can be used by postprocessing 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 new version of system software, SOMARIS/7 VA44, supports a Windows 7 operating system, additional scanning and evaluation techniques CARE (Combined Application to Reduce Exposure) and FAST (Fully Assisted Scanner Technology), and single click 3D reconstruction of Dual Energy Scans. The computer system delivered with the CT scanner is able to run the post processing applications optionally.

Here's an analysis of the provided Siemens 510(k) submission for the SOMATOM P45 CT system, focusing on acceptance criteria and supporting studies:

This 510(k) submission is for a software update (SOMARIS/7 VA44) to an existing CT system (SOMATOM P45), not for a novel device. The primary argument for substantial equivalence relies on the fact that the changes are not significant in terms of materials, energy source, or technological characteristics compared to predicate devices. This means that extensive clinical studies with new acceptance criteria, as one might expect for a completely new AI algorithm or diagnostic device, are not detailed in this type of submission.

Therefore, many of the typical acceptance criteria and study details requested in your prompt (e.g., number of experts, adjudication methods, MRMC studies, standalone performance with novel AI) are not applicable to this specific 510(k) summary. The "acceptance criteria" here are primarily met through verification and validation of the software changes and phantom testing to ensure the updated system continues to perform as expected and safely.

Here's a breakdown based on your request, with an emphasis on what is and isn't present in this type of 510(k):

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is a 510(k) for a software update to an existing CT system, the "acceptance criteria" revolve around ensuring the updated system maintains the safety and effectiveness of the predicate device and that the new software functions correctly. The submission states:

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

• Sample Size: Not specified in terms of patient data. The testing mentioned is "non clinical tests" and "phantom testing." This suggests that the "test set" primarily consisted of:
  • Software test cases for verification and validation.
  • Physical phantoms for image quality and performance assessment.
• Data Provenance: Not applicable in the context of clinical patient data for this submission. The tests are "non clinical" and involve "phantom testing" and internal "verification/validation." There's no mention of human subject data, country of origin, or retrospective/prospective clinical data for this specific 510(k) submission.

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

• Not Applicable: This submission does not describe a clinical study requiring human expert assessment for ground truth. Verification and validation of CT system software and phantom performance typically rely on engineering specifications, physical measurements, and image quality metrics, not expert consensus on diagnostic interpretations of patient data.

4. Adjudication Method for the Test Set

• Not Applicable: Since there's no expert-based ground truth establishment described for patient data, no adjudication method would be presented.

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, not specified and highly unlikely for this type of submission. This 510(k) is for a software update to an existing CT scanner, not a novel AI-driven diagnostic aid that would typically require an MRMC study to demonstrate clinical improvement. The new features (CARE, FAST, single-click 3D) are enhancements to existing CT capabilities, not AI for diagnostic interpretation.

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

• Not Applicable for a novel diagnostic algorithm. The "algorithm" here refers to the CT system's operating software for image acquisition, reconstruction, and basic post-processing. Its performance is always "standalone" in the sense that the system itself generates the images, but it's not a standalone diagnostic algorithm in the way a CAD system would be. The focus is on the system's ability to produce images according to specifications, not on its isolated diagnostic performance.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

• Engineering Specifications and Physical Measurements: For the software, the "ground truth" is adherence to its predefined functional and performance specifications. For phantom testing, the "ground truth" would be expected physical measurements, known phantom properties, and established image quality metrics (e.g., spatial resolution, contrast-to-noise ratio, dose efficiency). There is no mention of expert consensus, pathology, or outcomes data, as those are typically relevant for diagnostic interpretation, which is not the focus of this particular 510(k) update.

8. The Sample Size for the Training Set

• Not Applicable: This is not a machine learning or AI algorithm in the contemporary sense that requires a "training set" of data. It's an update to the operating software of a CT scanner. The software would have been developed and tested through traditional software engineering methods.

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

• Not Applicable: As there's no "training set" in the context of machine learning, there's no ground truth established for one. The "ground truth" for software development would be its design specifications and requirements.

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The Siemens SOMATOM Definition Flash system is 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.

In addition the SOMATOM Definition Flash is able to produce additional image planes and analysis results by executing optional post processing features, which operate on DICOM images.

The images and results delivered by the system can be used by a trained physician as an aid in diagnosis.

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

The Siemens SOMATOM Definition Flash is a Computed Tomography X- ray System, which features two continuously rotating tube-detector systems and functions according to the fan beam principle. The SOMATOM Definition Flash produces 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 new version of system software, SOMARIS/7 VA44, allows the reconstruction of images with a slice thickness of 0.5mm for SOMATOM Definition Flash systems equipped with Stellar Detector.

The computer system delivered with the CT scanner is able to run the post processing applications optionally. The Stellar Detector will be offered as an optional upgrade to the cleared SOMATOM Definition Flash CT systems.

The provided text describes a 510(k) submission for the SOMATOM Definition Flash CT System, focusing on modifications introduced with software version SOMARIS/7 VA44. The key modification is the ability to reconstruct 0.5mm slices for systems equipped with Stellar Detector and SAFIRE, providing a z-axis resolution of 0.3mm. The submission details non-clinical testing to support these modifications.

However, the provided text does not contain a table of acceptance criteria or reported device performance metrics in the way typically expected for a detailed study report. Instead, it focuses on demonstrating substantial equivalence to predicate devices through technical characteristic comparisons and non-clinical testing.

Here's an attempt to answer the questions based on the available information, highlighting what is missing or not explicitly stated:

Acceptance Criteria and Device Performance

The document does not explicitly state quantitative acceptance criteria or a table of reported device performance values in the context of a clinical study or a formal validation report against specific performance targets (e.g., sensitivity, specificity for a diagnostic task).

Instead, the "acceptance criteria" appear to be implicit in the non-clinical testing performed, which aimed to confirm the technical capabilities of the new software feature (0.5mm slice reconstruction).

Implicit Acceptance Criteria and Reported Performance (from non-clinical testing):

Study Details

1. Sample size used for the test set and the data provenance:

   • The document describes "phantom tests" to evaluate the 0.5mm slice width.
   • Test Set Sample Size: Not specified. Phantom studies typically involve multiple acquisitions or varying phantom configurations, but the number of "samples" or "cases" is not quantified.
   • Data Provenance: Phantom data (simulated/controlled environment). No human patient data is mentioned for this specific testing.

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

   • Not applicable/Not mentioned. Phantom studies typically do not involve human experts establishing ground truth in the same way clinical studies do. The "ground truth" for phantom measurements is based on the known physical properties and geometry of the phantom and the expected output based on theoretical understanding or established measurement techniques.

3. Adjudication method for the test set:

   • Not applicable. As this was non-clinical phantom testing, no expert adjudication was involved. The measurements are objective physical assessments.

4. 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. The document explicitly states "Nonclinical Testing" and describes phantom tests. There is no mention of an MRMC study or any assessment of human reader performance or AI assistance. This device is a CT scanner, and the modifications are about image reconstruction capabilities, not an AI-assisted diagnostic tool for human readers.

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

   • Yes, to some extent. The non-clinical testing of the software focuses on the performance of the image reconstruction algorithm itself using phantom data (e.g., measuring MTF, spatial resolution). This can be considered a standalone assessment of the algorithm's capability to produce specific image characteristics.

6. The type of ground truth used:

   • For the non-clinical phantom testing, the ground truth is derived from known physical properties and characteristics of the phantoms used (e.g., precisely manufactured structures for resolution assessment) and established measurement methodologies for CT performance.

7. The sample size for the training set:

   • Not applicable/Not mentioned. This submission does not describe an AI model that requires a training set. The software update is for image reconstruction logic and hardware capabilities, not a machine learning algorithm in the typical sense that would necessitate a trained model.

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

   • Not applicable. As no training set for an AI model is mentioned, there's no ground truth establishment for such a set.

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The Siemens SOMATOM Definition Flash (with Stellar Detector) system is 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.

In addition the SOMATOM Definition Flash (with Stellar Detector) is able to produce additional image planes and analysis results by executing optional post processing features, which operate on DICOM images.

The images and results delivered by the system can be used by a trained physician as an aid in diagnosis.

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

The Siemens SOMATOM Definition Flash (with Stellar Detector) is a Computed Tomography X- ray System, which features two continuously rotating tube-detector systems and functions according to the fan beam principle. 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 SOMATOM Definition Flash (with Stellar Detector) produces CT images in DICOM format, which can be used by post-processing applications commercially distributed by Siemens and other vendors.

The computer system delivered with the CT scanner is able to run such post processing applications optionally.

The provided text is a 510(k) summary for the Siemens SOMATOM Definition Flash (with Stellar Detector) Computed Tomography X-ray system. This document focuses on demonstrating substantial equivalence to a predicate device (Siemens SOMATOM FLASH DS, K082220) rather than presenting a study with specific acceptance criteria and detailed performance data of the new device against those criteria in the context of clinical accuracy or diagnostic efficacy.

Therefore, the information requested in your prompt regarding acceptance criteria, device performance, sample sizes, expert qualifications, and detailed study methodologies for assessing the device's diagnostic capabilities is not contained within the provided text.

The document discusses the device's technical specifications, intended use, and general safety and effectiveness concerns related to its design and manufacturing practices, which are typically part of a 510(k) submission for demonstrating substantial equivalence for a medical imaging device. It does not include clinical performance studies with specific metrics like sensitivity, specificity, or reader agreement that would typically be associated with answering the questions you've posed.

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