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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 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.

Siemens intends to update the software version syngo CT VB20 (update) for the following NAEOTOM Alpha class CT systems:

Dual Source NAEOTOM CT scanner systems:

• NAEOTOM Alpha (trade name ex-factory CT systems: NAEOTOM Alpha.Peak; trade name installed base CT systems with SW upgrade only: NAEOTOM Alpha)

For simplicity, the product name of NAEOTOM Alpha will be used throughout this submission instead of the trade name NAEOTOM Alpha.Peak.

• NAEOTOM Alpha.Pro

Single Source NAEOTOM CT scanner system:

• NAEOTOM Alpha.Prime

The subject devices NAEOTOM Alpha (trade name ex-factory CT systems: NAEOTOM Alpha.Peak) and NAEOTOM Alpha.Pro with software version SOMARIS/10 syngo CT VB20 (update) are Computed Tomography X-ray systems which feature two continuously rotating tube-detector systems, denominated as A- and B-systems respectively (dual source NAEOTOM CT scanner system).

The subject device NAEOTOM Alpha.Prime with software version SOMARIS/10 syngo CT VB20 (update) is a Computed Tomography X-ray system which features one continuously rotating tube-detector systems, denominated as A-system (single source NAEOTOM CT scanner system).

The detectors' function is based on photon-counting technology.

In this submission, the above-mentioned CT scanner systems are jointly referred to as subject devices by "NAEOTOM Alpha class CT scanner systems".

The NAEOTOM Alpha class CT scanner systems with SOMARIS/10 syngo CT VB20 (update) produce CT images in DICOM format, which can be used by trained staff for post-processing applications commercially distributed by Siemens and other vendors. The CT images can be used by a trained staff as an aid in diagnosis, treatment and radiation therapy planning as well as for diagnostic and therapeutic interventions. The radiation therapy planning support includes, but is not limited to, Brachytherapy, Particle Therapy including Proton Therapy, External Beam Radiation Therapy, Surgery. The computer system delivered with the CT scanner is able to run optional post-processing applications.

Only trained and qualified users, certified in accordance with country-specific regulations, are authorized to operate the system. For example, physicians, radiologists, or technologists. The user must have the necessary U.S. qualifications in order to diagnose or treat the patient with the use of the images delivered by the system.

The platform software for the NAEOTOM Alpha class CT scanner systems is syngo CT VB20 (update) (SOMARIS/10 syngo CT VB20 (update)). It is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation. The software platform provides plugin software interfaces that allow for the use of specific commercially available post-processing software algorithms in an unmodified form from the cleared stand-alone post-processing version.

Software version syngo CT VB20 (update) (SOMARIS/10 syngo CT VB20 (update)) shall support additional software features compared to the software version of the predicate devices NAEOTOM Alpha class CT systems with syngo CT VB20 (SOMARIS/10 syngo CT VB20) cleared in K243523.

Software version SOMARIS/10 syngo CT VB20 (update) will be offered ex-factory and as optional upgrade for the existing NAEOTOM Alpha class systems.

The bundle approach is feasible for this submission since the subject devices have similar technological characteristics, software operating platform, and supported software characteristics. All subject devices will support previously cleared software and hardware features in addition to the applicable modifications as described within this submission. The intended use remains unchanged compared to the predicate devices.

The provided document describes the acceptance criteria and a study that proves the device meets those criteria for the NAEOTOM Alpha CT Scanner Systems. However, the document primarily focuses on demonstrating substantial equivalence to a predicate device and safety and effectiveness based on non-clinical testing and adherence to standards, rather than detailing a specific clinical performance study with defined acceptance criteria for a diagnostic aid.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a specific table of acceptance criteria with corresponding performance metrics in the way one would typically find for a diagnostic AI device (e.g., sensitivity, specificity, AUC). Instead, it states that:

• Acceptance Criteria for Software: "The test specification and acceptance criteria are related to the corresponding requirements." and "The test results show that all of the software specifications have met the acceptance criteria."
• Acceptance Criteria for Features: "Test results show that the subject devices...is comparable to the predicate devices in terms of technological characteristics and safety and effectiveness and therefore are substantially equivalent to the predicate devices."
• Performance Claim: "The conclusions drawn from the non-clinical and clinical tests demonstrate that the subject devices are as safe, as effective, and perform as well as or better than the predicate devices."

The closest the document comes to defining and reporting on "performance criteria" for a specific feature, beyond basic safety and technical functionality, are for the HD FoV 5.0 and ZeeFree RT algorithms.

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

The document mentions "physical and anthropomorphic phantoms" for HD FoV 5.0 and "homogeneous water phantom" and "phantom with tissue-equivalent inserts," and "dynamic thorax phantom" for ZeeFree RT. It also refers to "retrospective blinded rater studies of respiratory 4D CT examinations performed at two institutions" for ZeeFree RT, but does not specify the sample size (number of cases/patients) or the country of origin for these real-world examination datasets. The data provenance (retrospective/prospective) is stated for the rater study for ZeeFree RT as retrospective, but not for the HD FoV 5.0 rater study (though implied by "retrospective blinded rater study").

3. Number of Experts and Qualifications for Ground Truth

For the HD FoV 5.0 and ZeeFree RT rater studies, the experts were "board-approved radio-oncologists and medical physicists." The number of experts is not specified, nor is their specific years of experience.

4. Adjudication Method for the Test Set

The document explicitly states "retrospective blinded rater study" for HD FoV 5.0 and ZeeFree RT. However, it does not specify the adjudication method (e.g., 2+1, 3+1, none) if there were multiple raters and disagreements.

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

The document states that for HD FoV 5.0 and ZeeFree RT, "the performance of the algorithm was evaluated by board-approved radio-oncologists and medical physicists by means of retrospective blinded rater study." This indicates a reader study, which is often a component of an MRMC study.

However, the study described does not appear to be comparing human readers with AI assistance vs. without AI assistance. Instead, for HD FoV 5.0, it's comparing the new algorithm's results to its predecessor, HD FoV 4.0. For ZeeFree RT, it's comparing the reconstruction to "Standard reconstruction" and assessing if it introduces errors or new artifacts. It's an evaluation of the algorithm's output, not necessarily a direct measure of human reader improvement with AI assistance. Therefore, no effect size for human reader improvement with AI vs. without AI assistance is reported because this specific type of comparative effectiveness study was not described.

6. Standalone (Algorithm Only) Performance Study

Yes, standalone (algorithm only) performance was conducted. The bench testing described for both HD FoV 5.0 and ZeeFree RT involves detailed evaluations of the algorithms' outputs using phantoms and comparing them to established standards or previous versions. For example, for ZeeFree RT, the bench test objectives include demonstrating that it "introduces no relevant errors in terms of CT values and noise levels measured in a homogeneous water phantom" and "does not introduce relevant new artefacts." This is an assessment of the algorithm's direct output.

7. Type of Ground Truth Used

The ground truth used primarily appears to be:

• Phantom-based measurements: For HD FoV 5.0 (physical and anthropomorphic phantoms) and ZeeFree RT (homogeneous water phantom, tissue-equivalent inserts, static torso phantom, dynamic thorax phantom). These phantoms have known properties which serve as ground truth for evaluating image quality metrics.
• Expert Consensus/Interpretation: For HD FoV 5.0 and ZeeFree RT, it involved "board-approved radio-oncologists and medical physicists" in "retrospective blinded rater studies." This suggests the experts' interpretations (potentially comparing image features or diagnostic quality) formed a part of the ground truth or served as the primary evaluation method. The text doesn't specify if there was a pre-established "true" diagnosis or condition for these clinical cases, or if the experts were rating image quality or agreement with a reference standard.

8. Sample Size for the Training Set

The document does not specify the sample size for the training set for any of the algorithms or software features. This document is a 510(k) summary, which generally focuses on justification for substantial equivalence rather than detailed algorithm development specifics.

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

The document does not describe how the ground truth for the training set was established, as it does not provide information about the training set itself.

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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 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.

Siemens intends to market a new Single source CT system NAEOTOM Alpha.Prime and a new Dual Source CT system NAEOTOM Alpha.Pro based on the SOMARIS/10 software platform.

Siemens also intends to market updated software version, SOMARIS/10 syngo CT VB20, for the new NAEOTOM CT scanner systems and for the NAEOTOM Alpha cleared in K233657 (clearance date March 28th, 2024). The updated software version SOMARIS/10 syngo CT VB20 incorporates mainly features for radiotherapy planning support.

With the new software version SOMARIS/10 syngo CT VB20, the trade name of NAEOTOM Alpha cleared in K233657 has been changed to NAEOTOM Alpha.Peak for ex-factory systems. Systems already installed will receive the software update without change of the trade name. The system label keeps the product name NAEOTOM Alpha. System label information and UDI are not changed and remain the same as the original submitted.

For simplicity, the product name of NAEOTOM Alpha will be used throughout this submission instead of the trade name NAEOTOM Alpha.Peak.

The subject devices NAEOTOM Alpha (trade name ex-factory CT systems: NAEOTOM Alpha.Peak) and NAEOTOM Alpha.Pro with software version SOMARIS/10 syngo CT VB20 are Computed Tomography X-ray systems which feature two continuously rotating tube-detector systems, denominated as Aand B-systems respectively (dual source NAEOTOM CT scanner system).

The subject device NAEOTOM Alpha.Prime with software version SOMARIS/10 syngo CT VB20 is a Computed Tomography X-ray system which features one continuously rotating tube-detector systems, denominated as A-system (single source NAEOTOM Alpha CT scanner system).

The detectors' function is based on photon-counting technology.

In this submission, the above-mentioned CT scanner systems are jointly referred to as subject devices by "NAEOTOM CT scanner systems".

The NAEOTOM CT scanner systems with SOMARIS/10 syngo CT VB20 produce CT images in DICOM format, which can be used by trained staff for post-processing applications commercially distributed by Siemens and other vendors. The CT images can be used by a trained staff as an aid in diagnosis, treatment and radiation therapy planning as well as for diagnostic and therapeutic interventions. The radiation therapy planning support includes, 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.

Only trained and qualified users, certified in accordance with country-specific regulations, are authorized to operate the system. For example, physicians, radiologists, or technologists. The user must have the necessary U.S. qualifications in order to diagnose or treat the patient with the use of the images delivered by the system.

The platform software for the NAEOTOM CT scanner systems is syngo CT VB20 (SOMARIS/10 syngo CT VB20). It is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation. The software platform provides plugin software interfaces that allow for the use of specific commercially available post-processing software algorithms in an unmodified form from the cleared stand-alone post-processing version.

Software version syngo CT VB20 (SOMARIS/10 syngo CT VB20) is a modified software version of the primary predicate device NAEOTOM Alpha, syngo CT VB10 (SOMARIS/10 syngo CT VB10) cleared in K233657.

Software version SOMARIS/10 syngo CT VB20 will be offered ex-factory and as optional upgrade for the existing NAEOTOM Alpha systems.

The bundle approach is feasible for this submission since the subject devices have similar technological characteristics, software operating platform, and supported software characteristics. All subject devices will support previously cleared software and hardware features in addition to the applicable modifications as described within this submission. The intended use remains unchanged compared to the predicate devices.

The provided document is a 510(k) summary for the Siemens NAEOTOM CT Scanner Systems, specifically addressing the updated software version SOMARIS/10 syngo CT VB20 and new system configurations (NAEOTOM Alpha.Pro and NAEOTOM Alpha.Prime).

The document does not contain a multi-reader, multi-case (MRMC) comparative effectiveness study with human readers improving with AI vs. without AI assistance. The device described is a Computed Tomography (CT) X-ray system, which is a medical imaging hardware device, not an AI software intended for image interpretation assistance to human readers in the way an MRMC study would typically evaluate. The software features described primarily relate to system control, image reconstruction, and workflow efficiency, some of which are automated ("FAST" technologies) but do not indicate an "AI assistance" that augments a human reader's diagnostic performance in a comparative study design. Therefore, the questions related to MRMC studies and human reader improvement are not applicable to the information provided in this 510(k) summary.

Additionally, the document describes non-clinical performance testing (bench testing), which evaluates the technical performance of the device and its features, rather than a clinical study evaluating diagnostic accuracy against a ground truth from expert readers or pathology. The performance data presented is based on phantom tests and technical assessments rather than a clinical study. Therefore, several of the requested elements (number of experts, adjudication methods, type of ground truth for test sets/training sets, sample sizes for training/test sets as they pertain to clinical data) are not directly addressed in the context of a clinical performance study as typically understood for AI/CADe devices.

The acceptance criteria and reported device performance are generally stated in terms of comparable or improved accuracy to predicate devices and successful completion of verification and validation testing against internal specifications and recognized standards.

Here's an attempt to answer the questions based on the provided document, noting the limitations regarding the type of device and performance data presented:

Acceptance Criteria and Device Performance Study Summary

The device in question is a Computed Tomography (CT) X-ray System (NAEOTOM CT Scanner Systems) with software version SOMARIS/10 syngo CT VB20. The performance data provided are primarily from non-clinical bench testing to demonstrate the device's technical capabilities and comparability to predicate devices. The focus is on functionality verification and image quality evaluation, particularly for new and modified features.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a specific, quantifiable table of "acceptance criteria" for features in the typical sense of a clinical trial (e.g., sensitivity/specificity thresholds). Instead, "acceptance criteria" are referenced as being "related to the corresponding requirements" for various verification and validation tests. The reported performance is generally qualitative, stating that features meet expectations or are comparable/improved to predicate devices.

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

The "test set" in this context refers to phantom test data used for non-clinical bench testing.

• Sample Size: Not explicitly quantified as a number of "cases" or "patients" in the way a clinical study would. The descriptions indicate testing was performed on "a dynamic phantom" for Direct i4D, and "additional data from adults and adolescence patients" for FAST 3D Camera accuracy (though this data was for optimizing the feature, not for an independent test set as typically understood for a clinical performance evaluation). For FAST Planning, testing was done on "patient data" but no sample size is given. For Low-Dose Lung Cancer Screening, "technical parameters" were compared, implying phantom or engineering data. The overall testing framework includes "System Validation test" and "System Verification test" with various activities, but no specific human subject test set is detailed.
• Data Provenance: The data is from non-clinical bench testing and internal verification/validation activities. There is no mention of data origin in terms of "country of origin" as it is not a clinical study involving patient data from specific geographical locations. The testing is described as part of product development, implying internal company testing. It is inherently retrospective in the sense that it's testing a developed product against its specifications.

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

This information is not provided as the performance data is from non-clinical bench testing, not from a clinical study with a ground truth established by medical experts interpreting images. The "ground truth" for these tests would be the pre-defined technical specifications and expected physical behavior of the system, verified by engineering and quality assurance personnel.

4. Adjudication Method for the Test Set

Since there is no clinical test set involving human expert interpretations and potential discrepancies, an "adjudication method" is not applicable. The "acceptance criteria" for the non-clinical tests are against internal requirements and performance metrics (e.g., accuracy against a known phantom truth, successful triggering of functions).

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

No, an MRMC comparative effectiveness study was not done according to the provided information. This submission is for a CT scanner system (hardware and associated control/reconstruction software), not an AI software intended to assist human readers in image interpretation. The performance data focuses on the technical capabilities of the CT system itself.

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

The "performance data" section describes the technical performance and functionality of various software and hardware features, which can be considered "standalone" in the sense of evaluating the algorithm/system's output against a known input (e.g., phantom data). For instance:

• Direct i4D: Performance evaluated based on data acquisition and artifact avoidance.
• FAST Planning: Assessed the algorithm's ability to calculate ranges correctly and its speed.
• Low-Dose Lung Cancer Screening: Compared technical parameters.

However, this is not a "standalone performance" measure for diagnostic accuracy of an AI algorithm in the context of interpreting medical images compared to a clinical ground truth, but rather the technical performance of the imaging device and its embedded functionalities.

7. The Type of Ground Truth Used

For the non-clinical testing, the "ground truth" is technical/physical ground truth based on phantom properties, defined test conditions, and engineering specifications. For instance:

• For Direct i4D, the ground truth is the "breathing pattern of a thorax phantom."
• For FAST 3D Camera, the ground truth for accuracy would be the known physical position/orientation relative to the scanner.
• For FAST Planning, the ground truth involves "correct" calculated ranges based on anatomical rules or system design.

There is no mention of ground truth established via expert consensus, pathology, or outcomes data, as these are non-clinical hardware/software performance tests.

8. The Sample Size for the Training Set

The document does not provide information on a "training set" in the context of machine learning or AI models with labelled clinical data. The software features described are primarily rule-based or optimized algorithms, not deep learning models that require large labelled training datasets. While some features like FAST 3D camera were "optimized using additional data," this refers to data used for algorithm refinement (development/internal testing) and not a distinct "training set" for an AI model that would then be tested on an independent "test set."

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

Since no explicit "training set" for AI/ML algorithms is described in the provided context, this question is not applicable. The development and optimization of the system's features rely on engineering specifications, physical models, and potentially iterative refinement using internal test data (phantoms, potentially anonymized patient data for feature optimization) where the "truth" is either known by design or derived from highly controlled measurements.

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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 staff as an aid in diagnosis and treatment 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 NAEOTOM Alpha with software version SOMARIS/10 syngo CT VB10 is a Computed Tomography X-ray system which features two continuously rotating tube-detector systems, denominated as A- and B-systems respectively (dual source CT scanner system). The detectors' function is based on photon-counting technology. The NAEOTOM Alpha with SOMARIS/10 syngo CT VB10 produces CT images in DICOM format, which can be used by trained staff for postprocessing applications commercially distributed by Siemens and other vendors as an aid in diagnosis and treatment as well as for diagnostic and therapeutic interventions. The computer system delivered with the CT scanner is able to run optional post-processing applications.

The platform software for the NAEOTOM Alpha is syngo CT VB10 (SOMARIS/10 syngo CT VB10). It is a command-based program used for patient management, data management, X-ray scan control, image reconstruction, and image archive/evaluation.

The software platform provides plugin software interfaces that allow for the use of specific commercially available post-processing software algorithms in an unmodified form from the cleared stand-alone post-processing version.

The provided text describes the Siemens NAEOTOM Alpha CT Scanner System with software version SOMARIS/10 syngo CT VB10. While it details extensive non-clinical testing and verification/validation activities, it does not include acceptance criteria for specific AI/software performance metrics (e.g., sensitivity, specificity, accuracy) nor does it describe a comparative clinical study (MRMC or standalone AI performance) with human readers or clinical outcomes. The submission focuses on demonstrating substantial equivalence to predicate devices through engineering verification and validation of new and modified features, rather than a clinical performance study of an AI-powered diagnostic aid.

Therefore, many of the requested details regarding AI performance acceptance criteria and a study proving device performance in a clinical AI context are not present in the provided document. The document primarily describes the general engineering and regulatory testing performed for a CT system and its software updates.

However, I can extract information related to the non-clinical testing performed to support the modifications, as well as the types of ground truth used where applicable.

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

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

The document defines "acceptance criteria" generally as part of the system validation tests (workflow and user manual tests, legal and regulatory tests) and system verification tests (system integration, functionality verification, image quality evaluation). For specific new/modified features, the acceptance criteria are generally qualitative or comparative relative to the predicate device, demonstrating comparability or improvement.

2. No new artifacts introduced.
3. Equivalent image quality in quantitative standard physics phantom-based measurements (noise, homogeneity, high-contrast resolution, slice thickness, CNR) compared to non-corrected standard reconstruction.
4. Equivalent image quality in quantitative and qualitative phantom-based measurements with respect to metal objects.
5. Algorithm can be successfully applied to phantom data from motion phantom. | "If misalignment artefacts are identified in non-corrected standard ECG-gated reconstructed sequence or spiral images, the feature 'Cardiac Stack Artefact Correction' (SAC, marketing name: ZeeFree) enables optional stack artefact corrected images, which reduce the number of alignment artefacts."
   "The SAC reconstruction does not introduce new artefacts, which were previously not present in the non-corrected standard reconstruction."
   "The SAC reconstruction does realize equivalent image quality in quantitative standard physics phantom-based measurements (ACR, Gammex phantom) in terms of noise, homogeneity, high-contrast resolution, slice thickness and CNR compared to a non-corrected standard reconstruction."
   "The SAC reconstruction does realize equivalent image quality in quantitative and qualitative phantom-based measurements with respect to metal objects compared to a non-corrected standard reconstruction."
   "The SAC algorithm can be successfully applied to phantom data if derived from a suitable motion phantom demonstrating its correct technical function on the tested device." |
   | myNeedle Guide (with myNeedle Detection) | 1. Accuracy of automatic needle detection algorithm.
6. Reduction of necessary user interactions for navigating to a needle-oriented view. | "It has been shown that the algorithm was able to consistently detect needle-tips over a wide variety of scans in 90.76% of cases."
   "Further, the results of this bench test clearly shows that the auto needle detection functionality reduces the number of interactions steps needed to generate a needle-aligned view in the CT Intervention SW. Zero user interactions are required and a needle-aligned view is displayed right away after a new scan, if auto needle detection is switched on in the SW configuration." |
   | Quantum Spectral Imaging | 1. T3D reconstructions in Quantumpeak mode possible with sharpest available kernels.
7. Quantumpeak scan mode allows monoenergetic images from 40 to 190 keV.
8. Monoenergetic reconstructions free of artifacts.
9. Measured CT values precisely match reference values.
10. Accuracy of monoenergetic reconstructions in iodine and calcium inserts comparable or better than secondary predicate. | "The results showed that: with T3D reconstructions from Quantumpeak scan modes, high resolution images with sharp kernel up to Br98 are obtained. The resolution is comparable to other Highresolution scan modes of the NAEOTOM Alpha."
    "Monoenergetic reconstructions from Quantumpeak scan modes are free of artifacts. Measured CT values precisely match the reference values."
    "The accuracy of monoenergetic reconstructions in iodine and calcium inserts at the NAEOTOM Alpha is comparable or better than on the secondary predicate device SOMATOM Force." |
    | Quantum HD Cardiac | Substantial equivalence in image quality (UHR and standard resolution spectral images) compared to single source spectral capable 120x0.2mm UHR scan mode. | "Based on the results it can be concluded that substantial equivalence in image quality is achieved by the images derived from the spectral capable cardiac acquisition mode 96x0.2mm for both, the high-resolution UHR and the standard resolution spectral image cases, compared to the single source spectral capable 120x0.2mm UHR scan mode." |
    | HD FoV (High Definition Field of View) | HU accuracy in extended field of view region. | "In the phantom study, an HU value accuracy of about +/- 40 HU was achieved with skin-line accuracy of about +/- 3 mm."
    "HD FoV enables the reconstruction of images while significantly improving the visualization of anatomy in the regions outside the scan field of view of 50 cm." |

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

• Sample Size: Not specified in terms of patient counts for clinical validation, as this document focuses on non-clinical (phantom and bench) testing. For the "myNeedle Guide" feature, it states "a wide variety of scans" were used, and the success rate was "90.76% of cases" but doesn't quantify the number of cases. Phantom studies are mentioned for other features without specific numbers of scans/readings.
• Data Provenance: The testing described is non-clinical (phantom, bench, and system integration/verification testing). There is no mention of human patient data or its country of origin. The manufacturing site is Siemens Healthcare GmbH in Forchheim, Germany, implying the testing likely occurred there.
• Retrospective or Prospective: Not applicable as it's non-clinical 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)

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.
• Role of Experts: For the non-clinical tests, "ground truth" generally refers to the known physical properties of the phantoms or the expected performance based on engineering specifications. Human experts are mentioned as trained staff who would use the device, but not as part of a formal ground truth establishment process for the performance studies presented.

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

• Adjudication Method: Not applicable, as no multi-reader human-based test set or clinical study is described. The assessment of performance is based on measurements from phantoms and internal engineering verification.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• MRMC Study: No MRMC comparative effectiveness study is mentioned. The document focuses on demonstrating that new/modified features of the CT system are comparable to or improve upon the predicate device through non-clinical testing. The device is a CT system, not an AI-powered diagnostic assist that would typically be evaluated with MRMC. The "myNeedle Detection" feature is a software algorithm within the CT system to aid in procedures, but its evaluation is described as a bench test of its detection accuracy and reduction of user interaction steps, not an MRMC study.

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

• Standalone Performance: The performance data provided is for the CT system and its integrated software features, including algorithms like ZeeFree and myNeedle Detection. The "algorithm only" performance is implicitly covered in the bench testing of these features (e.g., myNeedle Detection achieving 90.76% detection accuracy). However, this is not presented as a "standalone AI" product in the sense of a distinct AI diagnostic algorithm being submitted for clearance. It's an integrated feature of the CT system.

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

• Type of Ground Truth: For the non-clinical tests described, the ground truth is primarily based on:
  • Known physical properties of phantoms: Used for evaluating image quality metrics (noise, homogeneity, resolution, CNR, HU accuracy, etc.) and quantitative measurements.
  • Engineering specifications and expected functional behavior: For features like FAST 3D Camera accuracy and Multi-Purpose Table movement.
  • Reference values: For monoenergetic reconstructions in Quantum Spectral Imaging.
  • Manual verification/observation: For testing user interaction steps in myNeedle Guide.

8. The sample size for the training set

• Training Set Sample Size: Not specified. The document does not describe the development or training of AI models. It focuses on the verification and validation of specific software features within the CT system.

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

• Training Set Ground Truth Establishment: Not specified, as no training set or AI model development is described in this document.

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NAEOTOM Alpha:
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 staff as an aid in diagnosis and treatment 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.

Scan&GO:
This in-room scan application is a planning and information system the necessary functions required for planning and controlling scans of supported SIEMENS CT scanners. It allows users to work in close proximity to the scanner.
The in-room scan application runs on standard information technology hardware and software, utilizing the standard information technology operating systems and user interface. Communication and data exchange are using special protocols.

The subject device NAEOTOM Alpha with SOMARIS/10 syngo CT VA50 is a dual source Computed Tomography (CT) x-ray system featuring two detectors based on photon counting technology.
The CT scanner system algorithm is designed to allow image reconstruction by using photon counting data generated by the subject device. The reconstruction results are comparable with the primary and secondary predicate devices, but support with improved technological characteristics as described in Section 10.
The NAEOTOM Alpha with Software SOMARIS/10 syngo CT VA50 produces CT images in DICOM format, which can be used by trained staff for post-processing applications commercially distributed by Siemens and other vendors as an aid in diagnosis and treatment as well as for diagnostic and therapeutic interventions. The computer system delivered with the CT scanner is able to run optional post processing applications.
The Scan&GO mobile workflow is an optional planning and information software designed to perform the necessary functions required for planning and controlling of the workflow of the NAEOTOM Alpha. Scan&GO can be operated on a Siemens provided various tablet hardware that meets certain minimum technical requirements. It allows users to work in close proximity to the scanner and the patient.

The Siemens NAEOTOM Alpha, Scan&GO Software (K220814) is a computed tomography x-ray system that received 510(k) clearance. The provided documentation primarily focuses on establishing substantial equivalence to predicate devices through technical comparisons and non-clinical testing, rather than presenting a detailed clinical study with specific acceptance criteria and performance metrics against ground truth.

However, based on the information provided, we can infer acceptance criteria for the non-clinical testing conducted to support the device modifications and their performance.

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

1. Table of Acceptance Criteria and the Reported Device Performance

The document describes several non-clinical tests performed to demonstrate the functionality and performance of the modified features. The acceptance criteria for these tests are generally stated implicitly as the successful demonstration of the intended function and efficacy.

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

The document specifies "phantom tests" and "bench tests" for non-clinical testing. It does not provide specific sample sizes (e.g., number of phantoms, number of test runs) for these tests, nor does it explicitly state the data provenance in terms of country of origin or whether they were retrospective or prospective, beyond stating they were conducted "during product development." Given these are non-clinical hardware/software tests, the concept of "retrospective or prospective" data provenance (as typically applied to patient data) is not directly applicable.

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

The document does not mention the use of experts to establish a ground truth for the test set. The testing described is primarily non-clinical verification and validation of hardware and software modifications against engineering specifications and industry standards.

4. Adjudication method for the test set

As the testing is non-clinical and does not involve human interpretation against a ground truth, an adjudication method like "2+1" or "3+1" is not applicable and therefore not mentioned.

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

The document does not describe an MRMC comparative effectiveness study. The NAEOTOM Alpha and Scan&GO software, as described, do not appear to be an AI-assisted diagnostic tool that would typically undergo such a study. The software is for planning, control, image reconstruction, and post-processing, not for interpretation or AI-driven diagnostic assistance.

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

Yes, standalone (algorithm only) performance was assessed through the various non-clinical hardware and software verification and validation tests listed in the table above. These tests evaluate the device's inherent functionality, image quality, and compliance with technical specifications, without direct human interaction for interpretation or decision-making during the test itself.

7. The type of ground truth used

For the non-clinical tests described, the "ground truth" implicitly refers to:

• Engineering Specifications/Requirements: The design and performance targets set for the device's hardware and software features.
• Industry Standards: Compliance with recognized standards like NEMA, IEC, and ANSI AAMI for electrical safety, EMC, and image quality.
• Physical Properties: For tests like myNeedle Laser accuracy or iMAR efficacy, the ground truth would be the known physical characteristics or expected outcomes in phantom models.

There is no mention of "expert consensus, pathology, or outcomes data" as ground truth, which are typically found in clinical validation studies.

8. The sample size for the training set

The document does not provide information on a training set. This is consistent with the nature of the submission (510(k) for a CT system software update) which focuses on demonstrating substantial equivalence and safety/effectiveness through non-clinical testing, rather than developing or validating an AI algorithm that would typically require a training set.

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

Since no information on a training set is provided, how its ground truth was established is not applicable/not mentioned.

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NAEOTOM Alpha:
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.

Scan&GO:
This in-room scan application is a planning and information system the necessary functions required for planning and controlling scans of supported SIEMENS CT scanners. It allows users to work in close proximity to the scanner.
The in-room scan application runs on standard information technology hardware and software, utilizing the standard information technology operating systems and user interface. Communication and data exchange are done using special protocols.

Siemens intends to market a new CT scanner system NAEOTOM Alpha supporting software version, SOMARIS/10 syngo CT VA40 with mobile workflow options.
Dual Source CT Scanner System:

• NAEOTOM Alpha
• Scan&GO Mobile Medical Application (optional mobile workflow component) .
  The subject device NAEOTOM Alpha with SOMARIS/10 syngo CT VA40 is a dual-source Computed Tomography (CT) x-ray system featuring two detectors based on new photon counting technology. The CT scanner system algorithm is designed to allow image reconstruction by using photon counting data generated by the subject device. The reconstruction results are comparable with the predicate devices, but support with improved technological characteristics.
  The NAEOTOM Alpha with Software SOMARIS/10 synqo CT VA40 produces CT images in DICOM format, which can be used by trained staff for post-processing applications commercially distributed by Siemens 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 Scan&GO mobile workflow is an optional planning and information software designed to perform the necessary functions required for planning and controlling of the NAEOTOM Alpha. Scan&GO can be operated on a Siemens provided various tablet hardware that meets certain minimum technical requirements.
  NOTE: Scan&GO does not support storage of images. Additionally, Scan&GO cannot trigger a scan or radiation release.
  The software version for the NAEOTOM Alpha, syngo CT VA40 (SOMARIS/10 syngo CT VA40), is a command-based program used for patient management, data manaqement, X-ray scan control, image reconstruction, and image archive/evaluation.
  The software platform provides a software plugin interface that allows for the use of specific commercially available post processing software algorithms in an unmodified form from the cleared stand-alone post processing version.
  New software version syngo CT VA40 (SOMARIS/10 syngo CT VA40) is a modified software version based on syngo CT VA30A (SOMARIS/10 syngo CT VA30) which was cleared for the secondary predicate device and supports the same plugin interfaces for the subject device Scan&GO mobile workflow and integration of post-processing tasks as the secondary predicate device Scan&GO cleared in (K200524).

The provided text describes a 510(k) premarket notification for the NAEOTOM Alpha CT scanner and Scan&GO application. It includes performance data from non-clinical testing.

Here's a breakdown of the requested information:

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

The document provides a general overview of performance testing and states that "all of the software specifications have met the acceptance criteria" and that verification and validation testing was "found acceptable to support the claim of substantial equivalence." However, it does not present a specific table with quantitative acceptance criteria and corresponding reported device performance metrics in a structured format for each feature. Instead, it describes the type of performance testing conducted for various features.

For example, for "Detector - QuantaMax," it mentions "in-depth evaluation of NAETOM Alpha Image Quality for general CT imaging, based on phantom evaluation of Typical Modes, compared to the predicate device SOMATOM Force. It also includes parameters for supporting the suitability of the subject device for low dose lung cancer screening." For "CARE keV," it states "The test procedure includes phantom measurements with clinically relevant phantom diameters and contrast materials to support the contrast, noise, and radiation dose related CARE keV information."

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

The document primarily discusses non-clinical testing which involves phantom studies. There is no mention of patient data (test set) being used for performance evaluation in the context of proving substantial equivalence, nor any information about data provenance (country of origin, retrospective/prospective). The testing described is performed on the device itself and phantoms.

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)

Since the testing described is primarily non-clinical (phantom studies) and doesn't explicitly involve human reader interpretation for a test set, there is no mention of experts establishing ground truth for a test set or their qualifications.

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

Given that no human reader-based test set evaluation is described for performance, there is no information on an adjudication method.

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

The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study. The focus is on the substantial equivalence of the NAEOTOM Alpha CT scanner and its components to existing predicate devices, primarily through non-clinical performance testing and technical comparisons, not on measuring human reader performance with or without AI assistance.

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

Yes, the testing described appears to be a form of standalone algorithm-only (device-only) performance evaluation through phantom studies. The document details testing of features like "Quantum Iterative Reconstruction," "Detector - QuantaMax," "CARE keV," and "Quantum Pure Lumen" using phantom measurements and technical analyses to assess their performance characteristics, independent of human interpretation in a clinical setting.

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

For the non-clinical phantom studies, the ground truth would be the known physical properties and configurations of the phantoms (e.g., known material compositions, shapes, sizes, and concentrations of inserts). For example, for "Always Dual Energy," it mentions "phantoms with iodine inserts," where the known concentration and distribution of iodine would serve as ground truth for assessing accuracy.

8. The sample size for the training set

The document refers to the NAEOTOM Alpha as a new CT scanner system with modified software. It mentions that "software version SOMARIS/10 syngo CT VA40 is a further development of the SOMARIS/10 syngo CT VA30 software version," implying an evolution rather than a de novo AI algorithm that requires a separate training set. While the algorithms (like Quantum Iterative Reconstruction, CARE keV) have been optimized, the document does not specify a sample size for a training set in the context of distinct machine learning model training as one might expect for a typical AI/ML device. The focus is on the device's inherent imaging capabilities and reconstruction algorithms.

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

As there is no explicit mention of a training set or a distinct AI/ML model being trained with external data, there is no information on how ground truth for a training set was established. The development appears to be based on engineering principles, physics of CT imaging, and optimization of established reconstruction techniques for the new photon-counting detector technology.

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