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This computed tomography system is intended to generate and process cross-sectional images by computed reconstruction of x-ray transmission data within a 26 cm field-of-view, for the head and neck.

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

The SOMATOM On.site with software version syngo CT VB10 is a mobile computed tomography (CT) scanner system that will be offered in two variants:

• . SOMATOM On.site for Intensive Care Unit (ICU) Mobile CT scanner affixed to a motorized trolley for use in hospital situations. The scanner can be moved from patient bed to patient bed to perform scanning at the point of care. Although it might be used in other environments like emergency rooms or angiography labs, the main location where this scanner will be used, will be the intensive care unit (ICU).
• . SOMATOM On.site for Mobile Stroke Unit (MSU) Mobile CT Scanner that is mounted to the floor of a diagnostic room or vehicle. The system main place where the scanner will be mounted is in a mobile stroke unit (MSU), which is a specific type of ambulance.

The subject device SOMATOM On.site with SOMARIS/10 syngo CT VB10 is a mobile Computed Tomography X-ray Systems which features a continuously rotating tube-detector system and function according to the fan beam principle. The SOMATOM On.site with software 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 Healthcare and other vendors as an aid in diagnosis and treatment preparation. The computer system integrated with the CT scanner is able to run optional post processing applications.

The Siemens SOMATOM On.site (SOMARIS/10 syngo CT VB10) is a computed tomography (CT) X-ray system. The provided text describes the non-clinical testing performed to demonstrate the device's performance and substantial equivalence to predicate devices. The study focuses on evaluating specific upgraded software features (FAST kV, CARE Dose4D, X-CARE, ADMIRE).

Here's an analysis of the acceptance criteria and study details:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for the Test Set and Data Provenance

The document describes phantom-based measurements for the non-clinical testing. Specific numerical sample sizes (e.g., number of scans, number of phantoms) are not explicitly provided beyond mentioning "a cylindrical 20 cm water phantom" and "PTFE object" for ADMIRE. The data provenance is not explicitly stated as retrospective or prospective, but given it's "bench testing" performed "during product development," it implies a prospective non-clinical study design. The "country of origin of the data" is not specified but is likely internal to Siemens Healthineers.

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

For non-clinical phantom studies, the concept of "experts establishing ground truth" as it would apply to clinical image interpretation is not directly applicable. The "ground truth" for these tests is established by:

• Physical properties of the phantoms: The known composition and dimensions of the water and PTFE phantoms.
• Established quantitative image quality metrics: Such as CNR, MTF, and noise measurements, which are objectively calculated by the system or analysis software based on internationally recognized standards.
• Comparison to predicate device performance: For CARE Dose4D and X-CARE, performance is compared to the established and cleared predicate device, SOMATOM go.Up.

Therefore, no external clinical experts are mentioned for establishing ground truth in these specific non-clinical tests.

4. Adjudication Method for the Test Set

Not applicable for non-clinical phantom studies based on objective quantitative measurements. The assessment is based on direct measurement results against pre-defined acceptance criteria.

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

No. The provided text describes non-clinical bench testing using phantoms, not clinical studies involving human readers or cases. Therefore, no MRMC study was performed, and no effect size for human reader improvement with/without AI assistance is reported.

6. Standalone Performance Study

Yes, the studies reported are standalone (algorithm only) performance evaluations of specific software features (FAST kV, CARE Dose4D, X-CARE, ADMIRE) on the SOMATOM On.site CT scanner, using phantoms. This is a non-human-in-the-loop assessment of the technical performance of the algorithms and hardware.

7. Type of Ground Truth Used

The ground truth used is primarily based on:

• Known physical properties of phantoms: e.g., known dimensions, material composition (water, PTFE), and contrast agent concentrations.
• Objective quantitative measurements: Metrics like Contrast-to-Noise Ratio (CNR), Modulation Transfer Function (MTF) for sharpness, and noise levels.
• Performance of a predicate device: For CARE Dose4D and X-CARE, the performance of the predicate device (SOMATOM go.Up) serves as a benchmark for "comparable performance."

8. Sample Size for the Training Set

The document does not specify a separate "training set" or its size. The features being evaluated (FAST kV, CARE Dose4D, X-CARE, ADMIRE) are algorithmic components of the CT system. While these algorithms might have been developed using various data, the document focuses on the validation testing of their performance on the new device, not their initial development or training. It states that ADMIRE was "originally approved with K133646," indicating it's an existing algorithm that has been integrated.

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

As no training set is explicitly mentioned or detailed in this document, the method for establishing its ground truth is also not provided. The focus is on the verification and validation of the integrated system.

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This computed tomography system is intended to generate and process cross-sectional images by computer reconstruction of x-ray transmission data within a 25 cm field-of-view, primarily for the head and neck.

The images delivered by SOMATOM On.scene can be used by a trained physician as an aid in diagnosis.

The Siemens SOMATOM On scanners are comprised of a Computed Tomography (CT) Scanner System (SOMATOM On.scene) which can be mounted on an optional motorized base (SOMATOM On.site). The CT scanner features one continuously rotating tube-detector system that 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 On scanners produce 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 preparation. The computer system included in the CT Scanner is able to run optional post processing applications.

The software version for the SOMATOM On scanner system is Somaris/10 syngo CT VA35A, is a command-based program used for patient management, X-ray scan control, image reconstruction, and image archive/evaluation. The software platform SOMARIS/10 syngo CT VA35A is designed to provide a plugin interface to integrate potential advanced post processing tasks, tools, or extendable functionalities.

As with the primary predicate device, the SOMATOM On. Scanners will be available in a 32 row, 32 slice configuration.

This FDA 510(k) submission for the SOMATOM On.site and On.scene CT systems does not contain specific acceptance criteria or a study directly aimed at proving algorithm performance against a pre-defined set of metrics. Instead, the submission focuses on demonstrating substantial equivalence to predicate devices primarily through non-clinical testing, phantom studies, and adherence to various industry standards and guidance documents.

Here's an analysis based on the provided text, addressing your points where information is available:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria for specific quantitative performance metrics of an AI algorithm, nor does it report the device performance against such criteria. The "Performance Data" section discusses:

• Non-Clinical Testing (Integration and Functional): Included phantom tests and volunteer human scans.
• Electrical Safety and EMC Testing: Conformance to IEC 60601-1, 60601-2-44, and 60601-1-2 standards.
• Radiation Safety Testing: "Under published limits," with the protection curtain reducing radiation significantly.
• Usability Testing: Formative and Summative evaluations, identifying "No new use errors, hazards or hazardous situations."
• Imaging Studies: Phantom scans (adult heads, pediatric bodies, pediatric heads) and volunteer scans (brain with/without contrast, ankle, hand). All imaging results were "as expected and were determined by a board-certified radiologist to be of high diagnostic quality." This last point is the closest to a performance statement, but it's qualitative and without specific acceptance thresholds.

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

• Test Set Sample Size: Not explicitly stated. The document mentions "phantom tests and volunteer human scans" for non-clinical testing and "phantom scans... Additionally, volunteer scans" for imaging studies. There is no quantification of the number of volunteers or specific phantom cases used for performance evaluation that could be considered a "test set" for an AI algorithm.
• Data Provenance: Not explicitly stated. The document doesn't specify the country of origin for the volunteer scans or if the data was retrospective or prospective. Given that this is a Siemens product with manufacturing in Germany and sales in the US, the volunteer data could be from either region.

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

• Number of Experts: For the imaging studies, it states: "All imaging results were as expected and were determined by a board-certified radiologist to be of high diagnostic quality." This implies at least one board-certified radiologist provided an opinion.
• Qualifications: "board-certified radiologist." No specific experience level (e.g., "10 years of experience") is mentioned.

4. Adjudication Method for the Test Set

The document does not describe any formal adjudication method (e.g., 2+1, 3+1) for establishing ground truth from multiple experts. The statement "determined by a board-certified radiologist" suggests a single expert assessment for the imaging quality.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study focusing on how human readers improve with AI vs. without AI assistance was not mentioned or performed. The submission is for the CT system itself, not an AI-powered diagnostic aid that assists human readers.

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

The document describes the CT system as providing images that "can be used by a trained physician as an aid in diagnosis." It also states "The computer system included in the CT Scanner is able to run optional post processing applications." While the software platform (SOMARIS/10 syngo CT VA35A) is designed to "provide a plugin interface to integrate potential advanced post processing tasks, tools, or extendable functionalities," the submission does not describe the performance of any specific standalone AI algorithm (i.e., operating without human-in-the-loop for diagnosis). The focus is on the CT system's ability to produce diagnostically acceptable images.

7. The Type of Ground Truth Used

For the imaging studies described, the ground truth was based on expert consensus/opinion (specifically, a "board-certified radiologist" determining "high diagnostic quality"). There is no mention of pathology or outcomes data being used as ground truth for the device's image quality evaluation.

8. The Sample Size for the Training Set

The document does not provide any information regarding a training set sample size. This is consistent with the submission not detailing the performance of a specific AI algorithm for diagnostic aid, but rather the CT system's foundational image generation capabilities. The software updates mentioned are primarily for mobile workflow adaptation and hardware/reconstruction support, not a defined AI model.

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

Since no training set is discussed, there is no information on how ground truth was established for it.

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