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G-scan Brio is a Magnetic Resonance (MR) system that produces transversal, sagittal and coronal and oblique cross-section images of the head, limbs, joints and spinal column. It is intended for imaging the head, imaging portions of the upper limb, including the hand, wrist, forearm, elbow, arm and shoulder, imaging portions of the lower limb, including the foot, ankle, calf, knee, thigh and hip, imaging the temporomandibular joint and imaging the cervical, the lumbosacral sections as portions of the spinal column.

G-scan Brio images correspond to the spatial distribution of protons (hydrogen nuclei) that determine magnetic resonance properties and are dependent on the MR parameters, including spin-lattice relaxation time (T1), spin-spin relaxation time (T2), nuclei density, flow velocity and "chemical shift". When interpreted by a medical expert trained in use of MR equipment, the images can provide diagnostically useful information.

S-scan is a Magnetic Resonance (MR) system that produces transversal, sagittal and coronal and oblique cross-section images of the head, limbs, joints and spinal column. It is intended for imaging portions of the upper limb, including the hand, wrist, forearm, elbow, arm and shoulder, imaging portions of the foot, ankle, calf, knee, thigh and hip, imaging the temporomandibular joint and imaging the cervical, the thoracic and the lumbosacral sections as portions of the spinal column.

S-scan Brio images correspond to the spatial distribution of protons (hydrogen nuclei) that determine magnetic resonance properties and are dependent on the MR parameters, including spin-lattice relaxation time (T1), spin-spin relaxation time (T2), nuclei density, flow velocity and "chemical shift". When interpreted by a medical expert trained in use of MR equipment, the images can provide diagnostically useful information.

The change performed on the modified G-scan Brio, with respect to the cleared version - G-scan Brio K142421 - are due to the improvement of the system performance. This modification is for the introduction of the new Shoulder Coil 20 code 130000014 (already cleared with S-scan K161238), the Head Coil 16 code 13000100, and the head indication for use.

The change performed on the modified S-scan, with respect to the cleared version – S-scan K161238 – are due to the improvement of the system performance. This modification is the introduction of the new Head Coil 16 code 13000100 and the head indication for use.

The provided text describes a 510(k) premarket notification for the G-scan Brio and S-scan Magnetic Resonance (MR) systems. It confirms FDA clearance for these devices due to their substantial equivalence to legally marketed predicate devices.

However, the document does not contain information regarding acceptance criteria, reported device performance metrics (e.g., sensitivity, specificity), sample sizes for test sets, data provenance, number or qualifications of experts, adjudication methods, details of multi-reader multi-case studies or standalone algorithm performance, or the specific type of ground truth used outside of general "diagnostically useful information."

The document primarily focuses on:

• Regulatory Clearance: Affirming that the devices are substantially equivalent to predicates.
• Device Description and Intended Use: Outlining what the MR systems image (head, limbs, joints, spinal column) and how they function.
• Technological Characteristics: Describing the changes made (new coils for shoulder and head imaging) and stating they do not alter the core technology.
• Non-Clinical Tests: Listing adherence to various safety and performance standards (e.g., IEC, ISO, NEMA).
• Clinical Tests (briefly mentioned): Stating that "sample clinical images and attestation from a U.S. Board-Certified Diagnostic Radiologist that the images are of good diagnostic quality were provided."

Therefore, it is not possible to provide the requested information in the format of acceptance criteria and proven device performance based on the provided document. The document states that the devices are "as safe, as effective, and performs as well as or better than the predicate" based on non-clinical testing and general attestations about image quality, but it does not quantify these claims or provide the specific details of a performance study as outlined in your request.

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The MAGNETOM C! is indicated for use as magnetic resonance diagnostic devices (MRDD) that produce transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that display the internal structure and/or function of the head, body, or extremities. These images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

The MAGNETOM C! may also be used for imaging during interventional procedures when performed with MR compatible devices such as, in room display and MR safe biopsy needles

The MAGNETOM C! system is an open, whole body scanner designed to support improved higher resolution imaging and shorter scan times, which is was described in premarket notification K041111 which received FDA clearance on July 16, 2004. Siemens further market the Body spine XL coil, Wrist Array coil with 4 channels, Cordless Coil, Breast Array coil, Breast biopsy device, MR guided procedure Package, In Room MRC, Foot switch and the software update for the existing MAGNETOM C! MR system.

The provided text describes the acceptance criteria for the MAGNETOM C! MR System and the study used to demonstrate its substantial equivalence to predicate devices, rather than a study proving the device meets acceptance criteria in the context of an AI/algorithm-driven device.

Here's a breakdown of the requested information based on the provided text, and where the information requested for AI-related studies is not applicable or not present in the document:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample size for test set: Not applicable/not specified. The provided text describes a submission for substantial equivalence based on established performance parameters for an MRI system, not an algorithm's performance on a specific test set of cases.
• Data provenance: Not applicable/not specified. This is a submission for an entire MRI device, not an AI algorithm.

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

• Not applicable. Ground truth for an AI algorithm's performance is not relevant to this type of device submission. The device produces images "when interpreted by a trained physician yield information that may assist in diagnosis."

4. Adjudication method for the test set

• Not applicable.

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

• Not applicable. This is not an AI-assisted device.

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

• Not applicable. This is a medical imaging device, not a standalone algorithm.

7. The type of ground truth used

• Not applicable in the context of an AI algorithm's performance validation. For the MRI system itself, the ground truth relates to its physical performance parameters (Signal to Noise, Image Uniformity) as measured against NEMA and IEC standards, which represent established engineering and safety benchmarks for device functionality.

8. The sample size for the training set

• Not applicable. There is no AI algorithm being described as part of this submission.

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

• Not applicable.

Summary of the Study that Proves the Device Meets Acceptance Criteria (as described in the document):

The study described is an assessment of substantial equivalence for the MAGNETOM C! MR system, which is an upgrade to an existing system, including new coils and software updates. It's not a study validating an AI algorithm's performance.

The "acceptance criteria" for this device are its performance levels (Signal to Noise, Image Uniformity) and safety compliance. The study demonstrates that the device will conform to established industry and international standards.

• Criteria:

  • Signal to Noise
  • Image Uniformity
  • Compliance with safety requirements

• Methodology: The submission asserts that the MAGNETOM C! will conform to:

  • FDA recognized NEMA Standards for the measurement of performance and safety parameters (specifically for Signal to Noise and Image Uniformity).
  • International IEC standard for safety issues with Magnetic Resonance Imaging Devices.

• Conclusion: By demonstrating conformity to these recognized standards, Siemens believes the device can be considered safe and effective and is substantially equivalent to the predicate devices (Siemens MAGNETOM 0.2 T Concerto, Siemens MAGNETOM 1.0 T Harmony, and Siemens MAGNETOM 0.35 T C!). This approach assures that the performance of the device meets the necessary safety and effectiveness requirements.

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The MAGNETOM Systems with the syngo MR 2002B are indicated for use as magnetic resonance diagnostic devices (MRDD's) that produce transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that display the internal structure and/or function of the head, body, or extremities. These images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.

The syngo MR 2002B (Numaris 4 VA21A) software upgrade will be available for the following MAGNETOM Family systems:

• The MAGNETOM 1.0 Tesla Harmony system
• The MAGNETOM 1.5 Tesla Symphony system
• The MAGNETOM 1.5 Tesla Sonata system
• The MAGNETOM 0.2 Tesla Concerto system
• The MAGNETOM 3.0 Tesla Allegra system
• The MAGNETOM 3.0 Tesla Trio system
  This includes Siemens upgrades of currently used MAGNETOM Impact/Expert, Vision, and Open (Viva) systems to systems described above. Siemens Medical Solutions is adding an upgrade in software and hardware to the currently available MAGNETOM Systems. The MRI systems are exactly the same as what was described and cleared in the predicate premarket notifications.

The provided text is a 510(k) Summary for the Siemens syngo MR 2002B software upgrade for MAGNETOM MRI systems. It focuses on demonstrating substantial equivalence to previously cleared devices rather than presenting a study proving a new device meets specific performance acceptance criteria.

Therefore, much of the requested information regarding acceptance criteria, specific device performance, sample sizes, ground truth establishment, expert involvement, and MRMC studies is not present in this document. The document describes a software upgrade and asserts that the safety and performance parameters are not significantly changed from the predicate devices.

However, I can extract and infer some contextual information based on the document's content:

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

The document does not specify quantitative acceptance criteria for new performance metrics or report specific performance values for the syngo MR 2002B. Instead, it states that the performance parameters of the device are not significantly changed compared to its predicate devices, implying that they meet the same implicit standards. The listed performance parameters examined are:

For safety parameters (Maximum Static Field, Rate of Change of Magnetic Field, RF Power Deposition, Acoustic Noise Level), the document states they "remain below the level of concern."

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

The document does not explicitly mention a specific "test set" or its sample size. It states that "Laboratory testing were performed to support this claim of substantial equivalence," but provides no details on the data used for these tests. Data provenance (country of origin, retrospective/prospective) is also not specified.

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

The document does not describe the use of experts to establish ground truth for any specific test set. The nature of this submission (software upgrade for a diagnostic imaging device) suggests that the "ground truth" for evaluating image quality and safety would be established through technical specifications and physical measurements, and interpreted by qualified engineers and radiologists, but no details are provided.

4. Adjudication method for the test set

Not applicable, as no specific test set or adjudication process is described for establishing ground truth from experts.

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

No MRMC study is mentioned. This document pertains to an MRI system software upgrade, not an AI-assisted diagnostic tool.

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

This document describes a diagnostic imaging device and its software upgrade, not an algorithm meant for standalone diagnostic performance. The device is intended to produce images and/or spectra "when interpreted by a trained physician yield information that may assist in diagnosis." Therefore, a standalone algorithm performance evaluation would not be applicable in this context.

7. The type of ground truth used

The ground truth implicitly used for validating the performance and safety of the MRI system would be based on physical phantom measurements and technical specifications compared against established engineering standards and regulatory limits for MRI devices. This is inferred from the listed "Performance" and "Safety" parameters that were evaluated, which are standard metrics for MRI scanner performance.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device that would require a "training set" in the conventional sense. The "training" for the device's development would involve engineering and software development processes, not data-driven machine learning.

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

Not applicable, as there is no mention of a training set for an AI/ML model.

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