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The MAGNETOM Sempra is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra, when interpreted by a trained physician, yield information that may assist in diagnosis.

The MAGNETOM Sempra 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 subject device, MAGNETOM Sempra (1.5T) with syngo MR E11S, is an MRI system that is substantially equivalent to the previously cleared predicate device MAGNETOM Amira with software version syngo MR E11N; K152283).

MAGNETOM Sempra is equipped with Tim4G + Dot technology and Siemens latest software platform syngo MR E11 which includes latest applications like Quiet Suite for quiet brain, spine and musculoskeletal exams, CAIPIRINHA for shorter breathhold times and Advanced WARP which enables correction of in- through-plane distortions for better evaluation of soft tissue around metallic implants.

From the operational side, Brain, Spine and Large Joint Dot engines included in standard configuration of MAGNETOM Sempra deliver consistency in imaging of core body regions. The same software platform E11 would help users to shorten learning curve, plus the consistent result from Dot engines, MAGNETOM Sempra helps the user to get uniform quality. The Eco-Power technology is included and works by automatically switching off the cold head compressor during system standby or power off at night, and intelligently switching on/off of components between patients together with Zero Helium Boil-off technology to help customers to save operating cost.

MAGNETOM Sempra utilizes the similar design of hardware as the predicate device MAGNETOM Amira with syngo E11N (K152283), the main hardware changes are the modified Gradient Amplifier and introducing a new fixed patient table without vertical movement.

The provided document is a 510(k) premarket notification for a Medical Resonance Diagnostic Device (MRDD), the MAGNETOM Sempra with syngo MR E11S. This submission focuses on establishing substantial equivalence to a predicate device, MAGNETOM Amira (K152283), rather than presenting a detailed study proving the device meets specific acceptance criteria with performance metrics.

The document does not provide acceptance criteria in terms of specific performance metrics (e.g., sensitivity, specificity, accuracy). Instead, it demonstrates compliance with recognized medical device standards and a clinical study related to nerve stimulation. The claims for substantial equivalence are based on similar intended use and functionality, along with verification and validation of software and hardware.

Here's an analysis based on the information provided, highlighting what is present and what is absent regarding your requested points:

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

No explicit table of acceptance criteria with corresponding performance metrics (e.g., SNR, image uniformity values, specific diagnostic accuracy) is provided in this document relevant to clinical image quality or diagnostic performance. Instead, the document focuses on compliance with standards and safety aspects.

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

• Test Set Sample Size: For the clinical study related to nerve stimulation, a sample size of 34 individuals was used.
• Data Provenance: The document does not specify the country of origin for the 34 individuals in the nerve stimulation study, nor does it explicitly state if this study was retrospective or prospective, though such safety studies are typically prospective.
• For the non-clinical tests (SNR, image uniformity, heating), no "test set" in the sense of patient data is mentioned; these are likely tests performed on hardware components.

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

• Not Applicable / Not Provided: The nerve stimulation study is a physiological measurement, not one requiring expert interpretation to establish a diagnostic ground truth. The document does not describe any test set that would require expert-established ground truth for performance evaluation (e.g., radiologists evaluating image quality for diagnostic purposes against a gold standard). The device is an MRI system, not an AI algorithm making diagnostic predictions.

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

• Not Applicable / Not Provided: This question is typically relevant for studies involving human readers or expert consensus for labeling data. The nerve stimulation study does not involve this type of adjudication.

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 document describes a traditional MRI device. There is no mention of AI assistance or an MRMC study comparing human readers with and without AI.

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

• Not Applicable: This is an MRI system, not an algorithm being deployed in a standalone capacity for diagnosis. Its output (images and spectra) is intended for interpretation by a trained physician.

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

• For the nerve stimulation study: The "ground truth" was the observed Peripheral Nerve Stimulation (PNS) THRESHOLD LEVEL in the 34 individuals, measured according to IEC 60601-2-33 standards. This is a direct physiological measurement, not a diagnostic ground truth established by experts or pathology.
• For hardware tests (SNR, image uniformity, heating): The "ground truth" would be the physical measurements obtained from the system.

8. The sample size for the training set

• Not Applicable: This is a premarket notification for an MRI system, not an AI algorithm that requires a "training set" in the machine learning sense. The software component, syngo MR E11S, is verified and validated, but this process doesn't involve a 'training set' as it would for a deep learning model.

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

• Not Applicable: As there is no "training set" in the context of an AI algorithm, this question does not apply.

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