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The 13C/IH occipital headcoil for MAGNETOM Allegra is a transmit/receive surface coil type headcoil double resonant on carbon (13C) and proton (1H) frequencies.

Used in the Allegra system it is indicated for use as a diagnostic imaging device 1H Osed in the Anegra system it is in internal structures of the head. In addition, 13C spectra can be obtained within the same session without changing the coil.

The images produced reflect the spatial distribution of protons exhibiting magnetic resonance. The mages produced for ophich the nucleus under investigation is contained to be Specula "anow" the "moreoarer that determine the image and spectra appearance are spin density, spin-latice relaxation time (TI), spin-spin echo time (T2) and resonance frequency of the corresponding nucleus.

When interpreted by a trained physician, these images and spectra provide information that can be useful in determining diagnosis.

The 13C/1H occipital headcoil for MAGNETOM Allegra is a transmit/receive surface coil type 1H-The 13C/IT occipian headcoil double resonant on carbon (13C) and proton (1H) frequencies. It is quadrature) . C mical neader dodore rsoctanscopy potentially including proton decoupling.

The coil consists of the resonator and an electronic box which serves for switching transmit/receive, I he consists of the resoliation and an envolvening in the receive pathway. The latter being essential for proton decoupling.

The provided text describes a 510(k) summary for a medical device: a 13C/1H occipital headcoil for the MAGNETOM Allegra system. This document focuses on establishing substantial equivalence to previously cleared devices rather than presenting a study with specific acceptance criteria and performance metrics for a new, standalone diagnostic algorithm.

Therefore, much of the requested information regarding acceptance criteria, performance metrics, sample sizes, ground truth establishment, expert involvement, and comparative effectiveness studies is not available in the provided text. The document is primarily concerned with regulatory clearance based on substantial equivalence, and not the performance evaluation of a novel algorithm for diagnostic interpretation.

Here's what can be extracted based on the provided text, and what remains unknown:

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

• Acceptance Criteria: Not explicitly stated in terms of diagnostic performance (e.g., sensitivity, specificity). The acceptance criterion implicitly met is "substantial equivalence" to predicate devices for its intended use as a diagnostic imaging device for 1H and for obtaining 13C spectra, with the understanding that the images and spectra provide information "useful in determining diagnosis" when interpreted by a trained physician.
• Reported Device Performance: No specific quantitative performance metrics (e.g., accuracy, sensitivity, specificity, AUC) are reported for the device itself because it is a hardware component (a coil) used in an existing MRI system, not a diagnostic algorithm.

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

• Not applicable / Not provided. The submission is for a new hardware component (headcoil) being cleared through substantial equivalence, not a machine learning algorithm requiring a test set for performance evaluation.

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)

• Not applicable / Not provided. No test set or ground truth establishment by experts for a diagnostic algorithm's performance is described. The document states that images and spectra, when interpreted by a trained physician, provide useful diagnostic information.

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

• Not applicable / Not provided. No test set requiring expert adjudication is described.

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 done. This is a hardware submission, not a study evaluating an AI algorithm for improving human reader performance.

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

• No, not applicable. This device is a hardware component for an MRI system; it is not a standalone diagnostic algorithm.

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

• Not applicable / Not Provided. For the use of the device in diagnosis, the "ground truth" would ultimately be established clinically by "trained physicians" interpreting the images and spectra, but this is not part of a performance study for the coil itself.

8. The sample size for the training set

• Not applicable / Not provided. No training set is mentioned as this is a hardware device based on principles of physics, not a machine learning algorithm.

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

• Not applicable / Not provided. No training set or ground truth for it is mentioned.

Summary of available information:

The document is a 510(k) summary for a medical device, a specific type of headcoil for an MRI system. The submission aims to establish substantial equivalence to existing, legally marketed predicate devices, rather than demonstrating the diagnostic performance of a novel algorithm against specific acceptance criteria. The equivalence argument is based on the device's technological characteristics, intended use, and the fact that it performs similar functions (imaging with 1H, spectroscopy with 13C) to predicate devices that perform imaging with 1H and spectroscopy with 31P. The document explicitly states that the images and spectra produced by the device, when interpreted by a trained physician, can be useful for diagnosis. There are no details provided about performance studies, sample sizes, expert ground truth, or adjudication methods because the regulatory pathway chosen (510(k) substantial equivalence for a hardware component) does not typically require this level of detail for diagnostic performance beyond demonstrating safety and functional equivalence to predicates.

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