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The Carotid Coil is a receive-only coil, used for obtaining diagnostic images of carotid in magnetic resonance imaging systems. These images when interpreted by a trained physician, yielding information that may assist in diagnosis.

The Carotid Coil is an 8-channel phased array, receive-only coil, used for obtaining diagnostic images of carotid in magnetic resonance imaging systems. These images, when interpreted by a trained physician, yields information that may assist in diagnosis.

The provided text is a 510(k) summary for a medical device called the "Carotid Coil". It primarily focuses on demonstrating substantial equivalence to a predicate device and does not contain detailed information about specific acceptance criteria, performance studies with quantitative results, or information typically found in a clinical study report for AI/machine learning devices. The document is from 2009, prior to the widespread use of AI/ML in medical devices regulated under these detailed performance criteria.

Therefore, many of the requested items cannot be extracted from this document.

Here's a breakdown of what can and cannot be provided based on the input:

1. Table of Acceptance Criteria and Reported Device Performance

Explanation: The document states that the device was proven safe and effective through various tests, but it does not specify concrete, quantifiable acceptance criteria or provide the numerical results of these performance tests. This type of detail is more common in more recent submissions for computational devices or devices with specific performance claims.

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

• Sample Size for Test Set: Not specified.
• Data Provenance (e.g., country of origin, retrospective/prospective): Not specified. The document mentions "practical application tests," which suggests some form of evaluation in a real-world or simulated clinical setting, but details about the size and nature of the dataset are absent.

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

• Not applicable/Not specified. The document mentions "diagnostic images...when interpreted by a trained physician," implying human interpretation, but there's no mention of expert ground truth establishment for a test set to evaluate the coil's diagnostic performance in a comparative manner.

4. Adjudication method for the test set

• Not applicable/Not specified.

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

• Not applicable. This device is a passive MR coil, not an AI or software device that assists human readers. No MRMC study or AI assistance is mentioned.

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

• Not applicable. This is a hardware device (an MR coil), not an algorithm.

7. The type of ground truth used

• Not applicable/Not specified. The document describes the coil's function ("obtaining diagnostic images") and that these images are "interpreted by a trained physician." There is no mention of a ground truth in the context of evaluating a software algorithm or diagnostic aid. The validation likely focused on image quality parameters and safety, not diagnostic accuracy against a specific ground truth.

8. The sample size for the training set

• Not applicable. This is a hardware device and does not involve a training set as understood for AI/ML models.

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

• Not applicable.

Summary of Device and Approval:

The document describes the "Carotid Coil," an 8-channel phased array, receive-only coil for Magnetic Resonance Imaging (MRI) systems. Its intended use is for obtaining diagnostic carotid images (2D, 3D imaging, proton density, T1 and T2 weighted imaging, 2D, 3D time of flight, phase contrast imaging). The device was determined to be substantially equivalent to the Machnet Carotids Coil Array Assembly (K012491), a legally marketed predicate device. The approval (K092962) was based on safety tests, performance tests, bio-compatibility tests, practical application tests, and JEC60601-1 compliance tests, which collectively demonstrated its safety and effectiveness.

This submission predates the need for extensive clinical performance data for AI/ML devices, and therefore, the information requested for such specific studies is not present.

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