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The Endomag Magseed® Magnetic Marker is indicated for use to radiographically mark soft tissue during a surgical procedure or for future surgical procedures.

The Endomaq Maqseed® Magnetic Marker is intended for use as a tissue marker. The marker is visible under ultrasound and radiographic imaging. It is indicated for use to radiographically mark soft tissue during a surgical procedure or for future surgical procedures.

The Magseed Magnetic Marker is placed percutaneously into the tissue, using imaging guidance such as ultrasound or radiography, to mark a site that is for example intended for surgical removal. The Magseed Magnetic Marker is subsequently localized by using imaging quidance (such as ultrasound or radiography) or aided by non-imaging quidance (Endomag Sentimag® System, K153044 and K163541). The marker can be detected up to 3cm from the Sentimag® probe. The surgeon may use compression of the tissue with the probe to improve detection. The marker is located and surgically removed with the target tissue.

Based on the provided text, the device in question is the Endomag Magseed® Magnetic Marker, which is a tissue marker. The document is a 510(k) summary for its premarket notification.

It's important to note that this document does not describe a study proving the device meets specific acceptance criteria related to an AI/algorithm's performance. Instead, it details the non-clinical testing done to demonstrate the substantial equivalence of the Magseed Magnetic Marker to predicate devices for its intended use as a radiographic tissue marker.

Therefore, many of the requested categories related to AI/algorithm performance (e.g., sample size for test/training sets, expert ground truth, MRMC study, standalone performance, effect size) are not applicable to this specific device submission as described in the provided text.

The information primarily focuses on the device's physical properties, biocompatibility, and performance in simulated use, not an AI or algorithmic diagnostic performance.

Here's a breakdown of the information that can be extracted or inferred from the document:

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

The document doesn't present a formal table of acceptance criteria for a diagnostic performance study as would be seen for an AI/algorithm. Instead, it states that "Testing was conducted to evaluate and characterize the safety and performance of the Magseed Magnetic Marker." The acceptance here is based on demonstrating substantial equivalence to predicate devices.

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

• Sample Size: Not specified in terms of a "test set" for a diagnostic performance study. The document refers to "Pre-clinical testing included: Biological Evaluation, Simulated Use." The specific number of samples or instances tested for these evaluations is not mentioned.
• Data Provenance: Not specified (e.g., country, retrospective/prospective). This type of detail is typically for clinical performance studies, which are not the focus of this 510(k) for a tissue marker.

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

• Not Applicable. This information pertains to studies establishing ground truth for diagnostic AI/algorithms. This device is a passive tissue marker, not an AI/algorithm.

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

• Not Applicable. This refers to methods for resolving discrepancies in expert labeling for AI ground truth.

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 device is not an AI for diagnostic interpretation, nor does it assist human readers in that capacity.

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

• Not Applicable. This is not an algorithm or AI device.

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

• For the non-clinical tests, the "ground truth" would be established by engineering tests, material standards, and biological compatibility standards. For example, in biological evaluation, the "ground truth" is compliance with ISO standards for biocompatibility. For "simulated use," the "ground truth" is successful physical performance under conditions mimicking clinical use. There is no "ground truth" in the sense of a medical diagnosis.

8. The sample size for the training set:

• Not Applicable. This device does not involve machine learning or a "training set."

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

• Not Applicable. As above, no training set.

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