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The MOLLI Marker is intended to be placed percutaneously in soft tissue to temporarily mark a surgical site intended for surgical removal. The MOLLI Marker can only be implanted for less than 30 days. Using imaging guidance (such as ultrasound or radiography) or aided by non-imaging guidance (MOLLI System), the MOLLI Marker is located and surgically removed with the target tissue.

The MOLLI System is intended only for the non-imaging detection and localization of the MOLLI Marker that has been implanted in a site intended for surgical removal.

MOLLI is a precision surgical marking and guidance system for locating non-palpable lesions during surgery. MOLLI consists of a temporary marker (MOLLI Marker), a marker delivery system (MOLLI Introducer), a detection wand (MOLLI Wand), and a visualization tablet (MOLLI Tablet). The MOLLI Marker is preloaded in the MOLLI Introducer. The MOLLI Wand and the MOLLI Tablet constitute the MOLLI System. The MOLLI System is intended for the non-imaging detection and localization of the MOLLI Marker that has been implanted in a site intended for surgical removal.

This document is a 510(k) premarket notification from the FDA, and as such, it primarily focuses on demonstrating substantial equivalence to predicate devices based on non-clinical testing. It does not contain information about a clinical study involving human subjects to prove the device meets specific acceptance criteria based on performance metrics like accuracy, sensitivity, or specificity.

Therefore, I cannot provide the information requested in your prompt regarding acceptance criteria and a study proving device performance in a clinical context (e.g., sample size, expert ground truth, MRMC study, effect size of human reader improvement with AI, standalone performance, training set details).

Here's a breakdown of what can be extracted from the provided text, and what cannot:

Information NOT available in the document (and why):

• Acceptance Criteria Table with Reported Performance: This document describes non-clinical bench testing and safety standards, not clinical performance metrics with pre-defined acceptance criteria.
• Sample size used for the test set and data provenance: No clinical test set involving device performance on human subjects is described. The "test set" mentioned in this context refers to non-clinical bench testing.
• Number of experts used to establish the ground truth for the test set and qualifications of those experts: There is no clinical data from human subjects requiring expert ground truth for performance evaluation.
• Adjudication method for the test set: Not applicable as there's no clinical test set requiring adjudication.
• 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: This is a non-AI device (an implantable marker and detection system), and no clinical MRMC study is mentioned.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable for this device type.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable for clinical performance as no clinical study is described. Ground truth for non-clinical tests would be established by physical measurements and engineering specifications.
• The sample size for the training set: Not applicable as this is not an AI/machine learning device.
• How the ground truth for the training set was established: Not applicable.

What the document does describe (relevant to your prompt but not directly answering all parts):

The document focuses on non-clinical testing to demonstrate the device's safety and effectiveness compared to predicate devices. This includes:

• Summary of Non-Clinical Testing:
  • Biocompatibility testing per ISO 10993-1
  • Packaging validation testing per ISO 11607-1 and ASTM D4169-19
  • EO sterilization validation per ISO 14937 and ISO 10993-7
  • Software testing per IEC 62304
  • Electrical safety testing per IEC 60601-1
  • EMC testing per IEC 60601-1-2:2014
  • MRI compatibility testing per ASTM standards F2052-15, F2119-07, F2182-11, and F2213-17.
  • Non-clinical performance bench testing including V&V testing, MOLLI Marker displacement testing, tissue performance testing, and needle penetration testing (per ISO 7864)
  • Human factor validation testing

The document concludes that "Based on the testing performed... it can be concluded that the subject device does not raise new issues of safety or effectiveness compared to the predicate device." This is the core of a 510(k) submission: demonstrating substantial equivalence, often without the need for large-scale clinical trials if non-clinical data is sufficient to address safety and effectiveness concerns.

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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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