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The Atalia Titanium Surgical Mesh is indicated for use in the thoraco-lumbar spine (T1-LS), in cases where one vertebral body has been structurally compromised either by tumor or trauma. The objective is the restoration of anterior column support through introduction of a corpectomy construct in tandem with bone graft to ultimately realize spinal fusion. The Atalia Titanium Surgical Mesh is intended to be used with supplemental internal spinal fixation systems that are cleared by the FDA for use in the thoracic and/or lumbar spine.

The Atalia Titanium Surgical Mesh is a round-patterned, surgical mesh device. The body is manufactured from TI-6AL-4V ELI Alloy conforming to ASTM F 136. Because of the construction, the angle and the length of the mesh can be reduced incrementally to adjust it to individually anstomical conditions. The Atalia Surgical Mesh System is sold non-sterile.

The provided text is a 510(k) summary for the Atalia Titanium Surgical Mesh, a spinal implant. It details the device's description, indications for use, and a summary of testing. However, it does not contain the specific information requested about acceptance criteria, detailed study results proving a device meets those criteria, expert details, or training/test set specifics for an AI/ML device.

This document describes a medical device clearance for a physical surgical mesh, not a software-driven AI/ML diagnostic tool. Therefore, many of the questions related to AI/ML device evaluation metrics (e.g., sample size for test set, data provenance, ground truth establishment by experts, adjudication methods, MRMC studies, standalone performance, training set details) are not applicable to the information provided in this 510(k) summary.

The "SUMMARY of TESTING" section states: "The Atalia Titanium Mesh (U.S. Spinal Technologies) was tested in accordance with ASTM F2077." This indicates a biomaterial and mechanical performance test for spinal implants, not a clinical study or AI/ML performance evaluation.

To answer your request based on the provided text, I can only state what is directly available:

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

The document mentions testing was done in accordance with ASTM F2077. This ASTM standard defines mechanical test methods for spinal implants. However, the specific acceptance criteria (e.g., minimum compression strength, fatigue life) from ASTM F2077 and the reported performance of the Atalia Titanium Surgical Mesh against those specific criteria are not provided in this 510(k) summary. The summary only states that it was tested in accordance with the standard.

Regarding the other points, as the device is a physical surgical mesh and not an AI/ML diagnostic device, most of the requested information is not applicable to this 510(k) submission.

• 2. Sample sized used for the test set and the data provenance: Not applicable for a physical device mechanical test.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for a physical device performance typically refers to physical measurements and engineering specifications, not expert interpretation of medical data.
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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, as this is not an AI/ML device.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable, as this is not an AI/ML device.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For a physical device like this, the "ground truth" for mechanical testing would be the physical properties and performance measured according to the ASTM F2077 standard. The document does not detail these specific measurements.
• 8. The sample size for the training set: Not applicable, as this is not an AI/ML device.
• 9. How the ground truth for the training set was established: Not applicable, as this is not an AI/ML device.

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