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The MOBIS®II ST Spinal Implant is indicated for intervertebral body spinal fusion procedures in skeletally mature patients with degenerative disc disease (DDD) at one or two contiguous levels from L2-S1. DDD is defined as discogenic back pain with degeneration of the disc confirmed by patient history and radiographic studies. These DDD patients may also have up to Grade I spondylolisthesis at the involved level(s). MOBIS®II ST Spinal Implants are to be used with autogenous bone graft and implanted via an open posterior or transforaminal approach. The MOBIS®II ST Spinal Implant is to be used with supplemental fixation. Patients should have at least six (6) months of non-operative treatment with an intervertebral cage.

The MOBIS®II ST Spinal implants have a hollow, slightly curved frame with areas of an open-pore titanium grid structure. Restoration of the intervertebral space can be achieved by the large selection of implants that, at the same time, offers a high degree of intraoperative flexibility. In addition to straight implants, the MOBIS®II ST cage is also available with a 5° lordotic angle. Due to its design, the implant can be aligned with the anterior curvature of the intervertebral body and so is suited for unilateral, dorsal access (TLIF) in the L2 to S1 region of the spine.

This document is a 510(k) summary for the MOBIS®II ST Spinal Implant. It does not describe a study involving an AI/ML powered device, but rather a medical device (spinal implant). As such, many of the requested categories in the prompt are not applicable.

Here's an analysis based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Not directly applicable in the terms of typical AI system performance metrics (e.g., sensitivity, specificity, AUC). For this medical device, acceptance criteria are based on mechanical safety and performance, demonstrating equivalency to predicate devices.

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

Not applicable as this is a mechanical engineering study, not a study involving a "test set" of data in the AI/ML sense. The "sample size" would refer to the number of devices tested, which is not specified but would typically follow ASTM standards for such tests.

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

Not applicable. "Ground truth" in this context refers to the physical properties and performance measured by standardized tests, not expert interpretation of data.

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

Not applicable. Mechanical tests have objective outputs based on engineering principles and standards, not adjudication among human observers.

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 is not an AI-powered device, and no human reader study was conducted.

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

Not applicable. This is a physical spinal implant, not an algorithm.

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

Not applicable. The "ground truth" for mechanical testing is established by the specified ASTM (American Society for Testing and Materials) standards and the physical measurements obtained during the tests.

8. The sample size for the training set

Not applicable. There is no training set for a physical medical device.

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

Not applicable. There is no training set.

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