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The BN Cage is indicated for use 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. Patients should have received 6 months of non-operative treatment prior to treatment with the devices. The device must be used with supplemental fixation. These DDD patients may also have up to Grade I spondylolisthesis or retrolisthesis at the involved level(s). It is indicated to be use with autograft bone.

The Medyssey BN Cage is designed to provide mechanical support while biologic fusion takes place. The system consists of 105 sizes of implants in zero degrees and 8 degrees of lordosis. The lordotic angles are bi-convex to accommodate the convexity of the vertebral body above and below the implants are 9mm wide. Implant lengths range from 22-32mm and the height range from 8-15mm.

The Medyssey BN Cage implants are composed of PEEK Optima LT1 from Invibio. The radiopaque markers are made from Tantalum per ASTM F560.

The provided text is a 510(k) summary for the Medyssey BN Cage, an intervertebral body fusion device. It details product information, indications for use, and a brief discussion of non-clinical tests. However, it does not contain any information about a study involving an AI/Machine Learning device.

Therefore, I cannot fulfill your request for:

• A table of acceptance criteria and the reported device performance
• Sample size used for the test set and the data provenance
• Number of experts used to establish the ground truth
• Adjudication method
• Multi reader multi case (MRMC) comparative effectiveness study
• Standalone (i.e. algorithm only without human-in-the loop performance) study
• Type of ground truth used
• Sample size for the training set
• How the ground truth for the training set was established

The document focuses on demonstrating substantial equivalence to predicate devices through material similarity, dimensional equivalence, and mechanical testing. The "acceptance criteria" and "device performance" discussed are related to these mechanical tests and their comparison to predicate devices, not to an AI's performance.

If you have a document describing an AI/ML study, please provide that text, and I will be happy to extract the requested information.

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