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UNiD Patient specific 3D printed TLIF cage is indicated for intervertebral body 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). This device is to be used with autogenous bone graft.

UNiD Patient specific 3D printed TLIF cage is to be used with supplemental fixation. Patients should have at least six (6) months of non-operative treatment prior to treatment with an intervertebral cage.

MEDICREA® INTERNATIONAL UNiD Patient specific 3D Printed TLIF cage consists of one single implant with specific heights, length and lordosis angle to the patient. It is intended for insertion between two adjacent vertebrae by a posterior or a transforaminal approach. The MEDICREA® INTERNATIONAL implant is manufactured from titanium alloy Ti-6AI-4V ELI following standards ASTM F3001, a radio opaque material. As any orthopaedic implant, the lumbar interbody device must not be reused. The surgeon should strictly follow the recommendations provided in the surgical technique.

MATERIALS: Titanium Alloy (Ti-6Al-4V) according to the ASTM F3001.

Function:
The UNiD Patient specific 3D printed TLIF cage was developed as an implant:

• To provide immobilization and stabilization of posterior spinal segments ●
• to augment the development of a solid spinal fusion
• to provide stability to ease fusion ●
• to be mechanically resistant to allow the fusion of the operated level

The given text describes a 510(k) summary for the UNiD Patient specific 3D printed TLIF cage, which is an intervertebral body fusion device. The document primarily focuses on demonstrating substantial equivalence to predicate devices based on non-clinical testing. It does not contain information about studies involving acceptance criteria related to device performance in an AI/algorithm context, nor does it detail a study that proves the device meets such criteria through clinical trials or performance metrics typically associated with AI-driven devices.

Therefore, many of the requested categories of information cannot be extracted from the provided text as they pertain to AI/algorithm performance and clinical study designs which are not present in this regulatory submission for a physical medical device.

Here's a breakdown of what can be extracted and what cannot:

1. Table of acceptance criteria and the reported device performance:

This document does not specify quantitative acceptance criteria for the device performance that would typically be seen for an AI or algorithm-driven device. Instead, it relies on demonstrating substantial equivalence through material properties and mechanical testing comparisons to predicate devices. The "reported device performance" is essentially that it meets the same mechanical and biocompatibility standards as its predicates.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

Not applicable. The "test set" and "data provenance" refer to data used in evaluating AI/algorithm performance. This document describes mechanical and biocompatibility testing of a physical implant. The mechanical testing involved evaluating a "worst-case device," but the sample size for these specific tests is not provided.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

Not applicable, as this relates to expert-labeled data for AI/algorithm performance.

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

Not applicable, as this relates to expert adjudication for AI/algorithm 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 is a physical medical device (intervertebral cage), not an AI/algorithm.

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

Not applicable. This is a physical medical device.

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

For the mechanical testing, the "ground truth" would be the established engineering standards (ASTM F2077, ASTM F2267) which define acceptable mechanical properties and behaviors of intervertebral body fusion devices. For biocompatibility, the ground truth would be established international standards for the biocompatibility of medical device materials.

8. The sample size for the training set:

Not applicable. There is no AI/algorithm training set.

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

Not applicable. There is no AI/algorithm training set.

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