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The TiLink-P SI Joint Fusion System is intended for sacroiliac joint fusion for conditions including sacroiliac joint disruptions and degenerative sacroiliitis.

The purpose of this Special 510(k) is to introduce the TiLink-P with Window variant to the TiLink-P SI Joint Fusion System. The Window feature is designed to promote osteointegration.

The TiLink-P SI Joint Fusion System contains various orthopedic instruments to assist the user in implanting a titanium sacroiliac implant into the sacroiliac joint to transfix the joint. The SurGenTec TiLink-P SI Joint Fixation System includes TiLink Implants and associated Instruments. The TiLink-P implants may be used standalone. The TiLink-P SI Joint Fusion System fixates the sacroiliac joint by transfixing the cortices of the ilium and cortices of the sacrum.

The TiLink-P Compression Anchor is positioned so that it spans the cortices of ilium and cortices of sacrum, the TiLink-P Locking Screw is inserted through the TiLink-P Compression Anchor and along the SI Joint via a posterior approach, in order to compress the joint. Bone graft material is used with the TiLink-P SI Joint Fusion System to facilitate bone growth.

The FDA letter provided is a clearance letter for a medical device (TiLink-P SI Joint Fusion System), not an AI/ML device. Therefore, the document does not contain information about acceptance criteria or studies pertaining to AI/ML device performance. The information requested regarding sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance, and training data is not applicable to the content of this document.

The document discusses the substantial equivalence of the "TiLink-P SI Joint Fusion System" to a predicate device (TiLink-P Joint Fusion System K240720) through mechanical strength tests.

Here is the information that is available in the document:

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

The document states that performance testing was conducted according to specific ASTM standards to demonstrate substantial equivalence to the predicate device. However, it does not provide a table of acceptance criteria (e.g., specific thresholds for pullout strength or shear strength) nor the reported numerical performance data. It only lists the types of tests performed.

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" here refers to physical devices for mechanical testing, not a dataset for an AI/ML model. The document does not specify the number of devices tested. Data provenance such as country of origin or retrospective/prospective is not relevant for this type of device clearance.

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. Ground truth as typically understood in AI/ML (e.g., expert labels on images) is not relevant for this type of mechanical device testing. The "ground truth" for mechanical testing is derived from established engineering principles and ASTM standards.

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

Not applicable. Adjudication methods are typically used for resolving disagreements among human experts in labeling datasets, which is not relevant for mechanical testing.

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 clearance for a physical medical implant, not an AI/ML diagnostic or assistive device. No MRMC study was conducted.

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

Not applicable. This device is not an algorithm.

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

Not applicable. For mechanical testing, the "ground truth" is provided by the established ASTM standards and the physical properties and performance of the predicate device.

8. The sample size for the training set

Not applicable. There is no AI/ML model, and therefore no training set.

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

Not applicable. There is no AI/ML model, and therefore no training set or ground truth for a training set.

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