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The InTice™-C Porous Ti Cervical Interbody System is intended for spinal fusion procedures at one level (C2 - T1 inclusive) in skeletally mature patients with degenerative disc disease (defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies) of the cervical spine. Implants are to be implanted via an open, anterior approach and packed with autograft comprised of cancellous and/or corticocancellous bone graft. Patients should receive at least six (6) weeks non-operative treatment with the InTice™-C Porous Ti Cervical Interbody System.

This device is intended to be used with supplemental spinal fixation systems that have been cleared for use in the cervical spine (i.e. posterior cervical screw and rod systems and anterior cervical plate systems).

The InTice™-C Porous Ti Cervical Interbody System is an intervertebral fusion device, generally box or oval-shaped, and available in a variety of shapes and sizes to accommodate the individual patient anatomy. The implants are made from highly porous commercially pure titanium (CP-TI Grade 2) that complies with ASTM F67. The material is formed into an integrated titanium scaffold, OsteoSync™ Ti (manufactured by Sites Medical), which assists in securing the implant in the intervertebral space. The formed titanium material has a porosity created by a designed hole pattern, and the superior and inferior surfaces of the implant have a tooth pattern to help resist implant dislodgement or expulsion once placed in its desired location. The hollow center of the implant allows the device to be packed with autograft and/or allograft comprised of cancellous and/or corticocancellous bone graft. The single use implants are provided sterile, and should not be reused under any circumstances.

The system does not contain software/firmware or electrical equipment.

The provided text describes a 510(k) premarket notification for a medical device, the InTice™-C Porous Ti Cervical Interbody System. This type of submission aims to demonstrate that a new device is substantially equivalent to legally marketed predicate devices, rather than proving its safety and effectiveness through clinical trials designed to meet specific acceptance criteria for a novel technology.

Therefore, the document does not contain information about:

• Acceptance criteria in the context of clinical performance metrics for an AI/device (e.g., sensitivity, specificity, accuracy). The "acceptance criteria" here are related to proving substantial equivalence to a predicate device.
• A study that proves the device meets the acceptance criteria as would be done for a new device claiming improved clinical outcomes. Instead, it describes non-clinical testing to demonstrate performance equivalence to predicate devices.
• Sample size for a test set and data provenance: There is no "test set" in the sense of a clinical validation dataset. The "testing" refers to biomechanical and material tests.
• Number of experts and their qualifications, adjudication methods, MRMC studies, standalone performance, or type of ground truth used for a test set: These concepts are relevant to clinical or AI performance validation, which is not the focus of this 510(k) submission.
• Sample size for training set or how ground truth for training set was established: These concepts are relevant for AI/machine learning models which are not part of this device submission.

What the document does describe in terms of "acceptance":

The "acceptance" in this context refers to the FDA's acceptance of the 510(k) premarket notification and the determination of substantial equivalence. The criteria for this acceptance are primarily based on demonstrating that the new device has "substantially equivalent" technological characteristics and performs comparably to legally marketed predicate devices, without introducing new safety or effectiveness concerns.

Here's a breakdown of the relevant information provided in the document, framed against the requested points, highlighting what is not applicable:

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

• Acceptance Criteria (Implicit for 510(k) Substantial Equivalence): The implicit acceptance criteria for this 510(k) submission are that the device's technical characteristics and performance must be "substantially equivalent" to predicate devices and not raise new questions of safety or effectiveness. This is demonstrated through non-clinical testing.
• Reported Device Performance (Non-Clinical):

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

• Not Applicable: This is a 510(k) submission for a physical medical device (interbody system), not an AI algorithm or a clinical study dataset for performance evaluation. The "testing" refers to mechanical and material property testing, not clinical data sets.

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

• Not Applicable: Ground truth establishment by experts is relevant for clinical outcome or diagnostic accuracy studies, particularly for AI or image-based diagnostics. This is a submission for a spinal implant, relying on engineering and material standards for performance assessment relative to predicates.

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

• Not Applicable: Adjudication methods apply to studies involving human interpretation or clinical endpoint assessments, which are not detailed in this 510(k) for a physical implant.

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: MRMC studies are specific to evaluating diagnostic performance, often for AI-assisted image interpretation. This submission is for a physical orthopedic implant.

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

• Not Applicable: This criterion is for AI algorithms. The device described does not contain software/firmware or electrical equipment (Page extract 5).

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

• Not Applicable (in the clinical/AI sense): The "ground truth" for this device's performance is based on established engineering standards (ASTM and other biomechanical properties) and comparison to the known characteristics of predicate devices. There is no clinical "ground truth" established in this document, as it focuses on substantial equivalence through non-clinical means.

8. The sample size for the training set

• Not Applicable: There is no "training set" as this is not an AI/machine learning device.

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

• Not Applicable: There is no "training set" for this device.

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