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When intended to promote fusion of the cervical spine and occipito-cervico-thoracic junction (Occiput - T3), the SOLSTICE OCT System, when properly used, is intended for: Degenerative Disc Disease (as defined by neck pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies); spinal stenosis; fracture/dislocation: Atlanto/axial fracture with instability; occipitocervical dislocation; revision of previous cervical spine surgery; and tumors.

When used with occipital plate, the bone screws are limited to occipital fixation only. The bone screws are not intended to be used in the cervical spine.

The use of thoracic screws is limited to placement in T1-T3 for anchoring the construct only. They are not intended to be placed in the cervical spine.

The hooks and rods are also intended to provide stabilization following reduction of fracture/dislocation or trauma in the cervical/upper thoracic (C1-T3) spine.

The SOLSTICE OCT System is a temporary, titanium alloy (6AL-4V-ELI per ASTM F 136), multiple component system comprised of a variety of non-sterile, single use implantable components. The system consists of an assortment of occipital plates, occipital bone screws, polyaxial screws, hooks, connectors, rods, and locking caps.

This document is a 510(k) premarket notification for the SOLSTICE® OCT System, a spinal interlaminal fixation orthosis. The FDA has reviewed the submission and determined that the device is substantially equivalent to legally marketed predicate devices.

Here's the breakdown of the acceptance criteria and study information provided (or lack thereof, as this is a 510(k) and not a clinical study report):

1. Table of Acceptance Criteria and Reported Device Performance:

Important Note: This 510(k) summary focuses on demonstrating "substantial equivalence" to a predicate device rather than presenting detailed clinical performance metrics against predefined acceptance criteria for a novel device. Therefore, the acceptance criteria are largely related to mechanical performance and material specifications that demonstrate equivalence to the predicate, rather than clinical efficacy endpoints. Specific quantitative thresholds for static/dynamic compression and rod lockup are not provided in this document.

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

• This document describes mechanical testing of the device, not a clinical test set with patient data.
• The document does not specify the sample size for the mechanical tests (e.g., number of implant constructs tested).
• Data provenance is not applicable as it's mechanical benchtop testing, not human patient data.

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

• Not applicable. This pertains to mechanical testing, not clinical evaluation requiring expert ground truth for patient diagnoses or outcomes.

4. Adjudication method for the test set:

• Not applicable. This pertains to 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 document is for a spinal implant, which is a physical device, not an AI-powered diagnostic tool. Therefore, MRMC studies are not relevant here.

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

• Not applicable. This document is for a spinal implant, not a standalone algorithm.

7. The type of ground truth used:

• For the mechanical testing, the "ground truth" would be the engineering specifications and standards (e.g., ASTM F136 for material, and potentially other industry standards for static/dynamic compression and rod lockup of spinal instrumentation). The device's performance is compared against these standards or the performance of the predicate device.

8. The sample size for the training set:

• Not applicable. This document describes mechanical testing of a physical device, not a machine learning model that requires a training set.

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

• Not applicable. As above, no training set for a machine learning model is involved.

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