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When intended to promote fusion of the cervical spine and thoracic spine (C1-T3) and occipito-cervico-thoracic junction (occiput-T3) and are intended for the following:

• DDD (neck pain of discogenic origin with degeneration of the disc as confirmed by patient history and radiographic studies
• Spondylolisthesis
• Spinal Stenosis
• Fracture/dislocation
• Failed previous fusion
• Atlanto/axial fracture with instability
• Occipitocervical dislocation
• Revision of previous cervical spine surgery
• Tumors

The occipital bone screws are limited to occipital fixation only. The hooks and rods are also intended to provide stabilization to promote fusion following reduction of fracture/dislocation or trauma in the cervical/upper thoracic (C1-T3) spine.

The use of the polyaxial screws is limited to placement in T1-T3 in treating thoracic conditions only. Screws are not intended to be place in the cervical spine.

The Aesculap® S4 Cervical Occipital Plate Spinal System is an implant system used to facilitate the biological process of spinal fusion. This system is intended to oromote fusion of the cervical and thoracic spine (C1-T3) and occiptio-cervicothoracic junction (occiput-T3). The Aesculap S4 Cervical Occipital Plate Spinal System consists of plates, bone screws, rods, hooks, and connectors. The components are available in a variety of lengths in order to accommodate patient anatomy. The Aesculap® S4 Cervical Occipital Plate Spinal System is manufactured from Titanium Alloy and will be provided non-sterile.

The provided document is a 510(k) summary for the S4 Cervical Occipital Plate Spinal System, which is a medical device for spinal fusion. This type of document focuses on establishing substantial equivalence to previously cleared devices rather than presenting a standalone study with detailed acceptance criteria and performance metrics for an AI/software device.

Therefore, most of the requested information regarding acceptance criteria, study design, sample sizes, expert involvement, and ground truth establishment, which are typical for software-based medical device submissions, is not present in this document.

Here's an analysis of what can be extracted and what is explicitly not available based on the provided text:

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

• Not Available: The document does not provide a table of quantitative acceptance criteria for the device performance, nor does it report specific numerical performance metrics (e.g., accuracy, sensitivity, specificity, precision, recall) in the way a software device would.
• Instead, it states: "Biomechanical testing of the subject device was found to be similar in performance to previously cleared spinal systems with similar indications." and "Testing results demonstrate the Aesculap S4 Cervical Occipital Plate Spinal System is safe and effective comparable to other predicate systems currently on the market." This indicates a qualitative comparison to predicates rather than specific, measurable performance targets.

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

• Not Available: The document does not describe a "test set" in the context of data for a software device, nor does it refer to human subjects. The testing mentioned is "Biomechanical testing," which typically involves mechanical or cadaveric models rather than patient data. Therefore, data provenance is not applicable in this context.

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/Not Available: This device is a mechanical implant, not an AI/software device that requires expert-established ground truth from medical images or clinical data. "Ground truth" in this context would relate to the physical properties and biomechanical performance of the device itself, which are evaluated through engineering tests, not expert clinical review of data.

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

• Not Applicable/Not Available: As there is no "test set" of clinical data requiring expert review, there is no adjudication method described.

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/Not Available: This device is a physical spinal implant. MRMC studies and "human readers improving with AI assistance" are concepts specific to AI/software diagnostic or assistive devices, not for mechanical implants.

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

• Not Applicable/Not Available: This is a physical implant, not an algorithm.

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

• Not Applicable/Not Available: The "ground truth" for a mechanical device's performance would be derived from validated engineering standards and testing methodologies (e.g., measuring fatigue life, tensile strength, fixation strength against established biomechanical benchmarks). The document mentions "All required testing per 'Draft Guidance for the Preparation of Premarket Notifications (510(k)s) Applications for Orthopedic Devices-The Basic Elements'" and "'Spinal System 510(k)s'" were completed, implying adherence to these standards for establishing product safety and effectiveness.

8. The sample size for the training set

• Not Applicable/Not Available: This device is a mechanical implant; therefore, there is no "training set" in the context of machine learning.

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

• Not Applicable/Not Available: As there is no training set for an algorithm, there is no description of how ground truth for such a set would be established.

In summary: The provided 510(k) summary for the S4 Cervical Occipital Plate Spinal System pertains to a physical orthopedic implant. The information requested aligns with the requirements for software-as-a-medical-device (SaMD) or AI-powered medical devices, which typically involve clinical studies, data sets, and performance metrics like sensitivity and specificity. This document, therefore, does not contain the specific details you've asked for because they are not relevant to the type of device being described. The approval is based on "substantial equivalence" through biomechanical testing against predicate devices.

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