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When used with the Zavation ZLinkPC System for Posterior-Cervical-Thoracic (Occ-T3)

The Zavation Connector System is intended to provide immobilization of spinal segments in sketally mature patients as an adjunct to fusion in the treatment of the following acute and chronic instabilities of the craniocervical junction, the cervical spine (C1 to C7) and the thoracic spine (T1-T3): traumatic spinal fractures and/or traumatic dislocations; instability or deformity; failed previous fusions (e.g. pseudoarthrosis); tumors involving the cervical/thoracic spine; and degenerative disease, including intractable radior myelopathy, neck and/or arm pain of discogenic origin as confirmed by radiographic studies, and degenerative disease of the facets with instability.

When used with the Zavation Spinal System for Thoracic, Lumbar, and Sacral Spine Fixation (T1-S2/Illium)

The Zavation Connector System is intended to provide immobilization of spinal segments in sketally mature patients as an adjunct to fusion as a pedicle screw fixation system (T1-S2/Illium) in the treatment of the following acute and chronic instabilities or deformities of the thoracic, lumbar, and sacral spine: degenerative spondylolisthesis with objective evidence of neurological impairment, fracture, dislocation, scoliosis, spinal tumor, and failed previous fusion (pseudarthrosis).

The Connector System is designed to aid in revision surgeries and extensions of existing hardware constructs from the Occiput to the Ilium. The Connector System includes a variety of non-sterile titanium implants including parallel rod to rod domino connectors, axial connectors with and without attachment rods, bypass connectors, lateral offsets, double tulips (angled and parallel), and Z rods. The implant options allow revisions and extension to be performed without removing existing hardware. The Zavation Connector System is designed to be used with the Zavation Z-Linkpc System for Posterior-Cervical-Thoracic (Occ-T3) and the Zavation Spinal System for Thoracic, Lumbar, and Sacral Spine Fixation (T1-S2/Illium).

The provided text is a 510(k) summary for a medical device called the "Zavation Connector System." It details the device's purpose, description, indications for use, materials, and a comparison to predicate devices, along with performance data.

However, the provided text does not contain information about acceptance criteria, clinical studies involving human readers, expert ground truth establishment, sample sizes for training/test sets, or adjudication methods. The "Performance Data" section specifically states: "Static axial and torsional grip were performed according to ASTM F1798 on a worst-case construct. The mechanical test results demonstrated substantial equivalency to the predicate device." This indicates mechanical testing, not clinical performance studies involving human interpretation or AI assistance, which are the focus of your request.

Therefore, I cannot fulfill your request to describe the acceptance criteria and the study that proves the device meets them based on the provided document in the context of an AI/human reader performance study. The document describes the substantial equivalence of a physical medical implant (a pedicle screw system connector) based on mechanical properties, not an AI or imaging diagnostic device.

If this were a submission for an AI-powered diagnostic device, using the provided template, the description would approximate the following (hypothetical, as the actual data is not in the text):

Hypothetical Description of Acceptance Criteria and Study for an Imaginary AI-Powered Spinal Bone Fracture Detection Device (Not from the provided text)

Based on the provided document, the device in question is the "Zavation Connector System," which is a mechanical implant (thoracolumbosacral pedicle screw system) used to immobilize spinal segments. The provided performance data relates to static axial and torsional grip mechanical testing according to ASTM F1798, demonstrating substantial equivalence to a predicate device in terms of its physical properties and function, not its diagnostic accuracy or the performance of an AI algorithm.

Therefore, the detailed information requested regarding acceptance criteria, study sample sizes, expert ground truth establishment, MRMC studies, and AI performance metrics is not present in the provided 510(k) summary for the Zavation Connector System. This type of information is typically required for diagnostic imaging devices, especially those incorporating AI.

However, to illustrate how such a request would be addressed if the provided document were about an AI-powered diagnostic device, I will provide a hypothetical response demonstrating the structure and type of information that would be present.

Hypothetical Scenario: Acceptance Criteria and Study for an AI-Powered Spinal Bone Fracture Detection Device

Device Name (Hypothetical): SpinalFractureAI Assistant

Indications for Use (Hypothetical): The SpinalFractureAI Assistant is intended as a supplemental tool for radiologists to detect and localize vertebral fractures in thoracic and lumbar spine CT scans in adult patients.

1. Table of Acceptance Criteria and Reported Device Performance:

2. Sample Sizes and Data Provenance:

• Test Set Sample Size: 500 unique CT scans (patients).
• Data Provenance: Retrospective data collected from 3 major hospital systems across the United States (n=300), Germany (n=100), and Japan (n=100).
• Data Type: De-identified thoracic and lumbar spine CT scans.

3. Number of Experts for Ground Truth and Qualifications:

• Number of Experts: 3 independent expert radiologists.
• Qualifications: All were board-certified radiologists with subspecialty training in musculoskeletal radiology, each possessing at least 10 years of experience interpreting spinal CT scans.

4. Adjudication Method for the Test Set:

• Adjudication Method: 2+1 Consensus. Initial reads by two independent expert radiologists. In cases of disagreement on the presence or location of a fracture, a third, senior-level expert radiologist reviewed the case to establish the definitive ground truth.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• Yes, an MRMC comparative effectiveness study was performed.
• Effect Size: Human readers (radiologists) demonstrated a 7.2 percentage point improvement in fracture detection sensitivity when assisted by the AI algorithm compared to reading without AI assistance. This was statistically significant (p

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