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The Camber Spine Technologies Ti-Diagon® Oblique TLIF is indicated for intervertebral body fusion procedures in skeletally mature patients with degenerative disc disease (DDD) of the lumbar spine at one or two contiguous levels from L2-S1. DDD is defined as discogenic pain with degeneration of the disc confirmed by history and radios. These DDD patients may also have up to Grade I spondylolisthesis at the involved level(s). Camber Spine Technologies Ti-Diagon® Oblique TLIF is to be used with autologous bone graft and implanted via an open transforaminal or posterior approach. Camber Spine Technologies Ti Diagon Oblique TLIF implants are to be used with supplemental fixation. Patients should have at least six (6) months of non-operative treatment prior to treatment with an intervertebral cage.

The Camber Spine Technologies Ti-Diagon Oblique TLIF is an interbody fusion device with a hollow chamber to permit packing of autologous bone graft in order to facilitate fusion. The inferior and superior surfaces of the Ti-Diagon Oblique TLIF have a rough texture, as the result of a photochemical etching process, to help prevent movement of the device.

The provided text is a 510(k) summary for a medical device (Ti-Diagon Oblique TLIF), which primarily focuses on demonstrating substantial equivalence to predicate devices based on design, materials, and mechanical performance. It does not contain information about studies involving human readers, AI, or clinical ground truth in the way a diagnostic device submission might. Therefore, many of the requested fields cannot be populated from the provided document.

Here's an analysis of what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

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

• The document refers to "Performance Testing Summary" which included mechanical tests per ASTM F2077-14 and F2267-04. These standards are for in vitro mechanical testing of intervertebral body fusion devices.
• Sample Size: Not specified in the provided text.
• Data Provenance: The data provenance for this type of testing is generally lab-generated data from mechanical testing setups, not human or clinical data. Not explicitly stated where the tests were performed.
• Retrospective/Prospective: Not applicable for mechanical bench testing.

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

• Not applicable. The "ground truth" for mechanical testing is derived from quantitative measurements of physical properties, not expert opinion.

4. Adjudication method for the test set:

• Not applicable. Mechanical testing results are typically compared against pre-defined engineering specifications and predicate performance, not adjudicated by human experts.

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:

• No. This document does not pertain to an AI-assisted diagnostic device or any study involving human readers.

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

• No. This document does not describe an algorithm or AI device.

7. The type of ground truth used:

• For the mechanical testing, the "ground truth" is the quantitative measurement of the device's physical properties and mechanical performance, compared against the performance of predicate devices and relevant ASTM standards (ASTM F2077-14 and F2267-04).

8. The sample size for the training set:

• Not applicable. There is no mention of a "training set" as this is not an AI/ML device.

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

• Not applicable. There is no mention of a "training set" or "ground truth" in the context of AI/ML.

Summary of what cannot be answered from the provided text:

The document describes a 510(k) submission for a spinal implant (intervertebral body fusion device). The "acceptance criteria" and "study" refer to mechanical performance testing to demonstrate the device is as mechanically sound as its predicate devices. The information requested regarding AI performance, human readers, clinical ground truth, and specific sample sizes for such studies is not present because this device is a physical implant, not a diagnostic or AI-powered tool.

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The Synthes Radial Head Prosthesis System is intended for:

1. The replacement of the radial head for degenerative or post-traumatic disabilities presenting pain, crepitation, and decreased motion at the radio-humeral and/or proximal radio-ulnar joint with
   a. Joint destruction and/or subluxation visible on x-ray
   b. Resistance to conservative treatment
2. Primary replacement after fracture of the radial head.
3. Symptomatic sequelae after radial head resection
4. Revision following failed radial head arthroplasty.

The Synthes Radial Head Prosthesis is a two-piece modular system comprised of titanium alloy stem and cobalt chrome head components with an integral screw and side-loading application to allow for in situ assembly. The system consists of a range of lengths and diameters for the stem in both straight and curved configurations as well as heads in a range of diameters and heights to accommodate the surgical need.

This document is a 510(k) Summary for the Synthes Radial Head Prosthesis System. It is focused on demonstrating substantial equivalence to predicate devices, rather than establishing acceptance criteria and conducting a study to prove performance against those criteria in the way one might for a novel diagnostic or AI device.

Therefore, many of the specific questions regarding acceptance criteria, device performance metrics (e.g., sensitivity, specificity), sample sizes, ground truth establishment, expert qualifications, and MRMC studies are not directly applicable or explicitly detailed in this type of submission for a medical implant device.

However, I can extract the relevant information regarding the performance testing and the approach to demonstrating substantial equivalence.

Here's an analysis based on the provided text, addressing the applicable points and explaining why others are not present:

Context: The Synthes Radial Head Prosthesis System is a medical implant (a modular radial head prosthesis) intended for the replacement of the radial head in specific orthopaedic conditions. The 510(k) submission aims to demonstrate that this new device is "substantially equivalent" to existing, legally marketed predicate devices. This means it has the same intended use, fundamental technological characteristics, and similar materials, and that performance testing shows it is as safe and effective as the predicates.

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

The document does not explicitly present a table of quantitative acceptance criteria for performance metrics typical of, for example, diagnostic accuracy (like sensitivity, specificity, AUC). Instead, the "acceptance criteria" are implied by the demonstration of substantial equivalence to predicate devices through various tests and analyses.

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

• Sample Size: The document does not specify a "sample size" in terms of patients or anatomical specimens as one would for a clinical trial or diagnostic study. The "test set" here refers to the actual physical devices (or components thereof) that underwent in vitro performance testing and surface analysis. The number of such devices or samples tested is not disclosed in this summary.
• Data Provenance: The tests are described as "in vitro performance testing," "Macro Surface Analysis," "Scanning Electron Microscopy (SEM)," and "X-Ray Photoelectron Spectroscopy (XPS)." These are laboratory-based studies, not clinical studies involving patient data from specific countries or populations. The data provenance is controlled laboratory conditions.

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

• This question is not applicable to this type of device submission. The "ground truth" for a mechanical implant is its physical and mechanical properties, not expert-derived diagnostic labels. The performance is assessed through engineering and materials science testing, not clinical diagnosis by experts.

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

• This question is not applicable. Adjudication methods are typically used to resolve discrepancies in expert interpretations of clinical data or images. This submission focuses on the objective physical and mechanical properties of an 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

• This question is not applicable. The device is a physical implant, not a diagnostic imaging or AI algorithm that would involve human readers or AI assistance.

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

• This question is not applicable. The device is a physical implant, not an algorithm.

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

• The "ground truth" for this device's performance is established by engineering and materials science standards and measurements. This includes:
  • Mechanical properties: The ability to withstand clinical loads.
  • Material properties: Chemical composition and physical and macro/micro surface characteristics.
  • Peer-reviewed literature: Used to demonstrate how these material and surface characteristics relate to physiological responses.

8. The sample size for the training set

• This question is not applicable. There is no concept of a "training set" in the context of this 510(k) submission for a physical implant. The design and manufacturing processes are based on engineering principles and prior knowledge from predicate devices, rather than machine learning training.

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

• This question is not applicable, as there is no training set. The "ground truth" for the device's design and material selection would be established through established engineering principles, materials science, and conformity to relevant ASTM/ISO standards (though specific standards are not named in this summary).

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