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The Cure™ Lumbar Plate System is intended for use via a lateral or anterolateral surgical approach above the bifurcation of the great vessels in the treatment of thoracolumbar (T1-L5) spine instability or via the anterior surgical approach, below the bifurcation of the great vesses in the treatment of lumbosacral (L1-S1) spine instability as a result of fracture (including dislocation), tumor, degenerative disc disease (defined as back pain of discogenic origin with degeneration of the disc confirmed by patient history and radiographic studies), scoliosis, lordosis, spinal stenosis, or a failed previous spine surgery. The device is intended as a temporary fixation device until fusion is achieved.

The Cure™ Lumbar Plate System is composed of plates in a wide range of sizes to coincide with the surgical approach and screws that are available in multiple lengths and diameters. Cure™ Lumbar Plate System is manufactured from Grade 23 Titanium (Ti-6Al-4V ELI); manufactured according to ASTM F136 Standard Specification for Wrought Titanium-6Aluminum-4Vanadium ELI (Extra Low Interstitial) Alloy (UNS R56401) for Surgical Implant Applications.

The provided text describes a medical device, the Cure™ Lumbar Plate System, and its 510(k) premarket notification to the FDA. The information focuses on regulatory approval and equivalence to a predicate device, rather than the performance of a software or AI-driven diagnostic device. Therefore, the requested information regarding acceptance criteria, study details, sample sizes, expert involvement, and ground truth establishment, which are typical for studies evaluating AI/software device performance, is not present in the provided text.

The document states that the Cure™ Lumbar Plate System is substantially equivalent to a predicate device (K022791 Synthes Anterior Tension Band System) based on technological characteristics and non-clinical testing.

Here's a breakdown of the available information based on your request, highlighting what is not applicable or not found:

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

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
This information is not applicable as the document describes non-clinical mechanical and biological compatibility testing, not a clinical study on human subjects or an AI diagnostic test set.

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):
This information is not applicable as there is no mention of a "test set" in the context of expert ground truth for a diagnostic device. The evaluation was based on engineering and biological testing.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
This information is not applicable.

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 information is not applicable. This describes a physical implantable device, not an AI-assisted diagnostic tool.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
This information is not applicable.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
This information is not applicable in the context of diagnostic accuracy. For the non-clinical testing, the "ground truth" would be established engineering standards (ASTM F1717) and biological standards (ANSI/AAMI ST-72:2011).

8. The sample size for the training set:
This information is not applicable as there is no AI component or training set described.

9. How the ground truth for the training set was established:
This information is not applicable.

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The CITADEL™ Anterior Lumbar Plate System is intended for use in the treatment of lumbar and lumbosacral (L1-S1) spine instability as a result of fracture (including dislocation and subluxation), tumor, degenerative disc disease (defined as back pain of discogenic origin with degeneration of the disc confirmed by patient history and radiographic studies), spondylolysis, spondylolisthesis, scoliosis, kyphosis, lordosis, spinal stenosis, or failed previous spine surgery.

The CITADEL™ Anterior Lumbar Plate System consists of plates of various lengths with variable or fixed bone screws for spinal fixation of the anterior or anterolateral vertebral bodies of the lumbar or lumbosacral spine (L1-S1). The implants are composed of titanium alloy, as specified in ASTM F136, F1295.

The provided text describes a medical device, the "CITADEL™ Anterior Lumbar Plate System," and its 510(k) submission to the FDA. The submission focuses on establishing substantial equivalence to predicate devices through mechanical testing. However, the document does not contain the specific information requested in the prompt regarding acceptance criteria and a study that proves the device meets those criteria, particularly in the context of an AI/algorithm-based device.

Here's an analysis based on the provided text:

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

• Not found: The document states that "Mechanical testing in accordance with the 'Guidance for Industry and FDA Staff, Guidance for Spinal Systems 510(k)s', May 3, 2004 is presented." However, it does not provide a table of specific acceptance criteria (e.g., minimum tensile strength, fatigue life cycles) or the explicit performance results of the CITADEL™ device against these criteria. It only asserts that the device is "similar" to predicate devices in "technical characteristics, performance, and intended use."

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

• Not applicable/Not found: This device is a mechanical orthopedic implant, not an AI or algorithm-based diagnostic tool. Therefore, concepts like a "test set" with data provenance (country, retrospective/prospective) are not relevant in the context of the device described here. Mechanical testing typically uses physical samples of the device components. The document does not specify the number of samples used for the mechanical tests.

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: Ground truth using expert consensus is relevant for diagnostic performance studies, not for the mechanical testing of an implant.

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

• Not applicable: Adjudication methods are relevant for expert review in diagnostic studies, not for 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 is a mechanical implant, not an AI-assisted diagnostic tool.

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

• Not applicable: This is a mechanical implant, not an algorithm.

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

• Not applicable: For mechanical devices, performance is typically measured against established engineering standards (e.g., ASTM standards) rather than clinical ground truth types like pathology or outcomes data in the context of an AI model's performance. The "ground truth" here would be the physical properties and mechanical behavior of the device under test, compared to relevant standards or predicate devices.

8. The sample size for the training set

• Not applicable: This device is a mechanical implant and does not involve a "training set" in the sense of machine learning.

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

• Not applicable: As above, this concept does not apply to a mechanical implant.

In summary, the provided document relates to a 510(k) submission for a mechanical spinal implant. It confirms that mechanical testing was performed according to a guidance document for spinal systems. However, it does not offer the detailed information requested about acceptance criteria and a study design that would be relevant for an AI/algorithm-based medical device.

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