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The Stable-C Interbody System is an anterior cervical interbody fusion system. The Stable-C Interbody System is indicated for use in skeletally mature patients with degenerative disc disease (DDD) at one level from C2-T1. DDD is defined as back pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies. The Stable-C Interbody System is to be used with supplemental fixation cleared for use in the cervical spine. The system is intended to be used with autogenous or allogeneic bone graft comprised of cancellous and/or corticocancellous bone graft to facilitate fusion. The system is to be used in patients who have had six weeks of non-operative treatment.

The Stable-C Interbody System is an anterior cervical interbody device comprised of a cage (lordotic angles of 0 , 6°, and 12°) made from Ti-6Al-4V per ASTM F3001 and two fixation anchors made from Ti-6-Al-4V ELI per ASTM F136. The device is offered in a variety of sizes to accommodate patient anatomy. The devices and instruments are provided clean and non-sterile for steam sterilization at the user's facility.

The provided text is a 510(k) premarket notification FDA letter for a medical device called the "Stable-C Interbody System." This document primarily focuses on demonstrating substantial equivalence to pre-existing, legally marketed devices.

It does NOT describe a study involving an AI/Medical Device that uses machine learning, nor does it provide details about acceptance criteria and performance data in the context of an algorithm's accuracy or effectiveness.

The "Performance Data" section in the document refers to mechanical testing of the physical implant device to prove its structural integrity and safety, not the performance of an AI algorithm.

Therefore, I cannot extract the requested information (acceptance criteria, details of a study proving algorithm performance, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, ground truth types, training set details) from the provided text because it is not relevant to an AI/ML medical device.

To answer your request, I would need a document describing the validation and performance of an AI/ML-based medical device.

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The Incite Anchored Cervical Interbody Device is indicated for use in skeletally mature patients with degenerative disease (DDD) of the cervical spine with accompanying radicular symptoms at one disc level from C2-T1. DDD is defined as discogenic pain with degeneration of the disc confirmed by history and radiographic studies. These patients should have had six weeks of non-operative treatment. The Incite Anchored Cervical Interbody Device is to be used with autogenous bone graft and implanted via an open, anterior approach. Supplemental fixation, i.e. an anterior cervical plate, is required to properly utilize this system.

The Incite Anchored Cervical Interbody Fusion Device acts as a spacer to maintain proper Intervertebral and vertebral body spacing and angulation. The Incite Anchored Cervical Interbody Fusion Device is manufactured from PEEK and Ti6A14V titanium alloy with tantalum radiopaque markers

The provided text describes a Special 510(k) Summary for a medical device called the "Incite Anchored Cervical Interbody Fusion (ACI) Device." This type of submission focuses on demonstrating substantial equivalence to a predicate device, often for minor modifications rather than entirely new devices requiring extensive clinical trials for efficacy.

Based on the provided document, here's a breakdown of the acceptance criteria and the study used:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: The document explicitly states that "additional mechanical testing on the new size is not warranted." This means there was no new physical test set specifically for the 16x14mm device being cleared in this 510(k). The "test set" for the performance criteria refers to the testing data from the predicate device (K122008). The document does not specify the sample size (e.g., number of devices tested for static compression, torsion, etc.) used for the predicate device's original testing.
• Data Provenance: The data provenance is retrospective, as it relies entirely on the performance testing previously conducted and accepted for the predicate device (K122008). The country of origin of the data is not specified, but it would have been generated as part of the predicate device's original regulatory submission.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

• This information is not applicable and not provided in the document. The study is a mechanical performance comparison based on engineering principles and previous device testing, not a clinical or diagnostic study involving human expert interpretation for ground truth.

4. Adjudication Method for the Test Set

• This information is not applicable and not provided. As above, this is a mechanical performance study, not a study requiring adjudication of expert opinions.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. This type of study is typically performed for diagnostic or AI-assisted interpretation devices to assess the impact on human reader performance. This submission is for an implantable medical device, and the demonstration of substantial equivalence relies on mechanical performance data and comparison of physical attributes.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• No, a standalone performance study was not done. This device is a physical implant, not an algorithm or AI system.

7. The Type of Ground Truth Used

• The "ground truth" for the mechanical performance aspects is based on engineering and biomechanical testing standards and the results obtained from the predicate device's testing against those standards. It is not expert consensus, pathology, or outcomes data. The ground for "substantial equivalence" is the direct comparison of design, materials, and intended use to the predicate device, along with the reasoning that the new size does not introduce a "new worst case condition."

8. The Sample Size for the Training Set

• This information is not applicable and not provided. There is no "training set" in the context of this device and its regulatory submission, as it is not an AI/ML algorithm.

9. How the Ground Truth for the Training Set Was Established

• This information is not applicable and not provided. As there is no training set, there is no ground truth to establish for it.

In summary:

The study presented here is a Special 510(k) submission based on substantial equivalence to a predicate device (K122008). The "study" for acceptance criteria is primarily a justification based on engineering principles and previously accepted mechanical test data from the predicate device. The key argument is that the dimensional differences of the new device (a larger footprint 16x14mm) do not create a "new worst-case condition" compared to the predicate device, thus making the predicate's performance data applicable to the new size. No new testing was performed for this specific submission for the new size.

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