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510(k) Data Aggregation

    K Number
    K230026
    Device Name
    SQUALE
    Manufacturer
    Date Cleared
    2023-03-28

    (83 days)

    Product Code
    Regulation Number
    888.3080
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    SQUALE

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The SQUALE devices are indicated for use in cervical interbody fusion procedures in skeletally mature patients with degenerative disc disease (DDD) at one level from the C2-C3 disc to the C7-T1 disc. DDD is defined as neck pain of discogenic origin with degeneration of the disc confirmed by history and radiographic studies. The SQUALE devices are to be used with autogenous bone graft and/or allogenic bone graft comprised of cancellous and/or corticocancellous bone graft, and are to be implanted via an open, anterior approach.

    The SQUALE devices are intended to be used with supplemental fixation systems that have been cleared for use in the cervical spine. This cervical device is to be used in patients who have had six weeks of non-operative treatment.

    Device Description

    The SQUALE device consists of Polyetherketoneketone (PEKK) (compliant with ASTM F2820 standard) cervical cages of various widths and heights, which can be inserted between two cervical or cervico-thoracic vertebral bodies to give support and correction during cervical interbody fusion surgeries. The hollow geometry of the implants allows them to be filled with autogenous and/or allogenic bone graft.

    AI/ML Overview

    This document is a 510(k) premarket notification from the FDA for a medical device called SQUALE. It determines that the SQUALE device is substantially equivalent to legally marketed predicate devices.

    Here's an analysis of the provided text in the context of your request for acceptance criteria and study details:

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

    The provided FDA document does not explicitly state numerical acceptance criteria in a table format, nor does it present detailed numerical performance metrics for the SQUALE device against such criteria. Instead, it makes a general statement:

    Acceptance Criteria (Implied)Reported Device Performance
    Meet ASTM F2077 standardsPerformance testing conducted per ASTM F2077.
    Meet ASTM F2267 standardsPerformance testing conducted per ASTM F2267.
    Substantially equivalent to predicate devices for static and dynamic axial compression, static and dynamic compression shear, static and dynamic torsional, subsidence, and expulsion testing.The results of these studies were determined to be substantially equivalent to legally marketed devices.
    As safe and effective as the primary predicate device (Stryker's AVS AS PEEK Spacer).The SQUALE is as safe and effective as the primary predicate device. Performance data demonstrate that the SQUALE is as safe and effective as the predicate device.
    Raise no new issues of safety or effectiveness associated with technological differences.The minor technological differences between the SQUALE and its predicate device raise no new issues of safety or effectiveness.

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

    The document mentions "Performance testing was conducted per ASTM F2077 and ASTM F2267." These are standards for mechanical testing of intervertebral body fusion devices. These tests typically involve a specific number of devices to be tested to demonstrate compliance. However, the exact sample size (number of SQUALE devices tested) is not specified in this document.

    The data provenance (country of origin, retrospective or prospective) is also not specified. Given it's bench testing, the concept of "country of origin of the data" might refer to where the testing was performed, which is not stated. These are typically prospective tests performed on newly manufactured devices.

    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 the SQUALE device is an implantable medical device, and the "ground truth" for its performance is established through mechanical bench testing against industry standards (ASTM F2077, ASTM F2267) and comparison to predicate devices, rather than through expert interpretation of clinical data. Therefore, there are no "experts" in the context of establishing ground truth for a test set based on human interpretation.

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

    This information is not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical studies where human readers interpret data, and there's a need to resolve disagreements. For mechanical performance testing of an implantable device, the results are typically quantitative and objective; they either meet the standard or they don't. There's no human interpretation or adjudication process in the sense of a clinical trial.

    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

    There is no mention of an MRMC comparative effectiveness study, nor is there any indication that SQUALE is an AI-assisted device. The SQUALE is a physical intervertebral body fusion device.

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

    This question is not applicable as SQUALE is not an algorithm or an AI-powered device. It is a physical implant.

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

    For the SQUALE device, the "ground truth" for its performance is based on established engineering and biomechanical standards (ASTM F2077 and ASTM F2267). Compliance with these standards, along with demonstrating "substantial equivalence" to predicate devices through various mechanical tests, serves as the basis for its safety and effectiveness claims for regulatory purposes. There is no mention of expert consensus, pathology, or outcomes data being used to establish ground truth for the device's functional performance in this document.

    8. The sample size for the training set

    This information is not applicable. The SQUALE device is not an AI/ML algorithm that requires a training set. It is a physical medical device.

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

    This question is not applicable as there is no training set for a physical device like SQUALE.

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