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510(k) Data Aggregation

    K Number
    K142707
    Date Cleared
    2014-12-19

    (88 days)

    Product Code
    Regulation Number
    888.3040
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K970549, K020791, K132910

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

    For fracture fixation of small bones and small bone fragments including odontoid fractures.

    Device Description

    The AIS Odontoid Fracture Fracture Fixation System is comprised of screws and instruments. The 4.0mm cortical screws are either a fully-threaded or partially threaded. They are offered in various lengths and will be non-sterile. The screws are manufactured from titanium alloy (Ti6Al4V) per ISO 5832/3.

    AI/ML Overview

    This document is a 510(k) premarket notification summary for the AIS Odontoid Fracture Fixation System. It describes a new medical device and its equivalence to previously cleared devices. However, this type of document focuses on establishing substantial equivalence through non-clinical performance data (mechanical testing) rather than clinical studies of a device's performance in humans, especially for AI/algorithm-based devices.

    Therefore, most of the requested information regarding acceptance criteria, device performance from clinical studies, sample sizes for test/training sets, ground truth establishment, expert involvement, and MRMC studies, is not applicable or available within this provided text.

    Here's a breakdown of what can be extracted and what cannot:

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

    Acceptance CriteriaReported Device Performance
    Non-clinical Performance (Mechanical Testing):
    Static Testing per ASTM F543"meets or exceeds the performance of the predicate devices"
    Static and Dynamic Cantilever Testing per ASTM F2193"meets or exceeds the performance of the predicate devices"
    Clinical Performance (regarding AI/algorithm):Not applicable/Available

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

    • Not applicable/Available. This document describes mechanical testing of a physical implant, not an AI/algorithm. Sample sizes would refer to the number of implants tested in a lab, not patient data.

    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/Available. Ground truth in this context would relate to the physical properties measured in mechanical tests, not expert interpretation of medical images or patient outcomes.

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

    • Not applicable/Available. Adjudication methods are relevant for human interpretation tasks, not 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/Available. This document is for a physical orthopedic implant, not an AI/algorithm-based diagnostic aid.

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

    • Not applicable/Available. This is not an AI/algorithm device.

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

    • Ground Truth for Mechanical Testing: The "ground truth" for the mechanical tests (Static Testing per ASTM F543 and Static and Dynamic Cantilever Testing per ASTM F2193) would be defined by the standard specifications and performance requirements outlined in those ASTM standards and the performance of the predicate devices. These are engineering standards measuring physical properties.

    8. The sample size for the training set

    • Not applicable/Available. This device does not involve a "training set" in the context of machine learning.

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

    • Not applicable/Available. This device does not involve a machine learning training set or ground truth establishment in that sense.

    Summary of what the document does describe:

    The document focuses on establishing substantial equivalence for the AIS Odontoid Fracture Fixation System to predicate devices through non-clinical performance testing (mechanical testing). The acceptance criteria for these tests were that the subject device "meets or exceeds the performance of the predicate devices" when evaluated according to ASTM F543 (Static Testing) and ASTM F2193 (Static and Dynamic Cantilever Testing). The results showed that this criterion was met. This approach is standard for demonstrating the safety and effectiveness of a physical implant by ensuring it performs mechanically at least as well as existing, cleared devices.

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