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510(k) Data Aggregation

    K Number
    K172548
    Date Cleared
    2018-01-12

    (142 days)

    Product Code
    Regulation Number
    888.3070
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Wiltrom Spinal Fixation System is intended to provide immobilization of spinal segments in skeletally mature patients as an adjunct to fusion in the treatment of the following acute and chronic instabilities or deformities of the thoracic, lumbar, and sacral spine: severe spondylolisthesis (grades 3 and 4) of the L5-S1 vertebra; degenerative spondylolisthesis with objective evidence of neurologic impairment; fracture; scoliosis; kyphosis; spinal tumor; and failed previous fusion (pseudarthrosis).

    Device Description

    The Wiltrom Spinal Fixation System is comprised of screws, rods, cross-link connector and associated surgical instruments that allow the surgeon to build an implant system to fit the patient's anatomical and physiological requirements. The Wiltrom Spinal Fixation System is designed to be used to stabilize the vertebrae through a posterior approach. The Wiltrom spinal implants are made of Ti-6Al-4V ELI material which complies with ISO 5832-3 and ASTM F136. Wiltrom Spinal Fixation System is provided non-sterile, and the implants are for single use only.

    AI/ML Overview

    This document is a 510(k) premarket notification for a medical device called the Wiltrom Spinal Fixation System. It focuses on establishing substantial equivalence to a predicate device, the Fortex Pedicle Screw System (K090224). The information provided is primarily related to mechanical testing for safety and effectiveness, rather than a clinical study evaluating diagnostic or prognostic performance based on specific acceptance criteria for AI or algorithmic output. Therefore, many of the requested sections about AI/algorithm performance and ground truth establishment cannot be directly answered from this document.

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

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

    The document discusses mechanical testing criteria for the physical device, not for an AI or algorithm.

    Acceptance Criteria (Mechanical Testing)Reported Device Performance
    Static Torsion Testing (ASTM F1717-15)Conducted
    Static Axial Compression Bending Testing (ASTM F1717-15)Conducted
    Dynamic Axial Compression Bending Testing (ASTM F1717-15)Conducted
    Overall Goal: Evaluate safety and effectiveness, demonstrate performance in stabilizing the operative site, and mechanical safety.Overall Outcome: "The performance of Wiltrom spinal implants in stabilizing the operative site and the mechanical safety was demonstrated."

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

    This information is for mechanical testing of the physical device, not an AI test set. The sample size would refer to the number of implants/constructs tested. The document states "mechanical testing including static torsion testing, static and dynamic axial compression bending testing were conducted," but does not specify the number of samples for each test or the provenance of the data in the context of clinical or image 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. Ground truth, in this context, would relate to the physical integrity and performance of the device under stress, measured through engineering standards, not expert evaluation of clinical data.

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

    Not applicable. Adjudication methods are typically for clinical or imaging studies where expert consensus is needed. The testing here is mechanical.

    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 not a study involving human readers or AI assistance.

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

    Not applicable. This document does not describe an AI algorithm.

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

    For mechanical testing, the "ground truth" would be established by the engineering standards themselves (e.g., ASTM F1717-15) and the objective measurements of force, deformation, and failure points taken during the tests.

    8. The sample size for the training set

    Not applicable. This document does not pertain to the development of an AI algorithm with a training set.

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

    Not applicable. This document does not pertain to the development of an AI algorithm with a training set.

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