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510(k) Data Aggregation

    K Number
    K230088
    Manufacturer
    Date Cleared
    2024-03-21

    (434 days)

    Product Code
    Regulation Number
    888.3020
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K211388

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

    The 4WEB Medical Ankle Truss System (ATS) is for use as an accessory to the Stryker T2 Ankle Arthrodesis Nail or the Stryker Valor Hindfoot Fusion Nail as part of a tibiotalocalcaneal fusion construct in a salvage procedure following failed ankle arthrodesis or failed ankle arthroplasty for patients at risk for loss of limb. The ATS is not intended for standalone use.

    The anatomical landmarks necessary for the design and creation of ATS devices that are patient matched must be present and identifiable on appropriate radiography scans. The ATS is intended for use with autograft and/or allogenic bone graft comprised of cancellous and/or corticocancellous bone graft.

    Device Description

    The 4WEB Medical Ankle Truss System (ATS) is a permanently implanted device intended to provide mechanical support as an accessory to a tibiotalocalcaneal nail intended to fuse the tibiotalocalcaneal joint in a salvage procedure following a failed ankle arthrodesis or a failed ankle arthroplasty for patients at risk for loss of limb. ATS devices are titanium alloy (Ti6Al4V) structures in spherical or cuboidal configurations. The ATS device has an open architecture truss designed to provide structural support with open space throughout the implant to allow fusion. ATS devices are intended for use with the Stryker T2 Ankle Arthrodesis Nail or the Stryker Valor Hindfoot Fusion Nail as part of a tibiotalocalcaneal (TTC) fusion system.

    AI/ML Overview

    The provided FDA 510(k) summary (K230088) for the Ankle Truss System (ATS) does not contain the detailed information necessary to fully answer all aspects of your request regarding acceptance criteria and a study proving device conformance. The document primarily focuses on demonstrating substantial equivalence to predicate devices based on non-clinical and limited clinical performance evaluations.

    Here's a breakdown of what can be extracted and what is missing, based on the provided text:

    Device: Ankle Truss System (ATS) (K230088)

    1. Table of acceptance criteria and the reported device performance

    The document does not explicitly state specific acceptance criteria in a quantitative or tabular format for the device's performance. It mentions "Effectiveness endpoints included fusion, pain, and functional outcomes for the subject and control treatments" in the clinical evaluation section, but it does not provide target values or thresholds for these. Similarly, for non-clinical testing, it lists the types of tests performed (ASTM F2077, ASTM F1264, Corrosion, Wear) but doesn't detail the acceptance criteria or the reported device performance against those criteria.

    2. Sample size used for the test set and the data provenance

    • Sample Size: The document mentions a "retrospective, single arm, multi-center evaluation of the ATS device" but does not specify the sample size (number of patients enrolled or number of ATS devices evaluated) in this clinical study.
    • Data Provenance: The study was a "retrospective, single arm, multi-center evaluation." The country of origin is not specified, but given the FDA submission, it's highly probable the centers are within the United States.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    This information is not provided in the document. The study design does not appear to involve expert-driven ground truth establishment in the way typically seen for diagnostic AI or imaging devices. The "effectiveness endpoints" (fusion, pain, functional outcomes) and "safety outcomes" (adverse events, SSSI rates) would typically be gathered from patient records, imaging reports, and clinical assessments, rather than a panel of experts specifically establishing a "ground truth" for each case in the test set.

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

    This information is not provided and is generally not applicable to the type of clinical evaluation described for an implantable device assessing outcomes like fusion, pain, and functional improvement. Adjudication methods like 2+1 or 3+1 are more common in studies evaluating reader performance for diagnostic tasks where ground truth might be ambiguous or require expert consensus.

    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

    • MRMC Study: No, an MRMC comparative effectiveness study was not performed. This type of study is relevant for evaluating the impact of AI on human reader performance, particularly in diagnostic imaging. The ATS is an implantable device, not an AI diagnostic tool.
    • Effect Size: Therefore, effect size related to human reader improvement with AI assistance is not applicable and not provided.

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

    • Standalone Performance: No, a standalone performance evaluation of an algorithm was not performed. The ATS is a physical implantable device, not an AI algorithm.

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

    For the clinical evaluation, the "ground truth" or primary data used to assess effectiveness and safety were likely derived from:

    • Outcomes Data: "fusion, pain, and functional outcomes" derived from patient follow-up, clinical assessments, and potentially imaging (to assess fusion).
    • Adverse Event Data: "device and procedure related adverse events and rates of subsequent secondary surgical intervention (SSSI)" derived from patient medical records.

    8. The sample size for the training set

    This is not applicable as the ATS is a physical implant, not a machine learning model that requires a training set in the conventional sense. The "design and creation of ATS devices that are patient matched" suggests that individual devices might be tailored, but this is a design process, not an AI training process.

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

    This is not applicable for the same reasons as #8.

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    K Number
    K221283
    Manufacturer
    Date Cleared
    2022-09-06

    (126 days)

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

    K172392, K211388

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

    The HTS is indicated for the fixation of osteotomies and reconstruction of the lesser toes following correction procedures for hammertoe, claw toe, and mallet toe. Cannulated implants in the HTS can be used with K-wires for the delivery of implants or the temporary stabilization of outlying joints (e.g. MTP Joint).

    Device Description

    The 4WEB HTS implants consists of a series of titanium implants that are designed to provide stability and fixation of the lesser toes in the foot. The 4WEB HTS implants have proximal and distal fixation features to provide structural support and will be offered in multiple sizes to accommodate various patients' anatomy. The implants are manufactured from Ti6Al4V alloy. Each implant is available in a sterile/packaged form.

    AI/ML Overview

    This document is a 510(k) summary for the Hammertoe Truss System (HTS). It indicates that the purpose of the submission is to update the HTS implant offering to include two smaller sizes. The document outlines the device description, indications for use, and a comparison to predicate devices, focusing on the mechanical properties and MRI compatibility.

    Here's an analysis based on your request, keeping in mind that the document mainly focuses on mechanical performance and equivalence to a predicate device, rather than a clinical study with patients or human readers.

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

    Acceptance CriteriaReported Device Performance
    Mechanical Properties:
    Finite element analysis: No new worst-case implant compared to previously cleared devices.Validated finite element analysis demonstrated that the additional implant sizes for the Hammertoe Truss System (HTS) do not create a new worst-case implant compared to the previously cleared 4WEB Hammertoe Truss System devices for mechanical properties of the device.
    ASTM F1264: Static and Dynamic 3-Point Bend and Torque to FailurePerformance completed per this standard (specific values not provided but implied to meet acceptance for substantial equivalence).
    ASTM F543: Axial Push OutPerformance completed per this standard (specific values not provided but implied to meet acceptance for substantial equivalence).
    MR Conditional Testing (based on reference predicate):
    ASTM F2119: MR Image ArtifactHammertoe Truss System does not present a new worst case compared to the reference predicate which met this standard.
    ASTM F2052: MR Induced Displacement ForceHammertoe Truss System does not present a new worst case compared to the reference predicate which met this standard.
    ASTM F2213: MR Induced TorqueHammertoe Truss System does not present a new worst case compared to the reference predicate which met this standard.
    ASTM F2182: MR Induced HeatingHammertoe Truss System does not present a new worst case compared to the reference predicate which met this standard.

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

    This submission describes engineering performance testing and simulation analysis, not a clinical study on a test set of patient data. Therefore, the concepts of "sample size for the test set" and "data provenance" in a clinical context are not applicable. The testing was done on physical device prototypes or through computer-simulated models.

    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 is not applicable as the submission reports on mechanical and MRI compatibility testing of a physical device, not a diagnostic or AI-driven system requiring expert review of medical images.

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

    This is not applicable. Adjudication methods are relevant for studies involving human interpretation of data, typically in clinical trials or diagnostic accuracy studies.

    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

    No, a multi-reader, multi-case (MRMC) comparative effectiveness study was not done. This submission focuses on the safety and effectiveness of a physical implantable device based on mechanical and MRI compatibility testing, demonstrating substantial equivalence to a predicate device. It does not involve AI or human readers.

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

    No, a standalone algorithm performance study was not done. This submission is for a physical medical device (implant).

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

    The "ground truth" for this type of submission is based on engineering standards and established test methods (e.g., ASTM standards) for evaluating the mechanical properties and MRI compatibility of medical implants. The "truth" is whether the device physically performs in accordance with these validated standards and demonstrates similar characteristics to the predicate device.

    8. The sample size for the training set

    This is not applicable. The device is a physical implant, not an AI or machine learning model that requires a training set. The "training" for such devices involves design, manufacturing, and extensive bench testing.

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

    This is not applicable for the reasons mentioned in point 8.

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    K Number
    K220463
    Manufacturer
    Date Cleared
    2022-05-18

    (90 days)

    Product Code
    Regulation Number
    888.3030
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K211388

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

    The Osteotomy Truss System (OTS) is intended to be used for internal bone fractures or osteotomies in the foot, such as:

    • · Opening wedge osteotomies of the foot including osteotomies for Hallux Valgus
    • · Opening wedge of Medial Cuneiform or Cotton osteotomies
    • · Lateral Column Lengthening (Evans Lengthening Osteotomy or Calcaneal Z Osteotomy)
    • · Metatarsal/Cuneiform osteotomies
    • · Nonunion of arthrodesis of the Midfoot including Metatarsal/Cuneiform osteotomies (TMT or Lapidus)
    • · Hindfoot osteotomies
      The device is intended for use with supplemental fixation. The Osteotomy Truss System is not intended for use in the spine.
    Device Description

    The Osteotomy Truss System (OTS) consists of three implant designs in a variety of footprints and opening wedge height options to accommodate the patient's anatomy. It is intended to be used with supplemental fixations.
    The device is an open architecture truss design mathematically formulated to provide structural support with open space throughout the implant for bone growth and fusion. The 4WEB additive manufacturing process provides a hierarchical surface roughness. The implant is made from Ti6Al4V alloy.

    AI/ML Overview

    This 510(k) premarket notification describes a design update to an existing device, the Osteotomy Truss System (OTS). The submission focuses on demonstrating substantial equivalence to the predicate devices through non-clinical performance testing. Therefore, it does not involve clinical studies or in-depth performance metrics typically associated with AI/ML devices.

    Here's an analysis based on the provided text, focusing on the available information:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria (Standard Reference)Reported Device Performance (Summary)
    Static axial compression (ASTM F2077)Sufficient for intended use
    Dynamic axial compression fatigue (ASTM F2077)Sufficient for intended use
    Expulsion testing (ASTM F-04.25.02.02)Sufficient for intended use
    MR image artifact (ASTM F2119)Sufficient for intended use
    MR induced heating (ASTM F2182)Sufficient for intended use
    MR induced torque (ASTM F2213)Sufficient for intended use
    MR induced displacement force (ASTM F2052)Sufficient for intended use
    Finite element analysisDoes not introduce a new worst-case compared to previously cleared devices for mechanical properties.

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

    This submission relies on non-clinical performance testing (in vitro/bench testing and computational modeling). The document does not specify a "test set" in the context of patient data or clinical imaging. The tests were performed on the device itself and its components. Therefore, information regarding human data provenance (country of origin, retrospective/prospective) is not applicable.

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

    Not applicable. The ground truth for the non-clinical performance testing is established by the specifications defined in the referenced ASTM standards and engineering principles for finite element analysis.

    4. Adjudication Method for the Test Set

    Not applicable. This is not a study involving human interpretation of data where adjudication would be necessary.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    No, a multi-reader multi-case (MRMC) comparative effectiveness study was not conducted. This is a submission for a medical device (implant) and not an AI/ML-driven diagnostic or assistive tool.

    6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

    No, a standalone performance study in the context of an algorithm or AI was not conducted. The device itself is the subject of the testing.

    7. Type of Ground Truth Used

    The ground truth used for this submission is based on:

    • Established engineering standards: ASTM standards for mechanical testing and MR compatibility.
    • Computational modeling results: Finite element analysis, which provides simulated performance data.
    • Predicate device characteristics: The substantially equivalent performance to previously cleared predicate devices serves as the benchmark.

    8. Sample Size for the Training Set

    Not applicable. There is no mention of a "training set" as this is not an AI/ML device or a study involving machine learning.

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

    Not applicable, as there is no training set involved.

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