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510(k) Data Aggregation

    K Number
    K231515
    Date Cleared
    2023-12-07

    (196 days)

    Product Code
    Regulation Number
    888.3075
    Reference & Predicate Devices
    Why did this record match?
    Product Code :

    QSD

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

    MySpine Cervical is intended to be used with any 510(k) cleared, legally marketed, posterior cervical screw system (for its cleared indications for use) and its respective compatible components for cervical posterior spinal fixation procedures intended for fusion. MySpine Cervical guides are patient specific devices intended to be used as anatomical perforating quides, specific to a single patient's anatomy, to assist intra-operatively in the positioning of screws during posterior cervical fixation surgery between the levels of C2 to C7.

    For pedicle diameters equal or less than ø4mm. Medacta provides for the pilot hole preparation into the lateral mass without penetrating the pedicle.

    The use of the guides involves a surgical planning software, with which the surgeon preoperatively plans the surgical placement of the implants based upon the radiological images of the patients' anatomical landmarks and the selected surgical equipment. These components include patientspecific guides fabricated based on the surgical plan to precisely reference the placement of the implant components intra-operatively per the surgical plan. MySpine Cervical guides are intended for single use only.

    Device Description

    MySpine Cervical guides are patient specific devices intended to be used as anatomical perforating guides, specific to a single patient's anatomy, to assist intra-operatively in the positioning of screws during posterior cervical fixation surgery between the levels of C2 to C7.

    The MySpine software platform allows the surgeon to complete 3D pre-operative planning based on the patient's spinal CT scans. CT images are used to create a 3D model of the vertebrae that will represent the template used to generate the corresponding MySpine Cervical Guide fitting the patient's vertebral anatomy.

    The MySpine Cervical Guides as well as their bone models are single-use and they can be provided in sterile or non-sterile version.

    AI/ML Overview

    The provided text is a 510(k) summary for the MySpine Cervical Guides. It primarily focuses on demonstrating substantial equivalence to a predicate device rather than detailing an acceptance criteria study. Therefore, much of the requested information about device performance against acceptance criteria, sample sizes for test and training sets, expert qualifications, and ground truth establishment is not present in this document.

    However, based on the Performance Data section, we can infer some information about validation and the type of studies conducted.

    Here's a breakdown of the available and missing information:

    1. Table of Acceptance Criteria and Reported Device Performance

    This information is not explicitly provided in the document. The document states that "Design Validation workshops... were conducted... to validate the design and the overall functionality of the subject device as well as to evaluate their accuracy." It also mentions "MySpine Cervical stability assessment to evaluate the stability of the subject lateral mass guides." However, specific numerical acceptance criteria and the corresponding reported performance values from these validation activities are not detailed.

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

    This information is not explicitly provided. The document states that "Two validation workshops, one for the unilateral and the other for the mass lateral guides, have been performed." It does not specify the number of cases or subjects included in these workshops, nor the country of origin or whether the data was retrospective or prospective.

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

    This information is not explicitly provided. While "Design Validation workshops" imply expert involvement, the number of experts and their qualifications are not mentioned.

    4. Adjudication Method for the Test Set

    This information is not provided.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

    This type of study was not explicitly conducted or reported. The document focuses on design validation and stability assessment, not a comparative effectiveness study with human readers.

    6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

    The device described is a physical surgical guide generated by software (MySpine software platform). The validation activities mentioned ("Design Validation workshops" and "stability assessment") seem to relate to the physical guides and their interaction (functionality, accuracy, stability), rather than a standalone assessment of the software algorithm's performance independent of the physical guide or human surgeon. So, a standalone algorithm-only performance study in the typical sense of AI algorithms detecting pathologies is not applicable/not reported for this type of device. The accuracy evaluation would likely be for the guide's ability to direct screw placement as planned.

    7. The Type of Ground Truth Used

    The document mentions that the surgical planning software uses "radiological images of the patients' anatomical landmarks" to create a "3D model of the vertebrae." The guides are "patient-specific guides fabricated based on the surgical plan." The "accuracy" of the guides was evaluated. It is highly probable that the ground truth for evaluating the accuracy of the guides would involve comparing the intended screw placement (from the surgical plan) with the actual placement achieved using the guide, potentially through post-operative imaging or cadaveric studies. However, the exact type of ground truth (e.g., expert consensus on optimal placement, direct measurement from a phantom/cadaver after guide use, pathology) is not explicitly stated.

    8. The Sample Size for the Training Set

    The document describes the device as a "patient-specific device" generated from a patient's CT scans. It does not mention a "training set" in the context of machine learning or AI models learning from a dataset. The MySpine software platform "allows the surgeon to complete 3D pre-operative planning based on the patient's spinal CT scans." This implies a custom generation for each patient rather than a model trained on a large dataset. Therefore, the concept of a "training set" as typically understood for AI algorithms is not applicable here.

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

    As the concept of a "training set" is not applicable, this information is not provided.

    Summary of Available Information from the Document:

    • Acceptance Criteria & Performance: Not explicitly stated, but "design validation workshops" focused on "overall functionality" and "accuracy," and a "stability assessment" were performed.
    • Study Type: Non-clinical studies (design validation workshops, stability assessment). No clinical studies were conducted.
    • Sample Size (Test Set): Not specified beyond "Two validation workshops."
    • Data Provenance (Test Set): Not specified.
    • Experts for Ground Truth: Implied by "validation workshops," but number and qualifications not specified.
    • Adjudication Method: Not specified.
    • MRMC Study: Not conducted.
    • Standalone Performance: Not applicable/not reported in the AI sense; validation likely involved the physical guides' performance.
    • Type of Ground Truth: Not explicitly stated, but likely related to comparing planned vs. actual screw placement using the guides.
    • Training Set Size: Not applicable.
    • Training Set Ground Truth: Not applicable.
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    K Number
    K220132
    Date Cleared
    2022-10-26

    (281 days)

    Product Code
    Regulation Number
    888.3075
    Reference & Predicate Devices
    Why did this record match?
    Product Code :

    QSD

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

    The FIREFLY® Cervical Navigation Guide system is intended to provide mechanical guidance for the preparation and drilling of pilot holes for the placement of posterior cervical spine (C1-C7) and the upper thoracic spine (T1-T3). Pilot holes are created using the FIREFLY® Cervical Navigation Guide in the pedicles (C2-T3), Pars (C2), or lateral masses (C1) during open, posterior spinal fixation procedures, on skeletally mature patients, that are intended for fusion. The patient's pedicles, pars, or lateral masses must be dimensionally adequate to safely accommodate a posterior cervical screw, as determined on a preoperative CT/CTA scan.

    The FIREFLY® Cervical Navigation Guide system is compatible with FDA cleared, legally marketed, posterior cervical screw systems (and their respective components) that are specified in the precautions. Pedicle sounding probes (a.k.a. feeler/ball-tip probes) may be used to confirm each pedicle's integrity. Only qualified compatible OEM posterior cervical screw system taps may be used to visually guide the tapping of pilot holes. All other posterior cervical screw system components and accessories (including non-visually guided taps) are to be used, after removal of the FIREFLY @ Cervical Navigation Guide, as directed by the posterior cervical screw system's instructions for use.

    The FIREFLY® Cervical Navigation Guide system is only compatible with consoles systems (attachments and burs) listed in the precautions.

    This system (guide, bone model, drill bit, and depth stop) are intended for single use only.

    Device Description

    The FIREFLY® Cervical Navigation Guide is intended to assist in the accurate placement of posterior cervical screws. It consists of single-use components designed for treatment of a specific patient.

    The FIREFLY® Cervical Navigation Guide uses Patient-Specific Cervical Guides that fit on the patient's anatomy to guide surgical instruments in line with trajectories chosen presurgically, by the surgeon, based on the patient's CT/CTA imaging data. Navigation guides are intended to guide instruments to create pilot holes in the pedicles (C2-T3), Pars (C2), or lateral masses (C1) for placing screws following the Approved Patient-Specific Surgical Plan.

    Patient-Specific Bone Models are also provided.

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for the FIREFLY® Cervical Navigation Guide. It outlines the device's indications for use, technological characteristics, and a summary of performance data from cadaveric accuracy testing.

    Here's the breakdown of the requested information based on the provided text:

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

    The document states that "Cadaveric accuracy testing of the FIREFLY® Cervical Navigation Guide was performed. The results demonstrated that the acceptance criteria were met and that the FIREFLY® Cervical Navigation Guide's performance is adequate to perform as intended." However, the specific quantitative acceptance criteria and the corresponding reported device performance values (e.g., accuracy in angle or translation) are not explicitly provided in the document.

    Therefore, the table cannot be fully constructed.

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

    • Sample Size: Not explicitly stated in the document. The text only mentions "Cadaveric accuracy testing." It does not specify the number of cadavers or the number of pilot holes tested.
    • Data Provenance: The study was "Cadaveric accuracy testing." The country of origin is not specified, and it is a type of prospective study on cadavers.

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

    • Number of Experts: Not explicitly stated.
    • Qualifications of Experts: Not explicitly stated.

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

    • Adjudication Method: Not explicitly stated.

    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 involving human readers and AI assistance was not conducted or described. The device is a "Cervical Navigation Guide" which provides mechanical guidance for instrument placement. It is not an AI-assisted diagnostic or interpretation tool for human readers but rather a surgical guidance tool.

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

    • This question is less directly applicable to a mechanical surgical navigation guide. The "performance" described is the accuracy of the guide itself in directing instruments. Since it's a mechanical guide, its function is inherently "standalone" in guiding the physical instrument, although a human surgeon is always "in the loop" operating the instruments through the guide. The cadaveric testing assesses the mechanical accuracy of the guide as intended.

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

    • For the cadaveric accuracy testing, the ground truth would typically be established by highly precise measurements of the actual pilot hole trajectory and depth in relation to the pre-surgically planned trajectory, often using imaging (e.g., post-procedure CT scans) and/or metrology. The document does not specify the exact method for ground truth establishment.

    8. The sample size for the training set

    • The document describes a cadaveric performance study, not a machine learning model that relies on a training set. Therefore, this question is not applicable.

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

    • As this is not a machine learning device, this question is not applicable.
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