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510(k) Data Aggregation

    K Number
    K220593
    Date Cleared
    2022-05-27

    (87 days)

    Product Code
    Regulation Number
    882.4560
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Spine Guidance Software, Stryker Q Guidance System

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

    The Stryker Q Guidance System, when used with the Spine Guidance software, is intended as a planning and intraoperative guidance system to enable open or percutaneous computer assisted surgery in adult and pediatric (adolescent) patients.
    The system is indicated for any surgical procedure on the spine in which the use of computer assisted planning and surgery may be appropriate. The system can be used for intraoperative guidance where a reference to a rigid anatomical structure such as the spine, pelvis or skull can be identified.
    The system assists in the positioning of instruments for procedures on the spine and pelvis, including:

    • Screw Placement in the spine or pelvis

    The Q Guidance System is intended as an aid for precisely locating anatomical structures in open or percutaneous computer assisted surgery. The system is indicated for any medical condition in which the use of computer assisted planning and surgery may be appropriate and where reference to a rigid anatomical structure such as the skull, vertebra, or long bone can be identified.

    Device Description

    The Stryker Q Guidance System with Spine Guidance 4.0 Software system is a computer-assisted stereotaxic, image-guided, planning, and intraoperative guidance system intended to enable open or percutaneous computer-assisted surgery. It assists the surgeon in precisely positioning instruments and locating patient anatomy during spinal surgery.
    The Q Guidance System with Spine Guidance 4.0 Software system is comprised of a computer platform, Spine Guidance Software, navigated accessories/ instruments (e.g., patient/ instrument trackers, pointers), and various system components (i.e. Calibration Body, Registration Pointer, etc.). The system provides intraoperative guidance to the surgeon using passive and active wireless optical tracking technologies. The computer platform consists of a computer, camera, big touchscreen monitor, and a small touchscreen monitor.
    The Spine Guidance 4.0 Software is dedicated to spine surgical procedures as defined in the indications for use. Required navigated instruments include a patient tracker, an instrument tracker, pointers, etc. An instrument battery is required when a battery powered instrument or calibration device is used.
    The Spine Guidance 4.0 Software displays the intraoperative location of navigated surgical instruments relative to imported patient medical images via wireless optical tracking technology. The software provides the functions to perform the indicated navigated spine surgical procedures. The software guides the user through the necessary preoperative and intraoperative steps required to set-up and perform the navigated spine surgical procedures.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and the study details for the Spine Guidance Software and Q Guidance System, based on the provided document:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria (Required Performance)Reported Device Performance
    Mean accuracy of 2 mm for positional displacement and 2° for trajectory angle displacement within the working space.Mean Positional Displacement: 1.32 mm
    Mean Trajectory Angle Displacement: 0.73°
    95th percentile of positional displacement ≤ 3 mm within the registration zone.95% Confidence Interval (Upper) Positional Displacement: 2.60 mm
    95th percentile of angular axis displacement ≤ 3° within the registration zone.95% Confidence Interval (Upper) Trajectory Angle Displacement: 1.78°
    Effectiveness of all risk controls.All risk controls successfully verified; no new safety/effectiveness issues raised.
    Compliance with design specifications for all components.All requirements met; no new safety/effectiveness issues raised.
    Software verification and validation (IEC 62304 and FDA guidance).All requirements met; no new safety/effectiveness issues raised.
    Biocompatibility (ISO 10993-1:2018 and FDA guidance).All requirements met; no new safety/effectiveness issues raised.
    Electrical Safety (IEC 60601-1).Conformance to IEC 60601-1:2012 Reprint.
    Electromagnetic Compatibility (IEC 60601-1-2:2014, CISPR 11 Group 1, Class A, and RFID compatibility).Conformance to IEC 60601-1-2:2014, CISPR 11 Group 1, Class A, and RFID compatibility verified.
    Functionality after simulated shipping conditions.Functionality verified; no new safety/effectiveness issues raised.
    Reusable devices achieve a sterility assurance level (SAL) of 10-6 or greater after steam sterilization.All requirements met; no new safety/effectiveness issues raised.
    User needs and intended use requirements met as validated with intended users in cadaver labs or simulated use tests.All requirements met; no new issues of safety or effectiveness were raised.

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

    The document does not explicitly state the numerical sample size for the accuracy test. It mentions that the system was validated "in cadaver labs or simulated use tests," implying a test set. This suggests a retrospective or simulated prospective setting, as it's not a live clinical trial. The country of origin of this data is not specified in the provided text.

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

    The document does not specify the number of experts used or their qualifications for establishing ground truth in the context of the accuracy testing. It only mentions validation with "intended users."

    4. Adjudication Method for the Test Set

    The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for the test set.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

    No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The document explicitly states: "No clinical testing was performed."

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    The primary performance data provided (positional and angular displacement accuracy) appears to be a standalone (algorithm only) performance evaluation, measuring the system's inherent ability to track and guide without the variable of direct human interpretation influencing the core accuracy metric. The "Intended Use/User Needs" validation involved "intended users in cadaver labs or simulated use tests," which likely involved human interaction with the device, but the core accuracy metrics are stated as system capabilities.

    7. The Type of Ground Truth Used

    For the accuracy criteria (positional and angular displacement), the ground truth would likely be established by highly precise measurement tools and methods (e.g., coordinate measuring machines, optical tracking systems with higher precision than the device itself, or physical phantoms with known dimensions) rather than direct expert consensus on an image. For the "Intended Use/User Needs" validation, the ground truth would be based on the successful performance of the intended surgical tasks as evaluated by the "intended users" in the simulated environments.

    8. The Sample Size for the Training Set

    The document does not specify the sample size for the training set.

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

    The document does not provide information on how the ground truth for any potential training set was established. Given that this is a surgical navigation system, rather than an AI/ML diagnostic algorithm relying on image interpretation, the concept of a "training set" in the traditional sense for diagnostic AI may not directly apply. The system is calibrated and validated against known physical parameters and simulation standards, rather than being "trained" on a dataset of labeled medical images to learn patterns.

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