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510(k) Data Aggregation

    K Number
    K151511
    Device Name
    ROSA Spine
    Manufacturer
    Date Cleared
    2016-01-04

    (214 days)

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

    ROSA Spine

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

    The device is intended for the spatial positioning and orientation of instrument holders or tool guides to be used by surgeons to guide standard neurosurgical instruments during spine surgery. Guidance is based on an intra-operative plan developed with three dimensional imaging software provided that the required markers and rigid patient anatomy can be identified on 3D CT scans. The device is indicated for the placement of pedicle serews in lumbar vertebrae with a posterior approach

    Device Description

    ROSA Spine is a computer controlled electromechanical arm providing guidance of neurosurgical instruments during spinal surgery.

    ROSA Spine assists the surgeon in planning the position of instruments relative to intraoperative images.

    Adequate position of the instrument holder is obtained from three-dimensional calculations performed from desired surgical planning parameters and registration of spatial position of the patient.

    ROSA Spine provides a stable, accurate and reproducible mechanical guidance of neurosurgical instruments in accordance with an intraoperative planning.

    AI/ML Overview

    While the provided document is a 510(k) premarket notification for the ROSA Spine device, it primarily focuses on establishing substantial equivalence to predicate devices rather than detailing a specific clinical study with detailed acceptance criteria and ground truth establishment for a diagnostic or AI-driven medical device. The ROSA Spine is described as a computer-controlled electromechanical arm for surgical guidance, not a device that makes diagnoses or predictions based on medical images in the way an AI algorithm might.

    Therefore, many of the requested details, particularly those related to "AI improvement," "multi-reader multi-case studies," "ground truth establishment," and "training sets" are not applicable or explicitly stated for this type of surgical guidance system's 510(k) submission.

    However, I can extract the relevant performance data and address the questions to the best of my ability based on the provided text, making it clear where the information is not present or not applicable.

    Here's an attempt to answer your questions based on the provided document:


    Device: ROSA Spine (a computer-controlled electromechanical arm for spinal surgical guidance)

    1. Acceptance Criteria and Reported Device Performance

    The document does not explicitly present these as "acceptance criteria" in a formal table with pre-defined thresholds the way an AI or diagnostic device might. However, it does provide performance metrics tested and reported for the device and its predicates. I will interpret "acceptance criteria" as the performance levels achieved that demonstrate equivalence and safety/effectiveness for this type of device.

    Performance MetricAcceptance Criteria (or equivalent reported predicate performance)Reported Device Performance (ROSA Spine)
    Robot Absolute Accuracy
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