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510(k) Data Aggregation

    K Number
    K192653
    Device Name
    Perseus
    Date Cleared
    2020-09-09

    (351 days)

    Product Code
    Regulation Number
    882.4560
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    PERSEUS is a computer-controlled system, intended to assist in distal femoral resection and tibial resection during Total Knee Arthroplasty, determining reference alignment axes in relation to anatomical and instrumentation structures during stereotaxic orthopaedic surgical procedures.

    Device Description

    PERSEUS is a computer assisted system, that helps surgeon in the positioning of implant components, during total knee implant surgical procedure, according to the conventional reference axes in relation to anatomical landmarks. Perseus System is configured to detect, measure, and display angular and positional measurement changes in a triaxial format. The device assists the surgeon in: Establishing the mechanical axis of the femur, determining the varus/valgus angle and the flexion/extension angle of the cutting block relative to the femur. Establishing the mechanical axis of the tibia, determining the varus/valgus angle and the posterior slope angle of the cutting block relative to the tibia. Perseus system utilizes triaxial accelerometer and triaxial gyroscope to determine, through limb movement, reference axes of femur and tibia and relative orientation of distal femoral and tibial cutting guide with respect to frontal and sagittal planes of the limb.

    AI/ML Overview

    Here's a detailed breakdown of the acceptance criteria and the studies proving the device's performance, based on the provided text:

    Acceptance Criteria and Device Performance

    1. Table of Acceptance Criteria and Reported Device Performance

    MeasureAcceptance CriteriaReported Device Performance
    HKA (Hip-Knee-Ankle) angle deviationwithin 3° (for final leg alignment)Average post-operative HKA angle deviation: 0.3 ± 1.5°
    Average post-operative HKA alignment deviation: 0.7° (range 0-2°)
    Femoral distal resection deviationwithin 2° (for distal femoral resection, frontal and lateral planes)Femoral distal resection deviation: < 2° (frontal and lateral planes)
    Femoral implant flexionNot explicitly statedAverage femoral implant flexion: 0.8 ± 0.8°
    Tibial slopeNot explicitly statedAverage tibial slope: 0.1 ± 1.7°
    Blood lossReduced blood loss compared to conventional techniqueConfirmed reduced blood loss compared to conventional technique

    2. Sample Sizes Used for Test Sets and Data Provenance

    The document mentions several studies, primarily clinical evaluations. The provenance is Europe (aftermarket clinical evaluation). All studies appear to be prospective clinical evaluations or retrospective analysis of post-operative data.

    • Study 1 (Aftermarket Clinical Evaluation - Europe):
      • Test Set Sample Size: 3 cohorts of 10 patients each (total 30 patients)
        • EM Perseus: 10 patients
        • EM Nav: 10 patients (surgical navigation system)
        • IM Conv: 10 patients (conventional mechanical instrumentations)
      • Data Provenance: Europe (aftermarket clinical evaluation), the specific country is not mentioned. Data is from patients operated by the same surgical team.
    • Study 2 (Aftermarket Clinical Evaluation - Europe):
      • Test Set Sample Size: 2 cohorts of 18 patients each (total 36 patients)
        • Perseus: 18 patients
        • Conventional instrumentation: 18 patients
      • Data Provenance: Europe, multicentric study involving two centers.
    • Study 3 (Aftermarket Clinical Evaluation - Europe):
      • Test Set Sample Size: Single cohort of 20 patients.
      • Data Provenance: Europe.
    • Study 4 (Retrospective analysis of post-operative X-rays):
      • Test Set Sample Size: 20 cases.
      • Data Provenance: Not explicitly stated, but likely from European clinical practice given the context of aftermarket clinical evaluations.
    • Study 5 (Retrospective analysis of post-operative X-rays):
      • Test Set Sample Size: 53 patients operated with Perseus vs. 52 patients operated with conventional technique (total 105 patients).
      • Data Provenance: Not explicitly stated, but likely from European clinical practice.

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

    The document does not specify the number of experts, their qualifications, or their role in establishing ground truth for the test sets (patient data). It mentions that "Clinical evaluation has been done with the same performance requirement when possible or, in alternative, looking at final leg alignment with post-operative x-rays." This suggests that the ground truth for clinical outcomes like HKA angle, femoral implant flexion, and tibial slope was derived from post-operative X-rays, which are generally interpreted by qualified medical professionals (e.g., orthopedic surgeons or radiologists), but the specific details are not provided.

    4. Adjudication Method for the Test Set

    The document does not explicitly describe an adjudication method (like 2+1 or 3+1) for the clinical outcomes or the interpretation of post-operative X-rays. The analysis of X-rays for angular deviations is likely based on standard radiographic measurement techniques.

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

    No multi-reader multi-case (MRMC) comparative effectiveness study is explicitly described. The clinical studies compare patient outcomes (e.g., HKA alignment, blood loss) between those treated with Perseus and those with conventional techniques or other navigation systems, not specifically focusing on how human readers improve with vs. without AI assistance in interpretation.

    6. Standalone (Algorithm Only) Performance Study

    Yes, standalone performance was evaluated through bench tests and pre-clinical evaluation testing:

    • Bench tests: Conducted to quantify device accuracy and repeatability. These involved controlled setups to verify:
      • Measurement repeatability with different cursor positions.
      • Error introduced by mispositioning of ankle instrumentation.
      • Repeatability with different sensors.
      • Repeatability with different instrument positioning.
    • Pre-clinical evaluation testing: Verified accuracy, repeatability, and reproducibility in a simulated OR setup and consistency of the procedure with different users/experience levels.

    These tests evaluate the algorithm and device's performance in a controlled environment, separate from human-in-the-loop clinical scenarios.

    7. Type of Ground Truth Used

    • Bench Tests & Pre-clinical Evaluation: Ground truth was established using controlled variables within appropriate test setups, likely using precise measurement tools, and simulated surgical scenarios with known desired outcomes.
    • Clinical Studies: The primary ground truth for measuring clinical outcomes (e.g., HKA angle, femoral distal resection deviation, tibial slope) was derived from post-operative X-rays. Blood loss was also measured as an outcome.

    8. Sample Size for the Training Set

    The document does not provide details on a specific "training set" for the PERSEUS device. PERSEUS is described as a "computer-controlled system" using inertial sensors and physical positions for positional information. While such systems are developed based on algorithms, the document focuses on the validation studies rather than the development phase's data sets. Therefore, the sample size for an explicit training set is not reported.

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

    Since no specific training set is mentioned in the document, the establishment of ground truth for a training set is not described. The device's operation, based on accelerometers and gyroscopes, suggests it relies on engineering principles and sensor data processing rather than learning from a labeled training dataset in the way a typical AI/ML system for image classification might. The "performance tests" and "bench tests" served to validate the system's accuracy against established physical measurement standards and simulated scenarios.

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