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510(k) Data Aggregation

    K Number
    K053086
    Manufacturer
    Date Cleared
    2006-01-27

    (86 days)

    Product Code
    Regulation Number
    892.1200
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    MIE - GAMMA CAMERA SYSTEMS

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

    The MIE - Gamma Camera Systems for nuclear medicine, are used to perform static, dynamic and gated studies, as well as spect or planar procedure, on standing, seated or recumbent patients

    Device Description

    All MiE remanufactured Gamma Camera System have 3 functional units equivalent to the Siemens or GE Gamma Camera Systems. The modification to the SIEMENS- or GE-Gamma Camera System consisted of removal of certain low voltage cicuit boards in the gamma Camera and the gantry portions of the Siemens – or GE Gamma Camera System and installing proprietary low voltage circuit board that allow the use of our SCINTRON Computer and its software. All MIE Gamma Camera Systems consist of the same detector unit that is in use in the Siemens- or GE Gamma Camera System. The mechanical units (camera head with its supporting beam) hold the detector and make sure it can be moved around or along the patient for the optimal diagnostic procedure. The only difference to the basic SIEMENS or GE Gamma Camera system consists in our own imaging and processing software SCINTRON (already cleared by the FDA, K953193).

    AI/ML Overview

    This document describes a 510(k) premarket notification for MIE Gamma Camera Systems. The core of the submission is to demonstrate substantial equivalence to predicate devices (Siemens and GE Gamma Camera Systems), rather than proving the device meets specific acceptance criteria through a standalone study with a defined ground truth and expert review.

    Therefore, providing the exact requested information (acceptance criteria table, sample sizes, expert qualifications, adjudication methods, MRMC study details, etc.) is not directly applicable in the way it would be for a novel AI/CAD device.

    However, I can extract and infer information relevant to the spirit of your request:

    1. A table of "Acceptance Criteria" and the Reported Device Performance (Inferred from Substantial Equivalence Claim)

    Acceptance Criteria (Inferred from Substantial Equivalence)Reported Device Performance
    Indications for Use: Same as predicate devices"The MIE remanufactured Gamma Camera Systems have the same indications for use and target population as the predicate devices." (Page 2)
    Target Population: Same as predicate devices"The MIE remanufactured Gamma Camera Systems have the same indications for use and target population as the predicate devices." (Page 2)
    Diagnostic Effect: No differences from predicate devices"There are no differences regarding the diagnostic effect." (Page 2)
    Technological Characteristics: Same as predicate devices"The MIE remanufactured devices have the same technological characteristics as the basic SIEMENS or GE Devices." (Page 2)
    Technical Data/Specifications: Achieve same as predicate devices"The technical data's and specifications in Annex 1 show that the MIE remanufactured Gamma Camera System achieve the same technical data's as the basic SIEMENS or GE Gamma Camera systems." (Page 2)
    Electrical Safety: Compliance demonstrated"Performance testing addressed the following issues: Electrical safety." (Page 3)
    Electromagnetic Compatibility (EMC): Compliance demonstrated"Performance testing addressed the following issues: Electromagnetic compatibility." (Page 3)
    NEMA Performance Standards: Compliance demonstrated"Performance testing addressed the following issues: NEMA Performance standards." (Page 3)

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

    • Sample Size: Not applicable in the context of this 510(k). The submission relies on demonstrating that the remanufactured device, by using the same detector and mechanical units as the predicate devices and replacing only specific low-voltage circuit boards and implementing their own software (SCINTRON, already cleared), maintains the predicate's performance. There isn't a "test set" of patient data used in the typical sense for evaluating a diagnostic algorithm.
    • Data Provenance: Not specified, as it's not a study involving patient data collection for performance evaluation. The "data" refers to technical specifications and compliance with standards.

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

    • Not applicable. This submission is not based on expert-derived ground truth from a diagnostic imaging dataset. The "ground truth" here is the established performance and safety of the predicate devices.

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

    • Not applicable. No diagnostic test set requiring adjudication was used.

    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 MRMC study was conducted. This device is a remanufactured gamma camera system, not an AI or CAD software intended to assist human readers.

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

    • Not applicable. The device is a gamma camera system, not a standalone algorithm. Its software (SCINTRON) was previously cleared (K953193), suggesting its standalone function was assessed at that time, but the details are not part of this submission. This submission focuses on the system with the remanufactured components.

    7. The type of ground truth used:

    • The "ground truth" in this context is the established performance, safety, and technological characteristics of the legally marketed predicate devices (Siemens and GE Gamma Camera Systems). The MIE Gamma Camera System is claiming to perform equivalently by maintaining the core components and adhering to relevant standards.

    8. The sample size for the training set:

    • Not applicable. This is not a machine learning or AI device that requires a training set.

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

    • Not applicable, as there is no training set for an algorithm.
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