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510(k) Data Aggregation

    K Number
    K121109
    Device Name
    AERODR X70
    Manufacturer
    KONICA MINOLTA MEDICAL & GRAPHIC, INC.
    Date Cleared
    2012-05-23

    (41 days)

    Product Code
    KPR
    Regulation Number
    892.1680
    Type
    Traditional
    Panel
    Radiology
    Reference & Predicate Devices
    K073632
    Why did this record match?
    Device Name :

    AERODR X70

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

    AeroDR X70 is a stationary x-ray system intended for obtaining radiographic images of various portions of the human body in a clinical environment. The AeroDR X70 is not intended for mammography

    Device Description

    The AeroDR X70 is a stationary x-ray system with a ceiling mounted tube support, a floor mounted table and wall stand. The image receptor and the image receptor holder is placed in the table or the wall stand. The ceiling stand and the table are motorized for up and down movements, all other movements are manually operated. The standard equipment includes a graphic display showing X-ray tube rotation and film focus or source image distance, a generator control console and an Image system console.

    AI/ML Overview

    Here's an analysis of the provided text regarding the acceptance criteria and the study that proves the device meets them:

    1. Table of Acceptance Criteria and Reported Device Performance

    Based on the provided text, the device (AeroDR X70 Stationary X-ray System) is a conventional X-ray system, not an AI-powered device. Therefore, the "acceptance criteria" and "device performance" described primarily relate to safety and equivalency to a predicate device, rather than specific diagnostic performance metrics (like sensitivity, specificity, or AUC) that would be relevant for an AI-enabled diagnostic tool.

    The "acceptance criteria" can be inferred from the standards the device meets to demonstrate safety and substantial equivalence.

    Acceptance Criteria (Inferred)Reported Device Performance and Evidence
    Safety and Electrical Requirements: Conformance to relevant medical electrical equipment safety standards.Evidence: The device meets several IEC standards (IEC 60601-1, IEC 60601-1-2, IEC 60601-1-3, IEC 60601-1-4, IEC 60601-2-7, IEC 60601-2-28, IEC 60601-2-32) and NEMA XR7 regarding general safety, electromagnetic compatibility, radiation protection, programmable electrical medical systems, high-voltage generators, X-ray source assembly, and associated equipment. "The same scope of testing has been preformed by certification body."
    Equivalent Imaging Capability: Ability to produce radiographic images of various portions of the human body, equivalent to the predicate device.Evidence: "The provided performance data demonstrate that the imaging system in the AeroDR X70 system is substantially equivalent to the predicated device with reqards to the capability of producing radiographic images of various portions of the human body."
    "AeroDR X70 digital image system...have the same imaging principle, physical characteristic and Intended use" as the predicate device.
    Intended Use: Consistent with obtaining radiographic images of various human body portions, excluding mammography.Evidence: "AeroDR X70 is a stationary x-ray system intended for obtaining radiographic images of various portions of the human body in a clinical environment. The AeroDR X70 is not intended for mammography." This matches the predicate device's intended use.
    Functional Equivalence: Similar mechanical and operational characteristics compared to the predicate device.Evidence: "The AeroDR X70 is basically the same product as the predicate device Intuition." Both have motorized ceiling stand and table, manual operation for other movements. Wallstand modifications are noted but considered equivalent functionality (e.g., magnetic vs. manual brake release).

    Based on the provided document, the device described is a conventional X-ray system, not an AI-powered device. Therefore, the following sections about AI-specific study details (sample sizes, ground truth establishment, expert adjudication, MRMC studies, standalone performance) are not applicable to this submission. The "study" here refers to the testing and comparison performed to demonstrate substantial equivalence to a predicate conventional X-ray system.

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

    • Not applicable for an AI device.
    • For this conventional X-ray system, the "test set" would refer to the tests performed against the safety and performance standards listed (IEC, NEMA). The document does not specify a "sample size" in terms of patient data or images used for testing, as it's not a diagnostic AI algorithm. The testing focused on hardware performance and safety.
    • Data Provenance: Not specified as it's not a data-driven AI device.

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

    • Not applicable for an AI device.
    • For this conventional X-ray system, "ground truth" relates to compliance with engineering and safety standards, validated by accredited certification bodies. No medical experts are mentioned as establishing "ground truth" for the device's technical performance or safety tests.

    4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set

    • Not applicable for an AI device.
    • For the conventional X-ray system, the "adjudication" would involve technical verification against the standards by a certification body. The specific process (e.g., how disputes or interpretations during testing are resolved) is not detailed.

    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. Not applicable as this is a conventional X-ray system without AI.

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

    • No. Not applicable as this is a conventional X-ray system without an AI algorithm.

    7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

    • Not applicable for an AI device.
    • For the conventional X-ray system, the "ground truth" for demonstrating substantial equivalence is primarily based on:
      • Conformance to international safety and performance standards (IEC, NEMA).
      • Direct comparison of technical specifications and imaging principles with a legally marketed predicate device.
      • Performance data demonstrating the imaging system's capability to produce radiographic images, implicitly checked against expected image quality for general radiography.

    8. The Sample Size for the Training Set

    • Not applicable as this is a conventional X-ray system, not an AI model. There is no "training set" in the context of machine learning.

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

    • Not applicable as this is a conventional X-ray system, not an AI model.
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