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510(k) Data Aggregation

    K Number
    K161584
    Date Cleared
    2016-10-06

    (120 days)

    Product Code
    Regulation Number
    870.1330
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    ASAHI**®** Peripheral Vascular Guide Wire ASAHI Meister**®**16

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

    ASAHI Peripheral Vascular Guide Wire is intended for use in the peripheral vasculature, to facilitate the exchange and placement of diagnostic and therapeutic devices such as vascular catheters during peripheral interventional procedures. This guide wire is not intended for use in coronary arteries, lower limb blood vessels, neurovasculature and carotid arteries.

    Device Description

    The ASAHI® Peripheral Vascular Guide Wire ASAHI Meister® 16 consists of a core wire and a coil assembly. The coil assembly consists of an inner coil and an outer coil, soldered to the core wire. The distal portion of the coil is radiopaque so as to easily confirm its position under radioscopy. In addition, coatings are applied on the surface of ASAHI® Peripheral Vascular Guide Wire ASAHI Meister® 16. The coil and taper core wire of ASAHI® Peripheral Vascular Guide Wire ASAHI Meister® 16 are coated with polyurethane and coated with a hydrophilic polymer upon the polyurethane coat. The distal portion of ASAHI® Peripheral Vascular Guide Wire ASAHI Meister® 16 is soft in order to easily bend in accordance with the vessel curve. The ASAHI® Peripheral Vascular Guide Wire ASAHI Meister® 16 is available in various lengths and tip shapes. Accessories such as a Torque device, Shaping device and Inserter are included in the packaging of the ASAHI® Peripheral Vascular Guide Wire ASAHI Meister® 16.

    AI/ML Overview

    This document is a 510(k) Summary for the ASAHI® Peripheral Vascular Guide Wire ASAHI Meister® 16, submitted by ASAHI INTECC CO., LTD. It focuses on demonstrating substantial equivalence to a predicate device, not on presenting novel acceptance criteria or a dedicated study for a new clinical indication.

    Therefore, many of the requested categories regarding acceptance criteria and study design for a new device or algorithm are not directly applicable or available in this document. This document describes the testing performed to show the new device is as safe and effective as a previously cleared device.

    Here's the information extracted and organized as requested, with notes where information is not applicable or present in the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document states that non-clinical laboratory testing was performed and that the device "met all acceptance criteria." However, it does not explicitly list the specific quantitative acceptance criteria for each test. Instead, it generally states that the device "performed similarly to the predicate devices" and "functions as intended."

    Test PerformedAcceptance Criteria (Not explicitly stated as quantitative thresholds in the document)Reported Device Performance
    Tensile StrengthPerformed similarly to predicate devicesMet all acceptance criteria / Performed similarly to predicate devices
    Torque StrengthPerformed similarly to predicate devicesMet all acceptance criteria / Performed similarly to predicate devices
    TorqueabilityPerformed similarly to predicate devicesMet all acceptance criteria / Performed similarly to predicate devices
    Tip FlexibilityPerformed similarly to predicate devicesMet all acceptance criteria / Performed similarly to predicate devices
    Coating Adhesion/IntegrityPerformed similarly to predicate devicesMet all acceptance criteria / Performed similarly to predicate devices
    Catheter CompatibilityPerformed similarly to predicate devicesMet all acceptance criteria / Performed similarly to predicate devices
    BiocompatibilitySimilar to predicate/reference devices (for all endpoints except complement activation)Met all acceptance criteria / Leveraged from predicate/reference devices

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

    The document mentions "non clinical laboratory testing" and "in vitro bench tests." These are likely physical tests on device samples. The sample size for these tests is not specified in the provided text. The data provenance is laboratory testing (bench tests). There is no mention of patient data (country of origin, retrospective/prospective) as this is a physical device equivalence submission, not a clinical study of an AI/software device.

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

    This information is not applicable to this type of device submission. Ground truth for physical device performance is typically established through standardized testing methods, not expert human assessment in the way it's used for AI diagnostic tools.

    4. Adjudication method for the test set

    This information is not applicable as there are no expert readers or interpretations for physical bench testing outcomes.

    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

    This information is not applicable. This document describes a physical medical device (guide wire), not an AI algorithm, and therefore, an MRMC study or AI assistance is irrelevant.

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

    This information is not applicable as this is a physical medical device, not an algorithm.

    7. The type of ground truth used

    For the non-clinical testing, the "ground truth" would be established by objective measurements and predefined pass/fail criteria based on engineering specifications and comparison to the predicate device's established performance, rather than expert consensus, pathology, or outcomes data.

    8. The sample size for the training set

    This information is not applicable as this document does not describe an AI/ML algorithm that requires a training set.

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

    This information is not applicable as this document does not describe an AI/ML algorithm that requires a training set.

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