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510(k) Data Aggregation

    K Number
    K053463
    Manufacturer
    Date Cleared
    2006-03-07

    (84 days)

    Product Code
    Regulation Number
    892.1570
    Reference & Predicate Devices
    N/A
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Accuracy In Marking® is a marking device used in conjunction with a transducer during vascular mapping. The device allows the user to mark a vascular area immediately when it is identified during mapping process. The guide path underneath the transducer allows the user to identify the target vessel prior to marking. The product is supplied non-sterile and is intended for single use only.

    Device Description

    The marking device is enables the sonographer to mark the "targeted" vessel during vascular mapping. The shadow guide is an adhesive "film" adhered directly underneath the footing of the transducer used as guide on identifying the vessel. The marking device and the "shadow guide" are attached to a transducer using a non-latex adhesive. The device shall be sold non-sterile for single use only. This device is compatible with FDA approved linear and curved linear ultrasonic transducers in the frequency of 4MHz to 12MHz.

    AI/ML Overview

    The provided 510(k) submission for the "AiM Accuracy In Marking® System" (K053463) does not contain a detailed study report with specific acceptance criteria and performance data in the format typically required for advanced AI/ML medical devices.

    Instead, the submission focuses on demonstrating substantial equivalence to a predicate device (Sandel Medical Industries, LLC Skin Marker) based on similarities in function (skin marking) and the simplicity of the "shadow guide" component. The primary "test data" mentioned is to demonstrate that the safety and effectiveness of the transducer's function is not affected by the shadow guide.

    Therefore, many of the requested elements for describing acceptance criteria and study details cannot be extracted from this document. However, I can infer what information would be relevant if such a study were present, and provide the limited details available.

    Based on the provided document, here's an attempt to answer your questions:

    1. A table of acceptance criteria and the reported device performance

    • Acceptance Criteria: The document does not explicitly state quantitative acceptance criteria for the "AiM Accuracy In Marking® System." The primary "acceptance" seems to be based on demonstrating that the shadow guide does not adversely affect the safety and effectiveness of the existing ultrasound transducer function, rather than achieving a specific performance metric for aiding vessel marking. The core claim is that its function is "beneficial on identifying the target vessel."
    • Reported Device Performance: The document only makes a qualitative statement: "the simplicity of the design as well as test data demonstrates that safety and effectiveness of the function of the transducer is not affected by the shadow guide. The shadow guide's function is beneficial on identifying the target vessel during vascular mapping."
    Performance MetricAcceptance Criteria (Implied/Inferred)Reported Device Performance (Qualitative)
    Transducer SafetyNo adverse effect on transducer operation"safety...of the function of the transducer is not affected by the shadow guide"
    Transducer EffectivenessNo adverse effect on transducer operation"effectiveness of the function of the transducer is not affected by the shadow guide"
    Vessel Identification AidAid in identifying target vessels"The shadow guide's function is beneficial on identifying the target vessel during vascular mapping." and "allows the user to identify the target vessel prior to marking."

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Sample Size: Not specified. The document refers generally to "test data," but does not provide any numerical sample size for cases or participants.
    • Data Provenance: Not specified. While the applicant's address is in California, USA, the origin of any "test data" (e.g., country, institution) is not mentioned.
    • Retrospective or Prospective: Not specified.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    • Number of Experts: Not specified.
    • Qualifications of Experts: Not specified. The document does not detail how "ground truth" for beneficial vessel identification was established or if any expert evaluation was involved beyond general statements.

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

    • Adjudication Method: Not specified. Given the lack of detail on the "test data," no adjudication method is described.

    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

    • MRMC Study: No, an MRMC comparative effectiveness study was not described or referenced. This device is a passive marking accessory, not an AI/ML algorithm requiring a human-in-the-loop performance evaluation in the typical sense.
    • Effect Size: Not applicable, as no MRMC study was presented.

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

    • Standalone Performance: Not applicable. This device is a physical accessory (shadow guide and marker), not a standalone algorithm. Its function is to be used with a human sonographer and ultrasound transducer.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

    • Type of Ground Truth: Not explicitly stated. Based on the description, the "ground truth" for the device's function (identifying target vessels) would likely be based on the sonographer's visual confirmation of the vessel on the ultrasound image and their ability to accurately mark it based on the guide. However, the exact method for establishing this is not detailed in the submission.

    8. The sample size for the training set

    • Sample Size for Training Set: Not applicable. This is a physical accessory, not an AI/ML device that requires a training set.

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

    • Ground Truth for Training Set: Not applicable. This is a physical accessory, not an AI/ML device.

    Summary Limitations:

    The provided 510(k) summary is for a relatively simple accessory device. The requirements for demonstrating substantial equivalence for such devices are often less stringent regarding quantitative performance studies compared to complex AI/ML algorithms. The focus here is on demonstrating that the accessory does not impair the functionality or safety of the primary device (ultrasound transducer) and that its stated purpose (aiding identification and marking) is met in a general sense, without specific numerical performance targets or detailed study methodology being disclosed in this summary.

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