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510(k) Data Aggregation

    K Number
    K072090
    Date Cleared
    2007-09-14

    (46 days)

    Product Code
    Regulation Number
    892.1550
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    SIEMENS DIAGNOSTIC ULTRASOUND SYSTEMS

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

    The Siemens ultrasound imaging systems are intended for the following applications: General Radiology, Fetal, Abdominal, Intraoperative, Pediatric, Small Parts, Neonatal/Adult Cephalic, Cardiac, Transesophageal, Pelvic, Transcranial, OB/GYN, Urology, Vascular, Musculoskeletal, Superficial Musculoskeletal, and Peripheral Vascular applications.

    The systems also provide for the measurement of anatomical structures and for analysis packages that provide information that is used for clinical diagnosis purposes.

    Device Description

    The modified software features provide for the measurement of anatomical structures and for analysis packages that provide information that is used for clinical diagnosis purposes.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and study information based on the provided text for K072090:

    Note: The provided text is a 510(k) summary and FDA clearance letter. It is highly limited in the specific details of performance data and study methodologies. Much of the requested information (e.g., sample sizes, ground truth establishment, expert qualifications, MRMC studies, standalone performance details) is NOT present in this document. The document primarily states that testing was done and deemed sufficient for clearance, without providing the raw results or detailed methodology.


    1. Table of Acceptance Criteria and Reported Device Performance

    The provided 510(k) summary does not explicitly state specific acceptance criteria or quantitative performance metrics for Auto Ejection Fraction (Auto EF) or Velocity Vector Imaging (VVI). It broadly states that the modifications were "verified and validated according to the company's design control process." This implies that internal acceptance criteria were met, but these criteria and the specific results are not disclosed in this public summary.

    Therefore, the table cannot be fully completed from the provided text.

    Performance MetricAcceptance CriteriaReported Device Performance
    Auto Ejection Fraction (Auto EF)Not specified in documentNot specified in document
    Velocity Vector Imaging (VVI)Not specified in documentNot specified in document

    2. Sample Size and Data Provenance

    • Sample size for the test set: Not specified in the document.
    • Data provenance: Not specified in the document. (e.g., country of origin, retrospective or prospective)

    3. Number of Experts and Qualifications for Ground Truth

    • Number of experts: Not specified in the document.
    • Qualifications of experts: Not specified in the document.

    4. Adjudication Method

    • Adjudication method: Not specified in the document.

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

    • Was an MRMC study done? Not mentioned in the document. The document focuses on the device performance verification and validation, not a comparative human reader study.
    • Effect size of human readers improving with AI vs. without AI: Not applicable, as no MRMC study details are provided.

    6. Standalone (Algorithm Only) Performance Study

    • Was a standalone study done? The document states "The Auto Ejection Fraction (Auto EF) and Velocity Vector Imaging (VVI) Clinical Applications modifications are verified and validated according to the company's design control process." This generally implies standalone testing of the algorithm's performance against some form of ground truth or benchmark, but no specific metrics or methodology for standalone performance are provided.

    7. Type of Ground Truth Used

    • Type of ground truth: Not specified in the document. It is implied that some form of "clinical diagnosis purposes" data would be used, but the exact nature (e.g., expert consensus, comparison to a gold standard modality, pathology, outcomes data) is not detailed.

    8. Sample Size for the Training Set

    • Sample size for the training set: Not specified in the document. This document describes verification and validation of modifications, not the initial development or training process of the algorithms.

    9. How Ground Truth for the Training Set Was Established

    • How ground truth was established: Not specified in the document, as this document focuses on the verification and validation of modifications and does not delve into the initial training data or its ground truth establishment.
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