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510(k) Data Aggregation

    K Number
    K172732
    Device Name
    E-CUBE 8
    Date Cleared
    2017-12-14

    (94 days)

    Product Code
    Regulation Number
    892.1550
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The device is intended for use by a qualified physician for the evaluation of soft tissue and blood flow in the clinical applications; Fetal; Abdominal (renal & GYN/pelvic); Pediatric, Small Organ (breast, testes, thyroid); Neonatal Cephalic, Adult Cephalic; Trans-rectal, Trans-vaginal, Musculo-skeletal (Conventional); Musculo-skeletal (Superficial); Cardiac (adult& pediatric); Peripheral Vascular (PV); and Urology (including prostate).

    Device Description

    E-CUBE 8 product is an ultrasound imaging system for medical diagnosis. This innovative system platform provides optimal patient diagnosis workflow with the wide flat panel display, ergonomic control panel with easy user interface, optimal image quality.

    AI/ML Overview

    Here's an analysis of the acceptance criteria and study information for the ALPINION MEDICAL SYSTEMS Co., Ltd. E-CUBE 8 ultrasound system, based on the provided text:

    Important Note: The provided document is a 510(k) Premarket Notification from the FDA for a medical ultrasound system. It primarily focuses on demonstrating "substantial equivalence" to existing predicate devices, not on proving that the device meets specific acceptance criteria through a clinical study in the way an AI/ML device might. Therefore, many of the requested data points (like sample size for test sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance with ground truth, and training set details) are not applicable or not provided in this type of regulatory document for a general ultrasound system. The "studies" mentioned are largely non-clinical engineering and safety compliance tests.


    Acceptance Criteria and Reported Device Performance

    The acceptance criteria for the E-CUBE 8 are primarily related to its equivalency with predicate devices regarding Indications for Use, Imaging Modes, Imaging Functions, and adherence to established safety and performance standards. The reported device performance is that it meets these criteria by incorporating similar or improved features and by complying with relevant medical device standards.

    Acceptance Criteria CategorySpecific Criterion (Example for one transducer/mode)Reported Device Performance (E-CUBE 8)
    Indications for UseFetal, Abdominal, Pediatric, Small Organ, Neonatal Cephalic, Adult Cephalic, Trans-rectal, Trans-vaginal, Musculo-skeletal (Conventional & Superficial), Cardiac (adult & pediatric), Peripheral Vessel, Urology (including prostate) (Across various transducers)The device supports all listed clinical applications as "new indication" (N) or "previously cleared" (P) for each transducer (e.g., Fetal, Abdominal, Pediatric, Musculo-skeletal, Urology for C1-6CT) The entire system comprehensively covers all indications through the combination of its various transducers.
    Imaging ModesB mode, M mode, PWD, CWD, Color Doppler, Power Doppler, Tissue Harmonic Imaging, Combined, 3D/4D (across various transducers)All listed imaging modes are supported by the E-CUBE 8 system and its compatible transducers. (e.g., C1-6CT supports B/M/PWD/Color Doppler/Power Doppler/Tissue Harmonic Imaging/Combined).
    Imaging FunctionsXpeed™, Full SRI™, Spatial Compounding Image (SCI), Frequency Compounding Image (FCI), Panoramic, Stress Echo, Cube Strain™, Live HQ ™, Needle Vision™ / Needle Vision™ Plus, Elastography, Cube view™, Free Angle MSV, AnySlice™, Volume AnalysisAll listed imaging functions are supported, matching or exceeding features found in predicate devices. For instance, Xpeed™, Full SRI™, SCI, FCI, Panoramic, Stress Echo, Cube Strain™, Live HQ™, Needle Vision™/Needle Vision™ Plus, Cube view™, Free Angle MSV, AnySlice™, Volume Analysis are all supported. Elastography is also included.
    Safety and Performance StandardsConformance to IEC 60601-1, IEC 60601-1-2, IEC 60601-2-37, AAMI/ANSI/ISO10993-1, AAMI/ANSI/ISO14971, AIUM Medical Ultrasound Safety, NEMA UD2, NEMA UD3E-CUBE 8 was found to conform to all applicable medical device safety, electromagnetic compatibility, acoustic output, and biological evaluation standards.

    Study Information

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

      • N/A. The document does not describe a "test set" in the context of a dataset used for performance evaluation (e.g., for an AI/ML algorithm). The "testing" involved non-clinical validation against engineering specifications and industry standards.
      • Data Provenance: Not applicable in the context of device performance testing. The provenance of regulatory compliance data is the manufacturing and testing environment of ALPINION Medical Systems Co., Ltd., based in the Republic of Korea.
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

      • N/A. This information is not relevant or provided for a general ultrasound system's 510(k) submission. "Ground truth" in this context would primarily relate to the accuracy of physical measurements and image quality, which are assessed through engineering tests rather than expert interpretation of a diagnostic dataset.
    3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

      • N/A. No adjudication method for a test set is mentioned, as there isn't a diagnostic performance study described that would require it.
    4. 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. An MRMC comparative effectiveness study was not performed or referenced. This document is for a traditional ultrasound imaging system, not an AI-assisted diagnostic device.
    5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

      • No. This device is a diagnostic ultrasound system intended for use by a qualified physician. Its performance is inherent to the imaging capabilities and is not evaluated as a standalone algorithm without human intervention.
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

      • N/A. For this type of submission, "ground truth" refers to the established engineering specifications, physical laws, and recognized standards against which the device's technical performance (e.g., acoustic output, image resolution, measurement accuracy) is validated. It does not involve medical ground truth from patient data like pathology or outcomes.
    7. The sample size for the training set:

      • N/A. This device does not use a "training set" in the context of machine learning. Its functionality is based on established ultrasound physics and engineering design.
    8. How the ground truth for the training set was established:

      • N/A. Not applicable, as there is no training set for this device.
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