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510(k) Data Aggregation

    K Number
    K150249
    Date Cleared
    2015-03-04

    (29 days)

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

    ZONARE's ZS3 Ultrasound System K120703, ZONARE'S ZS3 & z.one.proUltrasound System K141641

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

    The ZS3 and z.one PRO Ultrasound Systems are intended for use by a qualified physician for ultrasound evaluation of Ophthalmic; Fetal/obstetric, gynecological; Abdominal (renal, GYN/Pelvic; Intra-operative (abdominal, thoracic, and vascular), Intra-operative neurological: Pediatric: small organ (thyroid, breast, testes, etc), Adult & Neonatal Cephalic; Trans-rectal, Trans-vaginal, Trans-cranial, Trans-esophageal (non-cardiac and cardiac); Musculosketal (conventional & superficial); 3D/4D; Cardiac - Adult/ Pediatric/ Fetal; Echo, Intra-Cardiac; Pelvic; Peripheral vascular; harmonic tissue and contrast imaging and Tissue elasticity.

    Device Description

    The ZS3 and z.onews Ultrasound Systems (hereafter referred to as "ZS3 Ultrasound Platform" or "ZS3" for simplicity) are full-featured, general purpose, software controlled, diagnostic ultrasound systems used to acquire and display high-resolution, real-time ultrasound data through multiple imaging modes. The platform utilizes ZONARE's patented zone technology which allows the system to collect more data at one time, thereby optimizing image quality.

    The exam dependent default settings for the ZS3 allows the user to have minimum adjustment for imaging the patient, while the in depth soft-menu control enables the advanced user to set the system based on image appearance preference. The architecture of the ZS3 Ultrasound Platform supports system integration to a variety of upgradable options and features. Up to three ZONARE transducers can be connected to the multi-transducer port permitting easy transducer transition. The ZS3 Ultrasound Platform can be operated on either battery or AC power.

    AI/ML Overview

    This document describes the ZS3 and z.onepro Ultrasound Systems and their transducers, stating they are substantially equivalent to previously cleared devices. It does not contain information about acceptance criteria or a study proving the device meets those criteria from an AI performance perspective, as it is a 510(k) submission for an ultrasound system, not an AI/ML device.

    However, I can extract information related to the general device performance and testing completed to ensure its safety and effectiveness, which serves as a form of acceptance criteria for a medical device regulatory submission.

    Here's a summary of the non-clinical testing performed for the ZS3 and z.onepro Ultrasound Systems, which implicitly demonstrates their compliance with established standards:

    1. Table of Acceptance Criteria and Reported Device Performance:

    Since this is a 510(k) submission for an ultrasound system, the "acceptance criteria" are embodied by compliance with recognized medical device standards and the device performance specifications as demonstrated through non-clinical testing. The "device performance" refers to the system passing these tests.

    Acceptance Criteria (Test)Reported Device Performance (Result)
    Mechanical VerificationPASS
    Electrical Safety (IEC 60601-1)PASS
    EMC Testing (IEC 60601-1-2)PASS
    Thermal and Acoustic Output (IEC 60601-2-37)PASS
    Biocompatibility (ISO 10993)PASS
    Cleaning & Disinfection (FDA Guidance)PASS
    Software Validation & Verification (62304 & FDA Guidance)PASS

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

    This document describes non-clinical testing of a hardware and software system, not an AI/ML algorithm that processes a "test set" of patient data. Therefore, the concept of "sample size for the test set" and "data provenance" in the context of clinical data does not apply here. The testing was carried out through standard engineering and laboratory methods on the physical device and its software.

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

    This is not applicable as the submission concerns a physical medical device (ultrasound system) and its compliance with engineering and safety standards, not the diagnostic accuracy of an AI algorithm evaluated against expert consensus. The "ground truth" for these tests are the established standards and specifications themselves.

    4. Adjudication method for the test set:

    Not applicable for a non-clinical device safety and performance evaluation.

    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:

    Not applicable. This is a submission for an ultrasound system, not an AI-assisted diagnostic tool. No MRMC study or AI performance evaluation is mentioned.

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

    Not applicable as this is a medical device (ultrasound system) submission and not an AI algorithm.

    7. The type of ground truth used:

    For the non-clinical testing described, the "ground truth" is defined by:

    • Engineering specifications and device performance requirements: These are internal standards set by the manufacturer for the device's functionality.
    • International and national standards: Such as IEC 60601-1, IEC 60601-1-2, IEC 60601-2-37, ISO 10993, and EN 62304.
    • FDA Guidance Documents: For cleaning & disinfection and software validation.

    8. The sample size for the training set:

    Not applicable as this is not an AI/ML algorithm requiring a training set.

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

    Not applicable as this is not an AI/ML algorithm requiring a training set.

    In summary, this document relates to the regulatory clearance of an ultrasound imaging system as a medical device. The "acceptance criteria" are compliance with established safety, performance, and manufacturing standards, demonstrated through rigorous non-clinical engineering and biological testing. It does not pertain to the performance evaluation of an AI algorithm.

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