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510(k) Data Aggregation

    K Number
    K181783
    Manufacturer
    Date Cleared
    2018-09-20

    (79 days)

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

    LOGIQ P9; LOGIQ P7

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

    The device is intended for use by a qualified physician for ultrasound evaluation of Fetal; Abdominal; Pediatric; Small Organ (breast, testes, thyroid); Neonatal Cephalic; Adult Cephalic; Cardiac (adult and pediatric); Peripheral Vascular; Musculo-skeletal Conventional and Superficial; Urology (including prostate); Transrectal; Transvaginal; Transesophageal and Intraoperative (abdominal, thoracic, vascular).
    When Pinpoint™ GT Technology, from C.R. Bard, Inc., is included with the system, the Indications for Use include: Pinpoint GT Technology is intended to provide clinicians with visual tools for passive magnetic tracking of a needle with respect to ultrasound image data.

    Device Description

    The LOGIQ P9; LOGIQ P7 is a full featured, general purpose diagnostic ultrasound system which consists of a mobile console approximately 53 cm wide, 74 cm deep and 157 cm high that provides digital acquisition, processing and display capability. The user interface includes a computer keyboard, specialized controls, 10.4 inch LCD touch screen and color 21.5 inch LCD image display.

    AI/ML Overview

    This document is a 510(k) Premarket Notification from GE Healthcare for their LOGIQ P9 and LOGIQ P7 diagnostic ultrasound systems. It primarily focuses on demonstrating substantial equivalence to previously cleared predicate devices, rather than presenting a de novo clinical study with detailed performance metrics against specific acceptance criteria. Therefore, the information typically found in an AI/Software as a Medical Device (SaMD) study for performance reporting (such as ROC curves, sensitivity/specificity, sample sizes for test/training sets, or expert ground truth adjudication) is not present.

    However, based on the provided text, we can infer and extracting relevant safety and effectiveness information as follows:

    1. Table of Acceptance Criteria (Inferred from Compliance and Testing) and Reported Device Performance

    Acceptance Criteria (Inferred)Reported Device Performance and Compliance
    Safety and Effectiveness (General Equivalence)The LOGIQ P9; LOGIQ P7 systems are substantially equivalent to predicate devices with regard to intended use, imaging capabilities, technological characteristics, safety, and effectiveness.
    Clinical Intended UsesThe LOGIQ P9; LOGIQ P7 systems have the same clinical intended uses as their predicate devices, with the addition of Transesophageal exams. The device is intended for use for ultrasound evaluation of Fetal; Abdominal; Pediatric; Small Organ; Neonatal Cephalic; Adult Cephalic; Cardiac (adult and pediatric); Peripheral Vascular; Musculo-skeletal Conventional and Superficial; Urology (including prostate); Transrectal; Transvaginal; Transesophageal and Intraoperative (abdominal, thoracic, vascular).
    Imaging ModesThe LOGIQ P9; LOGIQ P7 systems have the same imaging modes as their predicate devices, except for the addition of Shear wave elastography (migrated from LOGIQ S8) and enhancement of B-flow/B-flow color mode with high definition color. HDlive®, Tricefy, and LOGIQ P Apps features have also been migrated from other GE Ultrasound systems.
    Transducer CompatibilityTransducers are identical to predicate devices, with the addition of L3-12-RS, 6Tc-RS, P2D, and IC9-RS transducers.
    BiocompatibilityManufactured with materials evaluated and found to be safe; transducer materials and patient contact materials are biocompatible.
    Acoustic Output LevelsAcoustic power levels are below applicable FDA limits and conform to NEMA UD 2 (2004).
    Electrical, Electromagnetic, and Mechanical SafetyDesigned in compliance with approved electrical and physical safety standards, including AAMI/ANSI ES60601-1, IEC60601-1-2, and IEC60601-2-37.
    Risk ManagementApplication of risk management to medical devices (ISO14971:2007).
    Measurements, Digital Imaging, Reviewing, and ReportingSimilar capability to predicate devices for performing measurements, capturing digital images, reviewing, and reporting studies. Can recall non-ultrasound DICOM images.
    Compliance with FDA Ultrasound Specific GuidanceComplies with "Guidance for Industry and FDA Staff - Information for manufacturers Seeking Marketing Clearance of Diagnostic Ultrasound Systems and Transducers (September 9, 2008)".
    Quality Assurance MeasuresRisk Analysis, Requirements Reviews, Design Reviews, Testing on unit level (Module verification), Integration testing (System verification), Performance testing (Verification), Safety testing (Verification).

    2. Sample Sizes and Data Provenance for Test Set

    The document explicitly states: "The subject of this premarket submission, LOGIQ P9; LOGIQ P7, did not require clinical studies to support substantial equivalence."

    This means there wasn't a separate "test set" in the context of a prospective clinical trial or performance study against pre-defined metrics. The submission relies on bench testing, compliance with standards, and comparison to predicate devices to demonstrate substantial equivalence, rather than a clinical performance study with patient data.

    • Sample Size for Test Set: Not applicable as a clinical test set was not used for this 510(k) submission.
    • Data Provenance: Not applicable for clinical performance data. The data provenance discussed is related to compliance with engineering standards and existing clearances for predicate and reference devices (e.g., K163596, K170445, K160162, K173555).

    3. Number of Experts and Qualifications for Ground Truth for the Test Set

    • Not applicable, as a clinical test set requiring expert ground truth establishment for a performance study was not performed. The evaluation relies on technical performance and safety testing, and substantial equivalence to existing devices cleared through other means.

    4. Adjudication Method for the Test Set

    • Not applicable, as a clinical test set requiring adjudication was not utilized.

    5. MRMC Comparative Effectiveness Study

    • Not applicable. This submission is for a diagnostic ultrasound system, not an AI or imaging assistance device that would typically undergo an MRMC study to show human reader improvement with AI assistance. The focus is on the device's inherent safety and performance for imaging.

    6. Standalone Performance (Algorithm Only)

    • Not applicable in the context of an "algorithm only" performance typical for AI/SaMD. The device itself is an ultrasound imaging system. Its performance relates to its ability to generate diagnostic ultrasound images and fluid flow analysis, which is demonstrated through engineering and safety evaluations and comparison to predicate devices.
      • While new features like "Shear wave elastography" involve processing, their performance is demonstrated via technical validation and substantial equivalence, not a standalone algorithm efficacy study in the typical AI sense.

    7. Type of Ground Truth Used

    • Not applicable in the sense of 'ground truth' defined by expert consensus or pathology for a clinical performance study. The "ground truth" here is compliance with established engineering and safety standards, and the capabilities of the already cleared predicate devices.

    8. Sample Size for the Training Set

    • Not applicable. This is a hardware/software system, and the submission does not describe a machine learning model that was "trained" on a dataset in the way an AI/SaMD product would be. The "training" here refers to the device's design and engineering based on established physics and medical imaging principles.

    9. How the Ground Truth for the Training Set was Established

    • Not applicable, as no external "training set" with established ground truth was utilized for a machine learning model. The device's design and functionality are based on long-standing principles of ultrasound imaging and adherence to regulatory standards.
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    K Number
    K143452
    Manufacturer
    Date Cleared
    2015-01-29

    (58 days)

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

    LOGIQ P9, LOGIQ P7

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

    The device is intended for use by a qualified physician for ultrasound evaluation of Fetal; Abdominal; Pediatric; Small Organ (breast, testes, thyroid); Neonatal Cephalic; Cardiac (adult and pediatric); Peripheral Vascular; Musculo-skeletal Conventional and Superficial; Urology (including prostate); Transvaginal; and Intraoperative (abdominal, thoracic, vascular).

    Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows: Fetal / Obstetrics; Abdominal; Pediatric; Small Organ; Neonatal Cephalic; Adult Cephalic; Cardiac Adult & Pediatric; Peripheral Vascular; Musculo-skeletal Conventional; Musculo-skeletal Superficial; Other (Urology/Prostate); Transrectal; Transvaginal; Intraoperative.

    Device Description

    The LOGIQ P9 and LOGIQ P7 is a full featured, general purpose diagnostic ultrasound system which consists of a mobile console approximately 53 cm wide, 69 cm deep and 157 cm high that provides digital acquisition, processing and display capability. The user interface includes a computer keyboard, specialized controls, 10.4-inch LCD touch screen and color 21.5-inch LCD image display.

    AI/ML Overview

    This document is a 510(k) Premarket Notification Submission for the GE LOGIQ P9 and LOGIQ P7 ultrasound systems. It does not contain information about an AI/ML device or its performance criteria. Instead, it describes a conventional diagnostic ultrasound system and its equivalence to predicate devices, focusing on regulatory compliance and safety standards.

    Therefore, I cannot provide a response based on the requested information regarding acceptance criteria and study details for an AI/ML device.

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