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510(k) Data Aggregation

    K Number
    K182908
    Manufacturer
    Date Cleared
    2019-07-18

    (274 days)

    Product Code
    Regulation Number
    872.3640
    Panel
    Dental
    Why did this record match?
    Device Name :

    Ziacom Dental Implant Systems

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

    Ziacom Dental Implant Systems are intended to be surgically placed in the bone of the mandibular or maxillary jaw arches to provide support for prosthetic devices, such as artificial teeth, in order to restore the patient's chewing function and to aid in prosthetic rehabilitation. Ziacom Dental Implant Abutments are intended to be used with Ziacom Dental Implants to aid in prosthetic rehabilitation.
    The intended use for Ziacom Dental Implant Zinic® NP 3.30mm diameter is limited to replacement of mandibular incisors.

    Device Description

    Zinic® and Zinic MT implants are threaded, self-tapping, root-form dental implants manufactured from CP titanium Grade 4 conforming to ASTM F67 Standard Specification for Unalloyed Titanium for Surgical Implant Applications (UNS R50250, UNS R50400, UNS R50550, UNS R50700). The implants have apical flutes, an internal hexagonal abutment interface and a conical bevel at the abutment interface. They are threaded internally for attachment of mating abutments, cover screws, healing abutments or temporary abutments. The coronal portion of the implant has a microthread design. The Zinic design is a straight implant, while Zinic MT implants are tapered in the apical 40% of the implant length. All implants have a grit blasted and acid etched surface, designated Osseonova Surface.
    Implants and abutments with the same platform connection are compatible. Zinic and ZinicMT implants are available with following sizes: (Table of sizes provided in the document).
    Zinic and ZinicMT implants are provided sterile to the end-user in a single-unit package, and are for single-patient, single-use only. They are provided in ZPlus packaging or Z2Plus packaging, attached to the ZPlus or Z2Plus Mount, respectively, or in NoMount packaging, without an implant mount. Packaging facilitates the aseptic handling and placement of the implant, with the mounts also capable of serving either as a provisional abutment or a definitive abutment. Z2Plus also can serve as a transfer for a Snap-On impression technique.
    Subject device abutments include cover screws, healing abutments, provisional abutments, sculptable (prepable) abutments, conical abutments in straight and angled (15°, 25° and 30°) designs, castable abutments (CoCr base plus burn-out sleeve) in straight and angled (15°, 20°) designs, Basic and Unitary Basic abutments to serve as intermediate abutments between the implant and the prosthesis. XDrive multi-unit abutments in straight and angled (17°, 30°) designs.
    All subject device abutments have the universal internal implant connection and are compatible with both implant lines, except that NP abutments are compatible only with Zinic NP implants (there are no ZinicMT NP implants). Abutments are manufactured from Ti-6Al-4V alloy conforming to ASTM F136 Standard Specification for Wrought Titanium-6Aluminum-4Vanadium ELI (Extra Low Interstitial) Alloy for Surgical Implant Applications (UNS R56401), polyetheretherketone (PEEK) conforming to ASTM F2026 Standard Specification for Polyetheretherketone (PEEK) Polymers for Surgical Implant Applications or cobalt-chromium-molybdenum alloy conforming to ASTM F1537 Standard Specification for Wrought Cobalt-28-Chromium-6-Molybdenum Alloys for Surgical Implants (UNS R31537, UNS R31538, and UNS R31539).
    Subject device abutments include two overdenture abutments (Kirator,ZM-Equator). Kirator overdenture abutments are straight prosthetic abutments that are used for the retention of preexisting or newly fabricated full dentures (classified as implant-retained mucosupported overdentures). ZM-Equator abutments are straight prosthetic abutments used for the retention of tissue-supported implantretained prostheses. Its is indicated in rehabilitation of narrow ridges and/or reduced vertical dimension Each overdenture abutment is the "male" part of a removable prosthesis retention which contains a metal housing cap that incorporate plastic retention with different degrees of elastic retention. Abutments and housing caps are manufactured from Ti-6Al-4V alloy conforming to ASTM F136 Standard Specification for Wrought Titanium-6Aluminum-4Vanadium ELI (Extra Low Interstitial) Alloy for Surgical Implant Applications (UNS R56401). The different plastic retentions are manufacture from Kepital, Rilsan bmno and Pebax.
    All abutments are provided non-sterile to the end-user in a single-unit package, and are for singlepatient, single-use only.
    Clinical screws used to attach abutments and prosthetic components to implants are available with an M1.6 thread and 8 mm length to fit NP abutments and implants and with an M1.8 thread and 7.85 mm length to fit RP and WP abutments and implants. They are available in a machined Ti-6AI-4V design and in a design that is hard anodized to provide anti-loosening characteristics, designated Kiran®. Machined titanium alloy screws are anodized for identification, with the M1.6 thread screw that fits NP abutments and implants colored yellow and the M1.8 thread screws that fit RP and WP abutments and implants colored blue. Kiran screws are dark grey.
    A TX30 Torx screw is available for retention of the TX30 Mechanized Abutment. It incorporates a 6-lobed internal feature mating with a 6 lobed spherical tip screwdriver to permit driving the screw with the driver inserted through the angled portion of the restoration. It is provided with the Kiran hard anodizing treatment.
    Additional screws are available to attach prosthetic components to Basic abutments and to XDrive abutments. Basic screws have an M1.8 thread and are 4.3 mm long, while XDrive screws have an M1.4 thread and are 3.5 mm long. Each is available as an anodized titanium alloy screw or as a Kiran screw with the hard anodizing treatment.

    AI/ML Overview

    The provided text describes the Ziacom Dental Implant Systems and its substantial equivalence to predicate devices, but it does not contain information about an AI/ML-enabled medical device study or acceptance criteria for such a device.

    The document is a traditional 510(k) premarket notification for a Class II medical device (endosseous dental implant). The performance data presented focuses on mechanical strength testing, material characterization (surface roughness, chemistry), biocompatibility (cytotoxicity), and sterilization validation, which are standard for dental implants.

    Therefore, I cannot fulfill your request for the following sections as the necessary information is not present in the provided document:

    1. A table of acceptance criteria and the reported device performance (for an AI/ML device)
    2. Sample sizes used for the test set and data provenance
    3. Number of experts used to establish ground truth and their qualifications
    4. Adjudication method for the test set
    5. Multi-Reader Multi-Case (MRMC) comparative effectiveness study details
    6. Standalone (algorithm-only) performance
    7. Type of ground truth used
    8. Sample size for the training set
    9. How the ground truth for the training set was established

    The document describes the device's technical specifications and how it is demonstrated to be substantially equivalent to existing predicate devices based on non-clinical performance data (mechanical and biological testing), rather than clinical or AI/ML performance.

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    K Number
    K160852
    Device Name
    Zia
    Date Cleared
    2016-12-15

    (262 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Zia

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

    Zia™ Image Enhancement System is an image processing software that can be used for reducing noise in CT images. Enhanced images will be uploaded back to host/PACS systems and exist in conjunction to the original images. Zia™ is not intended for mammography applications. The device processing is not effective for lesion, mass, or abnormalities of sizes less than 2mm.

    Device Description

    Zia™ Image Enhancement System is an image processing software that can be used for reducing noise in CT images. Zia™ image enhancement software is based on a core noise reduction algorithm that reduces noise in flat regions via a regularization process while keeping the edges via data fidelity constrains. The software, which is installed on a remote computer, receives DICOM images from CT host computer (Zia DICOM node needs to be configured on the scanner), automatically processes the received images and uploads the post processed images back on to the host computer and/or other PACS systems. Enhanced images exist in conjunction to the original images.

    AI/ML Overview

    Here's a breakdown of the acceptance criteria and study details for the Zia™ Image Enhancement System based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance:

    Performance MetricAcceptance CriteriaReported Device PerformanceTest Result
    Noise ReductionReduces noise in processed images by at least 10%Reduced noise in processed images by at least 10%PASS
    CT# (Signal) AccuracyKeeps CT# (signal) accuracy within +/- 1.0 HUKept CT# (signal) accuracy within +/- 1.0 HUPASS
    High Contrast ResolutionMaintains (preserves) high contrast resolutionMaintained (preserved) high contrast resolutionPASS
    Low Contrast ResolutionMaintains (preserves) low contrast resolutionMaintained (preserved) low contrast resolutionPASS

    2. Sample Size Used for the Test Set and Data Provenance:

    • Sample Size: A total of 81 datasets were processed and analyzed.
    • Data Provenance: The data was generated using an ACR CT PHANTOM (Model 464) on three different CT scanners: GE BrightSpeed 4-Slice, Siemens Sensation 16-Slice, and Philips Brilliance 64-Slice. The images were acquired following specific protocols (Head 120KV, Head 80KV, and Body 120KV) with varying mAs (150-350mAs) and slice thicknesses (1.25-5mm). This indicates a controlled, simulated environment using a phantom, not retrospective or prospective patient data from a specific country of origin.

    3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

    The document does not mention the use of human experts to establish ground truth for the test set. The ground truth appears to be based on physical measurements of the ACR CT phantom.

    4. Adjudication Method for the Test Set:

    Not applicable, as human experts were not used for establishing ground truth or evaluating the test set. The performance was measured quantitatively using the phantom.

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

    No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed. The study focuses on the technical performance of the image processing software itself, not its impact on human reader performance.

    6. Standalone Performance Study:

    Yes, a standalone study was performed. The device's performance (noise reduction, CT# accuracy, contrast resolution) was evaluated directly by analyzing the processed images from the CT phantom, without human-in-the-loop.

    7. Type of Ground Truth Used:

    The ground truth used was based on the physical characteristics and known properties of the ACR CT PHANTOM (Model 464). Measurements of CT# and noise were obtained from specific regions of interest (ROIs) within the phantom, and resolution was assessed based on the phantom's design.

    8. Sample Size for the Training Set:

    The document does not specify a separate training set or its sample size. The description of the device's core algorithm as reducing noise in flat regions while keeping edges suggests it's a rule-based or model-based algorithm, rather than a machine learning algorithm requiring a separate, large training set with annotated data.

    9. How the Ground Truth for the Training Set Was Established:

    Not explicitly stated. Given the description of the algorithm, it likely relies on mathematical principles and image processing techniques. If there was any "training" in a general sense, it would have involved developing and refining these algorithms based on general image characteristics rather than a labeled training dataset with a specific ground truth.

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