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510(k) Data Aggregation

    K Number
    K251614

    Validate with FDA (Live)

    Date Cleared
    2026-02-06

    (255 days)

    Product Code
    Regulation Number
    880.6850
    Age Range
    N/A
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
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    Device Description
    AI/ML Overview
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    K Number
    K253959

    Validate with FDA (Live)

    Device Name
    Primevision 3D
    Manufacturer
    Date Cleared
    2026-02-05

    (57 days)

    Product Code
    Regulation Number
    892.1750
    Age Range
    N/A
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
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    K Number
    K253737

    Validate with FDA (Live)

    Manufacturer
    Date Cleared
    2026-02-03

    (71 days)

    Product Code
    Regulation Number
    862.1355
    Age Range
    N/A
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use
    Device Description
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    K Number
    K253282

    Validate with FDA (Live)

    Device Name
    ZSmile System
    Date Cleared
    2026-02-03

    (127 days)

    Product Code
    Regulation Number
    872.5470
    Panel
    Dental
    Age Range
    N/A
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use
    Device Description
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    K Number
    K252349

    Validate with FDA (Live)

    Date Cleared
    2026-01-29

    (184 days)

    Product Code
    Regulation Number
    890.3800
    Age Range
    18 - 120
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The device is intended for medical purposes to provide mobility to persons restricted to a sitting position.

    Device Description

    The Electric Scooter, has a base with metal frame, two front wheels, two rear wheels, a seat, a LCD Display, electric motor, electromagnetic brake, 1 rechargeable Lithium Battery with an off-board charger. The movement of the scooter is controlled by the rider who operates the control lever, speed control turn "speed" Knob. The device is installed with an electromagnetic brake that will engage automatically when the scooter is not in use and the brake cannot be used manually. The Scooter only can be operated on the flat surface. The device can be folded from front to back. Till height and armrest width is adjustable.

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    K Number
    K252347

    Validate with FDA (Live)

    Date Cleared
    2026-01-29

    (184 days)

    Product Code
    Regulation Number
    890.3800
    Age Range
    18 - 65
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The device is intended for medical purposes to provide mobility to persons restricted to a sitting position.

    Device Description

    The Electric Scooter, has a base with metal frame, two front wheels, two rear wheels, a seat, a LCD Display, electric motor, electromagnetic brake, 1 rechargeable Lithium Battery with an off-board charger. The movement of the scooter is controlled by the rider who operates the control lever, speed control turn "speed" Knob. The device is installed with an electromagnetic brake that will engage automatically when the scooter is not in use and the brake cannot be used manually. The Scooter only can be operated on the flat surface. The device can be folded from up to down by manual.

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    K Number
    K253761

    Validate with FDA (Live)

    Date Cleared
    2026-01-23

    (59 days)

    Product Code
    Regulation Number
    878.4300
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The HydroMARK™ Plus Breast Biopsy Site Marker is indicated to mark tissue during a percutaneous breast biopsy procedure, including axillary lymph nodes, be visible under ultrasound for at least six (6) weeks, and be permanently visible by x-ray and MRI.

    Device Description

    The HydroMARK™ Plus Breast Biopsy Site Marker (Dragonfly and Hummingbird shapes) is a two-component marker that provides permanent marking of a breast biopsy or axillary lymph node biopsy site following a breast biopsy procedure. The implantable marker is made of a highly expandable solid cylinder of polymerized and desiccated hydrogel that has the permanent titanium marker embedded. Upon fluid contact (e.g., water, blood, etc.), the hydrogel material expands to an equilibrium point. Once the material hydrates, it is visible under ultrasound. Over time, the hydrogel is resorbed by the patient's body. The titanium wire is permanently visible under x-ray and MRI even after the hydrogel is resorbed.
    The HydroMARK™ Plus Breast Biopsy Site Marker is a permanent implant and is not intended to be removed unless the marked tissue requires surgical removal. The marker is supplied pre-loaded in a sterile, disposable applicator that is designed to fit into specified commercially available breast biopsy devices. During a breast biopsy procedure, the marker is deployed through a compatible introducer into the biopsy cavity created by the breast biopsy device.
    The focus of this submission is a modification to the applicator of the marker, which has been modified to enhance compatibility of use in the MR Environment. The markers themselves remain unchanged from the predicate device.

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    K Number
    K251286

    Validate with FDA (Live)

    Device Name
    Affirm 400
    Date Cleared
    2026-01-21

    (271 days)

    Product Code
    Regulation Number
    882.4950
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Affirm 400 is a surgical microscope accessory used in fluorescent visualization of suspected grade III and IV gliomas during neurosurgery, comprising an excitation filter for blue spectral range between 390 nm and 420 nm and an observation filter for visible light with spectral range between 510 nm and 700 nm.

    Device Description

    Affirm 400 is an accessory to the Class I Digital Surgical Microscope (DSM). Affirm 400 is a hardware and software which allows intraoperative viewing of suspected grade III and IV gliomas under fluorescence with the 5-ALA optical imaging agent. Affirm 400 is composed of optical filters: the "Excitation" filter and the "Emission" filter. The Excitation filter is designed to filter light between 390-420 nanometers. The Emission filter is designed to filter light between 510 – 700 nanometers. The use of a suitable detection system allows for visualization of surgical interventions. The emitted light is then captured by the optics of the digital microscope, passed through filters to remove unwanted wavelengths of light, and finally detected by the image sensors. This detected signal is then projected on a monitor enabling the surgeon to view the magnified image. The Affirm 400 includes installation of a software license that facilitates use of the accessory. After the software license is installed, the user has the option to switch from the normal white light mode of the surgical microscope to the Affirm 400 mode.

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    K Number
    K252934

    Validate with FDA (Live)

    Device Name
    Diagnocat
    Manufacturer
    Date Cleared
    2026-01-15

    (122 days)

    Product Code
    Regulation Number
    892.2070
    Age Range
    22 - 120
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Diagnocat software is a radiological, automated, concurrent read computer-assisted detection software intended to aid in the detection of periapical radiolucency on permanent teeth captured on maxillofacial Cone Beam CT images, using scans that were previously acquired for clinically justified purposes independent of Diagnocat. Diagnocat may be used only when a dental professional has independently determined that CBCT imaging is necessary for further evaluation of the patient. The device provides additional aid for the dental professional to use in their identification of periapical radiolucency. The device is not intended as a replacement for a complete dental professional's review or their clinical judgment that considers other relevant information from the patient or other images or patient history. The system is to be used by professionally trained and licensed dental professionals with the appropriate knowledge and training to interpret maxillofacial CBCT images, including at least two years of clinical experience reading and assessing CBCT scans.

    Diagnocat is indicated for use by dental professionals for the second-read of CBCT radiographs of permanent teeth in patients 22 years of age or older.

    Device Description

    Diagnocat Software is a computer-assisted detection (CADe) software-only device intended to concurrently aid in the detection of periapical radiolucency areas. The device is designed to facilitate the analysis and interpretation of previously obtained dental Cone Beam Computed Tomography (CBCT) scans, specifically in cases where a periapical radiolucency condition is suspected, leveraging deep learning algorithms and artificial intelligence (AI). The key features of the software are:

    1. Tooth Detection and Localization: Diagnocat employs image processing techniques to identify, number, and segment each tooth within a CBCT scan. The segmentation algorithm is employed to achieve tooth segmentation for tooth numeration and identification.

    2. Periapical Radiolucency and Localization: The software uses computer vision models to distinguish between normal anatomical structures and areas suspected of periapical radiolucency, which is a radiographic sign of inflammatory bone lesions at the tooth's apex. The segmentation algorithm is used for both segmentation and heat mapping of regions suspected of periapical radiolucencies.

    3. Image Visualization: Users can upload and navigate previously acquired CBCT studies. A panoramic reconstruction view aids users in navigating between a patient's teeth and identifying points of interest, and multiplanar reformatted (MPR) slices allow for detailed examination of each tooth.

    The software also features non-device functions that supplement its achievement of the intended clinical use, including a user-friendly interface, the ability to integrate with various CBCT scanning devices, and cloud-based storage to facilitate access from multiple computers.

    AI/ML Overview

    Here's a summary of the acceptance criteria and the studies proving the device's performance, based on the provided FDA 510(k) clearance letter for Diagnocat:

    1. Table of Acceptance Criteria and Reported Device Performance

    Metric/EndpointAcceptance Criteria (Pre-defined Performance Goals - PG)Diagnocat Reported Performance
    Teeth Segmentation (Mean Dice Similarity Coefficient - DSC)DSC > Desired Threshold (Implied: All DSCs exceeded the pre-defined PGs)Cohort 1 (General population): 0.955 Cohort 2 (With confirmed PARL): 0.947
    Periapical Radiolucency (PARL) Segmentation (Mean Dice Similarity Coefficient - DSC)DSC > Desired Threshold (Implied: All DSCs exceeded the pre-defined PGs)Cohort 2 (With confirmed PARL): 0.804
    PARL Detection - Sensitivity>= Desired Threshold (Implied: Met the pre-defined PGs)0.854
    PARL Detection - Specificity>= Desired Threshold (Implied: Met the pre-defined PGs)0.991
    MRMC - Improvement in AUC (Aided vs. Unaided)AUC Difference > 0 (Implied: Significant improvement)+0.027

    Studies Proving Device Meets Acceptance Criteria:

    The provided document describes three distinct studies:

    Study 1: Segmentation (Teeth and Periapical Radiolucency)

    • Sample Size for Test Set: 100 CBCT images
      • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). However, the description of "previously acquired CBCT scans" suggests a retrospective dataset.
    • Number of Experts Used for Ground Truth: Not explicitly stated.
    • Qualifications of Experts: Described as "expert radiologists." No further details on years of experience or sub-specialty are provided.
    • Adjudication Method: Not explicitly stated.
    • MRMC Comparative Effectiveness Study: No, this was a standalone performance assessment for segmentation.
    • Standalone Performance: Yes, this study assessed the algorithm's ability to segment teeth and PARL against a reference standard.
    • Type of Ground Truth Used: Reference standard established by "expert radiologists."
    • Sample Size for Training Set: Not provided.
    • How Ground Truth for Training Set Established: Not provided.

    Study 2: Detection of Periapical Radiolucency

    • Sample Size for Test Set: 285 CBCT images
      • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). Similar to Study 1, "previously acquired CBCT scans" suggests a retrospective dataset.
    • Number of Experts Used for Ground Truth: Not explicitly stated.
    • Qualifications of Experts: Described as "expert radiologists." No further details on years of experience or sub-specialty are provided.
    • Adjudication Method: Not explicitly stated.
    • MRMC Comparative Effectiveness Study: No, this was a standalone performance assessment for detection.
    • Standalone Performance: Yes, this study assessed the algorithm's ability to detect PARL against a reference standard.
    • Type of Ground Truth Used: Reference standard established by "expert radiologists."
    • Sample Size for Training Set: Not provided.
    • How Ground Truth for Training Set Established: Not provided.

    Study 3: Multi-Reader Multi-Case (MRMC)

    • Sample Size for Test Set: Not explicitly stated (the passage only refers to the "AUC" values which would be derived from a test set of cases).
      • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective).
    • Number of Experts Used to Establish Ground Truth: Not explicitly stated.
    • Qualifications of Experts: Not explicitly stated for ground truth. However, the study involved "radiologist performance," implying the readers participating in the study were radiologists.
    • Adjudication Method: Not explicitly stated.
    • MRMC Comparative Effectiveness Study: Yes, "This study assessed whether the Diagnocat software improves radiologist performance in detecting PARL."
      • Effect Size of Human Readers Improvement: When aided by Diagnocat, the average Area Under the ROC Curve (AUC) increased by 0.027 compared to unaided interpretation.
    • Standalone Performance: While the algorithm's standalone performance contributes to the MRMC study, the MRMC study itself measures human performance with and without AI assistance, not the algorithm's standalone performance directly in this context (that was covered in Study 2).
    • Type of Ground Truth Used: Not explicitly stated for this study, but likely based on expert consensus for the cases used.
    • Sample Size for Training Set: Not provided.
    • How Ground Truth for Training Set Established: Not provided.

    General Notes from the document:

    • The document implies that the "reference standard established by expert radiologists" serves as the ground truth for both segmentation and detection studies.
    • The document does not explicitly detail the number of adjudicators, their specific qualifications (beyond "expert radiologists" for ground truth), or the specific adjudication rules (e.g., 2+1, 3+1).
    • Information regarding the training set's size and ground truth establishment is not provided in the summary.
    • The terms "pre-defined performance goals (PG)" are used, indicating that specific acceptance criteria were established prior to the studies, even if the exact numerical thresholds for DSC are not explicitly listed in the table provided.
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    K Number
    K253248

    Validate with FDA (Live)

    Date Cleared
    2026-01-13

    (106 days)

    Product Code
    Regulation Number
    872.3250
    Panel
    Dental
    Age Range
    All
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    • Lining the floor and walls of the cavity prior to application of filling materials

    Device Description

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