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510(k) Data Aggregation

    K Number
    K251730

    Validate with FDA (Live)

    Manufacturer
    Date Cleared
    2025-12-19

    (196 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The LIA Console is indicated for use as an imaging tool in the evaluation of human tissue microstructure in the tracheobronchial tree by providing two-dimensional, cross-sectional, real-time depth visualization using Optical Coherence Tomography (OCT).

    The safety and effectiveness of this device for diagnostic analysis (i.e., differentiating normal versus specific abnormalities) in any tissue microstructure or specific disease has not been evaluated.

    Device Description

    The LIA Console is indicated for use as an imaging tool in the evaluation of human tissue microstructure in the tracheobronchial tree by providing two-dimensional, cross-sectional, real-time depth visualization using Optical Coherence Tomography (OCT).

    The LIA Console is intended to be used only in conjunction with the LIA-1 Catheter in order to function as intended.

    LIA Console consists of the following main parts:

    1. Monitor: 24-inch multi-touch display monitor allowing software user interface.

    2. Catheter Driving Unit (CDU): Electromechanical and optical interface between the LIA Console and the LIA-1 Catheter. A rotary motor inside drives the LIA-1 Catheter to form 360-degree side view real-time imaging.

    3. Catheter Driving Arm (CDA): A supporting arm allowing CDU positioning, mobility and flexibility during the procedure.

    4. Image Engine: The main body of the LIA Console contains laser source, computing unit, data acquisition and power distribution module and other components.

    5. Caster: Four caster wheels installed at the base provide mobility for the LIA Console. Each caster is equipped with a brake that can lock the LIA Console in place as needed.

    6. OCTICA Software: A proprietary GUI-based software that controls data acquisition, rotary motor and other hardware components to enable real-time OCT imaging of tissue microstructure.

    AI/ML Overview

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    K Number
    K253101

    Validate with FDA (Live)

    Manufacturer
    Date Cleared
    2025-12-15

    (82 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The HyperVue™ Imaging System - Integrated with compatible HyperVue™ Software and Starlight™ Imaging Catheter is intended for the imaging of coronary arteries and is indicated in patients who are candidates for transluminal interventional procedures.

    The Starlight Imaging Catheter is intended for use in vessels 2.0 to 5.2 mm in diameter.

    The Starlight Imaging Catheter is not intended for use in a target vessel which has undergone a previous bypass procedure.

    The NIRS capability of the HyperVue Imaging System - Integrated is intended for the detection of lipid core containing plaques of interest.

    The NIRS capability of the HyperVue Imaging System - Integrated is intended for the assessment of coronary artery lipid core burden.

    The NIRS capability of the HyperVue Imaging System - Integrated is intended for the identification of patients and plaques at increased risk of major adverse cardiac events.

    Device Description

    The HyperVue Imaging System – Integrated is a stationary, capital equipment platform intended for intravascular optical imaging of coronary arteries. HyperVue Imaging System – Integrated with the HyperVue Software and the Starlight Imaging Catheter is used as an intravascular imaging device with the ability to simultaneously assess vessel composition and structure by combining Optical Coherence Tomography (OCT) and Near Infrared Spectroscopy (NIRS).

    AI/ML Overview

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    K Number
    K252851

    Validate with FDA (Live)

    Manufacturer
    Date Cleared
    2025-10-07

    (29 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    deepLive is intended to be used as a non-invasive imaging tool in the evaluation of external human tissue microstructure by providing three-dimensional, cross-sectional and en-face real-time depth visualization for assessment by physicians to support in forming a clinical judgment.

    Device Description

    The deepLive device is an update to the previously cleared deepLive device (K240610). The update includes the addition of a hand-held Dermoscope (DMS).

    deepLive was designed for an easy integration into clinical practices. The device is composed of:

    • A mobile cart, allowing the user to move the whole device and including a cart tablet for accessories.
    • A touchscreen, fixed on the cart mast, displaying the software interfaces to the user.
    • A first hand-held probe (LC-OCT), integrating the LC-OCT imaging system (interferometric microscope, OCT camera). The probe is connected to the CPU front panel by a sheathed cable bundle, and stored in a dedicated probe-holder fixed on the cart tablet.
    • A second hand-held probe (DMS), complementary to the LC-OCT, integrating a dermoscope and providing wide-field surface color images. The probe is connected to the CPU by a USB cable, and stored in a dedicated probe-holder fixed on the cart tablet.
    • A central power unit (CPU), mounted on the cart, integrating various imaging and electronic peripherals (laser, computer, electronic cards, drivers, power supplies, etc.), driving and powering the imaging probe.
    • A software running on the device's computer, which controls the components of the system, acquires and processes images, and provides user interfaces for performing examinations and managing data.

    deepLive hardware interfaces are located on the front-panel of the CPU. Input/output connections include:

    • 1 Display port to connect the screen
    • 3 USB ports to connect external drives (Wifi key, hard drive disk, etc.)

    deepLive software runs on a computer embedded in the CPU of the device. The computer uses Windows Enterprise LTSC operating system. The software executable and all dynamic libraries needed for program execution are deployed at a specific location in the file system.

    AI/ML Overview

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    K Number
    K251198

    Validate with FDA (Live)

    Manufacturer
    Date Cleared
    2025-07-16

    (90 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The HyperVue Software is intended to be used only with compatible HyperVue Imaging Systems and Starlight Imaging Catheter.

    The HyperVue Imaging System is intended for the imaging of coronary arteries and is indicated in patients who are candidates for transluminal interventional procedures.

    The Starlight Imaging Catheter is intended for use in vessels 2.0 to 5.2 mm in diameter.

    The Starlight Imaging Catheter is not intended for use in a target vessel which has undergone a previous bypass procedure.

    The NIRS capability of the HyperVue Imaging System is intended for the detection of lipid core containing plaques of interest.

    The NIRS capability of the HyperVue Imaging System is intended for the assessment of coronary artery lipid core burden.

    The NIRS capability of the HyperVue Imaging System is intended for the identification of patients and plaques at increased risk of major adverse cardiac events.

    Device Description

    The HyperVue Software (2.0) is resident on the HyperVue Imaging System (K230691) and is used with the Starlight Imaging Catheter (K243016). The HyperVue Software provides a user interface for executing clinical workflows, acquiring and processing OCT-NIRS data, and exporting patient data. The software update introduces the ability to connect to hospital PACS servers for data export.

    AI/ML Overview

    The provided FDA 510(k) clearance letter for the HyperVue™ Software primarily focuses on demonstrating substantial equivalence to a predicate device based on technological characteristics and general software verification and validation. It does not contain detailed information regarding clinical performance studies (e.g., MRMC studies, standalone performance), specific acceptance criteria, or the methodology for establishing ground truth for medical image analysis tasks, especially related to the NIRS capabilities like plaque assessment.

    The text states that the software update "introduces the ability to connect to hospital PACS servers for data export" and discusses "historical software and algorithm changes." However, it does not provide specifics on how these "historical algorithm changes" were validated in terms of clinical performance metrics that would typically be included in an AI/ML medical device submission.

    Based on the provided document, here's what can be extracted and what is missing:


    Acceptance Criteria and Device Performance

    The document does not provide a specific table of acceptance criteria for clinical performance (e.g., sensitivity, specificity, accuracy) or reported device performance metrics related to diagnostic tasks (like lipid core detection or plaque assessment). The performance data section focuses on software engineering aspects (verification, validation, cybersecurity, and adherence to design controls) rather than clinical accuracy or effectiveness.

    Table of Acceptance Criteria and Reported Device Performance (Based only on available information)

    Acceptance Criteria CategorySpecific Criteria (Expected but not found in document)Reported Device Performance (Not quantified in document)
    Software FunctionalityAll functions performed by the software are evaluated and passed.Passed all pre-determined acceptance criteria identified in the test plan.
    Design Control ComplianceVerification and validation testing completed per company's Design Control process (21 CFR Part 820.30) and FDA guidance for software.Verification and validation testing completed in accordance with the company's Design Control process in compliance with 21 CFR Part 820.30 and FDA "Guidance on Software Contained in Medical Devices".
    CybersecurityStatic Code Analysis, Vulnerability Scanning, Penetration Testing, Security Controls verified, Interoperability Assessment, Risk Analysis & Mitigation.Performed as per FDA guidance "Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions." Risks analyzed and satisfactorily mitigated.
    Clinical Performance (e.g., for NIRS capability)Not specified in the document (e.g., sensitivity, specificity, AUC for lipid core detection)Not reported in the document.

    Study Details (Based only on available information, with many points missing)

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

      • Test Set Sample Size: Not specified. The document mentions "an established test plan that fully evaluated all functions performed by the software," but it does not specify the number of cases or patients used for performance testing, especially not for clinical performance.
      • Data Provenance: Not specified. There is no mention of the country of origin of data or whether it was retrospective or prospective. The testing described appears to be primarily software-level functional and cybersecurity testing rather than a clinical performance study.
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

      • Not specified. The document does not describe the establishment of a clinical ground truth, suggesting that the primary validation for this 510(k) was based on software engineering and safety, not on a new clinical performance claim requiring expert ground truth.
    3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

      • Not specified. Since a clinical performance study with expert ground truth establishment is not detailed, adjudication methods are not mentioned.
    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 MRMC study is mentioned or implied. The submission emphasizes substantial equivalence based on technological characteristics and software updates rather than a new clinical claim supported by a reader study.
    5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

      • Not explicitly stated in terms of clinical performance metrics. The document claims that the software "processes reflected optical signals to construct images" and makes "mathematical comparisons of image data." However, it does not provide standalone performance metrics (e.g., sensitivity/specificity for lipid plaque detection) for these algorithmic functions. The clearance is for the software (2.0) that is resident on the imaging system, implying it's part of the overall system that assists physicians, but no specific standalone diagnostic performance is reported.
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

      • Not specified for clinical claims. For the "software functions," ground truth would likely be based on technical specifications and expected software behavior. For the NIRS capabilities (lipid core detection, plaque assessment), the method for establishing ground truth for performance evaluation is not described in this document. This suggests that the current 510(k) submission did not hinge on a new clinical efficacy claim for these NIRS functionalities that would require a new, robust clinical study with defined ground truth. Instead, it seems to rely on the predicate device's existing clearance for these capabilities.
    7. The sample size for the training set:

      • Not specified. The document does not discuss any machine learning model training or associated training sets. The primary focus of this 510(k) is a software update (version 2.0) mainly involving PACS connectivity and "historical" algorithm changes, which doesn't necessarily imply retraining a new ML model that would require a dedicated training set description in this context.
    8. How the ground truth for the training set was established:

      • Not applicable/Not specified. Since a training set is not mentioned, the method for establishing its ground truth is also not.

    Summary of Gaps:

    The provided FDA 510(k) clearance letter is for a software update (HyperVue™ Software 2.0) that appears to be primarily a software modification/upgrade (PACS connectivity, historical algorithm changes) to an existing cleared device. As such, the submission focuses heavily on software engineering verification and validation, cybersecurity, and demonstrating substantial equivalence to the predicate device based on technological characteristics and intended use.

    It does not contain the detailed clinical performance study information (e.g., specific acceptance criteria for diagnostic performance, quantitative performance metrics, sample sizes for clinical test sets, expert qualifications, ground truth methodology for clinical data) that would typically be seen for a novel AI/ML device making new clinical claims or demonstrating significantly improved diagnostic performance. The NIRS capabilities listed appear to be carried over from the predicate device's clearance.

    Therefore, for aspects related to clinical accuracy and effectiveness of features like "detection of lipid core containing plaques," this document does not provide the specific study details you requested.

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    K Number
    K250684

    Validate with FDA (Live)

    Date Cleared
    2025-07-02

    (118 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The OPUSWAVE System with DualView Catheter is intended for the intravascular imaging of coronary arteries and is indicated in patients who are candidates for transluminal interventional procedures.

    Device Description

    The OPUSWAVE Dual Sensor Imaging System consists of a wheeled console with monitor, keyboard, mouse, a software graphical user interface and a Motor Drive Unit (MDU) protected by an MDU cover. The MDU is connected to a DualView Catheter capable of imaging both, Optical Coherence Tomography (OCT) and Intravascular Ultrasound (IVUS) modalities, either simultaneously or asynchronously, without removing the catheter from the imaging site. The system allows image data to be exported and stored on external media (USB, DVD), and for integration with Cath Lab imaging technologies (angio, ECG).
    The sterile operator (physician) is able to control image acquisition by manually positioning the imaging sensor as well as performing pullback (automatically or manually) for defined regions of interest. The system provides analysis tools such as area and linear measurements.

    AI/ML Overview

    The provided FDA 510(k) Clearance Letter for the OPUSWAVE Dual Sensor Imaging System focuses on establishing substantial equivalence to predicate devices, primarily through engineering and regulatory compliance testing. While it mentions various verification and validation activities, it does not contain the detailed clinical study data typically found when a device’s performance against specific acceptance criteria is being proven, especially for AI-enabled devices requiring human reader studies or detailed standalone performance metrics.

    Based on the information given, here's an analysis of what can be extracted or inferred, and what cannot be answered:

    Acceptance Criteria and Study for OPUSWAVE Dual Sensor Imaging System

    1. Table of Acceptance Criteria and Reported Device Performance:

    The document primarily focuses on demonstrating equivalence to predicate devices for imaging capabilities (OCT and IVUS modalities), safety (electrical safety, EMC, laser output, acoustic output), and software functionality. There are no specific quantitative performance metrics or acceptance criteria reported similar to what would be found for an algorithm that provides diagnostic outputs (e.g., sensitivity, specificity, accuracy).

    However, based on the provided text, we can infer the "acceptance criteria" were met through various tests that showed compliance with standards and equivalence to predicates.

    Acceptance Criteria Category (Inferred)Reported Device Performance (Inferred/Directly Stated)
    Electrical SafetyComplies with IEC 60601-1 standard.
    Electromagnetic Compatibility (EMC)Complies with IEC 60601-1-2 standard.
    Software FunctionalitySoftware verification and validation testing successfully completed; fulfillment documentation provided as recommended by FDA guidance ("Enhanced" level, implying potential for serious injury/death from failure).
    Design VerificationPerforms pursuant to defined design input requirements.
    Design Validation (Simulated Use)Meets user needs and intended use.
    Acoustic Output (IVUS)Does not exceed Track 3 limits (equivalent to predicate 1 meeting 60601-2-37 requirements).
    Laser Output (OCT)Class 1 Laser Output per 60825-1 (equivalent to predicate 2 being Class 1M).
    Image Quality/Clinical EquivalenceDemonstrated substantial equivalence to predicate devices through animal testing. No quantitative imaging performance metrics (e.g., resolution, penetration depth, signal-to-noise ratio) are explicitly provided as acceptance criteria or results beyond "real-time grayscale image".

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

    • Test Set Sample Size: Not specified. The document mentions "animal testing" and "simulated use testing" for design validation. For software, general "verification and validation testing" is mentioned, but specific test set sizes (e.g., number of test cases, images, patients) are not provided.
    • Data Provenance:
      • Animal Study: Animal data. Details on geographic origin or whether it was retrospective/prospective are not provided.
      • Simulated Use Testing: Implies a controlled environment, likely within the manufacturer's facility, but specifics are not given.
      • Software V&V: Internal testing.

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

    • Not Applicable / Not Provided: The document does not describe the establishment of a "ground truth" in the clinical sense (e.g., for diagnostic accuracy) as it's not a device focusing on automated interpretation or diagnosis. The studies mentioned (animal, simulated use, software V&V) would have their own internal verification against design specifications or a recognized standard, but not a human expert-adjudicated ground truth as would be typical for AI/CADx devices.

    4. Adjudication Method for the Test Set:

    • Not Applicable / Not Provided: As there's no mention of expert-established ground truth for a diagnostic test set, there's no adjudication method described.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of how much human readers improve with AI vs. without AI assistance:

    • No: The document explicitly states: "Clinical testing was not required to demonstrate the substantial equivalence of the OPUSWAVE Dual Sensor Imaging System to the predicate devices and is not included as part of this premarket notification." Therefore, an MRMC study demonstrating human reader improvement with AI assistance was not conducted or reported. This device is an imaging system, not an AI interpretation tool.

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

    • Not Applicable (in the classic AI sense): This device is an imaging system, not an AI algorithm designed to provide standalone diagnostic outputs. Its "performance" would be related to image quality, system functionality, and safety parameters. While the system's software underwent "verification and validation testing," this is to ensure the software itself functions correctly and safely within the imaging system, not to assess its diagnostic accuracy as a standalone algorithm.

    7. The Type of Ground Truth Used:

    • Design Specifications, Regulatory Standards, and Animal Models:
      • For electrical safety and EMC: Compliance with IEC 60601-1 and IEC 60601-1-2.
      • For software: Compliance with FDA Software Guidance ("Enhanced" level), suggesting verification against defined requirements.
      • For design: Compliance with "defined design input requirements."
      • For clinical equivalence/imaging capabilities: Demonstrated equivalence in "animal testing," implying that normal anatomy and pathology in animal models served as a reference.

    8. The Sample Size for the Training Set:

    • Not Applicable / Not Provided: This device is not described as an AI/machine learning device that requires a "training set" in the context of model development. The verification and validation activities are for the entire system, not for training a specific algorithm.

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

    • Not Applicable / Not Provided: As there is no mention of a training set for an AI algorithm, there is no ground truth establishment process described for one.

    Summary of Device and Evidence Focus:

    The OPUSWAVE Dual Sensor Imaging System is an intravascular imaging system (OCT and IVUS). The 510(k) clearance relied on demonstrating substantial equivalence to existing predicate devices, rather than proving novel clinical efficacy or superior diagnostic accuracy through large-scale human clinical trials or AI performance evaluations. The "studies" primarily referenced are engineering verification and validation testing, animal studies for equivalence, and compliance with recognized safety and software standards. The document does not suggest that the device incorporates AI in a way that requires AI-specific performance criteria (e.g., sensitivity, specificity, MRMC studies) for its clearance.

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    K Number
    K242924

    Validate with FDA (Live)

    Date Cleared
    2025-06-23

    (272 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    18 - 65
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    OPXION Optical Skin Viewer is a non-invasive imaging system intended to be used for real-time visualization of the external tissues of the human body. The two-dimensional, cross-sectional, three-dimensional, and en-face images of tissue microstructures can be obtained.

    Device Description

    OPXION Optical Skin Viewer is composed of two parts consisting of a handheld probe and a mainframe, connected by an optical fiber cable. The device comes with three accessories: a USB 3.0 cable, a power adapter, and a power cord. The Optical Skin Viewer needs to be connected to a laptop or a personal computer. The device uses Optical Coherence Tomography (OCT) technology with a Superluminescent diode, 840 nm, 6 mW light source.

    AI/ML Overview

    Based on the provided FDA 510(k) clearance letter for the OPXION Optical Skin Viewer, an optical device that visualizes external tissue and is not an AI/ML powered device, the document does not contain the specific information requested about acceptance criteria and a study that proves the device meets the acceptance criteria in the context of AI/ML performance.

    The 510(k) summary focuses on demonstrating substantial equivalence to a predicate device (VivoSight Topical OCT System) primarily based on intended use, technology (Optical Coherence Tomography), and general performance (image quality accepted by a qualified medical professional for visualization).

    Therefore, I cannot provide a table of acceptance criteria, sample sizes for test sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, or details about training sets, as these specific details are not present in the provided document, nor are they typically required for a Class II medical imaging device like this one unless it incorporates AI/ML for diagnostic or interpretive functions.

    However, I can extract the general acceptance criteria and the type of study conducted for this device based on the provided text:

    Acceptance Criteria and Study:

    The document describes the device's performance in terms of its ability to produce images for visualization, rather than offering specific quantitative metrics for diagnostic accuracy, sensitivity, or specificity that would be typical for an AI/ML driven device.

    Here's an interpretation based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria (General)Reported Device Performance (General)
    Image quality confirmed and accepted by a qualified medical professional.The OPXION Optical Skin Viewer demonstrated consistent performance in producing images of a quality that is substantially equivalent to that produced by the cited predicate device. The device successfully displayed anatomical features of skin.
    No adverse events or safety concerns were reported. The scanning process was well-tolerated by all subjects.
    Safe and effective clinical imaging device capable of generating two-dimensional, cross-sectional, three-dimensional, and en-face images of external tissue microstructure.

    2. Sample Size Used for the Test Set and Data Providence

    • Test Set Sample Size: The study included three subjects with healthy skin and five subjects with diseased skin conditions.
    • Data Provenance: Not explicitly stated, but implies a prospective study given the "Study Design" description of scanning "each target area in three sessions." The country of origin of the data is not specified in the 510(k) summary.

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

    • Number of Experts: The document states that "Image quality was confirmed and accepted by a qualified medical professional." This implies at least one, but the exact number beyond "a" is not specified.
    • Qualifications of Experts: Described as "a qualified medical professional." No specific specialty (e.g., dermatologist, radiologist) or years of experience are provided.

    4. Adjudication Method for the Test Set

    • Adjudication Method: Not explicitly stated as an adjudication method in the context of multiple readers reaching consensus. The acceptance criterion notes "Image quality was confirmed and accepted by a qualified medical professional," which suggests a single reviewer or possibly an internal review process where consensus was reached without a formal adjudication method described.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

    • MRMC Study: No, an MRMC comparative effectiveness study was not conducted or described in the provided document. The study focuses on the device's ability to produce images and its substantial equivalence to a predicate, not on how human readers perform with or without the device.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    • Standalone Performance: This device is an imaging system for visualization, not an AI/ML algorithm that provides diagnostic outputs. Therefore, the concept of "standalone performance" of an algorithm is not applicable or described. Its "performance" is its ability to acquire and display images.

    7. The Type of Ground Truth Used

    • Type of Ground Truth: The ground truth for this device's performance evaluation was the visual assessment and acceptance of image quality by a qualified medical professional, based on the successful display of "anatomical features of skin" for both healthy and diseased conditions. This is a form of expert consensus/acceptance on display quality.

    8. The Sample Size for the Training Set

    • Training Set Sample Size: Not applicable. This is an optical imaging device, not an AI/ML algorithm that undergoes a training phase with a specific dataset.

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

    • Ground Truth for Training Set: Not applicable, as there is no mention of an AI/ML training set.

    In summary, the provided FDA 510(k) letter describes a traditional medical imaging device focused on visualization, not an AI/ML-powered device. Therefore, the detailed criteria and study designs typically associated with AI/ML device validation are absent from this document.

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    K Number
    K242098

    Validate with FDA (Live)

    Date Cleared
    2025-04-11

    (267 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Cornaris Intravascular Imaging System with Imaging Catheter is intended for the imaging of coronary arteries and is indicated in patients who are candidates for transluminal interventional procedures. LumenCross Imaging Catheter is intended for use in vessels 2.0 to 3.5 mm in diameter. The Imaging Catheter is not intended for use in the left main coronary artery or in a target vessel which has undergone a previous bypass procedure.

    The LumenCross Imaging Catheter (referred to as LumenCross) with the Cornaris Intravascular Imaging System produced by Vivolight, which is intended for intravascular imaging and is indicated for use in coronary arteries in patients who are candidates for transluminal interventional procedures. The LumenCross intended for use in vessels 2.0~3.5mm in diameter. The LumenCross is not indicated for use in the left main coronary artery or in a target vessel that has undergone a previous bypass procedure.

    Device Description

    Cornaris Intravascular Imaging System are cart-mounted computer and Imaging Engin(or optical engine) placed inside an ergonomically designed mobile cart with the cable underground. There are two models, P80-E is mainly composed of trolley, mouse, keyboard, two display monitors, optical engine, computer. Mobile-E is mainly composed of trolley, mouse, keyboard, one display monitor, monitor bracket, optical engine, computer. The both also includes the catheter connection unit (PIU), which provides the interconnection between the Cornaris Intravascular Imaging System and the LumenCross Imaging Catheter.P80-E and Mobile-E has the same software features.

    The imaging catheter contains two main components: the catheter body and imaging core (internal rotating fiber optic). The outer diameter of the distal shaft of the catheter was 2.67 F (0.89 mm, 0.035 in.), and the length of the distal shaft was 280mm. The imaging catheter has a working length of 1350mm. The imaging catheter is compatible with 0.014" (0.356 mm) guidewire, which with a guidewire lumen length of 16 mm, the guidewire enters through tip entrance and exit through the RX port. The hydrophilic coating is applied on the outer surface of distal shaft. The LumenCross Imaging Catheter is a single use device. The LumenCross Imaging Catheter is sterilized by Ethylene Oxide Gas to achieve a SAL of 10-6 and supplied in sterility maintenance package which could maintain the sterility of the device during the shelf life of two years.

    AI/ML Overview

    The provided FDA 510(k) clearance letter and its summary do not contain detailed information regarding the acceptance criteria, nor the specific study design and results typically associated with proving a device meets those criteria, especially in terms of algorithm performance for an imaging system. The submission focuses more on general product specifications, non-clinical bench testing, and animal studies related to the physical and material performance of the imaging catheter and system, rather than the quantitative performance of any imaging interpretation algorithm or AI component.

    However, based on the information provided, we can infer some aspects and highlight what is missing for a complete answer to your request.

    Here's a breakdown based on the provided text, with explicit notes where information is missing:


    Overview of Device and Purpose

    The Cornaris Intravascular Imaging System (P80-E, Mobile-E) and LumenCross Imaging Catheter (F2) are intended for imaging coronary arteries during transluminal interventional procedures. The system utilizes Optical Coherence Tomography (OCT) to visualize vessel structures. The 510(k) submission focuses on demonstrating substantial equivalence to predicate devices (ILUMIEN OPTIS and DRAGONFLY OPTIS IMAGING CATHETER).


    1. Table of Acceptance Criteria and Reported Device Performance

    The submission describes various performance tests conducted. These are primarily for hardware, optical parameters, and catheter physical characteristics, rather than interpretive accuracy.

    Acceptance Criterion (Measured Parameter)Reported Device Performance (or Compliance Statement)Notes on Relevance to AI/Imaging Interpretation
    Cornaris Intravascular Imaging System:
    Scan range(Compliance implied by substantial equivalence)Ensures adequate imaging area.
    Axial resolution(Compliance implied by substantial equivalence)Affects image quality and detail.
    Luminous Sensitivity(Compliance implied by substantial equivalence)Affects image quality and signal strength.
    A-line speed(Compliance implied by substantial equivalence)Affects imaging speed.
    Dynamic range(Compliance implied by substantial equivalence)Affects image contrast and detail.
    Frame rate(Compliance implied by substantial equivalence)Affects imaging speed.
    Pullback time and range(Compliance implied by substantial equivalence)Relates to image acquisition protocol.
    Fiber Optic Rotary Joint (FORJ) Insertion loss(Compliance implied by substantial equivalence)Ensures proper optical signal transmission.
    Fiber Optic Rotary Joint (FORJ) Rotational homogeneity(Compliance implied by substantial equivalence)Ensures consistent imaging across the rotation.
    Fiber Optic Rotary Joint (FORJ) Return loss(Compliance implied by substantial equivalence)Ensures proper optical signal transmission.
    LumenCross Imaging Catheter:
    Visual & Dimensional Inspection(Compliance implied by substantial equivalence)Basic quality control.
    Catheter bond Strength(Compliance implied by substantial equivalence)Safety and durability.
    Simulated use(Compliance implied by substantial equivalence)Evaluates real-world performance.
    Leakage(Compliance implied by substantial equivalence)Safety.
    Corrosion(Compliance implied by substantial equivalence)Safety and durability.
    Torque(Compliance implied by substantial equivalence)Ease of use and maneuverability in vessel.
    Particulates(Compliance implied by substantial equivalence)Safety (embolism risk).
    Coating integrity(Compliance implied by substantial equivalence)Safety and ease of use.
    Flexibility and Kink(Compliance implied by substantial equivalence)Ease of use and safety (prevents damage).
    Endotoxin(Compliance implied by substantial equivalence)Safety (prevents systemic reactions).
    Biological Safety Testing (LumenCross):
    Cytotoxicity(Compliance met per ISO 10993-1)Biocompatibility.
    Sensitization(Compliance met per ISO 10993-1)Biocompatibility.
    Mouse Lymphoma Assay(Compliance met per ISO 10993-1)Biocompatibility (genotoxicity).
    Bacterial Reverse Mutation Assay(Compliance met per ISO 10993-1)Biocompatibility (mutagenicity).
    Intracutaneous Reactivity(Compliance met per ISO 10993-1)Biocompatibility.
    Acute Systemc Toxicity(Compliance met per ISO 10993-1)Biocompatibility.
    Material Mediated Pyrogenicity(Compliance met per ISO 10993-1)Biocompatibility.
    Hemolysis (Direct and Indirect)(Compliance met per ISO 10993-1)Biocompatibility.
    Complement SC5b-9(Compliance met per ISO 10993-1)Biocompatibility.
    In Vivo Thrombogenicity(Compliance met per ISO 10993-1)Biocompatibility.
    Pre-clinical testing (Animal Study):
    Clear Image Length (CIL)"no significant differences between the subject device and the predicate device"Directly relates to imaging performance.
    Device Performance (system stability, ease of operation, usability of sterile cover and PIU, catheter crossability, catheter vulnerability, catheter marker visualization)"no significant differences between the subject device and the predicate device"Relates to practical usability and image quality.
    In vivo thrombus formation"no significant differences between the subject device and the predicate device"Safety.
    Safety"no significant differences between the subject device and the predicate device"Overall safety.

    Crucially, this submission does not describe acceptance criteria or performance for an AI algorithm's interpretation of images. It focuses on the hardware's ability to produce images and the catheter's physical characteristics. If there were an AI component for image analysis (e.g., automated lumen segmentation, plaque characterization), specific performance metrics (e.g., accuracy, sensitivity, specificity, Dice score for segmentation) would be listed here, along with their acceptance thresholds. This information is not present in the provided document.


    Specific Study Details (as inferable from the document, with noted gaps):

    Since the document focuses on showing substantial equivalence through non-clinical and pre-clinical tests, and explicitly states "No clinical study is included in this submission," most of the questions about AI algorithm performance studies cannot be answered from this text.

    2. Sample size used for the test set and the data provenance:
    * Test Set Sample Size: Not specified for a data-driven algorithm test set. The pre-clinical animal study "conducted to support substantial equivalence" did involve a "test set" of animal cases, but the exact number of animals or images generated from that study is not provided.
    * Data Provenance: The animal study is an in vivo (likely prospective) study, but the country of origin is not specified. It's safe to assume it was conducted under the company's control, likely in China given their location.
    * Retrospective/Prospective: The biological and pre-clinical studies were prospective tests on either ex-vivo materials or in-vivo animal models.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
    * Not Applicable / Not Specified: The ground truth for the biological and physical properties was established by adherence to ISO standards and direct measurements. For the animal study performance metrics, "no significant differences" were found, implying comparison to a predicate device or expert assessment, but the number or qualifications of experts involved in this specific assessment are not detailed. An AI study would typically involve expert readers.

    4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
    * Not Applicable / Not Specified: For the physical and biological tests, adjudication methods are not relevant. For the animal study, it's not specified how the "no significant differences" conclusion was reached, or if formal adjudication was used for subjective performance measures like "ease of operation."

    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:
    * No MRMC Study: The document explicitly states: "No clinical study is included in this submission." Therefore, no MRMC study comparing human readers with and without AI assistance was performed or reported here.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
    * Not Indicated: The submission does not describe any standalone algorithm performance testing. This suggests that the device, as cleared, does not include an AI algorithm that performs any automated image analysis or diagnosis requiring such testing. The "Software Features for Imaging" mentioned seem to refer to basic imaging display and system control, not AI.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
    * Defined Standards/Measurements & Comparative Animal Study:
    * For the physical and biological tests, ground truth was implicitly defined by the relevant ISO standards (e.g., ISO 10993-1) and direct physical measurements.
    * For the pre-clinical animal study, the "ground truth" was the observed performance of the device and its direct comparison to a predicate device (e.g., "Clear Image Length (CIL)" and "in vivo thrombus formation"). This is an in-vivo assessment.

    8. The sample size for the training set:
    * Not Applicable / Not Specified: Since no AI algorithm training is described, there is no mention of a training set.

    9. How the ground truth for the training set was established:
    * Not Applicable / Not Specified: As no AI training data is mentioned, the method for establishing its ground truth is also not.


    Conclusion:

    The provided FDA 510(k) summary focuses on demonstrating the substantial equivalence of the Cornaris Intravascular Imaging System and LumenCross Imaging Catheter to existing predicate devices based on physical, mechanical, optical, biological, and pre-clinical animal performance. It does not present any information related to the performance of an artificial intelligence (AI) component for image interpretation or analysis. Therefore, it cannot address the questions concerning acceptance criteria and study details for an AI algorithm's performance. The "device performance" described pertains to the system's ability to acquire and display images, and the catheter's physical safety and functionality, rather than any automated interpretive function.

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    K Number
    K243016

    Validate with FDA (Live)

    Manufacturer
    Date Cleared
    2025-03-20

    (174 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Starlight Imaging Catheter with Hyper Vue Imaging System is intended for imaging of coronary arteries and is indicated in patients who are candidates for transluminal interventional procedures.

    The Starlight Imaging Catheter is intended for use in vessels 2.0 to 5.2 mm in diameter.

    The Starlight Imaging Catheter is not intended for use in a target vessel which has undergone a previous bypass procedure.

    Device Description

    The Starlight Imaging Catheter is a sterile, single-use, non-pyrogenic device and consists of two main assemblies: the catheter body and the internal rotating fiber optic imaging core. The catheter has an insertable length of 141 cm and a 2.5 Fr imaging window. It is a rapid exchange design with monorail tip, designed for compatibility with 0.014" (0.355mm) steerable guidewires used during coronary interventional procedures.

    The Starlight Imaging Catheter connects to the HyperVue Imaging System through the HyperVue Controller (Controller), a reusable catheter connection allowing direct control of basic data acquisition. All fiber optic rotation and translational pullback is driven by the Controller and occurs inside the catheter.

    AI/ML Overview

    The provided text is a 510(k) summary for the Starlight Imaging Catheter. It discusses the device's substantial equivalence to a predicate device and details performance testing. However, it does not contain the specific information requested in your prompt regarding acceptance criteria, reported device performance, sample sizes for test and training sets, data provenance, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance.

    The summary states that no clinical testing was provided in this pre-market notification (Section 7.9), and usability evaluation testing was not required for the modifications (Section 7.8). This indicates that the device's performance against specific clinical acceptance criteria, as evaluated through human-in-the-loop or standalone algorithm studies with detailed ground truth establishment, is not described in this document.

    The performance testing described (Sections 7.1-7.7) includes:

    • Bench testing: Optical performance, catheter deliverability, pullback performance, trackability, kink resistance, tensile strength. These tests were performed using "well-established methods used for the predicate devices."
    • Biocompatibility testing: In accordance with ISO 10993-1.
    • Animal testing: Performed in 3 porcine models (18 imaging passes) to evaluate vascular injury, thrombogenicity, device safety, and device performance.

    Therefore, I cannot provide the requested table and details because the information is not present in the provided document.

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    K Number
    K242239

    Validate with FDA (Live)

    Manufacturer
    Date Cleared
    2024-08-16

    (17 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Gentuity® HF-OCT Imaging System with Vis-Rx® Micro-Imaging Catheter is intended for intravascular imaging and is indicated for use in coronary arteries in patients who are candidates for transluminal procedures. The Vis-Rx Micro-Imaging Catheter is intended for use in vessels 1.3 to 6.0 mm in diameter. The Vis-Rx Micro-Imaging Catheter is also intended for use prior to or following transluminal interventional procedures. The Vis-Rx Micro-Imaging Catheter is not intended for use in a target vessel that has undergone a previous bypass procedure.

    Device Description

    The Gentuity® Imaging System provides images of the coronary arteries in patients who are candidates for transluminal interventional procedures. The system utilizes fiber-optic technology to deliver near-infrared light and receive light reflected from coronary tissue to produce high resolution, real-time images. The Gentuity Imaging System consists of the following components:

      1. The Gentuity Imaging Console: A mobile system that houses the Optical Engine, the Computer and application software, and the Probe Interface Module (PIM). It also includes two monitors, keyboard, mouse, and cord storage as well as external interfaces to the system. The PIM provides the interconnection between the Gentuity Imaging Console and the Vis-Rx® Catheter.
      1. Vis-Rx® Micro-Imaging Catheter: The Vis-Rx catheter is a sterile, single-use catheter that consists of an external sheath and an optical imaging core. The external sheath facilitates placement of the device into the coronary artery, and houses the optical imaging core. An optical fiber and lens assembly rotates inside the optical imaging core. The optical fiber and lens deliver near-infrared light to the tissue and receive reflected light. The Vis-Rx catheter is a rapid exchange design, compatible with an 0.014″ guidewire. The catheter attaches to the PIM, which is mounted outside the sterile field on the table bed rail. A sterile 3 ml purge syringe is provided with the Vis-Rx catheter.
      1. Optional Gentuity Review Station: The Gentuity Review Station (GRS) is an optional standalone computer with the Gentuity application software that provides analysis and review capabilities similar to what may be performed on the Gentuity Console. The GRS allows physicians to review images for research, presentation and publication preparation outside the catheterization lab without the Gentuity Console.
    AI/ML Overview

    The provided document (K242239) is a 510(k) summary for the Gentuity® HF-OCT Imaging System with Vis-Rx® Micro-Imaging Catheter. This particular 510(k) states that "No additional non-clinical and clinical performance testing was required to support review of this 510(k) Premarket Notification" as the proposed device is identical to the predicate device (K230620).

    Therefore, the acceptance criteria and study information would be found in the 510(k) for the predicate device (K230620), not in the provided document (K242239).

    As this document does not contain the information requested regarding acceptance criteria and performance testing for the current device, I cannot provide an answer based solely on the provided text.

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    K Number
    K240610

    Validate with FDA (Live)

    Device Name
    deepLive
    Manufacturer
    Date Cleared
    2024-07-09

    (126 days)

    Product Code
    Regulation Number
    892.1560
    Age Range
    All
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticPediatricDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    deepLive is intended to be used as a non-invasive imaging tool in the evaluation of external human tissue microstructure by providing three-dimensional, cross-sectional and en-face real-time depth visualization for assessment by physicians to support in forming a clinical judgment.

    Device Description

    deepLive was designed for an easy integration into clinical practices. The device is composed of:

    • A. A mobile cart, allowing the user to move the whole device and including a cart tablet for accessories.
    • B. A touchscreen, fixed on the cart mast, displaying the software interfaces to the user.
    • C. A hand-held probe, integrating the LC-OCT imaging system (interferometric microscope, OCT camera). The probe is connected to the CPU front panel by a sheathed cable bundle, and stored in a dedicated probe-holder fixed on the cart tablet. The probe is the interface between the device, the doctor and the patient: its measuring head (tip) must be positioned in contact with the patient's skin.
    • D. A central power unit (CPU), mounted on the cart, integrating various imaging and electronic peripherals (laser, computer, electronic cards, drivers, power supplies, etc.), driving and powering the imaging probe.
    • E. A software running on the device's computer, which controls the components of the system, acquires and processes images, and provides user interfaces for performing examinations and managing data.

    deepLive hardware interfaces are located on the front-panel of the CPU. Input/output connections include:

    • 1 Display port to connect the screen
    • · 3 USB ports to connect external drives (Wifi key, hard drive disk, etc.)

    deepLive software runs on a computer embedded in the CPU of the device. The computer uses Windows Enterprise LTSC operating system. The software executable and all dynamic libraries needed for program execution are deployed at a specific location in the file system.

    The secured access to the computer operating system, deepLive software and data folders are managed by Windows sessions authentication system. The computer hosting deepLive is also likely to have applications installed by DAMAE Medical:

    • · Synology Drive: used to retrieve device data for maintenance and software improvement purposes.
    • TeamViewer: remote control software used for software manual update and software issues solving.
    AI/ML Overview

    The provided text is an FDA 510(k) clearance letter and associated summary for the deepLive device. It outlines the device's characteristics, indications for use, and a comparison to a predicate device. However, it does not contain the detailed information necessary to fully address all parts of your request regarding acceptance criteria and the comprehensive study that proves the device meets these criteria.

    Specifically, the document states: "Safety and performance of the deepLive device have been evaluated and verified in accordance with product and software specifications and applicable performance standards through verification, validation, nonclinical performance, and safety testing." and "Verification, validation, nonclinical performance, and safety test results established that the device meets its design requirements and indications for use, that it is as safe and as effective as the predicate device, and that no new questions of safety and effectiveness have been raised." However, it does not provide specific numerical acceptance criteria or the reported performance data from these tests in a detailed manner. There's also no mention of a clinical human-in-the-loop study (MRMC) or an AI-specific standalone performance study.

    Given the information provided in the input, here's what can be extracted and what cannot:


    Acceptance Criteria and Study for deepLive Device

    The deepLive device is an imaging system, not an AI/ML diagnostic tool in the sense that would require typical AI performance metrics like sensitivity, specificity, AUC, or reader studies for decision-making support. Its "performance" in this context primarily refers to its imaging capabilities, technical specifications, and safety.

    Since the document does not provide a table of acceptance criteria and reported device performance related to a diagnostic task or specific image interpretation metrics, it's impossible to create such a table in the requested format. The performance testing section broadly states that the device was evaluated according to product and software specifications and applicable standards, and that it met its design requirements.

    Here's a breakdown of what can be answered based on the provided text:

    1. A table of acceptance criteria and the reported device performance

    • Acceptance Criteria (Implicit): The text states that "Safety and performance of the deepLive device have been evaluated and verified in accordance with product and software specifications and applicable performance standards through verification, validation, nonclinical performance, and safety testing." and that "Verification, validation, nonclinical performance, and safety test results established that the device meets its design requirements and indications for use..." This implies the acceptance criteria were met internally based on design requirements, but these specific requirements and corresponding performance values are not detailed in the publicly available 510(k) summary.

    • Reported Device Performance: The document provides technical specifications of the deepLive device and compares them to the predicate device. These are performance characteristics of the imaging system itself, rather than performance on a diagnostic task (e.g., classifying disease).

      ParameterAcceptance Criteria (Implied: "Meets or Exceeds Predicate/Design Specs")Reported Device Performance (deepLive)Predicate Device (VivoSight Dx)Substantially Equivalent?
      Imaging ModalityBe OCTOptical Coherence TomographyOptical Coherence TomographyYes
      Near Infrared WavelengthYes (700-1400mm)YesYesYes
      Light Source WavelengthCompatible for imaging800 nm1305 nmYes
      Frame Rate (B-scan)Adequate for real-time imaging8 fps5 fpsYes
      Frame Rate (A-scan)Adequate for real-time imaging8 fpsN/A (not specified for Pred.)Yes
      Lateral Resolution≤ Predicate Resolution for comparable detail1.3 μm7.5 μmYes (deepLive is superior)
      Axial Resolution≤ Predicate Resolution for comparable detail1.1 μm10 μmYes (deepLive is superior)
      Lateral Scanning RangeAdequate for tissue assessment1.2 mm6 mmYes
      Axial Scanning RangeAdequate for tissue assessment0.5 mm1 mmYes
      Optical SafetyClass 1 medical deviceClass 1Class 1Yes

    2. Sample sized used for the test set and the data provenance

    • The document mentions "verification, validation, nonclinical performance, and safety testing" but does not provide sample sizes for any test sets (e.g., number of images, patients, or tissue samples).
    • Data provenance is not specified. The type of device (optical coherence tomography for external human tissue microstructure) suggests that if human data was used for validation of imaging quality, it would likely be prospective clinical data, but this is speculative given the lack of detail. There is no indication of country of origin.

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

    • This information is not provided because the nature of the device's clearance appears to be based on technical specifications and safety rather than a diagnostic performance study requiring expert ground truth beyond device design verification.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    • This information is not applicable/not provided as no diagnostic ground truth establishment process is described.

    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

    • No MRMC study is mentioned. The device is described as an "imaging tool" for physicians to assess and support clinical judgment, but there is no mention of an AI component that assists human readers or an evaluation of such assistance.

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

    • No standalone algorithm performance study is mentioned. The device provides image visualization; it is not presented as an AI algorithm making diagnoses.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

    • For the technical specifications, the "ground truth" would be engineering measurements and adherence to specified performance metrics. For safety, it would be compliance with international standards (IEC, EN, ASTM, ISO listed in the document). There is no mention of clinical ground truth (e.g., pathology, outcomes) in the context of a diagnostic performance study.

    8. The sample size for the training set

    • Not applicable/not provided. The document describes the device as an imaging system, not explicitly an AI/ML model that would require a "training set" in the context of machine learning.

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

    • Not applicable/not provided for the same reason as point 8.
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