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510(k) Data Aggregation

    K Number
    K092004
    Manufacturer
    Date Cleared
    2009-08-25

    (54 days)

    Product Code
    Regulation Number
    892.1650
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K052412, K050489, K060259, K061163, K083745, K031836

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

    The Innova systems are indicated for use in generating fluoroscopic images of human anatomy for vascular angiography, diagnostic and interventional procedures, and optionally, rotational imaging procedures. They are also indicated for generating fluoroscopic images of human anatomy for cardiology, diagnostic, and interventional procedures. They are intended to replace fluoroscopic images obtained through image intensifier technology. These devices are not intended for mammography applications.

    Device Description

    The Innova 4100 IQ, 3100 IQ, 2100 IQ Systems are modified with an optional software feature called StentViz. The StentViz feature enhances the visibility of stents in the x-ray images produced by the Innova systems. Specifically, StentViz provides an enhanced static image of the stent that is derived from the video image sequence as recorded during fluoroscopic guidance. It does not provide real-time guidance.

    AI/ML Overview

    The information provided focuses on demonstrating substantial equivalence to predicate devices rather than establishing specific acceptance criteria and detailed performance studies for the StentViz feature itself. Therefore, many of the requested details about acceptance criteria, sample sizes, expert involvement, and ground truth establishment are not explicitly stated in the provided text.

    Here's a breakdown of the available information:

    1. Table of Acceptance Criteria and Reported Device Performance:

    The document does not explicitly present a table of acceptance criteria with numerical targets. Instead, it relies on a qualitative comparison to predicate devices and general statements about image enhancement.

    Acceptance Criteria (Implied)Reported Device Performance
    Enhanced visibility of stents (compared to Innova without StentViz)Bench tests were performed "to assess the enhancement of stent visibility." The text states, "When StentViz is used, the image quality and visibility of the stent is improved."
    Comparable image quality/stent enhancement to predicate devices (StentOp and StentBoost)Bench tests were performed "to compare the performance of the Innova with StentViz to... the performance of the similar feature contained in the predicate device StentOp." The document concludes, "The image quality of the stent is enhanced in a comparable way with StentViz than with StentOp and StentBoost." Its performance is "substantially equivalent to the predicate devices."
    No adverse impact on safety or effectivenessThe improvement "does not adversely impact safety or effectiveness."
    Compliance with voluntary standardsThe Innova systems with StentViz comply with voluntary standards as detailed in Sections 9 and 17 of the premarket submission (details not provided in the extract).

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

    • Sample Size: "Bench tests were performed based on a library of clinical images." The exact number of images in this "library" is not specified.
    • Data Provenance: The document does not specify the country of origin of the data or whether it was retrospective or prospective. It only mentions "clinical images."

    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 in the document. The evaluation of "enhancement of stent visibility" appears to have been part of bench testing, but who performed these assessments and their qualifications are not mentioned.

    4. Adjudication method for the test set:

    • This information is not provided.

    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:

    • A MRMC comparative effectiveness study is not explicitly mentioned. The evaluation described is "bench tests" to assess enhancement and perform comparisons. The document does not discuss human reader performance or improvement with AI assistance (StentViz).

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

    • The evaluation was a "bench test" comparing the StentViz feature to the Innova without StentViz and to a predicate device's feature (StentOp). While human eyes would ultimately interpret the enhanced images, the description of "bench tests... to assess the enhancement of stent visibility" and compare performance suggests an evaluation of the algorithm's output (the enhanced image) itself, making it akin to a standalone performance assessment of the image enhancement capability. However, it's not explicitly stated as "algorithm only without human-in-the-loop performance" in the strict sense of a diagnostic task.

    7. The type of ground truth used:

    • The document mentions "a library of clinical images" being used for bench tests to assess "enhancement of stent visibility." The "ground truth" for assessing this enhancement is not explicitly defined. It likely relied on a subjective or objective assessment of image clarity and stent outline on the enhanced images compared to unenhanced images or images from predicate devices. There is no mention of pathology, or outcomes data being used as ground truth for this enhancement feature.

    8. The sample size for the training set:

    • The document does not provide information about a specific training set. The StentViz is described as an "optional software feature" that "enhances the visibility of stents." The development process mentioned includes "Risk Analysis, Requirements Reviews, Design Reviews, Testing on unit level (Module verification), Integration testing (System verification), Final acceptance testing (Validation), Performance testing (Verification), Safety testing (Verification)." This suggests a standard software development and testing cycle rather than a machine learning model that would typically have a distinct "training set."

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

    • As no specific training set for a machine learning model is mentioned, this information is not applicable/provided. The feature development would have followed established engineering principles for image processing, not a typical machine learning training paradigm with a labeled ground truth dataset.
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    K Number
    K091658
    Manufacturer
    Date Cleared
    2009-06-29

    (20 days)

    Product Code
    Regulation Number
    892.1650
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K052412, K050489, K060259, K061163

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

    The Innova systems are indicated for use in generating fluoroscopic images of human anatomy for vascular angiography, diagnostic and interventional procedures, and optionally, rotational imaging procedures. They are also indicated for generating fluoroscopic images of human anatomy for cardiology, diagnostic, and interventional procedures. They are intended to replace fluoroscopic images obtained through image intensifier technology. These devices are not intended for mammography applications.

    Device Description

    The Innova series digital fluoroscopy systems labeling is modified to allow the use of this device in an Operating Room environment that is suitable for this device. The device is suitable for Interventional XRAY procedures (catheter, needle, Minimally Invasive Surgery ) and can be used either in an Interventional Room (i.e. Cath Lab) or in an Operating Room Environment. The device is not suitable to do surgical procedures (ie. open surgery).

    AI/ML Overview
    1. Table of Acceptance Criteria and Reported Device Performance:

      The submission does not provide a table of acceptance criteria or quantitative performance metrics for the device itself. Instead, it focuses on the device's substantial equivalence to predicate devices based on a labeling change.

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

      • Sample Size: Not applicable. The submission explicitly states, "There is no clinical testing for this modification since the intended use, indications for use and other product specifications do not change."
      • Data Provenance: Not applicable. No new clinical or performance data was generated for this specific modification.
    3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications:

      Not applicable. No new test set requiring expert ground truth was used.

    4. Adjudication Method for the Test Set:

      Not applicable. No new test set was adjudicated.

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

      No. The submission explicitly states, "The subject of this Premarket submission, Innova in Operating room environment, did not require clinical studies to support substantial equivalence." Therefore, no MRMC study was conducted.

    6. Standalone (Algorithm Only) Performance Study:

      No. This submission is for a medical device (digital fluoroscopy system) whose labeling was modified, not a standalone algorithm. The device's performance is considered substantially equivalent to its predicate devices, which were previously cleared.

    7. Type of Ground Truth Used:

      Not applicable. No new ground truth was established for this submission. The ground truth for the predicate devices' initial clearance would have been established, but this information is not part of this specific submission.

    8. Sample Size for the Training Set:

      Not applicable. This submission is for a labeling modification to an existing device, not for the development of a new algorithm or system requiring a training set.

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

      Not applicable. No training set was used.

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