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510(k) Data Aggregation

    K Number
    K233433
    Manufacturer
    Date Cleared
    2024-08-07

    (300 days)

    Product Code
    Regulation Number
    870.1220
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Sphere-9Dx Diagnostic Catheter (AFR-00009)

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

    The Sphere-9Dx Diagnostic Catheter is indicated for electrophysiological mapping (recording and stimulation) of cardiac structures in the heart. This catheter is intended to obtain electrograms in the atrial regions of the heart. The catheter provides location information when used with a compatible Affera Mapping System.

    Device Description

    The Sphere-9Dx Diagnostic catheter (AFR-00009) is a steerable irrigated multi-electrode catheter with a bidirectional deflecting tip intended for intracardiac mapping (stimulation and recording). The catheter includes an expandable lattice electrode array that fits a 2.7 mm (8 Fr) straight introducer sheath or a 2.8 mm (8.5 Fr) curved or deflectable sheath and expands to a 9.3 mm diameter in the cardiac chamber. The catheter is supplied with an insertion tool that must be used to aid in collapsing the expandable lattice electrode array for insertion into an introducer or guiding sheath. The expandable lattice electrode array contains 9 mini surface electrodes mounted on its surface with roughly 5 mm spacing to collect local electrograms and monitor local impedance. All mini surface electrodes may be used for recording or stimulation.

    AI/ML Overview

    Here's an analysis of the acceptance criteria and study information for the Sphere-9Dx Diagnostic Catheter, based on the provided document:

    This document is a 510(k) summary, which typically focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed report of a single, comprehensive study with specific performance metrics and AI efficacy. Therefore, a lot of the requested information (especially concerning AI-specific metrics, ground truth details for training, and MRMC studies) is not present in this type of regulatory submission.

    1. Table of Acceptance Criteria and Reported Device Performance

    The document states that "all acceptance criteria were met," but it does not provide a table with specific acceptance criteria values or detailed performance metrics. It lists categories of testing performed.

    Acceptance Criteria CategoryReported Device Performance
    Design Verification Testing"All acceptance criteria were met"
    Design Validation"All acceptance criteria were met"
    Summative Usability Evaluation"All acceptance criteria were met"
    Pre-clinical Animal Testing"All acceptance criteria were met"
    Biocompatibility Testing"All acceptance criteria were met"
    Sterilization Validation and Adoption"All acceptance criteria were met"
    Packaging Validation"All acceptance criteria were met"
    Overall Safety and Effectiveness Claim"No questions of safety or effectiveness are raised as a result of the testing, and the subject device is considered substantially equivalent to the predicate device based on the performance data collected. The subject and predicate devices share the same intended use and have similar underlying technological characteristics... Differences between the subject and predicate devices do not result in differences in overall device performance or fundamental scientific technology, and the subject device is considered substantially equivalent to the predicate device."

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

    The document does not specify the sample sizes for the test sets within each testing category (Design Verification, Design Validation, Usability, etc.). It also does not explicitly state the data provenance (e.g., country of origin) or whether the data was retrospective or prospective. Pre-clinical animal testing suggests prospective animal data, but details are not provided.

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

    This information is not provided in the document. For a diagnostic catheter, "ground truth" would likely be established through clinical observation, correlation with other diagnostic modalities, or expert interpretation of electrograms. However, the details of how this was done for testing, including the number and qualifications of experts, are absent.

    4. Adjudication Method for the Test Set

    The document does not describe any specific adjudication methods (e.g., 2+1, 3+1) for establishing ground truth or resolving discrepancies in test results.

    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

    The document does not mention an MRMC study or any information related to AI assistance for human readers. This device is a diagnostic catheter for electrophysiological mapping, and the summary focuses on its hardware and basic functionality, not on software with AI capabilities that would directly assist human interpretation in a comparative effectiveness study.

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

    This study is not described. The device, a diagnostic catheter, functions to obtain electrograms and location information when used with a compatible Affera Mapping System. It's not an AI algorithm performing diagnostic interpretation independently.

    7. The Type of Ground Truth Used

    The document does not explicitly state the type of ground truth used for each test. For a diagnostic catheter, ground truth for electrophysiological mapping would generally involve confirmed anatomical locations, known electrical activity patterns, or correlation with established clinical diagnostic methods, likely validated by expert consensus or established physiological principles, especially in pre-clinical studies.

    8. The Sample Size for the Training Set

    The document does not mention a training set. This is consistent with the device being a hardware catheter rather than a machine learning algorithm that requires a training phase.

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

    Since no training set is mentioned, this information is not applicable and not provided.

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