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510(k) Data Aggregation

    K Number
    K060307
    Device Name
    12 RL ALGORITHM
    Date Cleared
    2006-08-04

    (178 days)

    Product Code
    Regulation Number
    870.2300
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The GE 12RL program generates a 12-lead ECG report from a subset of the electrodes used to acquire a standard 12 lead ECG. Four of the precordial channels of the 12-lead ECG (V2, V3, V4, V6) are not acquired from the patient; rather, they are reconstructed from information that is directly recorded in the other channels of the 12-lead ECG.

    The four signals generated by the GE 12RL program are similar but not identical to the standard 12-lead ECG. All ECG data generated via 12RL are clearly identified as to which channels have been synthesized.

    The GE 12RL program is intended for use in a monitoring environment. Computerized measurements may be generated from these data; however, a computerized interpretation will not.

    The product is intended for use in the general adult population ranging from healthy subjects to patients with cardiac and/or non-cardiac abnormalities.

    The product is to be used in conjunction with the patient's clinical history, symptoms, and other diagnostic tests for final clinical judgment.

    Device Description

    The 12RL feature is intended to reconstruct electrocardiograph (ECG) signals such that a 12-lead ECG presentation can be made when at least six electrodes are attached to a patient. These 12-lead ECGs may be 10 second records or continuous recordings suitable for ST segment trending.

    AI/ML Overview

    The provided text is a 510(k) summary for the GE 12RL (Twelve Lead Transformation Function) device, which reconstructs specific ECG leads. However, it does not contain a detailed study description with acceptance criteria and reported device performance. It primarily focuses on regulatory approval, predicate devices, and general statements about safety and effectiveness based on internal quality assurance measures.

    Therefore, I cannot fulfill all parts of your request with the provided input. I will extract the available information and explicitly state where the requested details are missing.

    Here's a breakdown of what can be extracted and what cannot:

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

    • Cannot be provided directly from the text. The document states: "The results of these measurements demonstrated that the 12RL program is as safe, as effective, and performs as well as the predicate device." This is a conclusion, not specific acceptance criteria or performance metrics.

    2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

    • Cannot be provided from the text. The document does not mention any specific test set, sample sizes, or data provenance for a study.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

    • Cannot be provided from the text. There is no mention of an expert panel or ground truth establishment process for a test set.

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

    • Cannot be provided from the text. There is no mention of adjudication for a test set.

    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, an MRMC study was not done, or at least not described. The document implies internal "Software Verification and Validation Testing" and "Risk Analysis" but no external or comparative effectiveness study involving human readers is mentioned. This device reconstructs ECG signals; it does not directly "assist" human readers in the way an AI diagnostic tool might.

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

    • Implied, but not detailed. The "Software Verification and Validation Testing" would likely involve evaluating the algorithm's output against some reference, which is a form of standalone testing. However, no specific details of this testing (e.g., metrics, methodology) are provided. The product description states: "Computerized measurements may be generated from these data; however, a computerized interpretation will not." This confirms it's an algorithm-only output device.

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

    • Cannot be provided from the text. The document does not describe how ground truth was established for any testing. For an ECG signal reconstruction device, "ground truth" would typically be the directly acquired 12-lead ECG signals themselves, against which the reconstructed signals are compared. However, this is not explicitly stated as the methodology.

    8. The sample size for the training set

    • Cannot be provided from the text. No training set or its size is mentioned.

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

    • Cannot be provided from the text. No training set or ground truth establishment for it is mentioned.

    Summary of Available Information:

    The document describes the GE 12RL (Twelve Lead Transformation Function) device, which reconstructs four precordial ECG channels (V2, V3, V4, V6) from other acquired 12-lead ECG channels.

    The regulatory submission primarily relies on:

    • Technology: The 12RL technology is based on linear equations, similar to predicate devices.
    • Quality Assurance Measures:
      • Risk Analysis
      • Requirements Specification Review
      • Code Inspections
      • Software Verification and Validation Testing
    • Conclusion: Based on these measures, the 12RL program is deemed "as safe, as effective, and performs as well as the predicate device."

    Missing Information:
    Crucially, the provided text does not contain any specific acceptance criteria, reported performance metrics, details of a clinical study (sample sizes, data provenance, ground truth establishment, expert qualifications, adjudication methods), or any information regarding AI assistance effects or training set details. The submission focuses on demonstrating substantial equivalence through internal development processes and technological similarity to predicate devices rather than a detailed performance study with quantitative results against specific criteria.

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