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Kurtosis as a statistical approach to identify the pivot point of the rotor

Shivaram P Arunachalam, Elizabeth M Annoni, Siva K Mulpuru

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 9, 2017
    PubMed

    Insights

    A novel Kurtosis mapping technique accurately identifies rotor pivot points in atrial fibrillation (AF), offering a new approach for persistent AF patients. Further clinical studies are needed for validation.

    Area of Science:

    • Cardiology
    • Medical Imaging
    • Computational Biology

    Background:

    • Atrial fibrillation (AF) is a common cardiac arrhythmia linked to stroke, affecting millions.
    • Current catheter ablation methods struggle with persistent AF due to limitations in mapping AF substrates beyond the pulmonary veins.

    Purpose of the Study:

    • To develop and validate a novel Kurtosis-based mapping technique for identifying atrial fibrillation rotor pivot points.
    • To assess the efficacy of Kurtosis mapping in distinguishing rotor cores from peripheral areas in cardiac electrograms.

    Main Methods:

    • Development of a Kurtosis-based mapping algorithm.
    • Application of the technique to ex-vivo isolated rabbit hearts with induced rotors.
    • Analysis of Kurtosis values to identify rotor pivot points based on signal chaoticity.

    Main Results:

    • The Kurtosis technique accurately identified rotor pivot points in ex-vivo rabbit hearts.
    • Higher Kurtosis values were observed at rotor pivot points compared to peripheral regions, indicating chaotic signal dynamics.
    • The method shows potential for identifying AF substrates in patient data.

    Conclusions:

    • Kurtosis-based mapping is a promising novel technique for identifying atrial fibrillation rotor pivot points.
    • This method could enhance catheter ablation success rates for persistent AF patients by improving substrate visualization.
    • Clinical validation with patient data is essential to confirm the efficacy of this 3D mapping technology.

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