Magnetocardiograms early detection of pulmonary arterial hypertension using inverse problem analysis in rat model

Shotaro Yasuda, Sho Higano, Atsushi Ishiyama, Yumie Ono, Ichige Kajimura, Susumu Minamisawa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Utilizing small animal magnetocardiograms (MCG), we have developed a diagnostic method to detect the development of pulmonary hypertension (PH) in a rat heart. We obtained multiple MCG of rats with monocrotaline-induced PH and monitored the development of pathophysiological conditions. Current dipole estimation was then applied to determine the association between abnormal propagation of the cardiac excited wavefront and disease states. The progress of right ventricular hypertrophy correlated with a decrease in the angles of the current dipoles during R and S waves. In addition, clear changes in the current dipole angles during S waves were observed 9-19 days before the availability of echocardiographic diagnosis of the PH. Our results showed, using a rat PH model, that continuous monitoring of myocardial conditions allows PH to be detected at an earlier stage than echocardiographic screening.

    Original languageEnglish
    Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages4475-4478
    Number of pages4
    Volume2015-November
    ISBN (Print)9781424492718
    DOIs
    Publication statusPublished - 2015 Nov 4
    Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
    Duration: 2015 Aug 252015 Aug 29

    Other

    Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
    Country/TerritoryItaly
    CityMilan
    Period15/8/2515/8/29

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition
    • Signal Processing
    • Biomedical Engineering
    • Health Informatics

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