Document Detail


Spatiotemporal correlation analyses: a new procedure for standardisation of DC magnetocardiograms.
MedLine Citation:
PMID:  17061938     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
There is a lack of standard methods for the analysis of magnetocardiograms (MCGs). MCG signals have a shape similar to the ECG (P wave, QRS complex, T wave). High-quality multichannel recordings can indicate even slight disturbances of de- and repolarisation. The purpose of our study was to apply a new approach in the analysis of signal-averaged DC-MCGs. DC-MCGs (31-channel) were recorded in 182 subjects: 110 patients after myocardial infarction and 72 controls. Spatiotemporal correlation analysis of the QRS complex and T wave patterns throughout the entire heart cycle was used to analyse homogeneity of de- and repolarisation. These plots were compared to standard ECG analyses (electrical axis, Q wave, ST deviation, T polarity and shape). Spatiotemporal correlation analyses seem to be applicable in assessing the course of electrical repolarisation with respect to homogeneity. MCG provided all diagnostic information contained in common ECG recordings at high significance levels. The ECG patterns were included in 5/8 of our parameters for electrical axis, 6/8 for Q-wave, 7/8 for ST deviation and 5/8 for T-polarity based on two time series of correlation coefficients. We conclude that our spatiotemporal correlation approach provides a new tool for standardised analysis of cardiac mapping data such as MCG.
Authors:
Matthias Goernig; Christian Tute; Mario Liehr; Stephan Lau; Jens Haueisen; Hans R Figulla; Uwe Leder
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Biomedizinische Technik. Biomedical engineering     Volume:  51     ISSN:  0013-5585     ISO Abbreviation:  Biomed Tech (Berl)     Publication Date:  2006 Oct 
Date Detail:
Created Date:  2006-10-25     Completed Date:  2006-12-26     Revised Date:  2010-11-05    
Medline Journal Info:
Nlm Unique ID:  1262533     Medline TA:  Biomed Tech (Berl)     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  198-200     Citation Subset:  IM    
Affiliation:
Department of Internal Medicine I, Friedrich Schiller University, Jena, Germany. matthias.goernig@med.uni-jena.de
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Body Surface Potential Mapping / methods,  standards
Diagnosis, Computer-Assisted / methods*,  standards*
Female
Germany
Humans
Magnetocardiography / methods*,  standards*
Male
Middle Aged
Myocardial Infarction / complications,  diagnosis*
Reproducibility of Results
Sensitivity and Specificity
Statistics as Topic

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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