Document Detail

Noninvasive functional imaging of volumetric cardiac electrical activity: a human study on myocardial infarction.
MedLine Citation:
PMID:  18979848     Owner:  NLM     Status:  MEDLINE    
Identification of infarct substrates provides necessary guidance to the prevention and treatment of cardiac arrhythmias. Compared to diagnostic criteria of body surface potentials (BSP) or electrophysiological information on heart surfaces, the underlying volumetric cardiac electrical activity is of more direct clinical relevance in exhibiting patient-specific arrhythmic dynamics and arrhythmogenic substrates. We have developed a paradigm for noninvasive imaging of volumetric myocardial transmembrane potential from BSPs. In this paper, we present a human study for a patient with acute myocardial infarction. Using patient MRI and BSP data, the framework is able to reconstruct details of the complete arrhythmic electrical activity on the 3D myocardium of the patient. Exploring a subset of the results, the extent, centroid and affected segments of the infarct is correctly evaluated, with comparable performance to existent best results. This human study demonstrates the potential of the presented paradigm as a noninvasive functional imaging technique for patient-specific volumetric cardiac electrical activity in practice.
Linwei Wang; Ken C L Wong; Heye Zhang; Pengcheng Shi
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention     Volume:  11     ISSN:  -     ISO Abbreviation:  Med Image Comput Comput Assist Interv     Publication Date:  2008  
Date Detail:
Created Date:  2008-11-04     Completed Date:  2008-12-09     Revised Date:  2009-12-11    
Medline Journal Info:
Nlm Unique ID:  101249582     Medline TA:  Med Image Comput Comput Assist Interv     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  1042-50     Citation Subset:  IM    
Golisano College of Computing and Information Science Rochester Institute of Technology, Rochester, NY, USA.
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MeSH Terms
Artificial Intelligence
Body Surface Potential Mapping / methods*
Computer Simulation
Heart Conduction System / pathology*,  physiopathology*
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Models, Cardiovascular
Myocardial Infarction / diagnosis*
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity

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

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