Document Detail


Three-dimensional mapping of acute ischemic regions using artificial neural networks and tagged MRI.
MedLine Citation:
PMID:  8987266     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Many methods for mapping ischemic myocardial regions by functional analysis have been suggested. However, the complicated relationship between myocardial function and perfusion, and the inherent limitations of the imaging techniques used, have led to a generally low mapping accuracy. We show herein, that highly accurate mapping can be obtained by combining tagged magnetic resonance imaging (MRI), three-dimensional (3-D) analysis, and artificial neural networks. Nine canine hearts with acute ischemia were studied using multiplanar tagged MRI. Twenty-four myocardial cuboids were tagged in each heart and reconstructed in 3-D at end diastole (ED) and end systole (ES). The cuboids were arranged in three slices approximately 1 cm thick and covered most of the left ventricle (LV). Transmural thickening and endocardial area strain were calculated for each cuboid. Applying a post-mortem (PM) analysis, the percent ischemia in each cuboid was estimated using monastral blue dye; the PM analysis served as a "gold standard." An artificial neural network (ANN), designed to estimate the percent ischemia in each cuboid from the functional indexes, was then created. The ANN "learned" the function-ischemia relationship in 192 cuboids taken from eight of the hearts and was asked to estimate the percent ischemia in the 24 cuboids of the ninth heart. The process was repeated nine times, each time using a different heart as test case. The average accuracy of mapping, i.e., the accuracy with which the ANN has mapped the normal and ischemic cuboids using the functional parameters, was 87.5% +/- 7.8 (s.d.). This accuracy was superior to the accuracy obtained by optimal thresholding of the same thickening (80.1%) and endocardial strain (76.9%) data.
Authors:
H Azhari; S Oliker; W J Rogers; J L Weiss; E P Shapiro
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.; Research Support, U.S. Gov't, P.H.S.    
Journal Detail:
Title:  IEEE transactions on bio-medical engineering     Volume:  43     ISSN:  0018-9294     ISO Abbreviation:  IEEE Trans Biomed Eng     Publication Date:  1996 Jun 
Date Detail:
Created Date:  1997-01-28     Completed Date:  1997-01-28     Revised Date:  2009-11-11    
Medline Journal Info:
Nlm Unique ID:  0012737     Medline TA:  IEEE Trans Biomed Eng     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  619-26     Citation Subset:  IM    
Affiliation:
Department of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel. haim@biomed.technion.ac.il
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MeSH Terms
Descriptor/Qualifier:
Animals
Diastole / physiology
Dogs
Image Processing, Computer-Assisted / methods*
Magnetic Resonance Imaging*
Myocardial Ischemia / diagnosis*,  physiopathology
Neural Networks (Computer)*
Nonlinear Dynamics
Predictive Value of Tests
Sensitivity and Specificity
Stress, Mechanical
Systole / physiology
Ventricular Function, Left
Grant Support
ID/Acronym/Agency:
5-FO5-TW04415-02/TW/FIC NIH HHS; HL-17655-16/HL/NHLBI NIH HHS; R01-HL-43722/HL/NHLBI NIH HHS
Comments/Corrections
Erratum In:
IEEE Trans Biomed Eng 1996 Sep;43(9):972

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


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