TY - JOUR
T1 - Noninvasive electrocardiographic imaging (ECGI)
T2 - Application of the generalized minimal residual (GMRes) method
AU - Ramanathan, Charulatha
AU - Jia, Ping
AU - Ghanem, Raja
AU - Calvetti, Daniela
AU - Rudy, Yoram
N1 - Funding Information:
The authors thank Dr. Bruno Taccardi for the isolated heart and infarction experiments, conducted in his laboratory at the University of Utah. The authors also thank John Burnes, Celeen Khrestian, James Golebiewski, and Jaykumar Sahadevan for their help in conducting the repolarization experiments at Case Western Reserve University. This study was supported by NIH–NHLBI Grant Nos. R37-HL-33343 and R01-HL-49054 to one of the authors (Y.R.). Additional support was provided by a development award from the Whitaker Foundation.
PY - 2003
Y1 - 2003
N2 - Electrocardiographic imaging (ECGI) is a developing imaging modality for cardiac electrophysiology and arrhythmias. It reconstructs epicardial potentials, electrograms, and isochrones from electrocardiographic body-surface potentials noninvasively. Current ECGI methodology employs Tikhonov regularization, which imposes constraints on the reconstructed potentials or their derivatives. This approach can sometimes reduce spatial resolution by smoothing the solution. Accuracy depends on a priori knowledge of solution characteristics and determination of an optimal regularization parameter. These properties led us to implement an independent, iterative approach for ECGI - the generalized minimal residual (GMRes) method - which does not apply constraints. GMRes was applied to experimental data using activation/repolarization of normal and infarcted hearts. GMRes reconstructions were compared to Tikhonov reconstructions and to measured "gold standards" in isolated hearts. Overall, the accuracy of GMRes solutions was similar to Tikhonov regularization. However, in certain cases GMRes recovered localized potential features (e.g., multiple potential minima), which were lost in the Tikhonov solution. Simultaneous use of these two complementary methods in clinical ECGI will ensure reliability and maximal extraction of diagnostic information in the absence of a priori information about a patient's condition.
AB - Electrocardiographic imaging (ECGI) is a developing imaging modality for cardiac electrophysiology and arrhythmias. It reconstructs epicardial potentials, electrograms, and isochrones from electrocardiographic body-surface potentials noninvasively. Current ECGI methodology employs Tikhonov regularization, which imposes constraints on the reconstructed potentials or their derivatives. This approach can sometimes reduce spatial resolution by smoothing the solution. Accuracy depends on a priori knowledge of solution characteristics and determination of an optimal regularization parameter. These properties led us to implement an independent, iterative approach for ECGI - the generalized minimal residual (GMRes) method - which does not apply constraints. GMRes was applied to experimental data using activation/repolarization of normal and infarcted hearts. GMRes reconstructions were compared to Tikhonov reconstructions and to measured "gold standards" in isolated hearts. Overall, the accuracy of GMRes solutions was similar to Tikhonov regularization. However, in certain cases GMRes recovered localized potential features (e.g., multiple potential minima), which were lost in the Tikhonov solution. Simultaneous use of these two complementary methods in clinical ECGI will ensure reliability and maximal extraction of diagnostic information in the absence of a priori information about a patient's condition.
KW - Electrocardiographic inverse problem
KW - Noninvasive arrhythmia diagnosis
KW - Tikhonov regularization
UR - https://www.scopus.com/pages/publications/0042878627
U2 - 10.1114/1.1588655
DO - 10.1114/1.1588655
M3 - Article
C2 - 12918913
AN - SCOPUS:0042878627
SN - 0090-6964
VL - 31
SP - 981
EP - 994
JO - Annals of biomedical engineering
JF - Annals of biomedical engineering
IS - 8
ER -