TY - JOUR
T1 - Image-based estimation of ventricular fiber orientations for personalized modeling of cardiac electrophysiology
AU - Vadakkumpadan, Fijoy
AU - Arevalo, Hermenegild
AU - Ceritoglu, Can
AU - Miller, Michael
AU - Trayanova, Natalia
N1 - Funding Information:
Manuscript received November 03, 2011; revised January 06, 2012; accepted January 12, 2012. Date of publication January 18, 2012; date of current version May 02, 2012. This work was supported in part by the National Institutes of Health under Grant R01-HL082729 and Grant R01-HL091036, and in part by the National Science Foundation under Grant CBET-0933029. Asterisk indicates corresponding author. *F. Vadakkumpadan is with the Institute for Computational Medicine and the Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205 USA (e-mail: fijoy@jhu.edu).
PY - 2012
Y1 - 2012
N2 - Technological limitations pose a major challenge to acquisition of myocardial fiber orientations for patient-specific modeling of cardiac (dys)function and assessment of therapy. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via semiautomatic segmentation, from an in vivo computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4°. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.
AB - Technological limitations pose a major challenge to acquisition of myocardial fiber orientations for patient-specific modeling of cardiac (dys)function and assessment of therapy. The objective of this project was to develop a methodology to estimate cardiac fiber orientations from in vivo images of patient heart geometries. An accurate representation of ventricular geometry and fiber orientations was reconstructed, respectively, from high-resolution ex vivo structural magnetic resonance (MR) and diffusion tensor (DT) MR images of a normal human heart, referred to as the atlas. Ventricular geometry of a patient heart was extracted, via semiautomatic segmentation, from an in vivo computed tomography (CT) image. Using image transformation algorithms, the atlas ventricular geometry was deformed to match that of the patient. Finally, the deformation field was applied to the atlas fiber orientations to obtain an estimate of patient fiber orientations. The accuracy of the fiber estimates was assessed using six normal and three failing canine hearts. The mean absolute difference between inclination angles of acquired and estimated fiber orientations was 15.4°. Computational simulations of ventricular activation maps and pseudo-ECGs in sinus rhythm and ventricular tachycardia indicated that there are no significant differences between estimated and acquired fiber orientations at a clinically observable level.
KW - Biomedical image processing
KW - Cardiomyocyte
KW - Electrophysiology
KW - Magnetic resonance imaging (MRI)
KW - Patient-specific modeling
KW - Simulation
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U2 - 10.1109/TMI.2012.2184799
DO - 10.1109/TMI.2012.2184799
M3 - Article
C2 - 22271833
AN - SCOPUS:84860655255
SN - 0278-0062
VL - 31
SP - 1051
EP - 1060
JO - IEEE transactions on medical imaging
JF - IEEE transactions on medical imaging
IS - 5
M1 - 6134677
ER -