TY - JOUR
T1 - In-silico heart model phantom to validate cardiac strain imaging
AU - Mukherjee, Tanmay
AU - Usman, Muhammad
AU - Mehdi, Rana Raza
AU - Mendiola, Emilio
AU - Ohayon , Jacques
AU - Lindquist, Diana
AU - Shah, Dipan J.
AU - Sadayappan, Sakthivel
AU - Pettigrew, Roderic I.
AU - Avazmohammadi, Reza
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/10
Y1 - 2024/10
N2 - The quantification of cardiac strains as structural indices of cardiac function has a growing prevalence in clinical diagnosis. However, the highly heterogeneous four-dimensional (4D) cardiac motion challenges accurate “regional” strain quantification and leads to sizable differences in the estimated strains depending on the imaging modality and post-processing algorithm, limiting the translational potential of strains as incremental biomarkers of cardiac dysfunction. There remains a crucial need for a feasible benchmark that successfully replicates complex 4D cardiac kinematics to determine the reliability of strain calculation algorithms. In this study, we propose an in-silico heart phantom derived from finite element (FE) simulations to validate the quantification of 4D regional strains. First, as a proof-of-concept exercise, we created synthetic magnetic resonance (MR) images for a hollow thick-walled cylinder under pure torsion with an exact solution and demonstrated that “ground-truth” values can be recovered for the twist angle, which is also a key kinematic index in the heart. Next, we used mouse-specific FE simulations of cardiac kinematics to synthesize dynamic MR images by sampling various sectional planes of the left ventricle (LV). Strains were calculated using our recently developed non-rigid image registration (NRIR) framework in both problems. Moreover, we studied the effects of image quality on distorting regional strain calculations by conducting in-silico experiments for various LV configurations. Our studies offer a rigorous and feasible tool to standardize regional strain calculations to improve their clinical impact as incremental biomarkers.
AB - The quantification of cardiac strains as structural indices of cardiac function has a growing prevalence in clinical diagnosis. However, the highly heterogeneous four-dimensional (4D) cardiac motion challenges accurate “regional” strain quantification and leads to sizable differences in the estimated strains depending on the imaging modality and post-processing algorithm, limiting the translational potential of strains as incremental biomarkers of cardiac dysfunction. There remains a crucial need for a feasible benchmark that successfully replicates complex 4D cardiac kinematics to determine the reliability of strain calculation algorithms. In this study, we propose an in-silico heart phantom derived from finite element (FE) simulations to validate the quantification of 4D regional strains. First, as a proof-of-concept exercise, we created synthetic magnetic resonance (MR) images for a hollow thick-walled cylinder under pure torsion with an exact solution and demonstrated that “ground-truth” values can be recovered for the twist angle, which is also a key kinematic index in the heart. Next, we used mouse-specific FE simulations of cardiac kinematics to synthesize dynamic MR images by sampling various sectional planes of the left ventricle (LV). Strains were calculated using our recently developed non-rigid image registration (NRIR) framework in both problems. Moreover, we studied the effects of image quality on distorting regional strain calculations by conducting in-silico experiments for various LV configurations. Our studies offer a rigorous and feasible tool to standardize regional strain calculations to improve their clinical impact as incremental biomarkers.
KW - Finite element simulations
KW - Four-dimensional regional strain calculations
KW - In-silico heart phantom
KW - Kinematic benchmark
KW - Validation
KW - Models, Cardiovascular
KW - Humans
KW - Magnetic Resonance Imaging/methods
KW - Heart/diagnostic imaging
KW - Animals
KW - Algorithms
KW - Computer Simulation
KW - Finite Element Analysis
KW - Mice
KW - Phantoms, Imaging
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UR - http://www.scopus.com/inward/citedby.url?scp=85202588307&partnerID=8YFLogxK
U2 - 10.1016/j.compbiomed.2024.109065
DO - 10.1016/j.compbiomed.2024.109065
M3 - Article
C2 - 39217965
AN - SCOPUS:85202588307
SN - 0010-4825
VL - 181
SP - 109065
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
M1 - 109065
ER -