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Meshless Electrophysiological Modeling of Cardiac Resynchronization Therapy—Benchmark Analysis with Finite-Element Methods in Experimental Data. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12136438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
Computational models of cardiac electrophysiology are promising tools for reducing the rates of non-response patients suitable for cardiac resynchronization therapy (CRT) by optimizing electrode placement. The majority of computational models in the literature are mesh-based, primarily using the finite element method (FEM). The generation of patient-specific cardiac meshes has traditionally been a tedious task requiring manual intervention and hindering the modeling of a large number of cases. Meshless models can be a valid alternative due to their mesh quality independence. The organization of challenges such as the CRT-EPiggy19, providing unique experimental data as open access, enables benchmarking analysis of different cardiac computational modeling solutions with quantitative metrics. We present a benchmark analysis of a meshless-based method with finite-element methods for the prediction of cardiac electrical patterns in CRT, based on a subset of the CRT-EPiggy19 dataset. A data assimilation strategy was designed to personalize the most relevant parameters of the electrophysiological simulations and identify the optimal CRT lead configuration. The simulation results obtained with the meshless model were equivalent to FEM, with the most relevant aspect for accurate CRT predictions being the parameter personalization strategy (e.g., regional conduction velocity distribution, including the Purkinje system and CRT lead distribution).
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2
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Martonová D, Holz D, Duong MT, Leyendecker S. Towards the simulation of active cardiac mechanics using a smoothed finite element method. J Biomech 2020; 115:110153. [PMID: 33388486 DOI: 10.1016/j.jbiomech.2020.110153] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 11/19/2020] [Accepted: 11/23/2020] [Indexed: 01/31/2023]
Abstract
In the last decades, various computational models have been developed to simulate cardiac electromechanics. The most common numerical tool is the finite element method (FEM). However, this method crucially depends on the mesh quality. For complex geometries such as cardiac structures, it is convenient to use tetrahedral discretisations which can be generated automatically. On the other hand, such automatic meshing with tetrahedrons together with large deformations often lead to elements distortion and volumetric locking. To overcome these difficulties, different smoothed finite element methods (S-FEMs) have been proposed in the recent years. They are known to be volumetric locking free, less sensitive to mesh distortion and so far have been used e.g. in simulation of passive cardiac mechanics. In this work, we extend for the first time node-based S-FEM (NS-FEM) towards active cardiac mechanics. Firstly, the sensitivity to mesh distortion is tested and compared to that of FEM. Secondly, an active contraction in circumferentially aligned fibre direction is modelled in the healthy and the infarcted case. We show, that the proposed method is more robust with respect to mesh distortion and computationally more efficient than standard FEM. Being furthermore free of volumetric locking problems makes S-FEM a promising alternative in modelling of active cardiac mechanics, respectively electromechanics.
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Affiliation(s)
- Denisa Martonová
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Applied Dynamics, Immerwahrstraße 1, 91058 Erlangen, Germany.
| | - David Holz
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Applied Dynamics, Immerwahrstraße 1, 91058 Erlangen, Germany
| | - Minh Tuan Duong
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Applied Dynamics, Immerwahrstraße 1, 91058 Erlangen, Germany; Hanoi University of Science and Technology, School of Mechanical Engineering, 1 Dai Co Viet Road, Ha Noi, Viet Nam
| | - Sigrid Leyendecker
- Friedrich-Alexander-Universität Erlangen-Nürnberg, Institute of Applied Dynamics, Immerwahrstraße 1, 91058 Erlangen, Germany
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Peyroteo MMA, Belinha J, Natal Jorge RM. A mathematical biomechanical model for bone remodeling integrated with a radial point interpolating meshless method. Comput Biol Med 2020; 129:104170. [PMID: 33352308 DOI: 10.1016/j.compbiomed.2020.104170] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 12/03/2020] [Accepted: 12/04/2020] [Indexed: 11/18/2022]
Abstract
Bone remodeling is a highly complex process, in which bone cells interact and regulate bone's apparent density as a response to several external and internal stimuli. In this work, this process is numerically described using a novel 2D biomechanical model. Some of the new features in this model are (i) the mathematical parameters used to determine bone's apparent density and cellular density; (ii) an automatic boundary recognition step to spatially control bone remodeling and (iii) an approach to mimic the mechanical transduction to osteoclasts and osteoblasts. Moreover, this model is combined with a meshless approach - the Radial Point Interpolation Method (RPIM). The use of RPIM is an asset for this application, especially in the construction of the boundary maps. This work studies bone's adaptation to a certain loading regime through bone resorption. The signaling pathways of bone cells are dependent on the level of strain energy density (SED) in bone. So, when SED changes, bone cells' functioning is affected, causing also changes on bone's apparent density. With this model, bone is able to achieve an equilibrium state, optimizing its structure to withstand the applied loads. Results suggest that this model has the potential to provide high quality solutions while being a simpler alternative to more complex bone remodeling models in the literature.
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Affiliation(s)
- M M A Peyroteo
- INEGI, Institute of Science and Innovation in Mechanical and Industrial Engineering, Rua Dr. Roberto Frias, 400, 4200-465, Porto, Portugal.
| | - J Belinha
- School of Engineering, Polytechnic of Porto (ISEP), Mechanical Engineering Department, Rua Dr. António Bernardino de Almeida, 431, 4200-072, Porto, Portugal.
| | - R M Natal Jorge
- Faculty of Engineering of the University of Porto, Mechanical Engineering Department, FEUP, Rua Dr. Roberto Frias, S/N, 4200-465, Porto, Portugal.
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Bahia MT, Hecke MB, Mercuri EG. Image-based anatomical reconstruction and pharmaco-mediated bone remodeling model applied to a femur with subtrochanteric fracture: A subject-specific finite element study. Med Eng Phys 2019; 69:58-71. [DOI: 10.1016/j.medengphy.2019.05.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Revised: 04/17/2019] [Accepted: 05/19/2019] [Indexed: 01/25/2023]
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Lluch È, De Craene M, Bijnens B, Sermesant M, Noailly J, Camara O, Morales HG. Breaking the state of the heart: meshless model for cardiac mechanics. Biomech Model Mechanobiol 2019; 18:1549-1561. [DOI: 10.1007/s10237-019-01175-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Accepted: 05/27/2019] [Indexed: 01/30/2023]
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Peyroteo MMA, Belinha J, Dinis LMJS, Natal Jorge RM. A new biological bone remodeling in silico model combined with advanced discretization methods. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2019; 35:e3196. [PMID: 30835964 DOI: 10.1002/cnm.3196] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 02/20/2019] [Accepted: 03/01/2019] [Indexed: 06/09/2023]
Abstract
Bone remodeling remains a highly researched topic investigated by many strands of science. The main purpose of this work is formulating a new computational framework for biological simulation, extending the version of the bone remodeling model previously proposed by Komarova. Thus, considering only the biological aspect of the remodeling process, the action of osteoclasts and osteoblasts is taken into account as well as its impact on bone mass. It is conducted a spatiotemporal analysis of a remodeling cycle obtaining a dynamic behavior of bone cells very similar to the biological process already described in the literature. The numerical example used is based on bone images obtained with scanning electron microscopy. During simulation, it is possible to observe the variation of bone's architecture through isomaps. These maps are obtained through the combination of biological bone remodeling models with three distinct numerical techniques-finite element method (FEM), radial point interpolation method (RPIM), and natural neighbor radial point interpolation method (NNRPIM). A study combining these numerical techniques allows to compare their performance. Ultimately, this work supports the inclusion of meshless methods due to their smoother results and its easiness to be combined with medical images from CT scans and MRI.
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Affiliation(s)
- Madalena M A Peyroteo
- INEGI, Institute of Science and Innovation in Mechanical and Industrial Engineering, Rua Dr. Roberto Frias, 400, 4200-465, Porto, Portugal
- Mechanical Engineering Department, Faculty of Engineering of the University of Porto, FEUP, Rua Dr. Roberto Frias, S/N, 4200-465, Porto, Portugal
| | - Jorge Belinha
- Mechanical Engineering Department, School of Engineering, Polytechnic of Porto (ISEP), Rua Dr. António Bernardino de Almeida, 431, 4200-072, Porto, Portugal
| | - Lucia M J S Dinis
- Mechanical Engineering Department, Faculty of Engineering of the University of Porto, FEUP, Rua Dr. Roberto Frias, S/N, 4200-465, Porto, Portugal
| | - Renato M Natal Jorge
- Mechanical Engineering Department, Faculty of Engineering of the University of Porto, FEUP, Rua Dr. Roberto Frias, S/N, 4200-465, Porto, Portugal
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7
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Peirlinck M, Sack KL, De Backer P, Morais P, Segers P, Franz T, De Beule M. Kinematic boundary conditions substantially impact in silico ventricular function. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2019; 35:e3151. [PMID: 30188608 DOI: 10.1002/cnm.3151] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 08/28/2018] [Accepted: 09/01/2018] [Indexed: 06/08/2023]
Abstract
Computational cardiac mechanical models, individualized to the patient, have the potential to elucidate the fundamentals of cardiac (patho-)physiology, enable non-invasive quantification of clinically significant metrics (eg, stiffness, active contraction, work), and anticipate the potential efficacy of therapeutic cardiovascular intervention. In a clinical setting, however, the available imaging resolution is often limited, which limits cardiac models to focus on the ventricles, without including the atria, valves, and proximal arteries and veins. In such models, the absence of surrounding structures needs to be accounted for by imposing realistic kinematic boundary conditions, which, for prognostic purposes, are preferably generic and thus non-image derived. Unfortunately, the literature on cardiac models shows no consistent approach to kinematically constrain the myocardium. The impact of different approaches (eg, fully constrained base, constrained epi-ring) on the predictive capacity of cardiac mechanical models has not been thoroughly studied. For that reason, this study first gives an overview of current approaches to kinematically constrain (bi) ventricular models. Next, we developed a patient-specific in silico biventricular model that compares well with literature and in vivo recorded strains. Alternative constraints were introduced to assess the influence of commonly used mechanical boundary conditions on both the predicted global functional behavior of the in-silico heart (cavity volumes, stroke volume, ejection fraction) and local strain distributions. Meaningful differences in global functioning were found between different kinematic anchoring strategies, which brought forward the importance of selecting appropriate boundary conditions for biventricular models that, in the near future, may inform clinical intervention. However, whilst statistically significant differences were also found in local strain distributions, these differences were minor and mostly confined to the region close to the applied boundary conditions.
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Affiliation(s)
- Mathias Peirlinck
- Biofluid, Tissue and Solid Mechanics for Medical Applications Lab (IBiTech, bioMMeda), Ghent University, Ghent, Belgium
| | - Kevin L Sack
- Department of Surgery, University of California at San Francisco, San Francisco, CA, USA
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, Observatory, South Africa
| | | | - Pedro Morais
- Lab on Cardiovascular Imaging and Dynamics, Department of Cardiovascular Sciences, KULeuven-University of Leuven, Leuven, Belgium
| | - Patrick Segers
- Biofluid, Tissue and Solid Mechanics for Medical Applications Lab (IBiTech, bioMMeda), Ghent University, Ghent, Belgium
| | - Thomas Franz
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, Observatory, South Africa
- Bioengineering Science Research Group, Engineering Sciences, Faculty of Engineering and the Environment, University of Southampton, Southampton, UK
| | - Matthieu De Beule
- Biofluid, Tissue and Solid Mechanics for Medical Applications Lab (IBiTech, bioMMeda), Ghent University, Ghent, Belgium
- FEops nv, Ghent, Belgium
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Zhang H, Gao Z, Xu L, Yu X, Wong KCL, Liu H, Zhuang L, Shi P. A Meshfree Representation for Cardiac Medical Image Computing. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE 2018; 6:1800212. [PMID: 29531867 PMCID: PMC5794334 DOI: 10.1109/jtehm.2018.2795022] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 12/14/2017] [Accepted: 01/09/2018] [Indexed: 12/25/2022]
Abstract
The prominent advantage of meshfree method, is the way to build the representation of computational domain, based on the nodal points without any explicit meshing connectivity. Therefore, meshfree method can conveniently process the numerical computation inside interested domains with large deformation or inhomogeneity. In this paper, we adopt the idea of meshfree representation into cardiac medical image analysis in order to overcome the difficulties caused by large deformation and inhomogeneous materials of the heart. In our implementation, as element-free Galerkin method can efficiently build a meshfree representation using its shape function with moving least square fitting, we apply this meshfree method to handle large deformation or inhomogeneity for solving cardiac segmentation and motion tracking problems. We evaluate the performance of meshfree representation on a synthetic heart data and an in-vivo cardiac MRI image sequence. Results showed that the error of our framework against the ground truth was 0.1189 ± 0.0672 while the error of the traditional FEM was 0.1793 ± 0.1166. The proposed framework has minimal consistency constraints, handling large deformation and material discontinuities are simple and efficient, and it provides a way to avoid the complicated meshing procedures while preserving the accuracy with a relatively small number of nodes.
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Affiliation(s)
- Heye Zhang
- Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
| | - Zhifan Gao
- Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen518055China
| | - Lin Xu
- Department of CardiologyGeneral Hospital of Guangzhou Military Command of PLAGuangzhou510000China
| | - Xingjian Yu
- State Key Laboratory of Modern Optical InstrumentationDepartment of Optical EngineeringZhejiang UniversityHangzhou310027China
| | - Ken C. L. Wong
- IBM Research – Almaden Research CenterSan JoseCA95120USA
| | - Huafeng Liu
- State Key Laboratory of Modern Optical InstrumentationDepartment of Optical EngineeringZhejiang UniversityHangzhou310027China
| | - Ling Zhuang
- Department of Radiation OncologyNorthwestern Lake forest HospitalLake forestIL60045USA
| | - Pengcheng Shi
- B. Thomas Golisano College of Computing and Information SciencesRochester Institute of TechnologyRochesterNY14623USA
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9
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Wong KCL, Summers RM, Kebebew E, Yao J. Pancreatic Tumor Growth Prediction With Elastic-Growth Decomposition, Image-Derived Motion, and FDM-FEM Coupling. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:111-123. [PMID: 27529869 PMCID: PMC5316467 DOI: 10.1109/tmi.2016.2597313] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Pancreatic neuroendocrine tumors are abnormal growths of hormone-producing cells in the pancreas. Unlike the brain which is protected by the skull, the pancreas can be significantly deformed by its surrounding organs. Consequently, the tumor shape differences observable from images at different time points arise from both tumor growth and pancreatic motion, and tumor growth model personalization may be compromised if such motion is ignored. Therefore, we incorporate pancreatic motion information derived from deformable image registration in model personalization. For more accurate mechanical interactions between tumor growth and pancreatic motion, elastic-growth decomposition is used with a hyperelastic constitutive law to model the mass effect, which allows growth modeling while conserving the mechanical properties. Furthermore, a way of coupling the finite difference method and the finite element method is proposed to greatly reduce the computation time. With both 2-[18F]-fluoro-2-deoxy-D-glucose positron emission tomographic and contrast-enhanced computed tomographic images, functional, structural, and motion data are combined for a patient-specific model. Experiments on synthetic and clinical data show the importance of image-derived motion on estimating pathophysiologically plausible mechanical properties and the promising performance of our framework. From seven patient data sets, the recall, precision, Dice coefficient, relative volume difference, and average surface distance between the personalized tumor growth simulations and the measurements were 83.2 ±8.8%, 86.9 ±8.3%, 84.4 ±4.0%, 13.9 ±9.8%, and 0.6 ±0.1 mm, respectively.
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Wong KC, Sermesant M, Rhode K, Ginks M, Rinaldi CA, Razavi R, Delingette H, Ayache N. Velocity-based cardiac contractility personalization from images using derivative-free optimization. J Mech Behav Biomed Mater 2015; 43:35-52. [DOI: 10.1016/j.jmbbm.2014.12.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2014] [Revised: 11/20/2014] [Accepted: 12/04/2014] [Indexed: 10/24/2022]
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11
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Wang X, Chen T, Zhang S, Schaerer J, Qian Z, Huh S, Metaxas D, Axel L. Meshless deformable models for 3D cardiac motion and strain analysis from tagged MRI. Magn Reson Imaging 2015; 33:146-60. [PMID: 25157446 PMCID: PMC4876045 DOI: 10.1016/j.mri.2014.08.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2013] [Revised: 05/28/2014] [Accepted: 08/08/2014] [Indexed: 12/12/2022]
Abstract
Tagged magnetic resonance imaging (TMRI) provides a direct and noninvasive way to visualize the in-wall deformation of the myocardium. Due to the through-plane motion, the tracking of 3D trajectories of the material points and the computation of 3D strain field call for the necessity of building 3D cardiac deformable models. The intersections of three stacks of orthogonal tagging planes are material points in the myocardium. With these intersections as control points, 3D motion can be reconstructed with a novel meshless deformable model (MDM). Volumetric MDMs describe an object as point cloud inside the object boundary and the coordinate of each point can be written in parametric functions. A generic heart mesh is registered on the TMRI with polar decomposition. A 3D MDM is generated and deformed with MR image tagging lines. Volumetric MDMs are deformed by calculating the dynamics function and minimizing the local Laplacian coordinates. The similarity transformation of each point is computed by assuming its neighboring points are making the same transformation. The deformation is computed iteratively until the control points match the target positions in the consecutive image frame. The 3D strain field is computed from the 3D displacement field with moving least squares. We demonstrate that MDMs outperformed the finite element method and the spline method with a numerical phantom. Meshless deformable models can track the trajectory of any material point in the myocardium and compute the 3D strain field of any particular area. The experimental results on in vivo healthy and patient heart MRI show that the MDM can fully recover the myocardium motion in three dimensions.
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Affiliation(s)
- Xiaoxu Wang
- Shenzhen Institute of Advance Technology, CAS, Xueyuan Ave. 1068, Xili, Nanshan, Shenzhen, Guangdong, China, 518055.
| | - Ting Chen
- Radiology Department, New York University, 660 first Avenue, New York, NY, 10016, USA
| | - Shaoting Zhang
- Department of Computer Science, Rutgers University, 110 Frelinghuysen Rd, Piscataway, NJ, 08854, USA
| | - Joël Schaerer
- CREATIS, INSA LYON, Bâtiment Blaise Pascal, 7 Avenue Jean Capelle, 69621, Villeurbanne Cedex, France
| | - Zhen Qian
- Department of Computer Science, Rutgers University, 110 Frelinghuysen Rd, Piscataway, NJ, 08854, USA
| | - Suejung Huh
- Department of Computer Science, Rutgers University, 110 Frelinghuysen Rd, Piscataway, NJ, 08854, USA
| | - Dimitris Metaxas
- Department of Computer Science, Rutgers University, 110 Frelinghuysen Rd, Piscataway, NJ, 08854, USA
| | - Leon Axel
- Radiology Department, New York University, 660 first Avenue, New York, NY, 10016, USA
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Wang H, Amini AA. Cardiac motion and deformation recovery from MRI: a review. IEEE TRANSACTIONS ON MEDICAL IMAGING 2012; 31:487-503. [PMID: 21997253 DOI: 10.1109/tmi.2011.2171706] [Citation(s) in RCA: 80] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Magnetic resonance imaging (MRI) is a highly advanced and sophisticated imaging modality for cardiac motion tracking and analysis, capable of providing 3D analysis of global and regional cardiac function with great accuracy and reproducibility. In the past few years, numerous efforts have been devoted to cardiac motion recovery and deformation analysis from MR image sequences. Many approaches have been proposed for tracking cardiac motion and for computing deformation parameters and mechanical properties of the heart from a variety of cardiac MR imaging techniques. In this paper, an updated and critical review of cardiac motion tracking methods including major references and those proposed in the past ten years is provided. The MR imaging and analysis techniques surveyed are based on cine MRI, tagged MRI, phase contrast MRI, DENSE, and SENC. This paper can serve as a tutorial for new researchers entering the field.
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Affiliation(s)
- Hui Wang
- Department of Electrical and Computer Engineering,University of Louisville, Louisville, KY 40292 USA.
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Wong KCL, Wang L, Zhang H, Liu H, Shi P. Physiological fusion of functional and structural images for cardiac deformation recovery. IEEE TRANSACTIONS ON MEDICAL IMAGING 2011; 30:990-1000. [PMID: 21224172 DOI: 10.1109/tmi.2011.2105274] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
The recent advances in meaningful constraining models have resulted in increasingly useful quantitative information recovered from cardiac images. Nevertheless, as most frameworks utilize either functional or structural images, the analyses cannot benefit from the complementary information provided by the other image sources. To better characterize subject-specific cardiac physiology and pathology, data fusion of multiple image sources is essential. Traditional image fusion strategies are performed by fusing information of commensurate images through various mathematical operators. Nevertheless, when image data are dissimilar in physical nature and spatiotemporal quantity, such approaches may not provide meaningful connections between different data. In fact, as different image sources provide partial measurements of the same cardiac system dynamics, it is more natural and suitable to utilize cardiac physiological models for the fusions. Therefore, we propose to use the cardiac physiome model as the central link to fuse functional and structural images for more subject-specific cardiac deformation recovery through state-space filtering. Experiments were performed on synthetic and real data for the characteristics and potential clinical applicability of our framework, and the results show an increase of the overall subject specificity of the recovered deformations.
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Affiliation(s)
- Ken C L Wong
- Computational Biomedicine Laboratory, B. Thomas Golisano College of Computing and Information Sciences, Rochester Institute of Technology, Rochester, NY 14623, USA.
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