The Establishment of a Heart Model: From CT Data to Finite Element Model with Fiber Orientation
Qian Li1, Wang Jianfei1, Jin Lian1, Song Biao1, Huang Yanqi1, Zhu Honglei1, Yan Shengjie1, Wu Xiaomei1,2,3#*
1(Electrical Engineering Department, Fudan University, Shanghai 200433, China) 2(China and Shanghai Engineering Research Center of Assistive Devices, Shanghai 200433, China) 3(The Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention (MICCAI) of Shanghai, Shanghai 200433, China)
Abstract：Cardiac computer model is a powerful tool for studying cardiac physiological/pathological function and treating patients with arrhythmias. The finite element model of the heart is the basis for building various heart models. Establishing personalized cardiac computer models from patients' clinical image data provides great convenience for clinical diagnosis and treatment. This paper developed a method for establishing a full-heart finite element model from human chest CT imaging data. It included following two steps: 1, establishment of a cardiac anatomical surface model by MIMICS based on chest CT images; 2, repairing the surface model with HyperMesh to obtain a finite element model of the heart entity. As the direction of myocardial fiber is closely related to the electrical/mechanical activity of the heart, after the reconstruction of cardiac anatomy from image data, we specifically investigated the addition of the myocardial fiber orientation. First, using the rule-based approach to add the direction of ventricular muscle fibers. Afterwards, based on rule-based approach, using structural tensor analysis to do the smoothing filtering. By this way, the atrial muscle fiber orientation was obtained. In order to verify the correctness of adding myocardial fibers, the fiber orientation of the special part in the heart was investigated. The angle between the direction of the myocardial fibers and the OX axis of the Bachmann′s bundle, the posterior left atrium, the superior posterior left atrium, and the interatrial groove was 4.97°±4.84° (Mean±Standard deviation), 111.99°±3.72°, 178.89°±3.73°, and 86.48°±4.01° respectively, consistent with myocardial fiber observations reported in the literature. The method proposed could construct a finite element model of the heart from the cardiac image data, which included myocardial fiber.
钱力, 王建飞, 金炼, 宋彪, 黄彦淇, 朱红蕾, 鄢盛杰, 邬小玫. 从CT数据到带纤维走向的全心脏有限元模型的建立[J]. 中国生物医学工程学报, 2020, 39(2): 180-189.
Qian Li, Wang Jianfei, Jin Lian, Song Biao, Huang Yanqi, Zhu Honglei, Yan Shengjie, Wu Xiaomei. The Establishment of a Heart Model: From CT Data to Finite Element Model with Fiber Orientation. Chinese Journal of Biomedical Engineering, 2020, 39(2): 180-189.
[1] Santos A, Fernández-Friera L, Villalba M, et al. Cardiovascular imaging: what have we learned from animal models?[J]. Frontiers in Pharmacology, 2015, 6: 1-25.
[2] Okajima M, Fujino T, Kobayash T, et al. Computer simulation of propagation process in excitation of vetricles[J]. Circulation Research, 1968, 23(2): 203-211.
[3] Dssel O, Krueger MW, Weber FM, et al. Computational modeling of the human atrial anatomy and electrophysiology[J]. Medical & Biological Engineering & Computing, 2012, 50(8): 773-799.
[4] 邵晓宇. 基于CT影像处理的心脏腔室四维建模及分析系统设计[D]. 南昌:南昌航空大学, 2017.
[5] Nielsen PM, Le Grice IJ, Smaill BH, et al. Mathematical model of geometry and fibrous structure of the heart[J]. The American Journal of Physiology, 1991, 260(4 Pt 2): H1365-H1378.
[6] Legrice I, Hunter P, Young A, et al. The architecture of the heart: A data-based model[J]. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2001, 359(1783): 1217-1232.
[7] Gao Hao, Griffith BE, Carrick D, et al. Initial experience with a dynamic imaging-derived immersed boundary model of human left ventricle[M]. Lecture Notes in Computer Science. Berlin:Springer Berlin Heidelberg, 2013, 7945: 11-18.
[8] Clayton RH, Panfilov AV. A guide to modelling cardiac electrical activity in anatomically detailed ventricles[J]. Progress in Biophysics and Molecular Biology, 2008, 96(1-3): 19-43.
[9] Varela M, Zhao Jichao, Aslanidi OV. Determination of atrial myofibre orientation using structure tensor analysis for biophysical modelling[M]. Lecture Notes in Computer Science. Berlin:Springer Berlin Heidelberg, 2013, 7945: 425-432.
[10] Spach MS, Miller WT, Dolber PC, et al. The functional-role of structural complexities in the propagation of depolarization in the atrium of the dog - cardiac conduction disturbances due to discontinuities of effective axial resistivity [J]. Circulation Research, 1982, 50(2): 175-191.
[11] Krueger MW, Schulze WHW, Rhode KS, et al. Towards personalized clinical in-silico modeling of atrial anatomy and electrophysiology[J]. Medical & Biological Engineering & Computing, 2013, 51(11): 1251-1260.
[12] Tseng WI, Reese TG, Weisskoff RM, et al. Cardiac diffusion tensor MRI in vivo without strain correction[J]. Magnetic Resonance in Medicine, 1999, 42(2): 393-403.
[13] Dou J, Reese TG, Tseng WI, et al. Cardiac diffusion MRI without motion effects[J]. Magnetic Resonance in Medicine, 2002, 48(1): 105-114.
[14] 孔凡辉. 基于粒子滤波的磁共振扩散成像人体心肌纤维重建方法研究[D]. 哈尔滨:哈尔滨工业大学, 2016.
[15] Bishop MJ, Plank G, Burton RAB, et al. Development of an anatomically detailed MRI-derived rabbit ventricular model and assessment of its impact on simulations of electrophysiological function[J]. AJP: Heart and Circulatory Physiology,2010, 298(2): H699-H718.
[16] Zhao Jichao, Hansen BJ, Wang Yufeng, et al. Three-dimensional integrated functional, structural, and computational mapping to define the structural “fingerprints” of heart-specific atrial fibrillation drivers in human heart ex vivo[J]. Journal of the American Heart Association,2017, 6(8): 1-8.
[17] Seemann G, Hoper C, Sachse FB, et al. Heterogeneous three-dimensional anatomical and electrophysiological model of human atria[J]. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2006, 364(1843): 1465-1481.
[18] Zhao Jichao, Butters TD, Zhang Henggui, et al. An image-based model of atrial muscular architecture: effects of structural anisotropy on electrical activation[J]. Circulation: Arrhythmia and Electrophysiology, 2012, 5(2): 361-370.
[19] Klos M, Calvo D, Yamazaki M, et al. Atrial septopulmonary bundle of the posterior left atrium provides a substrate for atrial fibrillation initiation in a model of vagally mediated pulmonary vein tachycardia of the structurally normal heart[J]. Circulation: Arrhythmia and Electrophysiology, 2008, 1(3): 175-183.
[20] Mcdowell KS, Vadakkumpadan F, Blake R, et al. Methodology for patient-specific modeling of atrial fibrosis as a substrate for atrial fibrillation[J]. Journal of Electrocardiology, 2012, 45(6): 640-645.
[21] Tobon C, Ruiz-Villa C A, Heidenreich E, et al. A three-dimensional human atrial model with fiber orientation [J]. Electrograms and Arrhythmic Activation Patterns Relationship, PLoS ONE. 2013, 8: 1-13.
[22] Fernández J, Li S. An improved algorithm for anisotropic nonlinear diffusion for denoising cryo-tomograms[J]. Journal of Structural Biology, 2003, 144(1-2): 152-161.
[23] Varela M, Zhao Jichao, Aslanidi OV. Determination of atrial myofibre orientation using structure tensor analysis for biophysical modelling[M]. Lecture Notes in Computer Science. Berlin: Springer Berlin Heidelberg, 2013, 7945: 425-432.
[24] Varela M, Colman MA, Hancox JC, et al. Atrial heterogeneity generates re-entrant substrate during atrial fibrillation and anti-arrhythmic drug action: mechanistic insights from canine atrial models[J]. PLoS Computational Biology, 2016, 12(12):1-22.
[25] Scollan DF, Holmes A, Winslow R, et al. Histological validation of myocardial microstructure obtained from diffusion tensor magnetic resonance imaging[J]. American Journal of Physiology-Heart and Circulatory Physiology, 1998, 275(6): H2308-H2318.
[26] Hsu EW, Muzikant AL, Matulevicius S A, et al. Magnetic resonance myocardial fiber-orientation mapping with direct histological correlation[J]. American Journal of Physiology-heart and Circulatory Physiology, 1998, 274(5): H1627-H1634.
[27] Gelaude F, Vander SJ, Lauwers B. Accuracy assessment of CT-based outer surface femur meshes[J]. Comput Aided Surg, 2008, 13(4): 188-199.
[28] Streeter D D, Spotnitz H M, Patel D P, et al. Fiber orientation in canine left ventricle during diastole and systole[J]. Circulation Research, 1969, 24(3): 339-347.
[29] Grant P R. Notes on muscular architecture of left ventricle[J]. Circulation Journal, 1965, 32(2): 169-171.
[30] Fox JJ, Gilmour RF, Bodenschatz E. Conduction block in one-dimensional heart fibers[J]. Physical Review Letters,2002, 89: 1-4.
[31] Plotkowiak M, Rodriguez B, Plank G, et al. High performance computer simulations of cardiac electrical function based on high resolution MRI datasets[M]// Computational Science-ICCS 2008. Berlin: Springer Berlin Heidelberg, 2008, 5101: 571-580.
[32] Lorensen WE, Cline H. Marching cubes: A high resolution 3D surface construction algorithm[M]. ACM SIGGRAPH Computer Graphics, 1987: 163-169.
[33] Ho SY, Sanchez-Quintana D. The importance of atrial structure and fibers[J]. Clin Anat, 2009, 22(1): 52-63.
[34] Wang K, Ho SY, Gibson DG, et al. Architecture of atrial musculature in humans[J]. Heart, 1995, 73(6): 559-565.
[35] Bakker P, van Vliet LJ, Verbeek P. Edge preserving orientation adaptive filtering[C]. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Fort Collins: Academic Press, 1999, 535-540.
[36] Klos M, Calvo D, Yamazaki M, et al. Atrial septopulmonary bundle of the posterior left atrium provides a substrate for atrial fibrillation initiation in a model of vagally mediated pulmonary vein tachycardia of the structurally normal heart[J]. Circulation: Arrhythmia and Electrophysiology, 2008. 1(3): 175-183.
[37] Hocini M, Ho SY, Kawara T, et al. Electrical conduction in canine pulmonary veins[J]. Circulation, 2002. 105(20): 2442-2448.
[38] Harrild DM, Henriquez CS. A computer model of normal conduction in the human atria[J]. Circulation Research, 2000. 87(7): 25-36.
[39] Jacquemet V, Virag N, Ihara Z, et al. Study of unipolar electrogram morphology in a computer model of atrial fibrillation[J]. Journal of Cardiovascular Electrophysiology, 2003. 14(10): 172-179.
[40] Sachse FB, Frech R, Werner CD, et al. A model based approach to assignment of myocardial fibre orientation[J]. Computers in Cardiology 1999, 26:145-148.
[41] Savadjiev P, Strijkers GJ, Bakermans AJ, et al. Heart wall myofibers are arranged in minimal surfaces to optimize organ function [J]. Proceedings of the National Academy of Sciences, 2012, 109: 9248-9253.
[42] Angeli S, Befera N, Peyrat J, et al. A high-resolution cardiovascular magnetic resonance diffusion tensor map from ex-vivo C57BL/6 murine hearts [J]. Journal of Cardiovascular Magnetic Resonance, 2014, 16: 77-91.
