A Novel Toolbox for Generating Realistic Biological Cell Geometries for Electromagnetic Microdosimetry

Document Type : Research Article

Authors

1 msaviz@aut.ac.ir

2 Biomedical Engineering Department, Amirkabir university of Technology (Tehran Polytechnic)

3 Amirkabir University of Technology, Department of Biomedical Engineering

Abstract

Researchers in bioelectromagnetics often require realistic tissue, cellular and sub-cellular geometry models for their simulations. However, biological shapes are often extremely irregular, while conventional geometrical modeling tools on the market cannot meet the demand for fast and efficient construction of irregular geometries. We have designed a free, user-friendly tool in MATLAB that combines several known or new algorithms for easy production of three-dimensional complex cell shapes based on minimum data. We have considered four different methods of creating objects: Generalized Rotation, Super-Formula, 3D reconstruction of 2D parallel cross-sections and branching models. Besides, many transformations such as translation and rotation, Boolean operations for 3D objects including union and intersection, random copy, etc. are also included in the toolbox. By utilizing different methods, our toolbox generates a larger variety of realistic biological geometries, especially tailored for irregular and branching cellular and sub-cellular shapes. We present a group of biological shape examples in this paper. The toolbox can export the geometries to common standard stl or voxel formats to be used for simulations in other software. We have developed an open, user-friendly toolbox, with specialization in cellular and sub-cellular irregular models. This toolbox can provide the essential realistic cellular models for scientific simulations in biomedical engineering, biotechnology, bioelectromagnetics, cell biomechanics, and serve as an educational visualization tool in teaching cell biology. Examples of microdosimetric simulations for electromagnetic exposure to RF frequencies are given and discussed.

Keywords

Main Subjects

References

[1] G. Pucihar, T. Kotnik, B. Valič, D. Miklavčič, Numerical determination of transmembrane voltage induced on irregularly shaped cells, Annals of biomedical engineering, 34(4) (2006) 642.
[2] S. Huclova, D. Erni, J. Fröhlich, Modelling and validation of dielectric properties of human skin in the MHz region focusing on skin layer morphology and material composition, Journal of Physics D: Applied Physics, 45(2) (2011) 025301.
[3] A. Chakraborty, R.K. Yadav, G.V. Reddy, A.K. Roy-Chowdhury, Cell resolution 3d reconstruction of developing multilayer tissues from sparsely sampled volumetric microscopy images, in:  2011 IEEE International Conference on Bioinformatics and Biomedicine, IEEE, 2011, pp. 378-383.
[4] J. Sebastián, S. Munoz, M. Sancho, J. Miranda, Analysis of the influence of the cell geometry, orientation and cell proximity effects on the electric field distribution from direct RF exposure, Physics in Medicine & Biology, 46(1) (2001) 213.
[5] D. Walker, B. Brown, R. Smallwood, D. Hose, D. Jones, Modelled current distribution in cervical squamous tissue, Physiological Measurement, 23(1) (2002) 159.
[6] T.R. Gowrishankar, J.C. Weaver, An approach to electrical modeling of single and multiple cells, Proceedings of the National Academy of Sciences, 100(6) (2003) 3203-3208.
[7] T.R. Gowrishankar, A.T. Esser, Z. Vasilkoski, K.C. Smith, J.C. Weaver, Microdosimetry for conventional and supra-electroporation in cells with organelles, Biochemical and biophysical research communications, 341(4) (2006) 1266-1276.
[8] S. Huclova, D. Erni, J. Fröhlich, Modelling effective dielectric properties of materials containing diverse types of biological cells, Journal of Physics D: Applied Physics, 43(36) (2010) 365405.
[9] A.E. Hartinger, R. Guardo, V. Kokta, H. Gagnon, A 3-D hybrid finite element model to characterize the electrical behavior of cutaneous tissues, IEEE Transactions on Biomedical Engineering, 57(4) (2009) 780-789.
[10] M. Saviz, R. Faraji-Dana, Realistic cell and organelle shape modeling for computational bioengineering: A new open-source toolbox, in:  2014 22nd Iranian Conference on Electrical Engineering (ICEE), IEEE, 2014, pp. 1859-1862.
[11] F. Sayyid, S. Kalvala, On the importance of modelling the internal spatial dynamics of biological cells, Biosystems, 145 (2016) 53-66.
[12] W.R. Holmes, L. Edelstein-Keshet, A comparison of computational models for eukaryotic cell shape and motility, PLoS computational biology, 8(12) (2012) e1002793.
[13] M. Kass, A. Witkin, D. Terzopoulos, Snakes: Active contour models, International journal of computer vision, 1(4) (1988) 321-331.
[14] J. Gielis, A generic geometric transformation that unifies a wide range of natural and abstract shapes, American journal of botany, 90(3) (2003) 333-338.
[15] P. Prusinkiewicz, A. Lindenmayer, The algorithmic beauty of plants.,(Springer-Verlag: New York),  (1990).
[16] Sven, stlwrite - Write binary or ascii STL file., in, 2012.
[17] A.H. Aitkenhead, Polygon mesh voxelisation, in, 2010.
[18] SAVI toolbox ver 2.00, in, 2017.
[19] J. Gimsa, T. Müller, T. Schnelle, G. Fuhr, Dielectric spectroscopy of single human erythrocytes at physiological ionic strength: dispersion of the cytoplasm, Biophysical journal, 71(1) (1996) 495-506.
[20] R.P. Joshi, Q. Hu, K.H. Schoenbach, Modeling studies of cell response to ultrashort, high-intensity electric fields-implications for intracellular manipulation, IEEE Transactions on Plasma Science, 32(4) (2004) 1677-1686.
[21] A. Molaei, M. Saviz, R. Faraji-Dana, Detailed modeling and numerical analysis of photoreceptor cells exposed to electromagnetic fields, in:  2011 19th Iranian Conference on Electrical Engineering, IEEE, 2011, pp. 1-6.
AUT Journal of Electrical Engineering
Volume 52, Issue 1
June 2020
Pages 89-96

Files

Share

How to cite

Statistics