Simulation and quantitative analysis of fluorescence intensity distribution based on the Monte Carlo method

Kun Zhou; Jian Tian; Qiushi Zhang; Xiangxi Meng; Kun Yang; Qiushi Ren

doi:doi:10.1142/s1793545815500388

Journal of Innovative Optical Health Sciences, 2015, 8 (6): 1550038, Published Online: Jan. 10, 2019

Simulation and quantitative analysis of fluorescence intensity distribution based on the Monte Carlo method

论文大纲

Kun Zhou ¹Jian Tian ¹Qiushi Zhang ^1,2Xiangxi Meng ¹Kun Yang ¹Qiushi Ren ^1,*

Author Affiliations

¹ Department of Biomedicine and Engineering College of Engineering, Peking University No. 5 Yiheyuan Road, Beijing 100871, P. R. China

² Institute for Drug and Instrument Control of PLA Beijing, P. R. China

Monte Carlo simulation FMT quantitative

Abstract

The Monte Carlo method is a versatile simulation algorithm to model the propagation of photons inside the biological tissues. It has been applied to the reconstruction of the fluorescence molecular tomography (FMT). However, such method suffers from low computational efficiency, and the time consumption is not desirable. One way to solve this problem is to introduce a priori knowledge which will facilitate iterative convergence. We presented an in vivo simulation environment for fluorescence molecular tomography (ISEFMT) using the Monte Carlo method to simulate the photon distribution of fluorescent objects and their sectional view in any direction quantitatively. A series of simulation experiments were carried out on different phantoms each with two fluorescent volumes to investigate the relationship among fluorescence intensity distribution and the excitation photon number, the locations and sizes of the fluorescence volumes, and the anisotropy coefficient. A significant principle was discovered, that along the direction of the excitation light, the fluorescent volume near the excitation point will provide shelter effect so that the energy of the fluorescent volume farther away from the excitation point is relatively lower. Through quantitative analysis, it was discovered that both the photon energy distribution on every cross section and the fluorescence intensity distributed in the two volumes exhibit exponential relationships. The two maximum positions in this distribution correspond to the centers of fluorescent volumes. Finally, we also explored the effect of the phantom coefficients on the exponential rule, and found out that the exponential rule still exists, only the coefficient of the exponential rule changed. Such results can be utilized in locating the positions of multiple fluorescent volumes in complicated FMT reconstruction involving multiple fluorescent volumes. Thus, a priori knowledge can be generalized, which would accelerate the reconstruction of FMT and even other images.

References

[1] J. R. Lakowicz, Principles of Fluorescence Spectroscopy, Springer (2009).

[2] R. Weissleder and V. Ntziachristos, "Shedding light onto live molecular targets," Nat. Med. 9, 123–128 (2003).

[3] Y. Zhang, Q. Xu, J. Li, S. Tang and X. Zhang, "In vivo simulation environment for fluorescence molecular tomography using Monte Carlo method," in Int. Conf. Optical Instrument and Technology, 715607-1–715607-6 (2008).

[4] R. Weissleder and U. Mahmood, "Molecular imaging," Radiology 219, 316–333 (2001).

[5] R. G. Blasberg and J. Gelovani-Tjuvajev, "Molecular-genetic imaging," J. Cell. Biochem. 87, 172–183 (2002).

[6] B. W. Rice, M. D. Cable and M. B. Nelson, "In vivo imaging of light-emitting probes," J. Biomed. Optics 6, 432–440 (2001).

[7] J. Chang, H. L. Graber and R. L. Barbour, "Luminescence optical tomography of dense scattering media," JOSA A 14, 288–299 (1997).

[8] E. E. Graves, J. Ripoll, R. Weissleder and V. Ntziachristos, "A submillimeter resolution fluorescence molecular imaging system for small animal imaging," Med. Phys. 30, 901 (2003).

[9] H. He, L. Zhang, F. Gao, Z. Ma, H. Zhao and J. Jiang, "An analytic reflection method for timedomain fluorescence diffuse optical tomography based on a generalized pulse spectrum technique," Biomedical Optics (BiOS), pp. 68500M–68500M-8 (2008).

[10] S. T. Flock, M. S. Patterson, B. C. Wilson and D. R. Wyman, "Monte Carlo modeling of light propagation in highly scattering tissues. I. Model predictions and comparison with diffusion theory," IEEE Trans. Biomed. Eng. 36, 1162–1168 (1989).

[11] L. Wang, S. L. Jacques and L. Zheng, "MCML— Monte Carlo modeling of light transport in multilayered tissues," Computer methods and programs in biomedicine, Vol. 47, pp. 131–146, 1995.

[12] A. T. Kumar, S. B. Raymond, A. K. Dunn, B. J. Bacskai and D. A. Boas, "A time domain fluorescence tomography system for small animal imaging," IEEE Trans. Med. Imaging 27, 1152–1163 (2008).

[13] X. Zhang, C. Badea, M. Jacob and G. A. Johnson, "Development of a noncontact 3-D fluorescence tomography system for small animal in vivo imaging," SPIE BiOS: Biomedical Optics, 71910D–71910D-10 (2009).

[14] G. Quan, H. Gong, Y. Deng, J. Fu and Q. Luo, "Monte Carlo-based fluorescence molecular tomography reconstruction method accelerated by a cluster of graphic processing units," J. Biomed. Optics 16, 026018-1–026018-8 (2011).

[15] H. Li, J. Tian, F. Zhu, W. Cong, L. V. Wang, E. A. Hoffman et al., "A mouse optical simulation environment (MOSE) to investigate bioluminescent phenomena in the living mouse with the Monte Carlo method," Acad. Radiol. 11, 1029–1038 (2004).

[16] C.-L. Tsai, J.-C. Chen and W.-J. Wang, "Near-infrared absorption property of biological soft tissue constituents," J. Med. Biol. Eng. 21, 7–14 (2001).

[17] V. V. Tuchin, "Light scattering study of tissues," Phys. — Uspekhi 40, 495 (1997).

[18] S. Tang, H. Yu and X. Mou, "Analytic simulation scheme for X-ray projections based on Physics Model," Optics & Photonics, pp. 63181T-1–63181T- 9 (2006).

Kun Zhou, Jian Tian, Qiushi Zhang, Xiangxi Meng, Kun Yang, Qiushi Ren. Simulation and quantitative analysis of fluorescence intensity distribution based on the Monte Carlo method[J]. Journal of Innovative Optical Health Sciences, 2015, 8(6): 1550038.

Simulation and quantitative analysis of fluorescence intensity distribution based on the Monte Carlo method

关于本站 Cookie 的使用提示

全站搜索

Simulation and quantitative analysis of fluorescence intensity distribution based on the Monte Carlo method

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索