Influence of Optical Fluence Distribution on Photoacoustic Imaging

Authors: Mohamed K. Metwally, Sherif H. El-Gohary, Kyung Min Byun, Seung Moo Han, Soo Yeol Lee, Min Hyoung Cho, Gon Khang, Jinsung Cho, Tae-Seong Kim

Abstract:

Photoacoustic imaging (PAI) is a non-invasive and non-ionizing imaging modality that combines the absorption contrast of light with ultrasound resolution. Laser is used to deposit optical energy into a target (i.e., optical fluence). Consequently, the target temperature rises, and then thermal expansion occurs that leads to generating a PA signal. In general, most image reconstruction algorithms for PAI assume uniform fluence within an imaging object. However, it is known that optical fluence distribution within the object is non-uniform. This could affect the reconstruction of PA images. In this study, we have investigated the influence of optical fluence distribution on PA back-propagation imaging using finite element method. The uniform fluence was simulated as a triangular waveform within the object of interest. The non-uniform fluence distribution was estimated by solving light propagation within a tissue model via Monte Carlo method. The results show that the PA signal in the case of non-uniform fluence is wider than the uniform case by 23%. The frequency spectrum of the PA signal due to the non-uniform fluence has missed some high frequency components in comparison to the uniform case. Consequently, the reconstructed image with the non-uniform fluence exhibits a strong smoothing effect.

Keywords: Finite Element Method, Fluence Distribution, Monte Carlo Method, Photoacoustic Imaging.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1094285

References:

[1] C. Li, and L. V. Wang, ”Photoacoustic tomography and sensing in biomedicine,” Phys. Med. Biol., vol. 54, no. 19, pp. R59- R97, 2009.
[2] L. V. Wang, and S. Hu, ”Photoacoustic tomography: in vivo imaging from organelles to organs,” Science, vol. 335, no. 6075, pp. 1458-1462, 2012.
[3] R. R. An, X. S. Luo, and Z. H. Shen, ”Numerical simulation of the influence of the elastic modulus of a tumor on laser-induced ultrasonics in soft tissue,” Applied Optics, vol. 51, no. 32, pp. 7869- 7876, 2012.
[4] R. An, X. Luo, and Z. Shen, ”Numerical and experimental investigation of the influence of tumor size on laser-induced ultrasonics in soft tissue,” Laser Physics, vol. 24, no. 4, 2014.
[5] Z. Wang, S. Ha, and K. Kim, ”Photoacoustic design parameter optimization for deep tissue imaging by numerical simulation,” Photons Plus Ultrasound: Imaging and Sensing Proc. SPIE , vol. 8223, pp. 822346-1-8, 2012.
[6] Y.-L. Sheu, and P.-C. Li, ”Simulation of photoacoustic wave propagation using a finite-difference time-domain method with Berenger’s perfectly matched layers,” J. Acoust. Soc. Am., vol. 124, no. 6, pp. 3471-3480, 2008.
[7] S. Telenkov, A. Mandelis, B. Lashkari, and M. Forcht, ”Frequencydomain photothermoacoustics: alternative imaging modality of biological tissues,” J. Appl. Phys., vol. 105, issue 10, pp. 102029-1-8, 2009.
[8] Z. Wang, S. Ha, and K. Kim, ”Evaluation of finite element based simulation model of photoacoustics in biological tissues,” Proc. SPIE, Medical Imaging: Ultrasonic Imaging, Tomography, and Therapy, vol. 8320, pp. 83201L1-9, 2012.
[9] B. Banerjee, S. Bagchi, R. M. Vasu, and D. Roy, ”Quantitative photoacoustic tomography from boundary pressure measurements: noniterative recovery of optical absorption coefficient from the reconstructed absorbed energy map,” J. Opt. Soc. Am. A., vol. 25, no. 9, pp. 2347-2356, 2008.
[10] K. P. Köstli, and P. C. Beard, ”Two-dimensional photoacoustic imaging by use of Fourier-transform image reconstruction and a detector with an anisotropic response,” Applied Optics, vol. 42, no. 10, pp. 1899-908, 2003.
[11] L. H. 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] M. K. Metwally, H.-S. Han, H. J. Jeon, G. Khang, and T.-S. Kim, ” Influence of the anisotropic mechanical properties of the skull in lowintensity focused ultrasound towards neuromodulation of the brain,” in Proc. 35th Annu. Inter. Conf. of IEEE EMBC, pp. 4565-4568, 2013.
[13] ANSYS available: http://www.ansys.com
[14] C. G. A. Hoelen and F. F. M. de Mul, ”A new theoretical approach to photoacoustic signal generation,” J. of Acoust. Soc. Am., vol. 106, no. 2, pp. 695-705, 1999.
[15] J. I. Sperl, K. Zell, P. Menzenbach, C. Haisch, S. Ketzer, M. Marquart, H. Koenig, and M. W. Vogel, " Photoacoustic image reconstruction -A quantitative analysis,” Novel Optical Instrumentation for Biomedical Applications III. SPIE, vol. 6631, pp. 663103-1-12, 2007.