Influence of Optical Fluence Distribution on Photoacoustic Imaging

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.

• 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

• Finite Element Method
• Fluence Distribution
• Monte Carlo Method
• Photoacoustic Imaging.

[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.