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Biomedical Optics & Medical Imaging
Numerical simulations improve biomedical visualization
Computational approaches to optoacoustic tomography allow optimization of imaging systems for biomedical applications and efficiency testing of image-reconstruction algorithms.
5 November 2008, SPIE Newsroom. DOI: 10.1117/2.1200810.1302
Optoacoustic (OA) imaging is a hybrid laser-ultrasonic method suitable for visualization of any absorbing heterogeneities in biological tissues, including blood vessels,1,2 tumors,3 and thermal lesions.4 In OA tomography, pulsed-laser radiation is absorbed, resulting in heat-source distribution in the tissue (see Figure 1). Transient thermoelastic tissue expansion leads to the excitation of a wideband ultrasonic pulse (an ‘OA signal’). Detection of this signal with an array of ultrasound transducers allows reconstruction of the laser-induced heat-release distribution (i.e., the OA image). For successful diagnosis the ultrasound-array transducer design must be optimized for a particular biomedical application. This requires a numerical model allowing us to simulate excitation, propagation, and measurement of OA signals.
OA emission of only very few objects (i.e., spheres, cylinders, and absorbing planes) can be described on the basis of analytical expressions.5 In all other cases the OA signal can only be calculated numerically using either a time-domain or a frequency-domain approach. The latter is very computationally efficient when simulating measurements of OA waves by a planar transducer.6 However, for more complex apertures it is convenient to use the time-domain approach. For example, in 2D OA tomography we employ array transducers consisting of focused elements: see Figure 1(a). Such a design allows us to restrict the sensitivity of each element to its narrow focal region, which constrains the operational area of the entire array to the imaging plane.7
Figure 1. Schematic diagram of an optoacoustic (OA) imaging system.
In the corresponding numerical algorithm the laser-induced heat-release distribution is divided into ‘voxels’ (volumetric pixels), which are small compared to the spatial resolution of the OA-signal detector. Each voxel is treated as source of spherical acoustic N waves5 (the signal typically produced by a sphere), with its amplitude corresponding to the magnitude of heat release in the voxel and the duration given by the voxel's size. The resulting observed OA signal is the superposition of the N waves from all contributing voxels.8 Spatial averaging of the wavefront over the acoustic-transducer surface and the spectral sensitivity of the transducer are also taken into account.9
This numerical model was employed to optimize an imaging system for early breast-cancer diagnosis.8 For this application one must detect the OA signal from an absorbing inclusion (a tumor) of less than 1cm in size located several centimeters deep within a highly scattering medium (i.e., healthy breast tissue). The initial heat-release distribution was found through Monte Carlo modeling of light transport in the medium with optical properties corresponding to breast tissue containing a small tumor.10 As OA-signal detectors we used an array of cylindrically focused piezoelements. The signals recorded by each array element were calculated, and the corresponding OA image of the ‘tumor’ was reconstructed using a backprojection algorithm.
Our numerical calculations were validated by phantom experiments. The experimental setup was guided by the results of the numerical calculations, which provided the optimal array-transducer design and ideal laser-irradiation geometry, among others. The array transducer consisted of 64 piezopolymer (polyvinylidene difluoride) elements (element width 1mm, focusing angle 30°, and radius of curvature 60mm) attached to the cylindrical surface of backing material.8 OA-signal excitation was achieved using a quality-switched (‘Q-switched’) neodymium-doped yttrium-aluminum-garnet (Nd:YAG) laser (with an operating wavelength λ = 1064nm, pulse duration 10ns, and beam width 3cm). The laser fluence was less than 10mJ/cm2, i.e., well below medical restrictions. As phantom medium we used a 3mm piece of bovine liver (absorption coefficient μa = 0:42cm−1) placed in diluted milk (characterized by μa = 0:18cm−1 and a reduced scattering coefficient μs′ = 1:85cm−1) at various depths. The optical properties of the phantom medium were measured in advance using the OA technique developed at our laboratory.11
An example of an OA signal recorded by an array element is shown in Figure 2(a). It consists of a smooth ‘background’ signal, corresponding to light attenuation within the diluted milk and a short peak corresponding to the inclusion. Both are in very good agreement with numerically calculated signals: see Figures 2(b) and (c). Before image reconstruction, all recorded signals were highpass filtered to remove the background without affecting the signal from the ‘tumor,’ and therefore to increase image contrast. The resulting OA images of the piece of bovine liver located at depths of 2 and 4cm below the irradiated surface are shown in Figure 3.
Figure 2. (a) OA signal excited in a phantom medium (diluted milk containing a piece of bovine liver) as detected by a single element of the array transducer before (black) and after (blue) highpass filtering. Comparison of experimental (black) and numerical (red) OA signals from (b) diluted milk and (c) a 3mm piece of bovine liver.
Figure 3. OA image of a 3mm piece of bovine liver located (a) 2cm and (b) 4cm deep in diluted milk.
In summary, we have developed a numerical model that allows us to simulate the entire process of OA imaging and to optimize the parameters of an imaging system for a particular biomedical application with relatively high spatial resolution (∼2mm) and image contrast. In our next steps we aim at imaging ex vivo tissue and adjusting the setup to prepare for clinical trials.
This work was supported by International Science and Technology Center grant 3691 and Russian Foundation for Basic Research grant 07-02-00940-a.
Tatiana Khokhlova, Ivan Pelivanov
Faculty of Physics
Moscow State University
Tatiana Khokhlova received MSc and PhD (2008) degrees in physics from Moscow State University. Her research interests focus on OA diagnostics and imaging of biological tissues and on high-intensity focused-ultrasound tumor therapy.
International Laser Center
Moscow State University
3. S. Manohar, S. E. Vaartjes, J. C. G. van Hespen, J. M. Klaase, F. M. van den Engh, W. Steenbergen, T. G. van Leeuwen, Initial results of in vivo non-invasive cancer imaging in the human breast using near-infrared photoacoustics, Opt. Express 15, no. 19, pp. 12277-12285, 2007.
8. T. D. Khokhlova, I. M. Pelivanov, V. V. Kozhushko, A. N. Zharinov, V. S. Solomatin, A. A. Karabutov, Optoacoustic imaging of absorbing objects in a turbid medium: ultimate sensitivity and application to breast cancer diagnostics, Appl. Opt. 46, no. 2, pp. 262-272, 2007.
9. V. V. Kozhushko, T. D. Khokhlova, A. N. Zharinov, I. M. Pelivanov, V. S. Solomatin, A. A. Karabutov, Focused array transducer for two-dimensional optoacoustic tomography, J. Acoust. Soc. Am. 116, no. 3, pp. 1498-1506, 2004.