Simulations and Inversions in Photoacoustic Tomography for High Resolution Quantitative Biomedical Imaging

Lead Research Organisation: University College London
Department Name: Medical Physics and Biomedical Eng


One out of every three people in the UK develops cancer at some stage in their life, and one in four die from it, according to the Office for National Statistics.It is well known that the early detection of cancer improves the chances of survival. For instance, malignant melanoma is a type of skin cancer that causes five deaths per day in the UK, but patients diagnosed at an early stage, when the treatments are much more effective, have an excellent prognosis with a five-year survival rate greater than 95%. A practical and inexpensive technique that could easily be deployed in clinics and hospitals to detect cancers at an earlier stage than is currently possible would therefore immediately improve survival rates.In the longer term, a better understanding of the processes and pathways that lead to cancerous tumours would aid in the development of new treatments and drugs. One of the most successful approaches to understanding disease in the human body has been to study similar diseases in small animals such as mice. There is sufficient similarity between murine and human physiology, such as in the way the immune system works, that 'mouse models' have become a mainstay of medical research. In recent years, advances in the techniques used to identify genes and proteins involved in disease mechanisms, and the increased availability of transgenic mice, have led to a demand for high-resolution, in vivo, small animal imaging modalities that can reveal where, and at what level, specific genes or proteins are being expressed, or other biomolecules or drugs are accumulating.Photoacoustic tomography is a new, inexpensive imaging technique that can provide 3D images of biological soft tissue, and has the potential to resolve structures within the tissue as narrow as a human hair (< 100 microns). By detecting the presence of small capillaries within nascent tumours, it may be able to detect cancers at an earlier stage than is currently possible. Early skin and breast tumours, for example, may be detectable using this approach. Furthermore, by using contrast agents, molecular markers or 'reporter' genes, 3D in vivo images of small animals showing the concentrations of the biomolecules of interest to within a few cells could become a realistic possibility.Photoacoustic tomography can distinguish between different biomolecules or tissues because of differences in their optical absorption spectra, ie. their colour. Small ultrasonic pulses are generated when light is absorbed in the tissue by, for instance, blood or a molecular marker. By illuminating the tissue with a colour of light that is absorbed only by the desired target, then only that target will generate ultrasound. By recording the ultrasound over several detectors, its origin can be calculated, in much the same way as we determine the location of a car horn by the difference in the time of arrival of the sound at our two ears. In this way a 3D image of the target absorber can be formed.Photoacoustic tomography clearly has great promise and the benefits to patients, clinicians and researchers could be enormous. However, some remaining technical hurdles must be overcome before all the potential benefits can be fully realised. For example, the speed at which the ultrasound travels through the tissue is not the same everywhere and so results in blurred images. Perhaps the most important outstanding problem is that of producing separate images of two or more absorbing substances (blood and a contrast agent, say) when they are simultaneously present in the tissue.The research proposed here will investigate a number of different ways to overcome the remaining challenges and so realize the full potential of photoacoustic tomography as a tool both for clinical diagnosis and high resolution imaging in biomedicine and the life sciences.
Description This project forms part of a larger and still very active research project on biomedical photoacoustic imaging ( which will have applications in pre-clinical imaging (eg. for cancer research) and potentially for clinical imaging of skin, superficial vasculature and breast, among other uses.

Photoacoustics - as the name suggests - involves both light and sound. Short pulses of light are used to generate ultrasound within biological tissue, and by measuring the ultrasonic waves emitted, it is possible to obtain an image of where the light was absorbed. One key absorber is hemoglobin in red blood cells, so this technique is very good for imaging vasculature to high resolution.

The principle aims of this grant were to develop numerical algorithms (ie. computer programs) that can be used for forming photoacoustic images from the measured ultrasonic data, and for extracting images of certain tissue components from a set of photoacoustic images obtained at multiple optical wavelengths.

To tackle these two 'inverse' problems it was first necessary to develop forward models of acoustic and optical propagation in tissue. During this grant we showed that spectral (k-space) methods are particularly suited to modelling photoacoustic waves in biological tissue, not least because the absorption can be modelled accurately and efficiently in k-space. We devised various approaches to image reconstruction in free-space as well as reflecting and reverberant cavities. In particular, we developed an image reconstruction algorithm based on 'time reversal' which is now used routinely in our group's work on cancer imaging (

The optical inversion was also studied intensely during the course of this grant and we showed that it is harder than it first seems (it is nonlinear, ill-posed and large scale). Nevertheless, we proposed various ways to attack the problem including a fixed-point iteration and the idea of fluence-dependent chromophores. Perhaps more significantly, we demonstrated that a gradient-based minimisation approach using adjoint fields, in particular using multiwavelength data, seems to be a promising way to tackle the problem.
Exploitation Route The k-Wave Toolbox, mentioned above, is already used widely outside, as well as within, academia. Photoacoustic imaging itself will become a key tool in many industries, not least in pharmaceutical development. The photoacoustic wave propagation codes and image reconstruction techniques developed under this grant are available in a free 3rd party Matlab Toolbox, k-Wave (, which is widely used in the photoacoustic research community. The software is regularly updated and we maintain an active forum to help users.

These models have also been extended to be applicable for simulating conventional ultrasound fields (clinical diagnostic and therapeutic ultrasound) - or indeed any acoustic waves in fluids - and have found a large user-base there too.

The task of obtaining quantitatively accurate photoacoustic images of optical absorbing agents, which was barely acknowledged as a problem at the start of this grant, is now recognised as a crucial challenge. Commercial pre-clinical photoacoustic scanners are becoming available, and the end-users, eg. cancer researchers, require not just high quality images but accurate quantitation.

All the areas of research covered in this grant continue to be studied, in close collaboration with experimentalist colleagues in the Photoacoustic Imaging Group at University College London ( as well as with mathematicians and computer scientists in several places around the world.
Sectors Digital/Communication/Information Technologies (including Software),Education,Environment,Healthcare,Other

Description The majority of the major research groups around the world in working in the field photoacoustic imaging use the software that arose from this grant. Furthermore, the question of how to achieve quantitative photoacoustic imaging, first raised by - and the first solutions first proposed by - this grant remains a hot topic today in pre-clinical and clinical imaging.
First Year Of Impact 2012
Sector Education,Healthcare,Other
Description photoacoustic image reconstruction 
Organisation University of Arizona
Department Department of Mathematics
Country United States 
Sector Academic/University 
PI Contribution We are working together to understand real life problems in photoacoustic image reconstruction. We have the experimental expertise, and some background in numerical modelling.
Collaborator Contribution Our partner, Leonid Kunyansky, is a mathematician with an interest in practical algorithms that are applicable to real world scenarios.
Impact A conference paper: • Cox, B.T., Holman, B. and Kunyansky, L. "Photoacoustic tomography in a reflecting cavity" Proc. SPIE 8581, 85811D (2013) A journal article: • Kunyansky, L., Holman, B. and Cox, B.T, "Photoacoustic Tomography in a Rectangular Reflecting Cavity" Inverse Problems, 29, 125010 (2013). [Also on arXiv]
Start Year 2012
Description quantitative photoacoustic imaging 
Organisation University of Eastern Finland
Department Department of Applied Physics
Country Finland 
Sector Academic/University 
PI Contribution We have experimental expertise, and a background in photoacoustic imaging, including acoustic modelling.
Collaborator Contribution Our partners are experts in the Bayesian approach to optical inverse problems, of which quantitative photoacoustic imaging is one.
Impact Journal articles: • Tarvainen, T. M., Cox, B.T., Kaipio, J. P., & Arridge, S. R. "Reconstructing absorption and scattering distributions in quantitative photoacoustic tomography." Inverse Problems, 28 (8) 084009. (2012) [Chosen as one of the highlights of 2012 by the IP editorial board] • Tarvainen, T., Pulkkinen, A., Cox, B.T., Kaipio, J.P. and Arridge, S.R. "Bayesian Image Reconstruction in Quantitative Photoacoustic Tomography" IEEE Transactions on Medical Imaging, 32(12), 2287-2298 (2013) • Saratoon, T., Tarvainen, T., Cox, B.T. and Arridge, S.R. "A gradient-based method for quantitative photoacoustic tomography using the radiative transfer equation" Inverse Problems, 29, 075006 (2013) • Pulkkinen, A., Kolehmainen, V., Kaipio, J.P., Cox, B.T., Arridge, S.R. and Tarvainen, T. "Approximate Marginalization of Unknown Scattering In Quantitative Photoacoustic Tomography" Inverse Problems in Imaging, 8(3), 811-829 (2014) • Pulkkinen, A., Cox, B.T., Arridge, S.R., Kaipio, J.P. and Tarvainen, T. "Bayesian approach to spectral quantitative photoacoustic tomography" Inverse Problems, 30, 065012 (2014) • Pulkkinen, A., Cox, B.T., Arridge, S.R., Kaipio, J.P., and Tarvainen, T. "Quantitative photoacoustic tomography using illuminations from a single direction" Journal of Biomedical Optics, 20(3), doi:10.1117/1.JBO.20.3.036015 (2015) Conference papers: • Tarvainen, T. Pulkkinen, A., Cox, B.T., Kaipio, J.P. and Arridge, S.R. "Image reconstruction in quantitative photoacoustic tomography using the radiative transfer equation and the diffusion approximation", Proc. SPIE 8800, 880006 (2013) • Saratoon, T., Tarvainen, T., Arridge, S.R. and Cox, B.T. "3D quantitative photoacoustic tomography using the d-Eddington approximation", Proc SPIE 8581, 85810V (2013) • Cox, B.T., Tarvainen, T. and Arridge, S., "Multiple Illumination Quantitative Photoacoustic Tomography using Transport and Diffusion Models" in Tomography and Inverse Transport Theory, eds. G. Bal, D. Finch, P. Kuchment, J. Schotland, P. Stefanov, & G. Uhlmann, American Mathematical Society, Contemporary Mathematics Series, 559, 1-12 (2012)
Start Year 2010
Description A method and apparatus are provided for performing photoacoustic tomography with respect to a sample that receives a pulse of excitation electromagnetic radiation and generates an acoustic field in response to said pulse. One embodiment provides an apparatus comprising an acoustically sensitive surface, wherein the acoustic field generated in response to said pulse is incident upon said acoustically sensitive surface to form a signal. The apparatus further comprises a source for directing an interrogation beam of electromagnetic radiation onto said acoustically sensitive surface so as to be modulated by the signal; means for applying a sensitivity pattern to the interrogation beam; and a read-out system for receiving the interrogation beam from the acoustically sensitive surface and for determining a value representing a spatial integral of the signal across the acoustically sensitive surface, wherein said spatial integral is weighted by the applied sensitivity pattern. The apparatus is configured to apply a sequence of sensitivity patterns to the interrogation beam and to determine a respective sequence of values for said weighted spatial integral for generating a photoacoustic image. 
IP Reference WO2014207440 
Protection Patent granted
Year Protection Granted 2014
Licensed No
Impact It is early days...
Description An imaging system comprises a sensor arrangement for detecting an acoustic signal which emanates from a sample; and means for analysing the sensor arrangement output signals to derive a property for different portions of the sample. A reflector arrangement reflects a portion of the signal generated within the sample which is not directed to the sensor arrangement, such that it is reflected to the sensor arrangement. The sensor arrangement output signals are processed over a time period which covers the direct receipt of the signal generated within the sample by the sensor arrangement as well as the reflected portion of the signal generated within the sample. 
IP Reference WO2008062199 
Protection Patent granted
Year Protection Granted 2008
Licensed No
Impact .
Title k-Wave: A MATLAB toolbox for the time-domain simulation of acoustic wave fields 
Description k-Wave is an open source acoustics toolbox for MATLAB. The software is designed for time domain acoustic and ultrasound simulations in complex and tissue-realistic media. The simulation functions are based on the k-space pseudospectral method and are both fast and easy to use. The toolbox includes: (1) An advanced time-domain model of acoustic wave propagation that can account for nonlinearity, acoustic heterogeneities, and power law absorption (1D, 2D, and 3D) (2) The ability to model pressure and velocity sources, including photoacoustic sources, and diagnostic and therapeutic ultrasound transducers (3) The ability to specify arbitrary detection surfaces with directional elements, with options to record acoustic pressure, particle velocity, and acoustic intensity (4) An optimised C++ version of the code that maximises computational performance for large simulations (5) The option to use the forward model as a flexible time reversal image reconstruction algorithm for photoacoustic tomography with an arbitrary measurement surface (6) A fast, one-step, photoacoustic image reconstruction algorithm for data recorded on a linear (2D) or planar (3D) measurement surface (7) Optional input parameters to adjust visualisation and performance, including options to generate movies and to run the simulations on a graphics processing unit (GPU) (8) An extensive user manual and many simple to follow tutorial examples to illustrate the capabilities of the toolbox 
Type Of Technology Software 
Year Produced 2012 
Open Source License? Yes  
Impact We have a user base of several thousand, including most of the major photoacoustic imaging groups from around the world. The question-and-answer forum, which we maintain, is constantly active. Our group (through my colleague Bradley Treeby) has received further funding for related projects in ultrasound therapy based on this software platform. We have also established a collaboration with Brno University of Technology based on the development of this suite for high performance computing platforms.