Iterative finite-element-based inversion for quantified detection of molecular targets using optoacoustic tomography Thomas Jetzfellner, Daniel Razansky, Amir Rosenthal, Ralf Schulz, K-H. Englmeier and Vasilis Ntziachristos Institute for Biological and Medical Imaging, Munich and Helmholtz Center Munich, German Research Center for Environmental Health, Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany ABSTRACT We describe an improved optoacoustic tomography method, that utilizes a diffusion-based photon propagation model in order to obtain quantified reconstruction of targets embedded deep in heterogeneous scattering and absorbing tissue. For the correction we utilize an iterative finite-element solution of the light diffusion equation to build a photon propagation model. We demonstrate image improvements achieved by this method by using tissue-mimicking phantom measurements. The particular strength of the method is its ability to achieve quantified reconstructions in non-uniform illumination configurations resembling whole-body small animal imaging scenarios. Keywords: optoacoustics, finite element methods, normalization methods, tomographic imaging, iterative methods 1. INTRODUCTION Optoacoustic tomography (OAT) is a fast emerging imaging modality, which was proven to provide high spatial resolution along with optical contrast at an adequate imaging depth [1][2] . For many molecular imaging studies, for example when assessing disease progression or treatment, it is often necessary to have robust and fast image normalization and accurate quantification of concentration of exogenously administered probes in the presence of various highly heterogeneous tissue chromophores [3][4] . For this reason we examine here image normalization schemes for optoacoustic tomography when applied to imaging tissue-like media [5][6] . Of particular importance has been the capacity of OAT to quantify objects of control by varying optical properties in the medium and to accurately correct for the non-homogenous light distribution in three dimensional optically dense tissues. In contrast therefore to studies that assume plane illumination and homogenous light distribution within appropriately selected sections of tissue, we consider herein the complete three-dimensional problem with geometry that simulates small animal imaging applications. [7][8][9] One of the difficulties in accurately quantifying OAT images is that they are proportional to the actual energy absorbed by the tissue, i.e. to the product between the absorption coefficient and light fluence. Thus, in order to reconstruct the object’s absorption coefficient map, which carries the actual information of the distribution of particular bio-marker of interest, the light fluence within the tissue should be known so that it can be cancelled out. However, the light distribution depends again on the precise map of tissue optical properties, which cannot be easily measured nor calculated. Cox et al. [10] suggested a simple iterative reconstruction algorithm for planar geometry that can possibly resolve this imaging paradox. In this algorithm, the optical absorption coefficient obtained in each iteration is used to calculate the fluence in the succeeding iteration. Theoretical simulations have shown that, under ideal conditions, the algorithm converges and accurately recovers the absorption coefficient. In the presence of noise, a regularizing term was added to the equation to ensure convergence, albeit on the expense of overall accuracy. We used a tuned infrared OPO laser and broadband acoustic hydrophone in a circular scanning configuration to acquire optoacoustic data from tissue-mimicking scattering and absorbing phantoms. OAT images were formed using a modified backprojection algorithm after being corrected for photon propagation, modeled using an iterative finite-element solution of the light diffusion equation. The results demonstrate that, after being corrected for photon distribution, the method can accurately quantify concentration and shape of absorbing targets in heterogeneous tissue-like media. Several factors limiting the applicability of this correction method are also studied and discussed. Medical Imaging 2009: Physics of Medical Imaging, edited by Ehsan Samei, Jiang Hsieh, Proc. of SPIE Vol. 7258, 725812 · © 2009 SPIE CCC code: 1605-7422/09/$18 · doi: 10.1117/12.811014 Proc. of SPIE Vol. 7258 725812-1