Improved bioluminescence and fluorescence reconstruction algorithms using diffuse optical tomography, normalized data, and optimized selection of the permissible source region

Reconstruction algorithms are presented for two-step solutions of the bioluminescence tomography (BLT) and the fluorescence tomography (FT) problems. In the first step, a continuous wave (cw) diffuse optical tomography (DOT) algorithm is used to reconstruct the tissue optical properties assuming known anatomical information provided by x-ray computed tomography or other methods. Minimization problems are formed based on L1 norm objective functions, where normalized values for the light fluence rates and the corresponding Green’s functions are used. Then an iterative minimization solution shrinks the permissible regions where the sources are allowed by selecting points with higher probability to contribute to the source distribution. Throughout this process the permissible region shrinks from the entire object to just a few points. The optimum reconstructed bioluminescence and fluorescence distributions are chosen to be the results of the iteration corresponding to the permissible region where the objective function has its global minimum This provides efficient BLT and FT reconstruction algorithms without the need for a priori information about the bioluminescence sources or the fluorophore concentration. Multiple small sources and large distributed sources can be reconstructed with good accuracy for the location and the total source power for BLT and the total number of fluorophore molecules for the FT. For non-uniform distributed sources, the size and magnitude become degenerate due to the degrees of freedom available for possible solutions. However, increasing the number of data points by increasing the number of excitation sources can improve the accuracy of reconstruction for non-uniform fluorophore distributions.

[1]  M. Schweiger,et al.  The finite element method for the propagation of light in scattering media: boundary and source conditions. , 1995, Medical physics.

[2]  Jie Tian,et al.  An optimal permissible source region strategy for multispectral bioluminescence tomography. , 2008, Optics express.

[3]  M S Patterson,et al.  Quantification of bioluminescence images of point source objects using diffusion theory models , 2006, Physics in medicine and biology.

[4]  A. Adibi,et al.  Optimal sparse solution for fluorescent diffuse optical tomography: theory and phantom experimental results. , 2007, Applied optics.

[5]  A B Thompson,et al.  Diagnostic imaging of breast cancer using fluorescence-enhanced optical tomography: phantom studies. , 2004, Journal of biomedical optics.

[6]  A. Chatziioannou,et al.  Tomographic bioluminescence imaging by use of a combined optical-PET (OPET) system: a computer simulation feasibility study , 2005, Physics in medicine and biology.

[7]  Huabei Jiang,et al.  Diffuse optical tomography guided quantitative fluorescence molecular tomography. , 2008, Applied optics.

[8]  Alexander D Klose,et al.  Transport-theory-based stochastic image reconstruction of bioluminescent sources. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.

[9]  Arion F Chatziioannou,et al.  Effect of optical property estimation accuracy on tomographic bioluminescence imaging: simulation of a combined optical–PET (OPET) system , 2006, Physics in medicine and biology.

[10]  S. Arridge Optical tomography in medical imaging , 1999 .

[11]  H. Jiang,et al.  Frequency-domain fluorescent diffusion tomography: a finite-element-based algorithm and simulations. , 1998, Applied optics.

[12]  M. Schweiger,et al.  A finite element approach for modeling photon transport in tissue. , 1993, Medical physics.

[13]  Vasilis Ntziachristos,et al.  Imaging performance of a hybrid x-ray computed tomography-fluorescence molecular tomography system using priors. , 2010, Medical physics.

[14]  Yasuyoshi Watanabe,et al.  [Molecular imaging for drug development]. , 2007, Brain and nerve = Shinkei kenkyu no shinpo.

[15]  A. Rehemtulla,et al.  Molecular Imaging , 2009, Methods in Molecular Biology.

[16]  Alexander D. Klose,et al.  Gradient-based iterative image reconstruction scheme for time-resolved optical tomography , 1999, IEEE Transactions on Medical Imaging.

[17]  Arye Nehorai,et al.  Image reconstruction for diffuse optical tomography using sparsity regularization and expectation-maximization algorithm. , 2007, Optics express.

[18]  C. Contag,et al.  Advances in in vivo bioluminescence imaging of gene expression. , 2002, Annual review of biomedical engineering.

[19]  Stephen B. Tuttle,et al.  Magnetic resonance-coupled fluorescence tomography scanner for molecular imaging of tissue. , 2008, The Review of scientific instruments.

[20]  E. Richer,et al.  Iterative reconstruction method for light emitting sources based on the diffusion equation. , 2005, Medical physics.

[21]  R. Leahy,et al.  Fast iterative image reconstruction methods for fully 3D multispectral bioluminescence tomography , 2008, Physics in medicine and biology.

[22]  C. Bouman,et al.  Fluorescence optical diffusion tomography. , 2003, Applied optics.

[23]  Gultekin Gulsen,et al.  Quantitative fluorescence tomography with functional and structural a priori information. , 2009, Applied optics.

[24]  Nanguang Chen,et al.  Reconstruction for free-space fluorescence tomography using a novel hybrid adaptive finite element algorithm. , 2007, Optics express.

[25]  Liji Cao,et al.  Geometrical co-calibration of a tomographic optical system with CT for intrinsically co-registered imaging , 2010, Physics in medicine and biology.

[26]  T. Chan,et al.  Source reconstruction for spectrally-resolved bioluminescence tomography with sparse a priori information. , 2009, Optics express.

[27]  Jie Tian,et al.  Truncated Total Least Squares Method with a Practical Truncation Parameter Choice Scheme for Bioluminescence Tomography Inverse Problem , 2010, Int. J. Biomed. Imaging.

[28]  Hamid Dehghani,et al.  Near infrared optical tomography using NIRFAST: Algorithm for numerical model and image reconstruction. , 2009, Communications in numerical methods in engineering.

[29]  M. Jiang,et al.  Uniqueness theorems in bioluminescence tomography. , 2004, Medical physics.

[30]  P. Peltié,et al.  Noncontact fluorescence diffuse optical tomography of heterogeneous media. , 2007, Applied optics.

[31]  Jie Tian,et al.  Multimodality Molecular Imaging , 2008, IEEE Engineering in Medicine and Biology Magazine.

[32]  Vasilis Ntziachristos,et al.  Looking and listening to light: the evolution of whole-body photonic imaging , 2005, Nature Biotechnology.

[33]  Birsen Yazici,et al.  Fluorescence diffuse optical image reconstruction with a priori information , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[34]  John L. Volakis,et al.  Finite Element Method Electromagnetics , 1998 .

[35]  M. Patterson,et al.  Algorithms for bioluminescence tomography incorporating anatomical information and reconstruction of tissue optical properties , 2010, Biomedical optics express.

[36]  Vasilis Ntziachristos,et al.  Fluorescence optical tomography with a priori information , 2007, SPIE BiOS.

[37]  B. Pogue,et al.  Spectrally resolved bioluminescence optical tomography. , 2006, Optics letters.

[38]  Jie Tian,et al.  A multi-phase level set framework for source reconstruction in bioluminescence tomography , 2010, J. Comput. Phys..

[39]  B. Pogue,et al.  Image-guided diffuse optical fluorescence tomography implemented with Laplacian-type regularization. , 2007, Optics express.

[40]  B. Rice,et al.  Three-dimensional reconstruction of in vivo bioluminescent sources based on multispectral imaging. , 2007, Journal of biomedical optics.

[41]  Geoffrey McLennan,et al.  Practical reconstruction method for bioluminescence tomography. , 2005, Optics express.

[42]  Hua-bei Jiang,et al.  Three-dimensional bioluminescence tomography with model-based reconstruction. , 2004, Optics express.

[43]  R. Leahy,et al.  Hyperspectral and multispectral bioluminescence optical tomography for small animal imaging , 2005, Physics in medicine and biology.

[44]  J. Willmann,et al.  Molecular imaging in drug development , 2008, Nature Reviews Drug Discovery.