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

Abstract

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.

Investigation of an adaptive regularization parameter selection methodin bioluminescence tomography

“…In the experiments, two bands (580 nm and 620 nm) were adopted. And the corresponding optical parameters could be found from the literature [19]. To avoid the "inverse crime", the synthetic simulated data was produced on a finer mesh which was different from the mesh used in reconstruction.…”

Systematic calibration of an integrated x‐ray and optical tomography system for preclinical radiation research

“…After converting the CCD reading into the emittance E at the tissue/phantom surface, the emittance was then used to calculate the fluence rate just inside the surface Φ in by considering the refractive index mismatch between air and tissue/phantom. With Robin type III boundary condition, 17 we can derive…”

“…15 Recently, optical imaging has advanced from two-dimensional planar imaging to three-dimensional tomography to provide improved spatial and quantitative accuracy. [16][17][18][19] By integrating the molecular optical imaging with the onboard CBCT, complementary image information can be acquired to guide focal tumor irradiation, with CBCT delineating anatomic structures and optical imaging differentiating and even quantifying luminescent tumor cells. The integrated imaging system can better localize the tumor to guide focal irradiation in the soft tissue environment.…”

Improved sparse reconstruction for fluorescence molecular tomography with L_1/2 regularization

“…In this experiment, a glass tube with 0.6 mm radius and 2.8 mm height, which contains Cy5.5 solution (with the extinction coefficient of about 0.019mm -1 µM -1 and quantum efficiency of 0.23 at the peak excitation wavelength of 671 nm) [42], was implanted into the abdomen of the anesthetized mouse. The true fluorescent yield of Cy5.5 is 1 0.0402mm − [43]. With Micro-CT, the true center of the target was determined as (28.5, 25.7, 13.4mm).…”