Image-guided diffuse optical fluorescence tomography implemented with Laplacian-type regularization

Abstract

A promising method to incorporate tissue structural information into the reconstruction of diffusion-based fluorescence imaging is introduced. The method regularizes the inversion problem with a Laplacian-type matrix, which inherently smoothes pre-defined tissue, but allows discontinuities between adjacent regions. The technique is most appropriately used when fluorescence tomography is combined with structural imaging systems. Phantom and simulation studies were used to illustrate significant improvements in quantitative imaging and linearity of response with the new algorithm. Images of an inclusion containing the fluorophore Lutetium Texaphyrin (Lutex) embedded in a cylindrical phantom are more accurate than in situations where no structural information is available, and edge artifacts which are normally prevalent were almost entirely suppressed. Most importantly, spatial priors provided a higher degree of sensitivity and accuracy to fluorophore concentration, though both techniques suffer from image bias caused by excitation signal leakage. The use of spatial priors becomes essential for accurate recovery of fluorophore distributions in complex tissue volumes. Simulation studies revealed an inability of the "no-priors" imaging algorithm to recover Lutex fluorescence yield in domains derived from T1 weighted images of a human breast. The same domains were reconstructed accurately to within 75% of the true values using prior knowledge of the internal tissue structure. This algorithmic approach will be implemented in an MR-coupled fluorescence spectroscopic tomography system, using the MR images for the structural template and the fluorescence data for region quantification.

Dynamic dual-tracer MRI-guided fluorescence tomography to quantify receptor density in vivo

“…Applying these principles, imaging fluorescence activity in relatively large tissue volumes (over 5 cm) is feasible. Substantial evidence exists suggesting that volumetric images of fluorescence activity are more accurate if additional information, such as the anatomical features of the tissue, is incorporated in the optical image reconstruction algorithm (29)(30)(31)(32)(33)(34).…”

“…The hybrid MRI-coupled FMT system has been described extensively in previous publications (29,30,45,46). Each animal was imaged with Gd-MRI at least 2 d before the MRI-FMT scans.…”

Spectral distortion in diffuse molecular luminescence tomography in turbid media

“…A complete description of the numerical implementation can be found elsewhere. 8,34,35,39 The emission spectrum of LuTex was modeled from 700 to 850 nm in intervals of at most 10 nm. Some intervals were smaller given the availability of information at additional wavelengths.…”

“…Images of fluorescence yield were recovered using diffusion-based optimization reconstruction techniques described extensively elsewhere. 34,35 Identical reconstruction algorithms were used to consider data detected using one of two measurement approaches. The first approach assumed that measured data were fully wavelength resolved.…”

“…The model platform, NIRFAST, has been developed previously 34,35 using the finite element method ͑FEM͒, which allows consideration of arbitrarily shaped domains with heterogeneous optical properties. Here, the model system is extended to calculate spectrally resolved emission spectra at discrete wavelengths based on fluorescence spectra of dilute solutions and wavelength-dependent optical properties of tissue.…”