Three‐dimensional fluorescence lifetime tomography

Godavarty, Anuradha; Sevick‐Muraca, Eva M.; Eppstein, Margaret J.

doi:10.1118/1.1861160

Cited by 106 publications

(91 citation statements)

References 40 publications

(63 reference statements)

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“…[15][16][17] The theoretical foundation of phosphorescence lifetime imaging (PLI) closely resembles that of fluorescence lifetime imaging (FLI). [18][19][20][21] However, large differences between phosphorescent and fluorescent lifetimes (typically 4-5 orders of magnitude) bring about considerable differences in instrumentation and approaches to lifetime distribution reconstruction. For example, photon migration times in tissue are comparable to singlet state lifetimes of fluorescent contrast agents (nanoseconds).…”

Section: Introductionmentioning

confidence: 99%

Tomographic imaging of oxygen by phosphorescence lifetime

2006

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Imaging of oxygen in tissue in three dimensions can be accomplished by using the phosphorescence quenching method in combination with diffuse optical tomography. We experimentally demonstrate the feasibility of tomographic imaging of oxygen by phosphorescence lifetime. Hypoxic phantoms were immersed in a cylinder with scattering solution equilibrated with air. The phantoms and the medium inside the cylinder contained near-infrared phosphorescent probe(s). Phosphorescence at multiple boundary sites was registered in the time domain at different delays (t d ) following the excitation pulse. The duration of the excitation pulse (t p ) was regulated to optimize the contrast in the images. The reconstructed integral intensity images, corresponding to delays t d , were fitted exponentially to give the phosphorescence lifetime image, which was converted into the threedimensional image of oxygen concentrations in the volume. The time-independent diffusion equation and the finite element method were used to model the light transport in the medium. The inverse problem was solved by the recursive maximum entropy method. We provide what we believe to be the first example of oxygen imaging in three dimensions using long-lived phosphorescent probes and establish the potential of these probes for diffuse optical tomography.

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Section: Introductionmentioning

confidence: 99%

Tomographic imaging of oxygen by phosphorescence lifetime

2006

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“…In fact, lifetime detection is highly suitable for tomographic imaging because of its concentration independence and because of the linear combination of lifetimes in a multispecies mixture and has been demonstrated successfully in a two-lifetime component phantom model of breast tissue (background fluorescence) with a deep fluorescent ''tumor'' target. A lifetime contrast of only a factor of 2 was completely sufficient to detect and map the target (40). Furthermore, a tumor-targeting fluorophore can be endowed with lifetime-encoded sensing capabilities.…”

Section: Rotation Projection Geometriesmentioning

confidence: 96%

“…Therefore, reconstruction-based statistical approaches can extract the true fluorescent lifetime of fluorophores and their depth distribution can be obtained as a separate reconstruction (51). A functional 3D fluorescence lifetime discriminating tomographic microscopy system based on this detection principle was constructed and successfully tested on a phantom mouse with two inclusions filled with fluorophores with different lifetimes (40).…”

Section: Depth-resolved Imagingmentioning

confidence: 99%

Advances in cellular, subcellular, and nanoscale imaging in vitro and in vivo

Wessels¹,

Yamauchi

Hoffman

et al. 2010

Cytometry Pt A

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This review focuses on technical advances in fluorescence microscopy techniques including laser scanning techniques, fluorescence-resonance energy transfer (FRET) microscopy, fluorescence lifetime imaging (FLIM), stimulated emission depletion (STED)-based super-resolution microscopy, scanning confocal endomicroscopes, thinsheet laser imaging microscopy (TSLIM), and tomographic techniques such as early photon tomography (EPT) as well as on clinical laser-based endoscopic and microscopic techniques. We will also discuss the new developments in the field of fluorescent dyes and fluorescent genetic reporters that enable new possibilities in high-resolution and molecular imaging both in in vitro and in vivo. Small animal and tissue imaging benefit from the development of new fluorescent proteins, dyes, and sensing constructs that operate in the far red and near-infrared spectrum. ' 2010 International Society for Advancement of Cytometry

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“…Simulations are used to show that time-domain fluorescence tomography, implemented via the asymptotic lifetime-based approach, offers a significantly better separability of multiple lifetime targets than a frequency-domain approach. We also demonstrate experimentally, using complex-shaped phantoms, the advantages of the asymptotic time-domain approach over a Fourier-based approach for analyzing time-domain fluorescence data.Optical technologies for noninvasive macroscopic fluorescence imaging in biological media utilize three main approaches: time domain (TD) using pulsed light sources [1][2][3][4][5], frequency domain (FD) using megahertz modulated sources [6][7][8], and continuous wave (CW) using steady state light sources [9][10][11]. Of these, the TD approach is the most comprehensive, since a short laser pulse (fs-ps) implicitly contains all the modulation frequencies, including the zero-frequency component.…”

mentioning

confidence: 99%

Comparison of frequency-domain and time-domain fluorescence lifetime tomography

et al. 2008

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We compare frequency-and time-domain formulations of deep-tissue fluorescence imaging of turbid media. Simulations are used to show that time-domain fluorescence tomography, implemented via the asymptotic lifetime-based approach, offers a significantly better separability of multiple lifetime targets than a frequency-domain approach. We also demonstrate experimentally, using complex-shaped phantoms, the advantages of the asymptotic time-domain approach over a Fourier-based approach for analyzing time-domain fluorescence data.Optical technologies for noninvasive macroscopic fluorescence imaging in biological media utilize three main approaches: time domain (TD) using pulsed light sources [1][2][3][4][5], frequency domain (FD) using megahertz modulated sources [6][7][8], and continuous wave (CW) using steady state light sources [9][10][11]. Of these, the TD approach is the most comprehensive, since a short laser pulse (fs-ps) implicitly contains all the modulation frequencies, including the zero-frequency component. The tomographic analysis of TD data can, however, pose computational challenges. Several simplifications have been attempted, primarily using derived data types such as the fast Fourier transform (FFT) [5,7]. The FFT simplifies the TD forward problem but reduces it to a FD forward problem, identical to that for a genuine FD measurement. Alternatively, TD fluorescence data may also be analyzed by estimating lifetimes directly from the asymptotic region, followed by the separate inversion of the yield of each lifetime component [3,12]. The question arises as to how the FD forward problem compares with the asymptotic TD (ATD) approach, when lifetime sensitive targets are used. In this Letter, we address this question both with simulated and experimental TD data in the context of small animal imaging applications.Consider a diffuse imaging medium of finite support Ω, embedded with fluorophores characterized by yield and lifetime distributions, η (r) and τ(r). In the FD approach, the forward problem takes the form [6] (1) Here, G x and G m are the FD Green's functions at frequency ω for propagation from a source r s and a detector r d , respectively, to a medium point r. Equation (1) is first inverted to obtainThe lifetimes are then obtained from the phase Ø(r,ω) of F, as τ(r)=ø(r,ω)/ω. Finally, the yield reconstructions are given by . In the ATD approach, the decay amplitudes, a n (r s ,r d ), for each lifetime component, τ n =1/Γ n , take the place of the Fourier amplitude, , as the measurement data set [3]. The a n 's are related to the yield distribution, η n (r), for the lifetime component at τ n , through a linear forward problem:Note that in Eq. (2), the Green's functions are the same as that for the FD case in Eq. (1), but evaluated at an imaginary frequency of -iΓ n . (see [12] for details). The difference between Eq.(1) and Eq. (2) is clear if we express F(r,ω) in terms of discrete lifetimes rather than the continuous distributions τ(r). We then get F(r,ω)=∑ n τ n η n (r)/(1-iωτ n ). Thus ...

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Three‐dimensional fluorescence lifetime tomography

Cited by 106 publications

References 40 publications

Tomographic imaging of oxygen by phosphorescence lifetime

Tomographic imaging of oxygen by phosphorescence lifetime

Advances in cellular, subcellular, and nanoscale imaging in vitro and in vivo

Comparison of frequency-domain and time-domain fluorescence lifetime tomography

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