Time-resolved imaging has been well-established as the most powerful imaging paradigm in optical tomography by providing rich information datasets for both functional and fluorescence tomography. The practical implementations of time-resolved imaging platforms however are limited by lengthy acquisition times and demand highly stable instrumentation for collection of robust datasets. In recent years, wide-field imaging strategies have been implemented for time-resolved imaging allowing a fast acquisition of spatially- and temporally- rich datasets within short acquisition times. In this work, we present wide-field illumination and processing strategies which significantly improve the signal-to-noise ratio of time-resolved measurements. First, we demonstrate the impact of temporal and photon noise on timeresolved measurements and compare the performance of various born-normalization schemes designed to improve the robustness of the time-resolved data-types used for reconstruction. Secondly, we present a de-noising algorithm design for time-gated data types which reduce errors arising due to noise and conclude with experimental validation of the approach. The adoption of these strategies alleviates some of the limitations associated with time-resolved imaging, especially when using more advanced data types such as early gates, thus allowing the wider acceptance of timeresolved methods for biomedical applications.
KEYWORDS: Monte Carlo methods, Luminescence, Tomography, Sensors, Computer simulations, Photon transport, Picosecond phenomena, Fluorescence tomography, Data modeling, In vivo imaging
We evaluated the potential of mesh-based Monte Carlo (MC) method for widefield time-gated fluorescence molecular tomography, aiming to improve accuracy in both shape discretization and photon transport modeling in preclinical settings. An optimized software platform was developed utilizing multithreading and distributed parallel computing to achieve efficient calculation. We validated the proposed algorithm and software by both simulations and in vivo studies. The results establish that the optimized mesh-based Monte Carlo (mMC) method is a computationally efficient solution for optical tomography studies in terms of both calculation time and memory utilization. The open source code, as part of a new release of mMC, is publicly available at http://mcx.sourceforge.net/mmc/.
KEYWORDS: Fluorescence resonance energy transfer, Molecules, Animal model studies, Near infrared, 3D modeling, Magnetic resonance imaging, Data modeling, Quantum efficiency, Optical tomography, Luminescence
We investigate the feasibility of 3-D localization of Foerster resonance energy transfer (FRET) between two NIR
fluorophores (Alexa Fluor 700 and Alexa Fluor 750) in small animal models. Specifically, the decrease in donor
lifetime upon FRET is used as the contrast mechanism to isolate donor-acceptor pairs undergoing FRET. The
optical tomography system uses a femtosecond tunable laser coupled with a micro-mirror device based digital
light processor as the source to generate wide-field patterns. The time-resolved detection is achieved using a gated
intensified CCD camera. The wide-field excitation scheme described herein provides an experimental advantage
by reducing the time of acquisition of temporally dense datasets. In this study, anatomical information obtained
using MR imaging is used in the computation of the Monte Carlo (MC) based forward model. The MC model
reconstructs the 3D distribution of the quantum yield of the donor fluorophore and the FRET complex using
the time-gate data type allowing the estimation of fractional distribution (D) of donor molecules undergoing
FRET and unquenched donor molecules. The performance of this approach in the estimation of D using the
position of fluorophores obtained using the MRI is investigated.
We propose the use of Time-Resolved Diffuse Optical Tomography in a multispectral scheme with anatomical constraints supplied by MR imaging to reconstruct functional parameters of the animal model with greater accuracy and resolution. The tomographic imaging system described is capable of acquiring temporal measurements
in multiple-views using a gated ICCD camera. A tunable Ti-Sapphire pulsed laser at wavelengths between 700nm - 1000nm is used as the source. Anatomical distribution is determined using MRI in a non-concurrent setting. Time-resolved measurements at multiple wavelengths in the NIR window combined with the anatomical constraints
is used to determine a 3D distribution of the functional parameters in vivo. Multispectral spectroscopy measurements on homogenous tissue simulating phantoms are used to demonstrate the accuracy of the system
in determining optical parameters in thin tissues. We show that temporal measurements combined with MRI data can be used to accurately quantify optical properties in heterogeneous tissues.
Diffuse optical tomography using perturbation Monte Carlo method can overcome the drawback inherent to the classical model based on the diffusion equation for pre-clinical applications. The combined use of information from different time gates enables image reconstruction with accurate quantification and reducing the crosstalk between the absorption and the scattering coefficients. In this work, we apply this approach to solve an inverse problem of a 3D mouse model, and investigate the benefit to incorporate the time-resolved data into the optical reconstruction for quantitative functional imaging.
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