Direct Monte Carlo computation of time-resolved fluorescence in heterogeneous turbid media

Beyond conventional wisdom: unveiling quantitative insights in fluorescence lifetime imaging via realistic simulation of biological systems

Fluorescence lifetime imaging microscopy (FLIM) and photometry (FLiP) are illuminating the dynamics of biological signals. Because fluorescence lifetime is an intensive property of a fluorophore that is insensitive to sensor expression levels, it excels over fluorescence intensity measurements by allowing comparison across animals, over chronic time periods, and quantitation of the absolute levels of biological signals. However, the insensitivity of lifetime to sensor expression level does not always hold true in biological experiments where autofluorescence, ambient light, dark currents and afterpulses of the detectors are present. To quantitatively evaluate the potential and limitations of fluorescence lifetime measurements, we introduce FLiSimBA, a flexible platform enabling realistic F luorescence Li fetime Sim ulation for B iological A pplications. FLiSimBA accurately recapitulates experimental data and provides quantitative analyses. Using FLiSimBA, we determine the photons required for minimum detectable differences in lifetime and quantify the impact of hardware innovation. Furthermore, we challenge the conventional view that fluorescence lifetime is insensitive to sensor expression levels and define the conditions in which sensor express levels do not result in statistically significant difference in biological experiments. Thus, we introduce an adaptable simulation tool that allows systematic exploration of parameters to define experimental advantages and limitations in biological applications. Moreover, we provide a statistical framework and quantitative insights into the impact of key experimental parameters on signal-to-noise ratio and fluorescence lifetime responses. Our tool and results will enable the growing community of FLIM users and developers to optimize FLIM experiments, expose limitations, and identify opportunities for future innovation of fluorescence lifetime technologies.

First-order approximation of fluorescence excitation-transmission to accelerate fluorescence molecular tomography image reconstruction

We present a method to accelerate image reconstruction in fluorescence molecular tomography based on the historical path fluorescence Monte Carlo model. The method exploits a first-order approximation expression during the fluorescence excitation-transmission process to merge the path and state information of the photon in a voxel. The experiments show that our method not only greatly reduces the amount of data required for storage in the hard disk and accelerates image reconstruction, but also maintains the quantitative and positioning accuracy of the conventional method.

Accelerating fDOT image reconstruction based on path-history fluorescence Monte Carlo model by using three-level parallel architecture

The excessive time required by fluorescence diffuse optical tomography (fDOT) image reconstruction based on path-history fluorescence Monte Carlo model is its primary limiting factor. Herein, we present a method that accelerates fDOT image reconstruction. We employ three-level parallel architecture including multiple nodes in cluster, multiple cores in central processing unit (CPU), and multiple streaming multiprocessors in graphics processing unit (GPU). Different GPU memories are selectively used, the data-writing time is effectively eliminated, and the data transport per iteration is minimized. Simulation experiments demonstrated that this method can utilize general-purpose computing platforms to efficiently implement and accelerate fDOT image reconstruction, thus providing a practical means of using path-history-based fluorescence Monte Carlo model for fDOT imaging.

Accurate quantification of fluorescent targets within turbid media based on a decoupled fluorescence Monte Carlo model

We propose a method based on a decoupled fluorescence Monte Carlo model for constructing fluorescence Jacobians to enable accurate quantification of fluorescence targets within turbid media. The effectiveness of the proposed method is validated using two cylindrical phantoms enclosing fluorescent targets within homogeneous and heterogeneous background media. The results demonstrate that our method can recover relative concentrations of the fluorescent targets with higher accuracy than the perturbation fluorescence Monte Carlo method. This suggests that our method is suitable for quantitative fluorescence diffuse optical tomography, especially for in vivo imaging of fluorophore targets for diagnosis of different diseases and abnormalities.

In vivo tomographic imaging of deep-seated cancer using fluorescence lifetime contrast

Preclinical cancer research would benefit from noninvasive imaging methods that allow tracking and visualization of early-stage metastasis in vivo. Although fluorescent proteins revolutionized intravital microscopy, two major challenges that still remain are tissue autofluorescence and hemoglobin absorption, which act to limit intravital optical techniques to large or subcutaneous tumors. Here, we use time-domain (TD) technology for the effective separation of tissue autofluorescence from extrinsic fluorophores, based on their distinct fluorescence lifetimes. In addition, we use cancer cells labeled with near infrared fluorescent proteins (iRFP) to allow deep-tissue imaging. Our results demonstrate that TD imaging allows the detection of metastasis in deep-seated organs of living mice with a more than 20-fold increase in sensitivity compared with conventional continuous wave techniques. Furthermore, the distinct fluorescence lifetimes of iRFPs enable lifetime multiplexing of three different tumors, each expressing unique iRFP labels in the same animal. Fluorescence tomographic reconstructions reveal three-dimensional distributions of iRFP720-expressing cancer cells in lungs and brain of live mice, allowing ready longitudinal monitoring of cancer cell fate with greater sensitivity than otherwise currently possible.

Evaluation of path-history-based fluorescence Monte Carlo method for photon migration in heterogeneous media

The path-history-based fluorescence Monte Carlo method used for fluorescence tomography imaging reconstruction has attracted increasing attention. In this paper, we first validate the standard fluorescence Monte Carlo (sfMC) method by experimenting with a cylindrical phantom. Then, we describe a path-history-based decoupled fluorescence Monte Carlo (dfMC) method, analyze different perturbation fluorescence Monte Carlo (pfMC) methods, and compare the calculation accuracy and computational efficiency of the dfMC and pfMC methods using the sfMC method as a reference. The results show that the dfMC method is more accurate and efficient than the pfMC method in heterogeneous medium.