Do fluorescence decays remitted from tissues accurately reflect intrinsic fluorophore lifetimes?

Noninvasive Optical Assessment of Implanted Engineered Tissues Correlates with Cytokine Secretion

Fluorescence lifetime sensing has been shown to noninvasively characterize the preimplantation health and viability of engineered tissue constructs. However, current practices to monitor postimplantation construct integration are either qualitative (visual assessment) or destructive (tissue histology). We employed label-free fluorescence lifetime spectroscopy for quantitative, noninvasive optical assessment of engineered tissue constructs that were implanted into a murine model. The portable system was designed to be suitable for intravital measurements and included a handheld probe to precisely and rapidly acquire data at multiple sites per construct. Our model tissue constructs were manufactured from primary human cells to simulate patient variability based on a standard protocol, and half of the manufactured constructs were stressed to create a range of health states. Secreted amounts of three cytokines that relate to cellular viability were measured in vitro to assess preimplantation construct health: interleukin-8 (IL-8), human β-defensin 1 (hBD-1), and vascular endothelial growth factor (VEGF). Preimplantation cytokine secretion ranged from 1.5 to 33.5 pg/mL for IL-8, from 3.4 to 195.0 pg/mL for hBD-1, and from 0.1 to 154.3 pg/mL for VEGF. In vivo optical sensing assessed constructs at 1 and 3 weeks postimplantation. We found that at 1 week postimplantation, in vivo optical parameters correlated with in vitro preimplantation secretion levels of all three cytokines (p < 0.05). This correlation was not observed in optical measurements at 3 weeks postimplantation when histology showed that the constructs had re-epithelialized, independent of preimplantation health state, supporting the lack of a correlation. These results suggest that clinical optical diagnostic tools based on label-free fluorescence lifetime sensing of endogenous tissue fluorophores could noninvasively monitor postimplantation integration of engineered tissues.

Hybrid Monte Carlo simulation with ray tracing for fluorescence measurements in turbid media

We present a hybrid Monte Carlo simulation method with geometrical ray tracing (hMC-GRT) to model fluorescence excitation and detection in turbid media by optical imaging or spectroscopy systems employing a variety of optical components. hMC-GRT computational verification was achieved via reflectance and fluorescence simulations on epithelial tissue models in comparison with a standard Monte Carlo code. The mean difference between the two simulations was less than 5%. hMC-GRT experimental verification employed depth-sensitive steady-state fluorescence measurements using an aspherical lens on two-layered tissue phantoms. hMC-GRT predictions agreed well with experimental results, achieving less than 3.5% error for measurements at the phantom surface. Verification results demonstrate that the hMC-GRT simulation has the potential to become a useful computational toolbox for designing tissue fluorescence imaging and spectroscopy systems. In addition, the hMC-GRT approach enables a wide variety of applications for computational modeling of fluorescence in turbid media. The source codes are available at https://github.com/ubioptronics/hMC-GRT.

Programmable LED-based integrating sphere light source for wide-field fluorescence microscopy

Wide-field fluorescence microscopy commonly uses a mercury lamp, which has limited spectral capabilities. We designed and built a programmable integrating sphere light (PISL) source which consists of nine LEDs, light-collecting optics, a commercially available integrating sphere and a baffle. The PISL source is tuneable in the range 365-490nm with a uniform spatial profile and a sufficient power at the objective to carry out spectral imaging. We retrofitted a standard fluorescence inverted microscope DM IRB (Leica) with a PISL source by mounting it together with a highly sensitive low- noise CMOS camera. The capabilities of the setup have been demonstrated by carrying out multispectral autofluorescence imaging of live BV2 cells.

Deconvolution of fluorescence lifetime imaging microscopy by a library of exponentials

Fluorescence lifetime microscopy imaging (FLIM) is an optic technique that allows a quantitative characterization of the fluorescent components of a sample. However, for an accurate interpretation of FLIM, an initial processing step is required to deconvolve the instrument response of the system from the measured fluorescence decays. In this paper, we present a novel strategy for the deconvolution of FLIM data based on a library of exponentials. Our approach searches for the scaling coefficients of the library by non-negative least squares approximations plus Thikonov/l₂ or l₁ regularization terms. The parameters of the library are given by the lower and upper bounds in the characteristic lifetimes of the exponential functions and the size of the library, where we observe that this last variable is not a limiting factor in the resulting fitting accuracy. We compare our proposal to nonlinear least squares and global non-linear least squares estimations with a multi-exponential model, and also to constrained Laguerre-base expansions, where we visualize an advantage of our proposal based on Thikonov/l₂ regularization in terms of estimation accuracy, computational time, and tuning strategy. Our validation strategy considers synthetic datasets subject to both shot and Gaussian noise and samples with different lifetime maps, and experimental FLIM data of ex-vivo atherosclerotic plaques and human breast cancer cells.

Blind deconvolution estimation of fluorescence measurements through quadratic programming

Time-deconvolution of the instrument response from fluorescence lifetime imaging microscopy (FLIM) data is usually necessary for accurate fluorescence lifetime estimation. In many applications, however, the instrument response is not available. In such cases, a blind deconvolution approach is required. An iterative methodology is proposed to address the blind deconvolution problem departing from a dataset of FLIM measurements. A linear combination of a base conformed by Laguerre functions models the fluorescence impulse response of the sample at each spatial point in our formulation. Our blind deconvolution estimation (BDE) algorithm is formulated as a quadratic approximation problem, where the decision variables are the samples of the instrument response and the scaling coefficients of the basis functions. In the approximation cost function, there is a bilinear dependence on the decision variables. Hence, due to the nonlinear nature of the estimation process, an alternating least-squares scheme iteratively solves the approximation problem. Our proposal searches for the samples of the instrument response with a global perspective, and the scaling coefficients of the basis functions locally at each spatial point. First, the iterative methodology relies on a least-squares solution for the instrument response, and quadratic programming for the scaling coefficients applied just to a subset of the measured fluorescence decays to initially estimate the instrument response to speed up the convergence. After convergence, the final stage computes the fluorescence impulse response at all spatial points. A comprehensive validation stage considers synthetic and experimental FLIM datasets of ex vivo atherosclerotic plaques and human breast cancer cell samples that highlight the advantages of the proposed BDE algorithm under different noise and initial conditions in the iterative scheme and parameters of the proposal.

Two-photon excited fluorescence enhancement with broadband versus tunable femtosecond laser pulse excitation

The inverse relationship between two-photon excited fluorescence (TPEF) and laser pulse duration suggests that two-photon microscopy (TPM) performance may be improved by decreasing pulse duration. However, for ultrashort pulses of sub-10 femtosecond (fs) in duration, its spectrum contains the effective gain bandwidth of Ti:Sapphire and its central wavelength is no longer tunable. An experimental study was performed to explore this apparent tradeoff between untuned sub-10 fs transform-limited pulse (TLP) and tunable 140 fs pulse for TPEF. Enhancement factors of 1.6, 6.7, and 5.2 are measured for Indo-1, FITC, and TRITC excited by sub-10 fs TLP compared with 140 fs pulse tuned to the two-photon excitation (TPE) maxima at 730 nm, 800 nm, and 840 nm, respectively. Both degenerate (v(1) = v(2)) and nondegenerate (v(1) ≠ v(2)) mixing of sub-10 fs TLP spectral components result in its broad second-harmonic (SH) power spectrum and high spectral density, which can effectively compensate for the lack of central wavelength tuning and lead to large overlap with dye TPE spectra for TPEF enhancements. These pulse properties were also exploited for demonstrating its potential applications in multicolor imaging with TPM.

Monte Carlo modeling of time-resolved fluorescence for depth-selective interrogation of layered tissue

Computational approaches for simulation of light-tissue interactions have provided extensive insight into biophotonic procedures for diagnosis and therapy. However, few studies have addressed simulation of time-resolved fluorescence (TRF) in tissue and none have combined Monte Carlo simulations with standard TRF processing algorithms to elucidate approaches for cancer detection in layered biological tissue. In this study, we investigate how illumination-collection parameters (e.g., collection angle and source-detector separation) influence the ability to measure fluorophore lifetime and tissue layer thickness. Decay curves are simulated with a Monte Carlo TRF light propagation model. Multi-exponential iterative deconvolution is used to determine lifetimes and fractional signal contributions. The ability to detect changes in mucosal thickness is optimized by probes that selectively interrogate regions superficial to the mucosal-submucosal boundary. Optimal accuracy in simultaneous determination of lifetimes in both layers is achieved when each layer contributes 40-60% of the signal. These results indicate that depth-selective approaches to TRF have the potential to enhance disease detection in layered biological tissue and that modeling can play an important role in probe design optimization.

Development of a spatially offset Raman spectroscopy probe for breast tumor surgical margin evaluation

The risk of local recurrence for breast cancers is strongly correlated with the presence of a tumor within 1 to 2 mm of the surgical margin on the excised specimen. Previous experimental and theoretical results suggest that spatially offset Raman spectroscopy (SORS) holds much promise for intraoperative margin analysis. Based on simulation predictions for signal-to-noise ratio differences among varying spatial offsets, a SORS probe with multiple source-detector offsets was designed and tested. It was then employed to acquire spectra from 35 frozen-thawed breast tissue samples in vitro. Spectra from each detector ring were averaged to create a composite spectrum with biochemical information covering the entire range from the tissue surface to ∼2 mm below the surface, and a probabilistic classification scheme was used to classify these composite spectra as "negative" or "positive" margins. This discrimination was performed with 95% sensitivity and 100% specificity, or with 100% positive predictive value and 94% negative predictive value.

Models of light propagation in human tissue applied to cancer diagnostics

Optical methods such as reflectance and fluorescence spectroscopy are being investigated for their potential to aid cancer detection in a quantitative, minimally invasive manner. Mathematical models of reflectance and fluorescence provide an important link between measured optical data and biomedically-relevant tissue parameters that can be extracted from these data to characterize the presence or absence of disease. The most commonly-used mathematical models in biomedical optics are the diffusion approximation (DA) to the radiative transfer equation, Monte Carlo (MC) computational models of light transport, and semi-empirical models. This paper presents a review of the applications of these models to reflectance and endogenous fluorescence sensing for cancer diagnostics in human tissues. Specific examples are given for cervical, breast, and pancreatic tissues. A comparison of the DA and MC methods in two biologically-relevant regimes of optical parameter space will also be discussed.

Photon-tissue interaction model enables quantitative optical analysis of human pancreatic tissues

A photon-tissue interaction (PTI) model was developed and employed to analyze 96 pairs of reflectance and fluorescence spectra from freshly excised human pancreatic tissues. For each pair of spectra, the PTI model extracted a cellular nuclear size parameter from the measured reflectance, and the relative contributions of extracellular and intracellular fluorophores to the intrinsic fluorescence. The results suggest that reflectance and fluorescence spectroscopies have the potential to quantitatively distinguish among pancreatic tissue types, including normal pancreatic tissue, pancreatitis, and pancreatic adenocarcinoma.

Instrumentation to rapidly acquire fluorescence wavelength-time matrices of biological tissues

A fiber-optic system was developed to rapidly acquire tissue fluorescence wavelength-time matrices (WTMs) with high signal-to-noise ratio (SNR). The essential system components (473 nm microchip laser operating at 3 kHz repetition frequency, fiber-probe assemblies, emission monochromator, photomultiplier tube, and digitizer) were assembled into a compact and clinically-compatible unit. Data were acquired from fluorescence standards and tissue-simulating phantoms to test system performance. Fluorescence decay waveforms with SNR > 100 at the decay curve peak were obtained in less than 30 ms. With optimized data transfer and monochromator stepping functions, it should be feasible to acquire a full WTM at 5 nm emission wavelength intervals over a 200 nm range in under 2 seconds.

Monte Carlo model of spatially offset Raman spectroscopy for breast tumor margin analysis

We have previously demonstrated the discrimination of two layers of soft tissue, specifically normal breast tissue overlying breast tumor, using spatially offset Raman spectroscopy (SORS). In this report, a Monte Carlo code for evaluating SORS in soft tissues has been developed and compared to experimental results. The model was employed to investigate the effects of tissue and probe geometry on SORS measurements and therefore to develop the design strategies of applying SORS for breast tumor surgical margin evaluation. The model was used to predict SORS signals for different tissue geometries difficult to precisely control experimentally, such as varying normal and tumor layer sizes and the addition of a third layer. The results from the model suggest that, using source-detector separations of up to 3.75 mm, SORS can detect sub-millimeter-thick tumors under a 1 mm normal layer, and tumors at least 1 mm thick can be detected under a 2 mm normal layer.

Optical spectroscopy detects histological hallmarks of pancreatic cancer

An empirical model was developed to interpret differences in the experimentally measured reflectance and fluorescence spectra of freshly excised human pancreatic tissues: normal, adenocarcinoma, and pancreatitis (inflammation). The model provided the first quantitative links between spectroscopic measurements and histological characteristics in the human pancreas. The reflectance model enabled the first (to our knowledge) extraction of wavelength resolved absorption and reduced scattering coefficients for normal and diseased human pancreatic tissues. The fluorescence model employed reflectance information to extract attenuation free "intrinsic" endogenous fluorescence spectra from normal pancreatic tissue, pancreatic adenocarcinoma, and pancreatitis. The method developed is simple, intuitive, and potentially useful for a range of applications in optical tissue diagnostics. This approach is potentially applicable to in vivo studies, because it can account for the absorptive effects of blood in tissues.

Half-ball lens couples a beveled fiber probe for depth-resolved spectroscopy: Monte Carlo simulations

In this study, we propose a beveled fiber-optic probe coupled with a half-ball lens for improving the depth-resolved fluorescence measurements of epithelial tissue. The Monte Carlo (MC) simulation results show that for a given excitation-collection fiber separation, the probe design with a bevel-angled collection fiber is more sensitive to detect fluorescence photons emitted from the shallow layer of tissue, whereas the flat-tip collection fiber is in favor of probing fluorescence photons originating from deeper tissue areas. This compact half-ball lens-beveled fiber probe design has the potential to facilitate the depth-resolved fluorescence detection of epithelial tissue.

Probing pancreatic disease using tissue optical spectroscopy

Pancreatic adenocarcinoma, one of the leading causes of cancer death in the United States, has a five-year survival rate of only 4%. Present detection methods do not provide accurate diagnosis in the disease's early stages. To investigate whether optical spectroscopy could potentially aid in early diagnosis and improve survival rates, reflectance and fluorescence spectroscopies were employed for the first time in a limited pilot study to probe freshly excised human pancreatic tissues (normal, pancreatitis, and adenocarcinoma) and in vivo human pancreatic cancer xenografts in nude mice. In human pancreatic tissues, measurements were associated with endogenous fluorophores NAD(P)H and collagen, as well as tissue optical properties, with larger relative collagen content detected in adenocarcinoma and pancreatitis than normal. Good correspondence was observed between spectra from adenocarcinoma and cancer xenograft tissues. Reflectance data indicated that adenocarcinoma had higher reflectance in the 430- to 500-nm range compared to normal and pancreatitis tissues. The observed significant differences between the fluorescence and reflectance properties of normal, pancreatitis, and adenocarcinoma tissues present an opportunity for future statistical validation on a larger patient pool and indicate a potential application of multimodal optical spectroscopy to differentiate between diseased and normal pancreatic tissue states.

Feasibility analysis of an epidermal glucose sensor based on time-resolved fluorescence

The goal of this study is to test the feasibility of using an embedded time-resolved fluorescence sensor for monitoring glucose concentration. Skin is modeled as a multilayer medium with each layer having its own optical properties and fluorophore absorption coefficients, lifetimes, and quantum yields obtained from the literature. It is assumed that the two main fluorophores contributing to the fluorescence at these excitation and emission wavelengths are nicotinamide adenine dinucleotide (NAD)H and collagen. The intensity distributions of excitation and fluorescent light in skin are determined by solving the transient radiative transfer equation by using the modified method of characteristics. The fluorophore lifetimes are then recovered from the simulated fluorescence decays and compared with the actual lifetimes used in the simulations. Furthermore, the effect of adding Poissonian noise to the simulated decays on recovering the lifetimes was studied. For all cases, it was found that the fluorescence lifetime of NADH could not be recovered because of its negligible contribution to the overall fluorescence signal. The other lifetimes could be recovered to within 1.3% of input values. Finally, the glucose concentrations within the skin were recovered to within 13.5% of their actual values, indicating a possibility of measuring glucose concentrations by using a time-resolved fluorescence sensor.

Combined depth- and time-resolved autofluorescence spectroscopy of epithelial tissue

A time-resolved confocal fluorescence spectroscopy system is built to measure the fine structure and localized biochemistry of epithelial tissue. It is found that the autofluorescence excited at 405 nm is sensitive to the cellular metabolism and can be used to sense the metabolic status of epithelial tissue. The decay of autofluorescence excited at 405 nm can be accurately fitted with a dual-exponential function consisting of short lifetime (0.4-0.6 ns) and long lifetime (3-4 ns) components. The ratio of the amplitudes of the two components provides information on the fine structure of epithelial tissue. We demonstrate that the combined depth- and time-resolved measurements with single excitation can potentially provide accurate information for the diagnosis of tissue pathology.

Time-resolved photon migration in bi-layered tissue models

In this article, we describe a novel Monte Carlo code for time-integrated and time-resolved photon migration simulations of excitation and fluorescent light propagation (with reabsorption) in bi-layered models of biological tissues. The code was experimentally validated using bi-layered, tissue-simulating phantoms and the agreement between simulations and experiment was better than 3%. We demonstrate the utility of the code for quantitative clinical optical diagnostics in epithelial tissues by examining design characteristics for clinically compatible waveguides with arbitrarily complex source-detector configurations. Results for human colonic tissues included a quantitative comparison of simulation predictions with time-resolved fluorescence data measured in vivo and spatio-temporal visualizations of photon migration characteristics in tissue models in both two- and three-dimensions for source-detector configurations, including variable waveguide spacing, numerical aperture, and diameter. These results were then extended from surface point spectroscopy to imaging modalities for both time-gated (fluorescence lifetime) and steady-state (fluorescence intensity) experimental conditions. To illustrate the flexibility of this computational approach, time-domain results were extended to simulate predictions for frequency-domain instrumentation. This work is the first demonstration and validation of a time-domain, multi-wavelength photon transport model with these capabilities in layered turbid-media.