Abstract

Fluorescence and phosphorescence lifetime imaging are powerful techniques for studying intracellular protein interactions and for diagnosing tissue pathophysiology. While lifetime-resolved microscopy has long been in the repertoire of the biophotonics community, current implementations fall short in terms of simultaneously providing 3D resolution, high throughput, and good tissue penetration. This report describes a new highly efficient lifetime-resolved imaging method that combines temporal focusing wide-field multiphoton excitation and simultaneous acquisition of lifetime information in frequency domain using a nanosecond gated imager from a 3D-resolved plane. This approach is scalable allowing fast volumetric imaging limited only by the available laser peak power. The accuracy and performance of the proposed method is demonstrated in several imaging studies important for understanding peripheral nerve regeneration processes. Most importantly, the parallelism of this approach may enhance the imaging speed of long lifetime processes such as phosphorescence by several orders of magnitude.

© 2012 OSA

1. Introduction

Fluorescence (FLIM) and phosphorescence (PLIM) lifetime microscopies are information-rich optical spectroscopic techniques [17]. A particularly important application of FLIM is in the quantification of Förster resonance energy transfer (FRET), the preferred method of quantifying intracellular protein-protein interactions in vivo. For example, FRET measurements have been used to measure intramolecular distances [8], and to observe dynamic conformational changes in proteins [9] and RNA [10]. FLIM has been also applied in disease diagnosis. Koenig and associates found that normal skin and cutaneous melanoma can be differentiated by their morphological appearances in combination with their fluorescence lifetime spectroscopic signatures [11]. A clinical trial across multiple centers in Europe is underway to test the utility of multiphoton FLIM in the minimally invasive diagnosis of melanoma [12].

While PLIM is not as widely used as FLIM, this methodology nonetheless has several important potential biomedical applications due to the availability of phosphorescence-based oxygen sensors. Quenching of phosphorescence by oxygen affects the phosphorescence lifetime of such sensors, which then enables measurement of oxygen partial pressure in vivo in tissues or thick biological samples with high temporal and spatial resolution [1315]. PLIM-based partial oxygen measurements can be used to quantify the degree of hypoxic tissues or tumors, a critical physiological parameter of solid tumors that determines tumor growth, gene expression [16], metastatic potential [17], metabolism, prognosis [1820], and response to therapy [21, 22]. The use of PLIM-based oxygen sensors has also enabled the quantification of oxygen supply and consumption in the brain, which is critical for understanding brain metabolism and cognitive function [23, 24]. Today, PLIM is not widely used mostly due to the associated long lifetime which entails typical image frame rate on the order of minutes to hours.

The implementations of FLIM and PLIM measurements in microscopy have different challenges. For FLIM, the need for picoseconds level timing resolution of photon arrival time requires fast electronics; for PLIM, the long lifetime (up to milliseconds) significantly lengthens the required pixel residence time and slows the image frame rate. In general, FLIM and PLIM measurements can be performed either in the time-domain or in the frequency-domain. In the time domain, a light pulse of short duration excites the sample and the time delay of the emitted photon is measured. A histogram of these time delays provides a direct measurement of the fluorophore’s lifetime. Typical fluorophores exhibit single exponential decay kinetics in a homogeneous micro-environment. However, in practice, even for fluorophores with single exponential decay dynamics, the experimentally measured time delay histogram is a convolution of an unknown instrumentation response and the exponential decay of the fluorophore. In the presence of more complex environments, multiple exponential decays must be resolved. The frequency-domain approach is, mathematically, the Fourier equivalent of the time-domain. In the frequency-domain, the excitation light is modulated at a frequency, ω. The intrinsic fluorescence temporal response acts as a low-pass filter and the emitted fluorescent light is phase shifted (∆ϕ) and modulated (M). For single exponential decay fluorophores, the modulation and phase shift are related to the fluorescence lifetime as:

Δφ=tan(ωτ)andM=11+ω2τ2

More complex decay mechanisms can be measured by measuring the modulation and phase shift at multiple excitation frequencies of ω. Importantly, the unknown instrumentation response can be more readily isolated and removed in the frequency domain. In order to obtain accurate phase shift and demodulation measurements, the excitation light modulation frequency of ω has to be of the same order of magnitude as the inverse of the lifetime (i.e. up to 108 Hz for FLIM). Phase shift and demodulation are often measured indirectly by either homodyne or heterodyne approaches. In the homodyne approach, measuring the steady state amplitudes at different phases allows the recovery of the waveform. In the case of heterodyne measurement, the signal is detected by a detector whose gain is modulated sinusoidally at a slightly increased frequency of ω + Δω. This electronic mixing process results in translating the phase and demodulation information to an electronic signal at the cross correlation frequency of Δω that can be readily isolated by low-pass filtering. The relative merits of time-domain vs. frequency-domain approaches and homodyne vs. heterodyne detection schemes have been discussed extensively in the literatures [25, 26].

High throughput FLIM has been the focus of technology development of several research groups. The developed instruments fall into two categories. In the first category, gated cameras are used for time-resolved full field imaging. These instruments have been implemented with traditional wide-field fluorescence microcopy without depth resolution [27, 28] or with spinning disk confocal microscope for 3D resolved imaging [29, 30]. Spectral-lifetime resolved imaging using this approach has also been implemented [31]. Another approach to achieve 3D imaging is based on using multifocal multiphoton microscopy (MMM), detecting in parallel the signal from each foci using separate time-correlated single photon counting (TCSPC) circuitry [32]. The next-generation instruments described in this report are built on the foundation established by these prior works.

2. Temporal focusing wide-field Two-Photon FLIM and PLIM

This paper describes the design of a fast 3D FLIM and PLIM imaging system that is based on combining two complementary technologies: (1) temporal focusing wide-field (TFWF) two-photon microscopy, a method for efficiently exciting a single 3D resolved plane in a translucent specimen, and (2) camera-based heterodyne frequency-domain lifetime measurement, a method for highly parallelized wide-field imaging with picosecond lifetime resolution. Figure 1 shows the optical and electronic design of the temporal focusing wide-field FLIM/PLIM system. A titanium sapphire femtosecond pulsed laser (Tsunami, Spectra-Physics, Mountain View, CA) pumped by a continuous-wave diode-pumped solid-state laser (Millennia V, Spectra-Physics, Mountain View, CA) is used to provide a 80 MHz train of 100 fs pulses at a center wavelength of 780 nm. The 1/e2 beam diameter of the ray is about 1-2 mm. The excitation light is intensity modulated using an acousto-optical modulator (AOM, 1205C-2, ISOMET, Springfield, VA). Excitation light is dispersed by a reflective diffraction grating with groove frequency of 600 grooves/mm (53004BK02-35IR, Richardson Grating Lab, Rochester, NY) and is directed towards a high numerical aperture objective (Fluar, 40X/1.30 NA Oil, Zeiss MicroImaging, Thornwood, NY). The diffraction grating surface is placed at the conjugate plane of the object plane resulting in an excitation area of approximately 100 × 100 μm2. Away from the focal plane, this arrangement guarantees that the different spectral components dispersed by the grating are separated spatially, resulting in broader pulse width and lower two-photon excitation (TPE) efficiency due to the constancy of the time-bandwidth product. At the focal plane, the different spectral components are recombined, the pulse width is minimized, and TPE efficiency is maximized. Volumetric imaging is accomplished by plane-by-plane excitation by translating the objective using a piezo-positioner (MIPOS500, piezosystem Jena Inc., Hopedale, MA).

 

Fig. 1 Temporal focusing wide-field (TFWF) FLIM/PLIM design. (a) Optical sub-system: temporal focusing widefield multiphoton microscopy, (b) Electronic sub-system: frequency domain lifetime measurement via heterodyne detection.

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The fluorescence or phosphorescence images are acquired using a high speed phase resolved camera (LI2CAM MD connected to a LIFA control unit, Lambert Instruments, Roden, Netherlands) modified for heterodyne detection. The high speed phase resolved camera consists of a high sensitivity proximity focused image intensifier. The gain of the intensifier can be modulated by injecting an external analog gating signal at the intensifier cathode. The phosphor output window of the intensifier is fiber optically coupled to a 1392x1040 pixel CCD camera, used in 2x2 binned mode, to ensure maximum light detection efficiency.

In TFWF FLIM, the femtosecond titanium-sapphire laser pulse train provides the required modulation frequencies at 80MHz and its harmonics. In TFWF PLIM, the AOM, driven by a frequency synthesizer (2024, Marconi Instruments, discontinued, and DS345, Stanford Research Systems, Sunnyvale, CA) and a digital modulation RF driver (522C-2, ISOMET, Springfield, VA), provides modulation frequency of ω from DC to about 1 MHz. The Lambert Instruments camera has an internal high voltage amplifier that controls the gain of the intensifier; this amplifier is driven by a second frequency synthesizer that provides a sinusoidal driving frequency at the modulation frequency of ω plus a small cross correlation frequency of Δω. The CCD camera frame acquisition is triggered by a third frequency synthesizer operating at a frequency equal to a quarter of the cross correlation frequency of Δω allowing the cross correlation signal to be sampled four times per wave. For precise phase resolved measurement, these three frequency synthesizers are phase locked to the output of the titanium laser pulse train at 80 MHz. The typical cross correlation frequency of Δω is chosen to be 1 Hz since the current version of the Lambert camera is not designed for heterodyne detection and has a maximum frame rate of about 4 Hz. Significantly faster imaging (up to kHz level) should be possible by using cameras of higher frame rate and by ensuring that the phosphor screen of the intensifier has sufficiently fast response time. The development of an improved camera for high speed heterodyne detection is underway under the Lambert Instrument/MIT collaboration.

3. Results and analysis

3.1 Fluorescence lifetime measurement performance and applications

The accuracy of the developed wide-field 3D lifetime imaging system was evaluated by measuring the fluorescence lifetimes of Rhodamine B (79754, Sigma-Aldrich Products, St. Louis, MO) solution in different solvents that have been carefully quantified in literature [33]. As a lifetime reference, fluorescein (R14782, Invitrogen, Grand Island, NY) was dissolved in 0.1M NaOH pH 8.0 buffer at a concentration of 50 μΜ. The lifetime of the fluorescein solution is assumed to be a 4.0 ns single exponential. Rhodamine B was dissolved in deionized water or spectroscopic grade methanol, or ethanol at a concentration of 50 μM. All fluorescein and rhodamine solutions were enclosed in a hanging-drop slides covered and sealed with #1.5 cover slip.

3D resolved wide-field images of these solutions were acquired 50 μm away from the cover slip. The modulation frequency and the cross correlation frequency were set to 80 MHz and 1 Hz respectively, while the lifetime camera readout rate was set at 4 Hz providing four amplitude measurements of each cross correlation waveform. Results from twenty cross correlated waveforms were integrated to generate a single data set resulting in a total image acquisition time of 20 seconds. The phase delay and demodulation of Rhodamine B solutions are then quantified relative to the modulation and phase of a reference fluorescein specimen. Fitting the measurements to a single exponential decay model allows the extraction of lifetimes tabulated in Fig. 2(a) . The lifetime measurements obtained by TFWF FLIM were in good agreement with literature values within about 0.05-0.1 ns. Note that the two ways to estimate the fluorescence lifetime (either from phase data or from modulation data) provide very similar results, which supports the choice of a single exponential decay model to fit Rhodamine B lifetime data. When plotting the lifetime measurements of each pixel into a single polar plot (a sine and cosine transform of temporal decay information into the spectral domain [34, 35]) the lifetime of individual pixels cluster around a single location located on the universal circle as expected for single exponential decay processes as shown in Fig. 2(b). The locations of these four distributions are consistent with the tabulated lifetimes obtained from averaging over the whole image.

 

Fig. 2 Demonstration of accurate measurement of fluorescence lifetime of Rhodamine B solutions in different solvents by TFWF FLIM. Fluorescence in water was used as a reference. (a) Tabulated results of estimated lifetime values of τ extracted from either phase (Ph) or modulation (Mod) measurements. Literature values are also included as a reference [33]. (b) Lifetime resolved data for each pixel from the fluorescein (FL) and rhodamine solution images shown in polar plot format.

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The high data acquisition speed of the developed instrument is demonstrated by FLIM imaging of fixed fibroblasts loaded with conjugated polymer nanoparticles (CPNs) of high two-photon cross section previously measured in excess of 15,000 GM [36]. Wide-field two-photon lifetime resolved imaging is fundamentally limited by the need to simultaneously and optimally excite fluorophores within a large area plane via two-photon absorption. Optimal excitation corresponds to two-photon absorption probability on the order of 10% per laser pulse. In this case fluorophores are excited without saturation and image resolution degradation [37]. The two-photon absorption probability per fluorophore per excitation photon pair per laser pulse can be expressed as [38]:

prδf2τ(PN)2
where N is the number of pixels (assuming diffraction-limited pixel size) measured in parallel, δ is the fluorophore two-photon cross section, P is the average power per image, f is the laser pulse repetition rate, and τ is the laser pulse width. For typical titanium-sapphire femtosecond laser sources and typical fluorophores with approximately 10 GM two-photon cross section, optimal excitation occurs at approximately N = 100. For imaging at diffraction limited resolution of about 0.5 μm, the maximum field of view is only about 10 × 10 μm2; an area too small for typical biological imaging. A recent study has shown that this limitation can be remedied by the use of high peak power sources such as regenerative amplifiers [39]. This limitation is less critical for fluorophores of high two-photon cross section such as quantum dots or CPNs where image size can be extended to about 100 × 100 μm2. Imaging CPN-labeled specimens by TFWF FLIM was used to demonstrate the data acquisition speed of TFWF FLIM and to ensure that this experiment was not limited by inefficient wide-field two-photon excitation. A representative intensity scaled lifetime image and the associated polar plot of pixel lifetime distribution of the specimen is shown in Fig. 3 . The non-symmetric, off universal circle distribution of pixel values in the polar plot indicates non-single exponential decay of CPNs. This is consistent with the different mean lifetimes measured from phase and modulation data. It is important to note that consistent pixel fluorescence lifetime measurements can be obtained with integration time as short as 5 ms (measurement uncertainty on the order of 0.1-0.2 ns). When the integration time is further reduced to 2 ms, phase-based lifetime measurement still provides a reasonable lifetime estimate (with less than 0.5 ns error) while modulation-based lifetime estimates start to deviate from values obtained with longer average time (> 0.5 ns).

 

Fig. 3 (a) An intensity scaled mean lifetime image of fixed fibroblasts with vacuoles loaded with endocytosed conjugated polymer nanoparticles of high two-photon absorption cross section. Color scale represents pixel lifetime values corresponding to the color bar with units of seconds. Image brightness represents pixel intensity values. Black regions are ignored in analysis corresponding to locations with intensity below 500 photons that are mostly outside the boundary of this cell. (b) Representative polar plot of pixel lifetime values for 10 ms data acquisition time. (c) Tabulated mean lifetime values and their standard deviations are estimated from the modulation or the phase data for four different image acquisition rates.

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The application of temporal focusing wide-field two-photon imaging in lifetime resolved biological imaging is demonstrated in a thin 6μm thick histological cross section of a formalin fixed injured rat sciatic nerve. After transecting the nerve, the two resulting nerve stumps were connected with a collagen tube [40, 41]. In order to quantify the degree of induced regeneration, myelin sheaths surrounding the newly-grown axons were visualized by labeling using FluroMyelin Green (F34651, Grand Island, NY). Lifetime imaging by the TFWF FLIM system was conducted using identical imaging parameters with the ones used in rhodamine solutions imaging. Figure 4(a) shows a zoom-in cropped image of 20μm × 20μm field of view displayed as an intensity scaled lifetime image, where the color of each pixel represents its mean lifetime and the brightness of each pixel is proportional to the number of photons acquired. Pixel lifetime information can also be displayed in a polar plot format as shown in Fig. 4(b). Unlike the rhodamine and fluorescein solutions, the distribution of pixel lifetimes is broader and does not fall directly on the universal circle indicating either that the fluorescence lifetime of FluroMyelin Green is not single-exponential or that its lifetime may be affected by the local tissue microenvironment. The broadening of the lifetime distribution may also be caused by the presence of autofluorescence signal emitted by the fixed nerve specimen. Since the fluorescence lifetime of FluoroMyelin Green has not been adequately quantified in the literature, we evaluated the accuracy of our TFWF lifetime measurement by imaging the identical specimen using a point-scanning two-photon microscopy equipped with a Becker and Hickl SPC730 TCSPC module for time-domain lifetime measurement as shown in Fig. 4(c). The total pixel residence time was 4.8ms and the integration time for a single lifetime resolved image was about 100 sec. The mean lifetimes for the labeled myelin sheath are in good agreement at approximately 2.5ns. The long lifetime blobs in the TCSPC correspond to nuclei separately labeled with DAPI with a typical lifetime of approximately 4ns.

 

Fig. 4 Fluorescence lifetime imaging of an ex vivo histological sample by TFWF FLIM. (a) Intensity-scaled fluorescence lifetime-resolved image of a regenerated ex vivo rat sciatic nerve after injury stained with FluroMyelin Green. The image field of view is approximately 20 × 20 μm2 (a) and 100 × 100 μm2(c). Scale bar has units of seconds. (b) Polar plot representation of the pixel lifetime estimated based on the phase data. (c) A larger view of the same sample acquired using a point scanning two-photon microscope equipped with TCSPC lifetime resolved imaging system. The scale bar has unit of nanoseconds. The lifetime measurements for both systems are in excellent agreement.

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Fast lifetime-resolved imaging with 3D resolution is demonstrated by imaging fluorescent beads of 15μm (F8844, Invitrogen Inc, Grand Island, NY) and 4μm diameter (F8858). Figure 5(a) shows the intensity-scaled lifetime images taken at 5μm axial steps. The depth resolution of the system is on the order of 2μm. The 4μm bead is uniformly labeled with fluorophores while the 15μm is only labeled at the surface while its interior is not impregnated with fluorophore. It is interesting to note that while the 15μm and 4μm beads are emitting in the yellow-green and red spectral ranges respectively, these beads have essentially the same lifetimes. The associated polar plot of pixel lifetimes acquired at z = 15μm depth suggests an almost single exponential decay for these fluorophores as shown in Fig. 5(b).

 

Fig. 5 Demonstration of fast 3D-resolved lifetime imaging by TFWF FLIM system. (a) Intensity scaled lifetime images of 15 μm yellow-green beads and 4 μm red beads imaged at different axial plane locations z. Pixel lifetimes were estimated from modulation data. The scale bar represents 5 μm in length. (b) Representative polar plot of pixel lifetime information at z = 15 μm.

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The 3D resolved imaging ability of the developed system in living biological specimens was demonstrated by imaging live human dermal fibroblasts interacting with a porous collagen scaffold, similar to the one used to induce nerve regeneration in Fig. 4 [42, 43]. Fibroblasts were labeled by either Calcein AM (a marker of cytoplasm and nucleus), or Syto 13 (a nucleic acid marker) or both. 3D-resolved lifetime imaging was performed using the same imaging parameters as described in Fig. 3-5. A representative image of a cell labeled with both markers is shown in Fig. 6(a) . The lifetime of Calcein AM was estimated to be 3.5 ns and 3.1 ns using phase or modulation data respectively. These two lifetime rate estimates are in good agreement with the published TCSPC measurements [44]. The fluorescence lifetime of Syto 13 was estimated to be 2.9 ns and 1.8 ns using phase and modulation data respectively. The large difference between phase and modulation results indicates the non-single exponential nature of the decay. Similar non-single exponential decay has been observed when Syto 13 was used in bacterial cultures, where a similarly broad distribution of lifetime from 1.5 to 2.5 ns were observed suggesting different lifetimes depending on whether the dye binds to DNA or RNA [45]. The polar plot of the pixel lifetimes for specimens labeled only with Calcein AM shows a tight distribution of pixel lifetimes close to the unit circle, which indicates a single exponential decay (Fig. 6(b)). On the contrary, the polar plot for specimen labeled with only Syto 13 shows broad distribution of pixel lifetime rates that suggests a non-single exponential nature of fluorescence decay (Fig. 6(d)). As expected, the polar plot in specimens labeled with both markers has a pixel distribution at the algebraic mean between the tight distribution of Calcein AM close to the unit circle and the broad distribution of Syto 13 (Fig. 6(c)).

 

Fig. 6 Fluorescence lifetime imaging of human fibroblasts seeded inside a collagen scaffold double-stained with Calcein AM and Syto 13 by TFWF FLIM. (a) Intensity scaled lifetime images. (b) Polar plot of fibroblasts labeled only with Calcein AM. (c) Polar plot of fibroblasts labeled with both Calcein AM and Syto 13. (d) Polar plot of fibroblasts labeled only with Syto 13.

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3.2 Demonstration of 3D phosphorescence and fluorescence lifetime-resolved imaging in tissue engineering scaffolds

Wide-field lifetime-resolved imaging systems enable not only efficient 3D fluorescence lifetime imaging, but also fast quantification of phosphorescence lifetime. Phosphorescence lifetime measurement has significant applications in biophysics including background-free labeling, and monitoring the binding of high molecular weight proteins. However, the most important biomedical use of molecular phosphorescence is monitoring oxygen concentration in biological systems. Minimally invasive measurements of partial oxygen pressure can be used, for example, to quantify hypoxia in tumors, an important determinant of tumor physiology [16, 17] and its response to therapy [22, 46]. Improved methods to quantify the 3D distribution of molecular oxygen partial pressure pO2 with cellular resolution inside solid tumors in animal models could provide novel information for understanding how cancer physiology affects therapeutic responses. Oxygen sensors based on phosphorescence quenching offer a powerful method to measure pO2 distribution in vivo. Phosphorescence measurement is necessary since tumor pO2 concentration is low and the chromophores must have an excited state lifetime longer than the characteristic time of chromophore-oxygen interaction. Both phosphorescence intensity and lifetime are sensitive functions of pO2. Intensity-based measurements are undesirable since they depend on the local concentration of the phosphorescence probe in the tissue, which cannot be readily quantified. In contrast, phosphorescence lifetime provides a concentration-independent probe for measuring oxygen quenching rate. The lifetime of typical phosphorescence sensors for pO2 range between hundreds of ns to several hundred μs. In simple biological samples that do not require 3D imaging, single-photon wide field phosphorescence lifetime imaging has been implemented efficiently [4750]. However, 3D PLIM using point scanning confocal or multiphoton excitation is always slow since the required pixel residence time must be substantially longer than the phosphorescence lifetime (as long as a fraction of a millisecond). The estimated necessary duration for high-resolution 3D mapping of oxygen distribution in a tumor can exceed days using palladium based probes (lifetime approaches one millisecond). While these very long lifetime probes are sensitive to oxygen concentration and suitable for hypoxic environments, such as the interior of a solid tumor, their long “turn-around” time greatly limits the speed of PLIM. Importantly, unlike FLIM measurements, PLIM measurement speed cannot be easily improved using conventional speed-enhancement methods such as spinning-disk confocal, since the long phosphorescence lifetime will result in significant signal loss due to the motion of the pinholes unless disk rotation rate is kept sufficiently low. On the other hand, the parallelized nature of the proposed TFWF two-photon lifetime resolved imaging system shortens PLIM acquisition time by several orders of magnitude with frame rate approaching phosphorescence lifetimes.

In order to demonstrate the accuracy of the developed TFWF PLIM system, we quantified oxygen concentration in solutions of 1 mM Tris (2,2′-bipyridyl) dichlororuthenium(II) hexahydrate (TDRT, 544981, Sigma Aldrich Products, St. Louis, MO) in PBS equilibrated with several independently calibrated oxygen/nitrogen gas mixtures of O2 mass fraction of 0, 4, 8, and 21%. The phosphorescence lifetime of the ruthenium solution equilibrated with each mixture was found to be single exponential as indicated by the distribution of the estimated pixel lifetime that lies on the universal circle of the polar plot (Fig. 7(a) ). The measured phosphorescence lifetime ranges from about 400 to 600 ns. There is an inverse dependence of the phosphorescence lifetime on oxygen partial pressure in agreement with a Stern-Volmer relationship (Fig. 7(b), Fig. 7(c)):

 

Fig. 7 Fast measurement of partial oxygen pressure by TFWF phosphorescence lifetime imaging. (a) Polar plot of phosphorescence lifetime of 1 mM Tris(2,2′-bipyridyl)dichlororuthenium(II) hexahydrate solutions equilibrated with 0, 4, 8, and 21% pO2 gas mixtures. Inverse phosphorescence lifetimes ((b), from modulation data; (c), from phase data) are plotted against O2 concentration demonstrating Stern-Volmer dependence with R2 values of 0.99 and 0.95 respectively for linear regression.

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1τpO2

The accuracy of TFWF two-photon PLIM method is a function of integration time of each image frame. Specifically, measurement accuracy comparable to the one shown in Fig. 7 can be obtained when the integration time is on the order of several seconds. It is important to note that this relative long integration time is due to the relatively low two-photon cross section of TDRT, the limited number of phosphorescence photons generated, and the limited excitation laser power (about 3W maximum output power for typical Ti-Sapphire laser sources) since the power of about 0.7W is distributed over a 100x100 μm2 area. The uncertainty of ruthenium phosphorescence lifetime measurements at integration times of 1.2, 1.5, 2.4, 3.0, 3.6, 5.5 and 6.0 seconds are shown in Fig. 8(a) and the representative polar plots at the integration times of 1.5, 3.0 and 6.0 seconds are shown in Fig. 8(b). It is clear that as integration time decreases, the distribution of the polar plot broadens indicating greater uncertainty of lifetime measurement. The uncertainty in the pixel lifetime measurements of an image for given integration time, as quantified by the full-width-at-half-maximum of the pixel lifetime values in the polar plot, can be related to the average number of photons per pixel. When plotted in a log-log format, linear regression gives a slope of approximately 0.5 indicating that the lifetime measurement error is dominated by photon shot noise.

 

Fig. 8 Uncertainty in estimating the lifetime of 1mM TDRT solutions depends on the image integration time. (a) TDRT phosphorescence lifetime measurement uncertainties (FWHM) for images acquired with different integration times are plotted against the average number of photons contained in these images. (b) Representative polar plots of TDRT solution pixel phosphorescence lifetime measurements at integration times of 1.5, 3, and 6 sec.

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The application of TFWF imaging in fast sequential phosphorescence and fluorescence lifetime 3D imaging is demonstrated in an in vitro 3D cell-matrix system that can be used to study how oxygenation affects cell-matrix interactions inside tissue engineering devices. The system consists of live human dermal fibroblasts stained with Rhodamine DHPE (the dye is soon endocytosed and primarily localized in intracellular vesicles) seeded inside a porous collagen scaffold similar to Fig. 6. In situ monitoring of the oxygenation state of cells was accomplished by adding 1mM TDRT in the cell culture buffer (PBS). 3D-resolved fluorescence and phosphorescence lifetime imaging of the cell-seeded scaffolds was acquired sequentially using modulation frequency (ω) of 80 MHz and 300 kHz respectively. Representative images are shown in Fig. 9 . In PLIM imaging cells can be distinguished based on the increased lifetime (less oxygen) observed intracellularly compared to the surrounding medium pixels. Representative intensity scaled lifetime-resolved images are shown in Fig. 10 . At each pixel, the relative intensity contributions from fluorescence and phosphorescence components can be readily separated based on the pixel location within the polar plot. The distributions of the fluorescence and phosphorescence components are shown in Fig. 11 . As expected, the fluorescence emission of Rhodamine DHPE is localized in cellular vesicles, while the phosphorescence emission of TDRT is predominately localized in the medium surrounding the cells and the scaffold.

 

Fig. 9 Fast 3D-resolved TFWF PLIM in sample consisting of human fibroblasts stained with Rhodamine DHPE, seeded inside a collagen matrix and treated, in PBS buffer containing 1 mM TDRT ruthenium-based oxygen sensor. PLIM Images were acquired at 300 kHz modulation frequency. In sequence from left to right: intensity image, phosphorescence lifetime-resolved image from phase data, phosphorescence lifetime-resolved image from modulation data. On the far right is the polar plot of the pixel phosphorescence lifetime-resolved measurements. The pixel lifetime data in the polar plot distributes between the ruthenium phosphorescence lifetime that lies close to the universal circle and the rhodamine fluorescence lifetime at the lower right hand corner corresponding to an effective zero lifetime for 300 kHz modulation frequency. PLIM Movie sequences corresponding to phase and modulation lifetime measurements throughout a 3D matrix are included (Supplementary material Media 1, Media 2).

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Fig. 10 Representative single plane intensity scaled lifetime-resolved image measured at a modulation frequency of 300 kHz.

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Fig. 11 Fast sequential 3D-resolved TFWF FLIM and PLIM imaging of human dermal fibroblasts seeded in a collagen scaffold. Representative images of the fluorescence component emitted by Rhodamine DHPE (top), and the phosphorescence component, emitted by TDRT ruthenium-based oxygen sensor (bottom), of the signal emitted from a single 3D resolved plane. 3D resolved image stacks of these two components can be seen in accompanying movie sequences (Media 3, Media 4)

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4. Conclusions

We have developed an efficient fluorescence and phosphorescence lifetime resolved imaging system. The system combines temporal focusing two-photon excitation for 3D resolved wide-field excitation, and highly parallelized frequency domain lifetime resolved measurement using a nanosecond gated imager. There are two primary limitations of the proposed system.

The first limitation stems from the fact that the peak power of typical titanium-sapphire lasers is not sufficient to optimally excite many commonly available fluorophores over a large area, therefore reducing the efficiency of this approach. This low excitation efficiency can be compensated by using fluorophores of higher two-photon cross section (such as CPNs demonstrated here). However, the most generalizable approach is using high peak power light sources (such as regenerative amplifiers) for more efficient wide-field excitation. In general, sufficient laser flux should be provided to ensure fluorophores are effectively excited by each laser pulse without excitation saturation, corresponding to two-photon excitation probability per fluorophore per pulse of about 10%. Mathematically, two-photon excitation probability can be expressed as in Eq. (2). This equation can be rewritten as to estimate the number of pixels that can be simultaneously excited per excitation pulse:

NδPrτp0f
We can further estimate imaging efficiency in terms of the number of pixels that can be excited per unit time:
rNNfδPrτp0
For given fluorophore cross section, laser average power and pulse width, the number of pixel that can be simultaneously excited scales inversely with the laser repetition rate. This is the reason that higher peak power, lower repetition rate regenerative amplifiers are superior for simultaneous wide field imaging compared with lower peak power, higher repetition rate oscillators. However, does wide field imaging (imaging many pixels simultaneously) provide an imaging speed advantage compared with point scanning or multi-foci scanning methods ? Since rN is independent of repetition rate, it would appear that it is just as efficient to image a single pixel at a time as imaging many pixels at the same time. However, this conclusion must be modified by taking into account of at least three additional time constants of the imaging system. One of these time constants is the excited state lifetime of the chromophores. For efficient excitation, the inverse of the laser repetition rate must be much longer in duration than the fluorophore lifetime. Otherwise, depleting the molecular ground state will not only results in a reduction of the efficiencies of the subsequent pulses but will also cause resolution degradation. Given the nanosecond lifetime of most fluorescence probes, this is not a concern for fluorescence lifetime-resolved imaging. However, for phosphorescence molecules with microsecond to millisecond lifetimes, the laser repetition rate should be chosen to be sufficiently slow such that these phosphorescence molecules can be relaxed prior to the next excitation pulse. Therefore, wide field imaging is almost always more efficient for phosphorescence lifetime-resolved imaging. Another time constant is the detector “dead time.” Photon detectors, especially lifetime resolved detectors, have a finite “dead time” between subsequent measurements. Depending on the principles underlying these detectors, the “dead time” is typically on the order of microseconds. The other relevant time constant is the scan speed of the imaging system. Depending on the scanning mechanism, stage, galvanometric scanner, acousto-optical scanner, scan speed quantifies how fast laser light can be directed across individual pixels (point scanning) or a group of pixels (multi-foci scanning). Scan speed typically ranges from microsecond to millisecond time scale. In general, image efficiency can be increased if pixel integration time is made substantially longer than the detector “dead time” and the scan speed. Taking these three time constants into account, more efficient imaging can often be achieved with wide field imaging mode using a high peak power amplifier for both fluorescence and phosphorescence modes.

The second major limitation of the current system is that the read-out rate of the camera is limited to four frames per second. While we have demonstrated that lifetime-resolved images can be acquired with integration time as short as several milliseconds, the slow read-out rate limits the actual frame rate to about 4 Hz. This limitation results from the fact that the camera used in this experiment is not specifically designed for frequency domain heterodyne lifetime measurement but was custom modified for this experiment. Today, CCD or CMOS cameras can be readily read out at a rate in excess of 1 GHz. By coupling a high speed gated microchannel plate with a high frame rate, low noise camera will produce an ideal system that can perform fluorescence lifetime-resolved measurements in excess of kHz. For phosphorescence imaging, the integration time must be at least over an order of magnitude longer than the phosphorescence lifetime of the probe. Nonetheless, phosphorescence lifetime imaging with sub-second frame rate should be possible for even millisecond lifetime phosphorescence probes.

Finally, wide-field two-photon imaging uses significantly higher power than point scanning; possible specimen photodamage should be considered. In the absence of one-photon absorber and thermal damage, the two main mechanisms for photodamage are multiphoton ionization and oxidative damage. The probability of multiphoton ionization is proportional to laser flux. With a 3W titanium-sapphire laser, approximately 1W of power is eventually delivered upon a 100 × 100 μm2 specimen surface. The laser flux is approximately 0.1 mW/m2. As a comparison, the laser flux of typical single focus scanning is on the order of 10-100 mW/m2. As discussed previously, a regenerative amplifier is a better laser source for wide-field two-photon imaging providing higher laser flux such that the two-photon excitation probability can reach about 10%. Since both wide-field and point-scanning approaches reach the same excitation probability level at the same flux, they have the same potential for photodamage. In terms of oxidative damage, since the amount of reactive oxygen generation is proportional to the total fluorescence signal, the total dosage of reactive oxygen species generated is also the same for these two approaches. Of course, since wide-field imaging has higher frame rate, the dose rate is higher for the wide-field case. A priori, it is impossible to determine whether higher dose rate results in significantly greater photodamage. Future studies are needed to carefully compare the oxidative damage potentials of two-photon wide field imaging and point-scanning for different biological systems under study.

Acknowledgments

This research was supported by NIH, EBICS (NSF), Singapore–MIT Alliance for Research and Technology (SMART) centre, Singapore-MIT Alliance 2 (SMA-2). The authors thank Dr Sergeii Pochekailov (Zhang lab, MIT) for valuable assistance in calibrating the oxygen sensors.

References and links

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2. W. Becker, A. Bergmann, M. A. Hink, K. König, K. Benndorf, and C. Biskup, “Fluorescence lifetime imaging by time-correlated single-photon counting,” Microsc. Res. Tech. 63(1), 58–66 (2004). [CrossRef]   [PubMed]  

3. H. C. Gerritsen, J. M. Vroom, and C. J. de Grauw, “Combining two-photon excitation with fluorescence lifetime imaging,” IEEE Eng. Med. Biol. Mag. 18(5), 31–36 (1999). [CrossRef]   [PubMed]  

4. E. Gratton, S. Breusegem, J. Sutin, Q. Ruan, and N. Barry, “Fluorescence lifetime imaging for the two-photon microscope: time-domain and frequency-domain methods,” J. Biomed. Opt. 8(3), 381–390 (2003). [CrossRef]   [PubMed]  

5. I. Gryczynski, A. Razynska, and J. R. Lakowicz, “Two-photon induced fluorescence of linear alkanes; a possible intrinsic lipid probe,” Biophys. Chem. 57(2-3), 291–295 (1996). [CrossRef]   [PubMed]  

6. K. König, P. T. So, W. W. Mantulin, B. J. Tromberg, and E. Gratton, “Two-photon excited lifetime imaging of autofluorescence in cells during UVA and NIR photostress,” J. Microsc. 183(Pt 3), 197–204 (1996). [PubMed]  

7. J. R. Lakowicz, “Emerging applications of fluorescence spectroscopy to cellular imaging: lifetime imaging, metal-ligand probes, multi-photon excitation and light quenching,” Scanning Microsc. Suppl. 10, 213–224 (1996). [PubMed]  

8. R. M. Clegg, A. I. Murchie, and D. M. Lilley, “The four-way DNA junction: a fluorescence resonance energy transfer study,” Braz. J. Med. Biol. Res. 26(4), 405–416 (1993). [PubMed]  

9. A. A. Deniz, T. A. Laurence, G. S. Beligere, M. Dahan, A. B. Martin, D. S. Chemla, P. E. Dawson, P. G. Schultz, and S. Weiss, “Single-molecule protein folding: diffusion fluorescence resonance energy transfer studies of the denaturation of chymotrypsin inhibitor 2,” Proc. Natl. Acad. Sci. U.S.A. 97(10), 5179–5184 (2000). [CrossRef]   [PubMed]  

10. X. Zhuang and M. Rief, “Single-molecule folding,” Curr. Opin. Struct. Biol. 13(1), 88–97 (2003). [CrossRef]   [PubMed]  

11. K. König, A. Ehlers, I. Riemann, S. Schenkl, R. Bückle, and M. Kaatz, “Clinical two-photon microendoscopy,” Microsc. Res. Tech. 70(5), 398–402 (2007). [CrossRef]   [PubMed]  

12. E. Dimitrow, I. Riemann, A. Ehlers, M. J. Koehler, J. Norgauer, P. Elsner, K. König, and M. Kaatz, “Spectral fluorescence lifetime detection and selective melanin imaging by multiphoton laser tomography for melanoma diagnosis,” Exp. Dermatol. 18(6), 509–515 (2009). [CrossRef]   [PubMed]  

13. G. Helmlinger, F. Yuan, M. Dellian, and R. K. Jain, “Interstitial pH and pO2 gradients in solid tumors in vivo: high-resolution measurements reveal a lack of correlation,” Nat. Med. 3(2), 177–182 (1997). [CrossRef]   [PubMed]  

14. I. P. Torres Filho, M. Leunig, F. Yuan, M. Intaglietta, and R. K. Jain, “Noninvasive measurement of microvascular and interstitial oxygen profiles in a human tumor in SCID mice,” Proc. Natl. Acad. Sci. U.S.A. 91(6), 2081–2085 (1994). [CrossRef]   [PubMed]  

15. L. S. Ziemer, W. M. Lee, S. A. Vinogradov, C. Sehgal, and D. F. Wilson, “Oxygen distribution in murine tumors: characterization using oxygen-dependent quenching of phosphorescence,” J. Appl. Physiol. 98(4), 1503–1510 (2005). [CrossRef]   [PubMed]  

16. A. L. Harris, “Hypoxia--a key regulatory factor in tumour growth,” Nat. Rev. Cancer 2(1), 38–47 (2002). [CrossRef]   [PubMed]  

17. E. K. Rofstad, “Microenvironment-induced cancer metastasis,” Int. J. Radiat. Biol. 76(5), 589–605 (2000). [CrossRef]   [PubMed]  

18. S. M. Evans and C. J. Koch, “Prognostic significance of tumor oxygenation in humans,” Cancer Lett. 195(1), 1–16 (2003). [CrossRef]   [PubMed]  

19. M. I. Koukourakis, A. Giatromanolaki, R. A. Brekken, E. Sivridis, K. C. Gatter, A. L. Harris, and E. H. Sage, “Enhanced expression of SPARC/osteonectin in the tumor-associated stroma of non-small cell lung cancer is correlated with markers of hypoxia/acidity and with poor prognosis of patients,” Cancer Res. 63(17), 5376–5380 (2003). [PubMed]  

20. M. Weinmann, C. Belka, and L. Plasswilm, “Tumour hypoxia: impact on biology, prognosis and treatment of solid malignant tumours,” Onkologie 27(1), 83–90 (2004). [CrossRef]   [PubMed]  

21. J. M. Brown and A. J. Giaccia, “The unique physiology of solid tumors: opportunities (and problems) for cancer therapy,” Cancer Res. 58(7), 1408–1416 (1998). [PubMed]  

22. I. F. Tannock and D. Rotin, “Acid pH in tumors and its potential for therapeutic exploitation,” Cancer Res. 49(16), 4373–4384 (1989). [PubMed]  

23. S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods 7(9), 755–759 (2010). [CrossRef]   [PubMed]  

24. Y. Wang, S. Hu, K. Maslov, Y. Zhang, Y. Xia, and L. V. Wang, “In vivo integrated photoacoustic and confocal microscopy of hemoglobin oxygen saturation and oxygen partial pressure,” Opt. Lett. 36(7), 1029–1031 (2011). [CrossRef]   [PubMed]  

25. W. Becker, Advanced Time-Correlated Single Photon Counting Techniques, (Springer, Berlin, 2005).

26. A. Periasamy and R. M. Clegg, eds., FLIM Microscopy in Biology and Medicine, (Chapman and Hall, Boca Raton, 2009).

27. K. Suhling, J. Siegel, P. M. Lanigan, S. Lévêque-Fort, S. E. Webb, D. Phillips, D. M. Davis, and P. M. French, “Time-resolved fluorescence anisotropy imaging applied to live cells,” Opt. Lett. 29(6), 584–586 (2004). [CrossRef]   [PubMed]  

28. J. Requejo-Isidro, J. McGinty, I. Munro, D. S. Elson, N. P. Galletly, M. J. Lever, M. A. Neil, G. W. Stamp, P. M. French, P. A. Kellett, J. D. Hares, and A. K. Dymoke-Bradshaw, “High-speed wide-field time-gated endoscopic fluorescence-lifetime imaging,” Opt. Lett. 29(19), 2249–2251 (2004). [CrossRef]   [PubMed]  

29. D. M. Grant, D. S. Elson, D. Schimpf, C. Dunsby, J. Requejo-Isidro, E. Auksorius, I. Munro, M. A. Neil, P. M. French, E. Nye, G. Stamp, and P. Courtney, “Optically sectioned fluorescence lifetime imaging using a Nipkow disk microscope and a tunable ultrafast continuum excitation source,” Opt. Lett. 30(24), 3353–3355 (2005). [CrossRef]   [PubMed]  

30. J. McGinty, K. B. Tahir, R. Laine, C. B. Talbot, C. Dunsby, M. A. Neil, L. Quintana, J. Swoger, J. Sharpe, and P. M. French, “Fluorescence lifetime optical projection tomography,” J Biophotonics 1(5), 390–394 (2008). [CrossRef]   [PubMed]  

31. D. M. Owen, E. Auksorius, H. B. Manning, C. B. Talbot, P. A. de Beule, C. Dunsby, M. A. Neil, and P. M. French, “Excitation-resolved hyperspectral fluorescence lifetime imaging using a UV-extended supercontinuum source,” Opt. Lett. 32(23), 3408–3410 (2007). [CrossRef]   [PubMed]  

32. S. Kumar, C. Dunsby, P. A. De Beule, D. M. Owen, U. Anand, P. M. Lanigan, R. K. Benninger, D. M. Davis, M. A. Neil, P. Anand, C. Benham, A. Naylor, and P. M. French, “Multifocal multiphoton excitation and time correlated single photon counting detection for 3-D fluorescence lifetime imaging,” Opt. Express 15(20), 12548–12561 (2007). [CrossRef]   [PubMed]  

33. D. Magde, G. E. Rojas, and P. G. Seybold, “Solvent dependence of the fluorescence lifetimes of xanthene dyes,” Photochem. Photobiol. 70(5), 737–744 (1999). [CrossRef]  

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36. N. A. A. Rahim, W. McDaniel, K. Bardon, S. Srinivas, V. Vickerman, P. T. C. So, and J. H. Moon, “Conjugated polymer nanoparticles for two-photon imaging of endothelial cells in a tissue model,” Adv. Mater. (Deerfield Beach Fla.) 21(34), 3492–3496 (2009). [CrossRef]  

37. A. Nagy, J. Wu, and K. M. Berland, “Observation volumes and gamma-factors in two-photon fluorescence fluctuation spectroscopy,” Biophys. J. 89(3), 2077–2090 (2005). [CrossRef]   [PubMed]  

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References

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  1. P. I. Bastiaens, P. J. Bonants, F. Müller, and A. J. Visser, “Time-resolved fluorescence spectroscopy of NADPH-cytochrome P-450 reductase: demonstration of energy transfer between the two prosthetic groups,” Biochemistry28(21), 8416–8425 (1989).
    [CrossRef] [PubMed]
  2. W. Becker, A. Bergmann, M. A. Hink, K. König, K. Benndorf, and C. Biskup, “Fluorescence lifetime imaging by time-correlated single-photon counting,” Microsc. Res. Tech.63(1), 58–66 (2004).
    [CrossRef] [PubMed]
  3. H. C. Gerritsen, J. M. Vroom, and C. J. de Grauw, “Combining two-photon excitation with fluorescence lifetime imaging,” IEEE Eng. Med. Biol. Mag.18(5), 31–36 (1999).
    [CrossRef] [PubMed]
  4. E. Gratton, S. Breusegem, J. Sutin, Q. Ruan, and N. Barry, “Fluorescence lifetime imaging for the two-photon microscope: time-domain and frequency-domain methods,” J. Biomed. Opt.8(3), 381–390 (2003).
    [CrossRef] [PubMed]
  5. I. Gryczynski, A. Razynska, and J. R. Lakowicz, “Two-photon induced fluorescence of linear alkanes; a possible intrinsic lipid probe,” Biophys. Chem.57(2-3), 291–295 (1996).
    [CrossRef] [PubMed]
  6. K. König, P. T. So, W. W. Mantulin, B. J. Tromberg, and E. Gratton, “Two-photon excited lifetime imaging of autofluorescence in cells during UVA and NIR photostress,” J. Microsc.183(Pt 3), 197–204 (1996).
    [PubMed]
  7. J. R. Lakowicz, “Emerging applications of fluorescence spectroscopy to cellular imaging: lifetime imaging, metal-ligand probes, multi-photon excitation and light quenching,” Scanning Microsc. Suppl.10, 213–224 (1996).
    [PubMed]
  8. R. M. Clegg, A. I. Murchie, and D. M. Lilley, “The four-way DNA junction: a fluorescence resonance energy transfer study,” Braz. J. Med. Biol. Res.26(4), 405–416 (1993).
    [PubMed]
  9. A. A. Deniz, T. A. Laurence, G. S. Beligere, M. Dahan, A. B. Martin, D. S. Chemla, P. E. Dawson, P. G. Schultz, and S. Weiss, “Single-molecule protein folding: diffusion fluorescence resonance energy transfer studies of the denaturation of chymotrypsin inhibitor 2,” Proc. Natl. Acad. Sci. U.S.A.97(10), 5179–5184 (2000).
    [CrossRef] [PubMed]
  10. X. Zhuang and M. Rief, “Single-molecule folding,” Curr. Opin. Struct. Biol.13(1), 88–97 (2003).
    [CrossRef] [PubMed]
  11. K. König, A. Ehlers, I. Riemann, S. Schenkl, R. Bückle, and M. Kaatz, “Clinical two-photon microendoscopy,” Microsc. Res. Tech.70(5), 398–402 (2007).
    [CrossRef] [PubMed]
  12. E. Dimitrow, I. Riemann, A. Ehlers, M. J. Koehler, J. Norgauer, P. Elsner, K. König, and M. Kaatz, “Spectral fluorescence lifetime detection and selective melanin imaging by multiphoton laser tomography for melanoma diagnosis,” Exp. Dermatol.18(6), 509–515 (2009).
    [CrossRef] [PubMed]
  13. G. Helmlinger, F. Yuan, M. Dellian, and R. K. Jain, “Interstitial pH and pO2 gradients in solid tumors in vivo: high-resolution measurements reveal a lack of correlation,” Nat. Med.3(2), 177–182 (1997).
    [CrossRef] [PubMed]
  14. I. P. Torres Filho, M. Leunig, F. Yuan, M. Intaglietta, and R. K. Jain, “Noninvasive measurement of microvascular and interstitial oxygen profiles in a human tumor in SCID mice,” Proc. Natl. Acad. Sci. U.S.A.91(6), 2081–2085 (1994).
    [CrossRef] [PubMed]
  15. L. S. Ziemer, W. M. Lee, S. A. Vinogradov, C. Sehgal, and D. F. Wilson, “Oxygen distribution in murine tumors: characterization using oxygen-dependent quenching of phosphorescence,” J. Appl. Physiol.98(4), 1503–1510 (2005).
    [CrossRef] [PubMed]
  16. A. L. Harris, “Hypoxia--a key regulatory factor in tumour growth,” Nat. Rev. Cancer2(1), 38–47 (2002).
    [CrossRef] [PubMed]
  17. E. K. Rofstad, “Microenvironment-induced cancer metastasis,” Int. J. Radiat. Biol.76(5), 589–605 (2000).
    [CrossRef] [PubMed]
  18. S. M. Evans and C. J. Koch, “Prognostic significance of tumor oxygenation in humans,” Cancer Lett.195(1), 1–16 (2003).
    [CrossRef] [PubMed]
  19. M. I. Koukourakis, A. Giatromanolaki, R. A. Brekken, E. Sivridis, K. C. Gatter, A. L. Harris, and E. H. Sage, “Enhanced expression of SPARC/osteonectin in the tumor-associated stroma of non-small cell lung cancer is correlated with markers of hypoxia/acidity and with poor prognosis of patients,” Cancer Res.63(17), 5376–5380 (2003).
    [PubMed]
  20. M. Weinmann, C. Belka, and L. Plasswilm, “Tumour hypoxia: impact on biology, prognosis and treatment of solid malignant tumours,” Onkologie27(1), 83–90 (2004).
    [CrossRef] [PubMed]
  21. J. M. Brown and A. J. Giaccia, “The unique physiology of solid tumors: opportunities (and problems) for cancer therapy,” Cancer Res.58(7), 1408–1416 (1998).
    [PubMed]
  22. I. F. Tannock and D. Rotin, “Acid pH in tumors and its potential for therapeutic exploitation,” Cancer Res.49(16), 4373–4384 (1989).
    [PubMed]
  23. S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
    [CrossRef] [PubMed]
  24. Y. Wang, S. Hu, K. Maslov, Y. Zhang, Y. Xia, and L. V. Wang, “In vivo integrated photoacoustic and confocal microscopy of hemoglobin oxygen saturation and oxygen partial pressure,” Opt. Lett.36(7), 1029–1031 (2011).
    [CrossRef] [PubMed]
  25. W. Becker, Advanced Time-Correlated Single Photon Counting Techniques, (Springer, Berlin, 2005).
  26. A. Periasamy and R. M. Clegg, eds., FLIM Microscopy in Biology and Medicine, (Chapman and Hall, Boca Raton, 2009).
  27. K. Suhling, J. Siegel, P. M. Lanigan, S. Lévêque-Fort, S. E. Webb, D. Phillips, D. M. Davis, and P. M. French, “Time-resolved fluorescence anisotropy imaging applied to live cells,” Opt. Lett.29(6), 584–586 (2004).
    [CrossRef] [PubMed]
  28. J. Requejo-Isidro, J. McGinty, I. Munro, D. S. Elson, N. P. Galletly, M. J. Lever, M. A. Neil, G. W. Stamp, P. M. French, P. A. Kellett, J. D. Hares, and A. K. Dymoke-Bradshaw, “High-speed wide-field time-gated endoscopic fluorescence-lifetime imaging,” Opt. Lett.29(19), 2249–2251 (2004).
    [CrossRef] [PubMed]
  29. D. M. Grant, D. S. Elson, D. Schimpf, C. Dunsby, J. Requejo-Isidro, E. Auksorius, I. Munro, M. A. Neil, P. M. French, E. Nye, G. Stamp, and P. Courtney, “Optically sectioned fluorescence lifetime imaging using a Nipkow disk microscope and a tunable ultrafast continuum excitation source,” Opt. Lett.30(24), 3353–3355 (2005).
    [CrossRef] [PubMed]
  30. J. McGinty, K. B. Tahir, R. Laine, C. B. Talbot, C. Dunsby, M. A. Neil, L. Quintana, J. Swoger, J. Sharpe, and P. M. French, “Fluorescence lifetime optical projection tomography,” J Biophotonics1(5), 390–394 (2008).
    [CrossRef] [PubMed]
  31. D. M. Owen, E. Auksorius, H. B. Manning, C. B. Talbot, P. A. de Beule, C. Dunsby, M. A. Neil, and P. M. French, “Excitation-resolved hyperspectral fluorescence lifetime imaging using a UV-extended supercontinuum source,” Opt. Lett.32(23), 3408–3410 (2007).
    [CrossRef] [PubMed]
  32. S. Kumar, C. Dunsby, P. A. De Beule, D. M. Owen, U. Anand, P. M. Lanigan, R. K. Benninger, D. M. Davis, M. A. Neil, P. Anand, C. Benham, A. Naylor, and P. M. French, “Multifocal multiphoton excitation and time correlated single photon counting detection for 3-D fluorescence lifetime imaging,” Opt. Express15(20), 12548–12561 (2007).
    [CrossRef] [PubMed]
  33. D. Magde, G. E. Rojas, and P. G. Seybold, “Solvent dependence of the fluorescence lifetimes of xanthene dyes,” Photochem. Photobiol.70(5), 737–744 (1999).
    [CrossRef]
  34. G. I. Redford and R. M. Clegg, “Polar plot representation for frequency-domain analysis of fluorescence lifetimes,” J. Fluoresc.15(5), 805–815 (2005).
    [CrossRef] [PubMed]
  35. M. A. Digman, V. R. Caiolfa, M. Zamai, and E. Gratton, “The phasor approach to fluorescence lifetime imaging analysis,” Biophys. J.94(2), L14–L16 (2008).
    [CrossRef] [PubMed]
  36. N. A. A. Rahim, W. McDaniel, K. Bardon, S. Srinivas, V. Vickerman, P. T. C. So, and J. H. Moon, “Conjugated polymer nanoparticles for two-photon imaging of endothelial cells in a tissue model,” Adv. Mater. (Deerfield Beach Fla.)21(34), 3492–3496 (2009).
    [CrossRef]
  37. A. Nagy, J. Wu, and K. M. Berland, “Observation volumes and gamma-factors in two-photon fluorescence fluctuation spectroscopy,” Biophys. J.89(3), 2077–2090 (2005).
    [CrossRef] [PubMed]
  38. W. Denk, J. H. Strickler, and W. W. Webb, “Two-photon laser scanning fluorescence microscopy,” Science248(4951), 73–76 (1990).
    [CrossRef] [PubMed]
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2012 (2)

L. C. Cheng, C. Y. Chang, C. Y. Lin, K. C. Cho, W. C. Yen, N. S. Chang, C. Xu, C. Y. Dong, and S. J. Chen, “Spatiotemporal focusing-based widefield multiphoton microscopy for fast optical sectioning,” Opt. Express20(8), 8939–8948 (2012).
[CrossRef] [PubMed]

E. C. Soller, D. S. Tzeranis, K. Miu, P. T. So, and I. V. Yannas, “Common features of optimal collagen scaffolds that disrupt wound contraction and enhance regeneration both in peripheral nerves and in skin,” Biomaterials33(19), 4783–4791 (2012).
[CrossRef] [PubMed]

2011 (1)

2010 (1)

S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
[CrossRef] [PubMed]

2009 (3)

E. Dimitrow, I. Riemann, A. Ehlers, M. J. Koehler, J. Norgauer, P. Elsner, K. König, and M. Kaatz, “Spectral fluorescence lifetime detection and selective melanin imaging by multiphoton laser tomography for melanoma diagnosis,” Exp. Dermatol.18(6), 509–515 (2009).
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N. A. A. Rahim, W. McDaniel, K. Bardon, S. Srinivas, V. Vickerman, P. T. C. So, and J. H. Moon, “Conjugated polymer nanoparticles for two-photon imaging of endothelial cells in a tissue model,” Adv. Mater. (Deerfield Beach Fla.)21(34), 3492–3496 (2009).
[CrossRef]

D. Sud and M. A. Mycek, “Calibration and validation of an optical sensor for intracellular oxygen measurements,” J. Biomed. Opt.14(2), 020506 (2009).
[CrossRef] [PubMed]

2008 (3)

P. Walczysko, U. Kuhlicke, S. Knappe, C. Cordes, and T. R. Neu, “In situ activity of suspended and immobilized microbial communities as measured by fluorescence lifetime imaging,” Appl. Environ. Microbiol.74(1), 294–299 (2008).
[CrossRef] [PubMed]

M. A. Digman, V. R. Caiolfa, M. Zamai, and E. Gratton, “The phasor approach to fluorescence lifetime imaging analysis,” Biophys. J.94(2), L14–L16 (2008).
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J. McGinty, K. B. Tahir, R. Laine, C. B. Talbot, C. Dunsby, M. A. Neil, L. Quintana, J. Swoger, J. Sharpe, and P. M. French, “Fluorescence lifetime optical projection tomography,” J Biophotonics1(5), 390–394 (2008).
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2007 (4)

D. M. Owen, E. Auksorius, H. B. Manning, C. B. Talbot, P. A. de Beule, C. Dunsby, M. A. Neil, and P. M. French, “Excitation-resolved hyperspectral fluorescence lifetime imaging using a UV-extended supercontinuum source,” Opt. Lett.32(23), 3408–3410 (2007).
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S. Kumar, C. Dunsby, P. A. De Beule, D. M. Owen, U. Anand, P. M. Lanigan, R. K. Benninger, D. M. Davis, M. A. Neil, P. Anand, C. Benham, A. Naylor, and P. M. French, “Multifocal multiphoton excitation and time correlated single photon counting detection for 3-D fluorescence lifetime imaging,” Opt. Express15(20), 12548–12561 (2007).
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K. König, A. Ehlers, I. Riemann, S. Schenkl, R. Bückle, and M. Kaatz, “Clinical two-photon microendoscopy,” Microsc. Res. Tech.70(5), 398–402 (2007).
[CrossRef] [PubMed]

G. Mehta, K. Mehta, D. Sud, J. W. Song, T. Bersano-Begey, N. Futai, Y. S. Heo, M. A. Mycek, J. J. Linderman, and S. Takayama, “Quantitative measurement and control of oxygen levels in microfluidic poly(dimethylsiloxane) bioreactors during cell culture,” Biomed. Microdevices9(2), 123–134 (2007).
[CrossRef] [PubMed]

2006 (2)

D. Sud, G. Mehta, K. Mehta, J. Linderman, S. Takayama, and M. A. Mycek, “Optical imaging in microfluidic bioreactors enables oxygen monitoring for continuous cell culture,” J. Biomed. Opt.11(5), 050504 (2006).
[CrossRef] [PubMed]

D. Sud, W. Zhong, D. G. Beer, and M. A. Mycek, “Time-resolved optical imaging provides a molecular snapshot of altered metabolic function in living human cancer cell models,” Opt. Express14(10), 4412–4426 (2006).
[CrossRef] [PubMed]

2005 (4)

A. Nagy, J. Wu, and K. M. Berland, “Observation volumes and gamma-factors in two-photon fluorescence fluctuation spectroscopy,” Biophys. J.89(3), 2077–2090 (2005).
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L. S. Ziemer, W. M. Lee, S. A. Vinogradov, C. Sehgal, and D. F. Wilson, “Oxygen distribution in murine tumors: characterization using oxygen-dependent quenching of phosphorescence,” J. Appl. Physiol.98(4), 1503–1510 (2005).
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G. I. Redford and R. M. Clegg, “Polar plot representation for frequency-domain analysis of fluorescence lifetimes,” J. Fluoresc.15(5), 805–815 (2005).
[CrossRef] [PubMed]

D. M. Grant, D. S. Elson, D. Schimpf, C. Dunsby, J. Requejo-Isidro, E. Auksorius, I. Munro, M. A. Neil, P. M. French, E. Nye, G. Stamp, and P. Courtney, “Optically sectioned fluorescence lifetime imaging using a Nipkow disk microscope and a tunable ultrafast continuum excitation source,” Opt. Lett.30(24), 3353–3355 (2005).
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2004 (5)

K. Suhling, J. Siegel, P. M. Lanigan, S. Lévêque-Fort, S. E. Webb, D. Phillips, D. M. Davis, and P. M. French, “Time-resolved fluorescence anisotropy imaging applied to live cells,” Opt. Lett.29(6), 584–586 (2004).
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J. Requejo-Isidro, J. McGinty, I. Munro, D. S. Elson, N. P. Galletly, M. J. Lever, M. A. Neil, G. W. Stamp, P. M. French, P. A. Kellett, J. D. Hares, and A. K. Dymoke-Bradshaw, “High-speed wide-field time-gated endoscopic fluorescence-lifetime imaging,” Opt. Lett.29(19), 2249–2251 (2004).
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M. Weinmann, C. Belka, and L. Plasswilm, “Tumour hypoxia: impact on biology, prognosis and treatment of solid malignant tumours,” Onkologie27(1), 83–90 (2004).
[CrossRef] [PubMed]

W. Becker, A. Bergmann, M. A. Hink, K. König, K. Benndorf, and C. Biskup, “Fluorescence lifetime imaging by time-correlated single-photon counting,” Microsc. Res. Tech.63(1), 58–66 (2004).
[CrossRef] [PubMed]

S. Pelet, M. J. Previte, L. H. Laiho, and P. T. So, “A fast global fitting algorithm for fluorescence lifetime imaging microscopy based on image segmentation,” Biophys. J.87(4), 2807–2817 (2004).
[CrossRef] [PubMed]

2003 (4)

E. Gratton, S. Breusegem, J. Sutin, Q. Ruan, and N. Barry, “Fluorescence lifetime imaging for the two-photon microscope: time-domain and frequency-domain methods,” J. Biomed. Opt.8(3), 381–390 (2003).
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S. M. Evans and C. J. Koch, “Prognostic significance of tumor oxygenation in humans,” Cancer Lett.195(1), 1–16 (2003).
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M. I. Koukourakis, A. Giatromanolaki, R. A. Brekken, E. Sivridis, K. C. Gatter, A. L. Harris, and E. H. Sage, “Enhanced expression of SPARC/osteonectin in the tumor-associated stroma of non-small cell lung cancer is correlated with markers of hypoxia/acidity and with poor prognosis of patients,” Cancer Res.63(17), 5376–5380 (2003).
[PubMed]

X. Zhuang and M. Rief, “Single-molecule folding,” Curr. Opin. Struct. Biol.13(1), 88–97 (2003).
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2002 (2)

A. L. Harris, “Hypoxia--a key regulatory factor in tumour growth,” Nat. Rev. Cancer2(1), 38–47 (2002).
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J. M. Brown, “Tumor microenvironment and the response to anticancer therapy,” Cancer Biol. Ther.1(5), 448–458 (2002).
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2000 (2)

E. K. Rofstad, “Microenvironment-induced cancer metastasis,” Int. J. Radiat. Biol.76(5), 589–605 (2000).
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A. A. Deniz, T. A. Laurence, G. S. Beligere, M. Dahan, A. B. Martin, D. S. Chemla, P. E. Dawson, P. G. Schultz, and S. Weiss, “Single-molecule protein folding: diffusion fluorescence resonance energy transfer studies of the denaturation of chymotrypsin inhibitor 2,” Proc. Natl. Acad. Sci. U.S.A.97(10), 5179–5184 (2000).
[CrossRef] [PubMed]

1999 (2)

H. C. Gerritsen, J. M. Vroom, and C. J. de Grauw, “Combining two-photon excitation with fluorescence lifetime imaging,” IEEE Eng. Med. Biol. Mag.18(5), 31–36 (1999).
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D. Magde, G. E. Rojas, and P. G. Seybold, “Solvent dependence of the fluorescence lifetimes of xanthene dyes,” Photochem. Photobiol.70(5), 737–744 (1999).
[CrossRef]

1998 (2)

J. M. Brown and A. J. Giaccia, “The unique physiology of solid tumors: opportunities (and problems) for cancer therapy,” Cancer Res.58(7), 1408–1416 (1998).
[PubMed]

L. J. Chamberlain, I. V. Yannas, H. P. Hsu, G. Strichartz, and M. Spector, “Collagen-GAG substrate enhances the quality of nerve regeneration through collagen tubes up to level of autograft,” Exp. Neurol.154(2), 315–329 (1998).
[CrossRef] [PubMed]

1997 (1)

G. Helmlinger, F. Yuan, M. Dellian, and R. K. Jain, “Interstitial pH and pO2 gradients in solid tumors in vivo: high-resolution measurements reveal a lack of correlation,” Nat. Med.3(2), 177–182 (1997).
[CrossRef] [PubMed]

1996 (3)

I. Gryczynski, A. Razynska, and J. R. Lakowicz, “Two-photon induced fluorescence of linear alkanes; a possible intrinsic lipid probe,” Biophys. Chem.57(2-3), 291–295 (1996).
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K. König, P. T. So, W. W. Mantulin, B. J. Tromberg, and E. Gratton, “Two-photon excited lifetime imaging of autofluorescence in cells during UVA and NIR photostress,” J. Microsc.183(Pt 3), 197–204 (1996).
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J. R. Lakowicz, “Emerging applications of fluorescence spectroscopy to cellular imaging: lifetime imaging, metal-ligand probes, multi-photon excitation and light quenching,” Scanning Microsc. Suppl.10, 213–224 (1996).
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1994 (1)

I. P. Torres Filho, M. Leunig, F. Yuan, M. Intaglietta, and R. K. Jain, “Noninvasive measurement of microvascular and interstitial oxygen profiles in a human tumor in SCID mice,” Proc. Natl. Acad. Sci. U.S.A.91(6), 2081–2085 (1994).
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1993 (1)

R. M. Clegg, A. I. Murchie, and D. M. Lilley, “The four-way DNA junction: a fluorescence resonance energy transfer study,” Braz. J. Med. Biol. Res.26(4), 405–416 (1993).
[PubMed]

1990 (1)

W. Denk, J. H. Strickler, and W. W. Webb, “Two-photon laser scanning fluorescence microscopy,” Science248(4951), 73–76 (1990).
[CrossRef] [PubMed]

1989 (2)

P. I. Bastiaens, P. J. Bonants, F. Müller, and A. J. Visser, “Time-resolved fluorescence spectroscopy of NADPH-cytochrome P-450 reductase: demonstration of energy transfer between the two prosthetic groups,” Biochemistry28(21), 8416–8425 (1989).
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I. F. Tannock and D. Rotin, “Acid pH in tumors and its potential for therapeutic exploitation,” Cancer Res.49(16), 4373–4384 (1989).
[PubMed]

1982 (1)

I. V. Yannas, J. F. Burke, D. P. Orgill, and E. M. Skrabut, “Wound tissue can utilize a polymeric template to synthesize a functional extension of skin,” Science215(4529), 174–176 (1982).
[CrossRef] [PubMed]

Anand, P.

Anand, U.

Arai, K.

S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
[CrossRef] [PubMed]

Auksorius, E.

Bardon, K.

N. A. A. Rahim, W. McDaniel, K. Bardon, S. Srinivas, V. Vickerman, P. T. C. So, and J. H. Moon, “Conjugated polymer nanoparticles for two-photon imaging of endothelial cells in a tissue model,” Adv. Mater. (Deerfield Beach Fla.)21(34), 3492–3496 (2009).
[CrossRef]

Barry, N.

E. Gratton, S. Breusegem, J. Sutin, Q. Ruan, and N. Barry, “Fluorescence lifetime imaging for the two-photon microscope: time-domain and frequency-domain methods,” J. Biomed. Opt.8(3), 381–390 (2003).
[CrossRef] [PubMed]

Bastiaens, P. I.

P. I. Bastiaens, P. J. Bonants, F. Müller, and A. J. Visser, “Time-resolved fluorescence spectroscopy of NADPH-cytochrome P-450 reductase: demonstration of energy transfer between the two prosthetic groups,” Biochemistry28(21), 8416–8425 (1989).
[CrossRef] [PubMed]

Becker, W.

W. Becker, A. Bergmann, M. A. Hink, K. König, K. Benndorf, and C. Biskup, “Fluorescence lifetime imaging by time-correlated single-photon counting,” Microsc. Res. Tech.63(1), 58–66 (2004).
[CrossRef] [PubMed]

Beer, D. G.

Beligere, G. S.

A. A. Deniz, T. A. Laurence, G. S. Beligere, M. Dahan, A. B. Martin, D. S. Chemla, P. E. Dawson, P. G. Schultz, and S. Weiss, “Single-molecule protein folding: diffusion fluorescence resonance energy transfer studies of the denaturation of chymotrypsin inhibitor 2,” Proc. Natl. Acad. Sci. U.S.A.97(10), 5179–5184 (2000).
[CrossRef] [PubMed]

Belka, C.

M. Weinmann, C. Belka, and L. Plasswilm, “Tumour hypoxia: impact on biology, prognosis and treatment of solid malignant tumours,” Onkologie27(1), 83–90 (2004).
[CrossRef] [PubMed]

Benham, C.

Benndorf, K.

W. Becker, A. Bergmann, M. A. Hink, K. König, K. Benndorf, and C. Biskup, “Fluorescence lifetime imaging by time-correlated single-photon counting,” Microsc. Res. Tech.63(1), 58–66 (2004).
[CrossRef] [PubMed]

Benninger, R. K.

Bergmann, A.

W. Becker, A. Bergmann, M. A. Hink, K. König, K. Benndorf, and C. Biskup, “Fluorescence lifetime imaging by time-correlated single-photon counting,” Microsc. Res. Tech.63(1), 58–66 (2004).
[CrossRef] [PubMed]

Berland, K. M.

A. Nagy, J. Wu, and K. M. Berland, “Observation volumes and gamma-factors in two-photon fluorescence fluctuation spectroscopy,” Biophys. J.89(3), 2077–2090 (2005).
[CrossRef] [PubMed]

Bersano-Begey, T.

G. Mehta, K. Mehta, D. Sud, J. W. Song, T. Bersano-Begey, N. Futai, Y. S. Heo, M. A. Mycek, J. J. Linderman, and S. Takayama, “Quantitative measurement and control of oxygen levels in microfluidic poly(dimethylsiloxane) bioreactors during cell culture,” Biomed. Microdevices9(2), 123–134 (2007).
[CrossRef] [PubMed]

Biskup, C.

W. Becker, A. Bergmann, M. A. Hink, K. König, K. Benndorf, and C. Biskup, “Fluorescence lifetime imaging by time-correlated single-photon counting,” Microsc. Res. Tech.63(1), 58–66 (2004).
[CrossRef] [PubMed]

Boas, D. A.

S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
[CrossRef] [PubMed]

Bonants, P. J.

P. I. Bastiaens, P. J. Bonants, F. Müller, and A. J. Visser, “Time-resolved fluorescence spectroscopy of NADPH-cytochrome P-450 reductase: demonstration of energy transfer between the two prosthetic groups,” Biochemistry28(21), 8416–8425 (1989).
[CrossRef] [PubMed]

Brekken, R. A.

M. I. Koukourakis, A. Giatromanolaki, R. A. Brekken, E. Sivridis, K. C. Gatter, A. L. Harris, and E. H. Sage, “Enhanced expression of SPARC/osteonectin in the tumor-associated stroma of non-small cell lung cancer is correlated with markers of hypoxia/acidity and with poor prognosis of patients,” Cancer Res.63(17), 5376–5380 (2003).
[PubMed]

Breusegem, S.

E. Gratton, S. Breusegem, J. Sutin, Q. Ruan, and N. Barry, “Fluorescence lifetime imaging for the two-photon microscope: time-domain and frequency-domain methods,” J. Biomed. Opt.8(3), 381–390 (2003).
[CrossRef] [PubMed]

Brown, J. M.

J. M. Brown, “Tumor microenvironment and the response to anticancer therapy,” Cancer Biol. Ther.1(5), 448–458 (2002).
[CrossRef] [PubMed]

J. M. Brown and A. J. Giaccia, “The unique physiology of solid tumors: opportunities (and problems) for cancer therapy,” Cancer Res.58(7), 1408–1416 (1998).
[PubMed]

Bückle, R.

K. König, A. Ehlers, I. Riemann, S. Schenkl, R. Bückle, and M. Kaatz, “Clinical two-photon microendoscopy,” Microsc. Res. Tech.70(5), 398–402 (2007).
[CrossRef] [PubMed]

Burke, J. F.

I. V. Yannas, J. F. Burke, D. P. Orgill, and E. M. Skrabut, “Wound tissue can utilize a polymeric template to synthesize a functional extension of skin,” Science215(4529), 174–176 (1982).
[CrossRef] [PubMed]

Caiolfa, V. R.

M. A. Digman, V. R. Caiolfa, M. Zamai, and E. Gratton, “The phasor approach to fluorescence lifetime imaging analysis,” Biophys. J.94(2), L14–L16 (2008).
[CrossRef] [PubMed]

Chamberlain, L. J.

L. J. Chamberlain, I. V. Yannas, H. P. Hsu, G. Strichartz, and M. Spector, “Collagen-GAG substrate enhances the quality of nerve regeneration through collagen tubes up to level of autograft,” Exp. Neurol.154(2), 315–329 (1998).
[CrossRef] [PubMed]

Chang, C. Y.

Chang, N. S.

Chemla, D. S.

A. A. Deniz, T. A. Laurence, G. S. Beligere, M. Dahan, A. B. Martin, D. S. Chemla, P. E. Dawson, P. G. Schultz, and S. Weiss, “Single-molecule protein folding: diffusion fluorescence resonance energy transfer studies of the denaturation of chymotrypsin inhibitor 2,” Proc. Natl. Acad. Sci. U.S.A.97(10), 5179–5184 (2000).
[CrossRef] [PubMed]

Chen, S. J.

Cheng, L. C.

Cho, K. C.

Clegg, R. M.

G. I. Redford and R. M. Clegg, “Polar plot representation for frequency-domain analysis of fluorescence lifetimes,” J. Fluoresc.15(5), 805–815 (2005).
[CrossRef] [PubMed]

R. M. Clegg, A. I. Murchie, and D. M. Lilley, “The four-way DNA junction: a fluorescence resonance energy transfer study,” Braz. J. Med. Biol. Res.26(4), 405–416 (1993).
[PubMed]

Cordes, C.

P. Walczysko, U. Kuhlicke, S. Knappe, C. Cordes, and T. R. Neu, “In situ activity of suspended and immobilized microbial communities as measured by fluorescence lifetime imaging,” Appl. Environ. Microbiol.74(1), 294–299 (2008).
[CrossRef] [PubMed]

Courtney, P.

Dahan, M.

A. A. Deniz, T. A. Laurence, G. S. Beligere, M. Dahan, A. B. Martin, D. S. Chemla, P. E. Dawson, P. G. Schultz, and S. Weiss, “Single-molecule protein folding: diffusion fluorescence resonance energy transfer studies of the denaturation of chymotrypsin inhibitor 2,” Proc. Natl. Acad. Sci. U.S.A.97(10), 5179–5184 (2000).
[CrossRef] [PubMed]

Davis, D. M.

Dawson, P. E.

A. A. Deniz, T. A. Laurence, G. S. Beligere, M. Dahan, A. B. Martin, D. S. Chemla, P. E. Dawson, P. G. Schultz, and S. Weiss, “Single-molecule protein folding: diffusion fluorescence resonance energy transfer studies of the denaturation of chymotrypsin inhibitor 2,” Proc. Natl. Acad. Sci. U.S.A.97(10), 5179–5184 (2000).
[CrossRef] [PubMed]

De Beule, P. A.

de Grauw, C. J.

H. C. Gerritsen, J. M. Vroom, and C. J. de Grauw, “Combining two-photon excitation with fluorescence lifetime imaging,” IEEE Eng. Med. Biol. Mag.18(5), 31–36 (1999).
[CrossRef] [PubMed]

Dellian, M.

G. Helmlinger, F. Yuan, M. Dellian, and R. K. Jain, “Interstitial pH and pO2 gradients in solid tumors in vivo: high-resolution measurements reveal a lack of correlation,” Nat. Med.3(2), 177–182 (1997).
[CrossRef] [PubMed]

Deniz, A. A.

A. A. Deniz, T. A. Laurence, G. S. Beligere, M. Dahan, A. B. Martin, D. S. Chemla, P. E. Dawson, P. G. Schultz, and S. Weiss, “Single-molecule protein folding: diffusion fluorescence resonance energy transfer studies of the denaturation of chymotrypsin inhibitor 2,” Proc. Natl. Acad. Sci. U.S.A.97(10), 5179–5184 (2000).
[CrossRef] [PubMed]

Denk, W.

W. Denk, J. H. Strickler, and W. W. Webb, “Two-photon laser scanning fluorescence microscopy,” Science248(4951), 73–76 (1990).
[CrossRef] [PubMed]

Devor, A.

S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
[CrossRef] [PubMed]

Digman, M. A.

M. A. Digman, V. R. Caiolfa, M. Zamai, and E. Gratton, “The phasor approach to fluorescence lifetime imaging analysis,” Biophys. J.94(2), L14–L16 (2008).
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Rahim, N. A. A.

N. A. A. Rahim, W. McDaniel, K. Bardon, S. Srinivas, V. Vickerman, P. T. C. So, and J. H. Moon, “Conjugated polymer nanoparticles for two-photon imaging of endothelial cells in a tissue model,” Adv. Mater. (Deerfield Beach Fla.)21(34), 3492–3496 (2009).
[CrossRef]

Razynska, A.

I. Gryczynski, A. Razynska, and J. R. Lakowicz, “Two-photon induced fluorescence of linear alkanes; a possible intrinsic lipid probe,” Biophys. Chem.57(2-3), 291–295 (1996).
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G. I. Redford and R. M. Clegg, “Polar plot representation for frequency-domain analysis of fluorescence lifetimes,” J. Fluoresc.15(5), 805–815 (2005).
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X. Zhuang and M. Rief, “Single-molecule folding,” Curr. Opin. Struct. Biol.13(1), 88–97 (2003).
[CrossRef] [PubMed]

Riemann, I.

E. Dimitrow, I. Riemann, A. Ehlers, M. J. Koehler, J. Norgauer, P. Elsner, K. König, and M. Kaatz, “Spectral fluorescence lifetime detection and selective melanin imaging by multiphoton laser tomography for melanoma diagnosis,” Exp. Dermatol.18(6), 509–515 (2009).
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K. König, A. Ehlers, I. Riemann, S. Schenkl, R. Bückle, and M. Kaatz, “Clinical two-photon microendoscopy,” Microsc. Res. Tech.70(5), 398–402 (2007).
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E. K. Rofstad, “Microenvironment-induced cancer metastasis,” Int. J. Radiat. Biol.76(5), 589–605 (2000).
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D. Magde, G. E. Rojas, and P. G. Seybold, “Solvent dependence of the fluorescence lifetimes of xanthene dyes,” Photochem. Photobiol.70(5), 737–744 (1999).
[CrossRef]

Rotin, D.

I. F. Tannock and D. Rotin, “Acid pH in tumors and its potential for therapeutic exploitation,” Cancer Res.49(16), 4373–4384 (1989).
[PubMed]

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S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
[CrossRef] [PubMed]

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E. Gratton, S. Breusegem, J. Sutin, Q. Ruan, and N. Barry, “Fluorescence lifetime imaging for the two-photon microscope: time-domain and frequency-domain methods,” J. Biomed. Opt.8(3), 381–390 (2003).
[CrossRef] [PubMed]

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S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
[CrossRef] [PubMed]

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M. I. Koukourakis, A. Giatromanolaki, R. A. Brekken, E. Sivridis, K. C. Gatter, A. L. Harris, and E. H. Sage, “Enhanced expression of SPARC/osteonectin in the tumor-associated stroma of non-small cell lung cancer is correlated with markers of hypoxia/acidity and with poor prognosis of patients,” Cancer Res.63(17), 5376–5380 (2003).
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[CrossRef] [PubMed]

Schenkl, S.

K. König, A. Ehlers, I. Riemann, S. Schenkl, R. Bückle, and M. Kaatz, “Clinical two-photon microendoscopy,” Microsc. Res. Tech.70(5), 398–402 (2007).
[CrossRef] [PubMed]

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Schultz, P. G.

A. A. Deniz, T. A. Laurence, G. S. Beligere, M. Dahan, A. B. Martin, D. S. Chemla, P. E. Dawson, P. G. Schultz, and S. Weiss, “Single-molecule protein folding: diffusion fluorescence resonance energy transfer studies of the denaturation of chymotrypsin inhibitor 2,” Proc. Natl. Acad. Sci. U.S.A.97(10), 5179–5184 (2000).
[CrossRef] [PubMed]

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L. S. Ziemer, W. M. Lee, S. A. Vinogradov, C. Sehgal, and D. F. Wilson, “Oxygen distribution in murine tumors: characterization using oxygen-dependent quenching of phosphorescence,” J. Appl. Physiol.98(4), 1503–1510 (2005).
[CrossRef] [PubMed]

Seybold, P. G.

D. Magde, G. E. Rojas, and P. G. Seybold, “Solvent dependence of the fluorescence lifetimes of xanthene dyes,” Photochem. Photobiol.70(5), 737–744 (1999).
[CrossRef]

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J. McGinty, K. B. Tahir, R. Laine, C. B. Talbot, C. Dunsby, M. A. Neil, L. Quintana, J. Swoger, J. Sharpe, and P. M. French, “Fluorescence lifetime optical projection tomography,” J Biophotonics1(5), 390–394 (2008).
[CrossRef] [PubMed]

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Sivridis, E.

M. I. Koukourakis, A. Giatromanolaki, R. A. Brekken, E. Sivridis, K. C. Gatter, A. L. Harris, and E. H. Sage, “Enhanced expression of SPARC/osteonectin in the tumor-associated stroma of non-small cell lung cancer is correlated with markers of hypoxia/acidity and with poor prognosis of patients,” Cancer Res.63(17), 5376–5380 (2003).
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I. V. Yannas, J. F. Burke, D. P. Orgill, and E. M. Skrabut, “Wound tissue can utilize a polymeric template to synthesize a functional extension of skin,” Science215(4529), 174–176 (1982).
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E. C. Soller, D. S. Tzeranis, K. Miu, P. T. So, and I. V. Yannas, “Common features of optimal collagen scaffolds that disrupt wound contraction and enhance regeneration both in peripheral nerves and in skin,” Biomaterials33(19), 4783–4791 (2012).
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S. Pelet, M. J. Previte, L. H. Laiho, and P. T. So, “A fast global fitting algorithm for fluorescence lifetime imaging microscopy based on image segmentation,” Biophys. J.87(4), 2807–2817 (2004).
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K. König, P. T. So, W. W. Mantulin, B. J. Tromberg, and E. Gratton, “Two-photon excited lifetime imaging of autofluorescence in cells during UVA and NIR photostress,” J. Microsc.183(Pt 3), 197–204 (1996).
[PubMed]

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N. A. A. Rahim, W. McDaniel, K. Bardon, S. Srinivas, V. Vickerman, P. T. C. So, and J. H. Moon, “Conjugated polymer nanoparticles for two-photon imaging of endothelial cells in a tissue model,” Adv. Mater. (Deerfield Beach Fla.)21(34), 3492–3496 (2009).
[CrossRef]

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E. C. Soller, D. S. Tzeranis, K. Miu, P. T. So, and I. V. Yannas, “Common features of optimal collagen scaffolds that disrupt wound contraction and enhance regeneration both in peripheral nerves and in skin,” Biomaterials33(19), 4783–4791 (2012).
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L. J. Chamberlain, I. V. Yannas, H. P. Hsu, G. Strichartz, and M. Spector, “Collagen-GAG substrate enhances the quality of nerve regeneration through collagen tubes up to level of autograft,” Exp. Neurol.154(2), 315–329 (1998).
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N. A. A. Rahim, W. McDaniel, K. Bardon, S. Srinivas, V. Vickerman, P. T. C. So, and J. H. Moon, “Conjugated polymer nanoparticles for two-photon imaging of endothelial cells in a tissue model,” Adv. Mater. (Deerfield Beach Fla.)21(34), 3492–3496 (2009).
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S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
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Stamp, G. W.

Strichartz, G.

L. J. Chamberlain, I. V. Yannas, H. P. Hsu, G. Strichartz, and M. Spector, “Collagen-GAG substrate enhances the quality of nerve regeneration through collagen tubes up to level of autograft,” Exp. Neurol.154(2), 315–329 (1998).
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W. Denk, J. H. Strickler, and W. W. Webb, “Two-photon laser scanning fluorescence microscopy,” Science248(4951), 73–76 (1990).
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D. Sud, G. Mehta, K. Mehta, J. Linderman, S. Takayama, and M. A. Mycek, “Optical imaging in microfluidic bioreactors enables oxygen monitoring for continuous cell culture,” J. Biomed. Opt.11(5), 050504 (2006).
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Sutin, J.

E. Gratton, S. Breusegem, J. Sutin, Q. Ruan, and N. Barry, “Fluorescence lifetime imaging for the two-photon microscope: time-domain and frequency-domain methods,” J. Biomed. Opt.8(3), 381–390 (2003).
[CrossRef] [PubMed]

Swoger, J.

J. McGinty, K. B. Tahir, R. Laine, C. B. Talbot, C. Dunsby, M. A. Neil, L. Quintana, J. Swoger, J. Sharpe, and P. M. French, “Fluorescence lifetime optical projection tomography,” J Biophotonics1(5), 390–394 (2008).
[CrossRef] [PubMed]

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J. McGinty, K. B. Tahir, R. Laine, C. B. Talbot, C. Dunsby, M. A. Neil, L. Quintana, J. Swoger, J. Sharpe, and P. M. French, “Fluorescence lifetime optical projection tomography,” J Biophotonics1(5), 390–394 (2008).
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D. Sud, G. Mehta, K. Mehta, J. Linderman, S. Takayama, and M. A. Mycek, “Optical imaging in microfluidic bioreactors enables oxygen monitoring for continuous cell culture,” J. Biomed. Opt.11(5), 050504 (2006).
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J. McGinty, K. B. Tahir, R. Laine, C. B. Talbot, C. Dunsby, M. A. Neil, L. Quintana, J. Swoger, J. Sharpe, and P. M. French, “Fluorescence lifetime optical projection tomography,” J Biophotonics1(5), 390–394 (2008).
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I. F. Tannock and D. Rotin, “Acid pH in tumors and its potential for therapeutic exploitation,” Cancer Res.49(16), 4373–4384 (1989).
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I. P. Torres Filho, M. Leunig, F. Yuan, M. Intaglietta, and R. K. Jain, “Noninvasive measurement of microvascular and interstitial oxygen profiles in a human tumor in SCID mice,” Proc. Natl. Acad. Sci. U.S.A.91(6), 2081–2085 (1994).
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K. König, P. T. So, W. W. Mantulin, B. J. Tromberg, and E. Gratton, “Two-photon excited lifetime imaging of autofluorescence in cells during UVA and NIR photostress,” J. Microsc.183(Pt 3), 197–204 (1996).
[PubMed]

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E. C. Soller, D. S. Tzeranis, K. Miu, P. T. So, and I. V. Yannas, “Common features of optimal collagen scaffolds that disrupt wound contraction and enhance regeneration both in peripheral nerves and in skin,” Biomaterials33(19), 4783–4791 (2012).
[CrossRef] [PubMed]

Vickerman, V.

N. A. A. Rahim, W. McDaniel, K. Bardon, S. Srinivas, V. Vickerman, P. T. C. So, and J. H. Moon, “Conjugated polymer nanoparticles for two-photon imaging of endothelial cells in a tissue model,” Adv. Mater. (Deerfield Beach Fla.)21(34), 3492–3496 (2009).
[CrossRef]

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S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
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L. S. Ziemer, W. M. Lee, S. A. Vinogradov, C. Sehgal, and D. F. Wilson, “Oxygen distribution in murine tumors: characterization using oxygen-dependent quenching of phosphorescence,” J. Appl. Physiol.98(4), 1503–1510 (2005).
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P. I. Bastiaens, P. J. Bonants, F. Müller, and A. J. Visser, “Time-resolved fluorescence spectroscopy of NADPH-cytochrome P-450 reductase: demonstration of energy transfer between the two prosthetic groups,” Biochemistry28(21), 8416–8425 (1989).
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H. C. Gerritsen, J. M. Vroom, and C. J. de Grauw, “Combining two-photon excitation with fluorescence lifetime imaging,” IEEE Eng. Med. Biol. Mag.18(5), 31–36 (1999).
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P. Walczysko, U. Kuhlicke, S. Knappe, C. Cordes, and T. R. Neu, “In situ activity of suspended and immobilized microbial communities as measured by fluorescence lifetime imaging,” Appl. Environ. Microbiol.74(1), 294–299 (2008).
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Wang, Y.

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W. Denk, J. H. Strickler, and W. W. Webb, “Two-photon laser scanning fluorescence microscopy,” Science248(4951), 73–76 (1990).
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[CrossRef] [PubMed]

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L. S. Ziemer, W. M. Lee, S. A. Vinogradov, C. Sehgal, and D. F. Wilson, “Oxygen distribution in murine tumors: characterization using oxygen-dependent quenching of phosphorescence,” J. Appl. Physiol.98(4), 1503–1510 (2005).
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A. Nagy, J. Wu, and K. M. Berland, “Observation volumes and gamma-factors in two-photon fluorescence fluctuation spectroscopy,” Biophys. J.89(3), 2077–2090 (2005).
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Xu, C.

Yannas, I. V.

E. C. Soller, D. S. Tzeranis, K. Miu, P. T. So, and I. V. Yannas, “Common features of optimal collagen scaffolds that disrupt wound contraction and enhance regeneration both in peripheral nerves and in skin,” Biomaterials33(19), 4783–4791 (2012).
[CrossRef] [PubMed]

L. J. Chamberlain, I. V. Yannas, H. P. Hsu, G. Strichartz, and M. Spector, “Collagen-GAG substrate enhances the quality of nerve regeneration through collagen tubes up to level of autograft,” Exp. Neurol.154(2), 315–329 (1998).
[CrossRef] [PubMed]

I. V. Yannas, J. F. Burke, D. P. Orgill, and E. M. Skrabut, “Wound tissue can utilize a polymeric template to synthesize a functional extension of skin,” Science215(4529), 174–176 (1982).
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S. Sakadzić, E. Roussakis, M. A. Yaseen, E. T. Mandeville, V. J. Srinivasan, K. Arai, S. Ruvinskaya, A. Devor, E. H. Lo, S. A. Vinogradov, and D. A. Boas, “Two-photon high-resolution measurement of partial pressure of oxygen in cerebral vasculature and tissue,” Nat. Methods7(9), 755–759 (2010).
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G. Helmlinger, F. Yuan, M. Dellian, and R. K. Jain, “Interstitial pH and pO2 gradients in solid tumors in vivo: high-resolution measurements reveal a lack of correlation,” Nat. Med.3(2), 177–182 (1997).
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M. A. Digman, V. R. Caiolfa, M. Zamai, and E. Gratton, “The phasor approach to fluorescence lifetime imaging analysis,” Biophys. J.94(2), L14–L16 (2008).
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X. Zhuang and M. Rief, “Single-molecule folding,” Curr. Opin. Struct. Biol.13(1), 88–97 (2003).
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L. S. Ziemer, W. M. Lee, S. A. Vinogradov, C. Sehgal, and D. F. Wilson, “Oxygen distribution in murine tumors: characterization using oxygen-dependent quenching of phosphorescence,” J. Appl. Physiol.98(4), 1503–1510 (2005).
[CrossRef] [PubMed]

Adv. Mater. (Deerfield Beach Fla.) (1)

N. A. A. Rahim, W. McDaniel, K. Bardon, S. Srinivas, V. Vickerman, P. T. C. So, and J. H. Moon, “Conjugated polymer nanoparticles for two-photon imaging of endothelial cells in a tissue model,” Adv. Mater. (Deerfield Beach Fla.)21(34), 3492–3496 (2009).
[CrossRef]

Appl. Environ. Microbiol. (1)

P. Walczysko, U. Kuhlicke, S. Knappe, C. Cordes, and T. R. Neu, “In situ activity of suspended and immobilized microbial communities as measured by fluorescence lifetime imaging,” Appl. Environ. Microbiol.74(1), 294–299 (2008).
[CrossRef] [PubMed]

Biochemistry (1)

P. I. Bastiaens, P. J. Bonants, F. Müller, and A. J. Visser, “Time-resolved fluorescence spectroscopy of NADPH-cytochrome P-450 reductase: demonstration of energy transfer between the two prosthetic groups,” Biochemistry28(21), 8416–8425 (1989).
[CrossRef] [PubMed]

Biomaterials (1)

E. C. Soller, D. S. Tzeranis, K. Miu, P. T. So, and I. V. Yannas, “Common features of optimal collagen scaffolds that disrupt wound contraction and enhance regeneration both in peripheral nerves and in skin,” Biomaterials33(19), 4783–4791 (2012).
[CrossRef] [PubMed]

Biomed. Microdevices (1)

G. Mehta, K. Mehta, D. Sud, J. W. Song, T. Bersano-Begey, N. Futai, Y. S. Heo, M. A. Mycek, J. J. Linderman, and S. Takayama, “Quantitative measurement and control of oxygen levels in microfluidic poly(dimethylsiloxane) bioreactors during cell culture,” Biomed. Microdevices9(2), 123–134 (2007).
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Biophys. Chem. (1)

I. Gryczynski, A. Razynska, and J. R. Lakowicz, “Two-photon induced fluorescence of linear alkanes; a possible intrinsic lipid probe,” Biophys. Chem.57(2-3), 291–295 (1996).
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A. Nagy, J. Wu, and K. M. Berland, “Observation volumes and gamma-factors in two-photon fluorescence fluctuation spectroscopy,” Biophys. J.89(3), 2077–2090 (2005).
[CrossRef] [PubMed]

M. A. Digman, V. R. Caiolfa, M. Zamai, and E. Gratton, “The phasor approach to fluorescence lifetime imaging analysis,” Biophys. J.94(2), L14–L16 (2008).
[CrossRef] [PubMed]

S. Pelet, M. J. Previte, L. H. Laiho, and P. T. So, “A fast global fitting algorithm for fluorescence lifetime imaging microscopy based on image segmentation,” Biophys. J.87(4), 2807–2817 (2004).
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M. I. Koukourakis, A. Giatromanolaki, R. A. Brekken, E. Sivridis, K. C. Gatter, A. L. Harris, and E. H. Sage, “Enhanced expression of SPARC/osteonectin in the tumor-associated stroma of non-small cell lung cancer is correlated with markers of hypoxia/acidity and with poor prognosis of patients,” Cancer Res.63(17), 5376–5380 (2003).
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[PubMed]

Curr. Opin. Struct. Biol. (1)

X. Zhuang and M. Rief, “Single-molecule folding,” Curr. Opin. Struct. Biol.13(1), 88–97 (2003).
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Exp. Dermatol. (1)

E. Dimitrow, I. Riemann, A. Ehlers, M. J. Koehler, J. Norgauer, P. Elsner, K. König, and M. Kaatz, “Spectral fluorescence lifetime detection and selective melanin imaging by multiphoton laser tomography for melanoma diagnosis,” Exp. Dermatol.18(6), 509–515 (2009).
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Exp. Neurol. (1)

L. J. Chamberlain, I. V. Yannas, H. P. Hsu, G. Strichartz, and M. Spector, “Collagen-GAG substrate enhances the quality of nerve regeneration through collagen tubes up to level of autograft,” Exp. Neurol.154(2), 315–329 (1998).
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IEEE Eng. Med. Biol. Mag. (1)

H. C. Gerritsen, J. M. Vroom, and C. J. de Grauw, “Combining two-photon excitation with fluorescence lifetime imaging,” IEEE Eng. Med. Biol. Mag.18(5), 31–36 (1999).
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E. K. Rofstad, “Microenvironment-induced cancer metastasis,” Int. J. Radiat. Biol.76(5), 589–605 (2000).
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J. McGinty, K. B. Tahir, R. Laine, C. B. Talbot, C. Dunsby, M. A. Neil, L. Quintana, J. Swoger, J. Sharpe, and P. M. French, “Fluorescence lifetime optical projection tomography,” J Biophotonics1(5), 390–394 (2008).
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Supplementary Material (4)

» Media 1: AVI (2009 KB)     
» Media 2: AVI (1671 KB)     
» Media 3: AVI (1414 KB)     
» Media 4: AVI (1390 KB)     

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Figures (11)

Fig. 1
Fig. 1

Temporal focusing wide-field (TFWF) FLIM/PLIM design. (a) Optical sub-system: temporal focusing widefield multiphoton microscopy, (b) Electronic sub-system: frequency domain lifetime measurement via heterodyne detection.

Fig. 2
Fig. 2

Demonstration of accurate measurement of fluorescence lifetime of Rhodamine B solutions in different solvents by TFWF FLIM. Fluorescence in water was used as a reference. (a) Tabulated results of estimated lifetime values of τ extracted from either phase (Ph) or modulation (Mod) measurements. Literature values are also included as a reference [33]. (b) Lifetime resolved data for each pixel from the fluorescein (FL) and rhodamine solution images shown in polar plot format.

Fig. 3
Fig. 3

(a) An intensity scaled mean lifetime image of fixed fibroblasts with vacuoles loaded with endocytosed conjugated polymer nanoparticles of high two-photon absorption cross section. Color scale represents pixel lifetime values corresponding to the color bar with units of seconds. Image brightness represents pixel intensity values. Black regions are ignored in analysis corresponding to locations with intensity below 500 photons that are mostly outside the boundary of this cell. (b) Representative polar plot of pixel lifetime values for 10 ms data acquisition time. (c) Tabulated mean lifetime values and their standard deviations are estimated from the modulation or the phase data for four different image acquisition rates.

Fig. 4
Fig. 4

Fluorescence lifetime imaging of an ex vivo histological sample by TFWF FLIM. (a) Intensity-scaled fluorescence lifetime-resolved image of a regenerated ex vivo rat sciatic nerve after injury stained with FluroMyelin Green. The image field of view is approximately 20 × 20 μm2 (a) and 100 × 100 μm2(c). Scale bar has units of seconds. (b) Polar plot representation of the pixel lifetime estimated based on the phase data. (c) A larger view of the same sample acquired using a point scanning two-photon microscope equipped with TCSPC lifetime resolved imaging system. The scale bar has unit of nanoseconds. The lifetime measurements for both systems are in excellent agreement.

Fig. 5
Fig. 5

Demonstration of fast 3D-resolved lifetime imaging by TFWF FLIM system. (a) Intensity scaled lifetime images of 15 μm yellow-green beads and 4 μm red beads imaged at different axial plane locations z. Pixel lifetimes were estimated from modulation data. The scale bar represents 5 μm in length. (b) Representative polar plot of pixel lifetime information at z = 15 μm.

Fig. 6
Fig. 6

Fluorescence lifetime imaging of human fibroblasts seeded inside a collagen scaffold double-stained with Calcein AM and Syto 13 by TFWF FLIM. (a) Intensity scaled lifetime images. (b) Polar plot of fibroblasts labeled only with Calcein AM. (c) Polar plot of fibroblasts labeled with both Calcein AM and Syto 13. (d) Polar plot of fibroblasts labeled only with Syto 13.

Fig. 7
Fig. 7

Fast measurement of partial oxygen pressure by TFWF phosphorescence lifetime imaging. (a) Polar plot of phosphorescence lifetime of 1 mM Tris(2,2′-bipyridyl)dichlororuthenium(II) hexahydrate solutions equilibrated with 0, 4, 8, and 21% pO2 gas mixtures. Inverse phosphorescence lifetimes ((b), from modulation data; (c), from phase data) are plotted against O2 concentration demonstrating Stern-Volmer dependence with R2 values of 0.99 and 0.95 respectively for linear regression.

Fig. 8
Fig. 8

Uncertainty in estimating the lifetime of 1mM TDRT solutions depends on the image integration time. (a) TDRT phosphorescence lifetime measurement uncertainties (FWHM) for images acquired with different integration times are plotted against the average number of photons contained in these images. (b) Representative polar plots of TDRT solution pixel phosphorescence lifetime measurements at integration times of 1.5, 3, and 6 sec.

Fig. 9
Fig. 9

Fast 3D-resolved TFWF PLIM in sample consisting of human fibroblasts stained with Rhodamine DHPE, seeded inside a collagen matrix and treated, in PBS buffer containing 1 mM TDRT ruthenium-based oxygen sensor. PLIM Images were acquired at 300 kHz modulation frequency. In sequence from left to right: intensity image, phosphorescence lifetime-resolved image from phase data, phosphorescence lifetime-resolved image from modulation data. On the far right is the polar plot of the pixel phosphorescence lifetime-resolved measurements. The pixel lifetime data in the polar plot distributes between the ruthenium phosphorescence lifetime that lies close to the universal circle and the rhodamine fluorescence lifetime at the lower right hand corner corresponding to an effective zero lifetime for 300 kHz modulation frequency. PLIM Movie sequences corresponding to phase and modulation lifetime measurements throughout a 3D matrix are included (Supplementary material Media 1, Media 2).

Fig. 10
Fig. 10

Representative single plane intensity scaled lifetime-resolved image measured at a modulation frequency of 300 kHz.

Fig. 11
Fig. 11

Fast sequential 3D-resolved TFWF FLIM and PLIM imaging of human dermal fibroblasts seeded in a collagen scaffold. Representative images of the fluorescence component emitted by Rhodamine DHPE (top), and the phosphorescence component, emitted by TDRT ruthenium-based oxygen sensor (bottom), of the signal emitted from a single 3D resolved plane. 3D resolved image stacks of these two components can be seen in accompanying movie sequences (Media 3, Media 4)

Equations (5)

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Δφ=tan(ωτ) and M= 1 1+ ω 2 τ 2
pr δ f 2 τ ( P N ) 2
1 τ p O 2
N δ Prτ p 0 f
r N Nf δ Prτ p 0

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