Noninvasive optical methods for measuring tissue concentrations of endogenous and exogenous substances have several benefits over invasive techniques. Most importantly, optical concentration measurements allow nondestructive in vivo monitoring of drug pharmacokinetics at various tissue sites.1, 2, 3, 4, 5 Two different sources of optical contrast are routinely used for target compound concentration measurements in tissue: absorption and fluorescence.
Methods based on absorption (reflectance) spectroscopy have the advantage that the measurement setup is relatively simple compared to fluorescence measurements. A typical setup consists of a fiber-optic probe, a broadband light source, and a spectrometer. The signal analysis is based on attenuation of elastically scattered light. Integration times are generally small, which enables measurements in the presence of ambient lighting (e.g., endoscopic illumination) and allows continuous measurements with a high temporal resolution. The optical contrast depends on the product of path length and target compound absorption coefficient, where the latter is the product of molar extinction coefficient and concentration. This implies that the absorption contrast might become too low for accurate concentration measurements for short path lengths, small molar extinction coefficients, and small target compound concentrations. An additional problem arises when the absorption band of the target compound overlaps the absorption bands of highly absorbing endogenous chromophores such as blood. In that case, the attenuation of the scattered light due to blood might prevent accurate concentration estimates of the target compound as well.
For most fiber-optic measurement geometries, the optical path length depends on the scattering coefficient and on the absorption coefficient of the tissue. Since and both vary significantly in tissue, quantitative measurements prove to be difficult in tissue unless specific fiber-optic measurement geometries are chosen. For example, the optical pharmacokinetics spectroscopy (OPS) system developed by Mourant 1 uses elastic scattering spectra of tissue to calculate the concentration of chromophores in tissue using a fiber-optic probe with a source–detector separation of . The separation of was chosen to minimize the path length dependence of the collected photons on scattering properties of tissue. For scattering parameters that are typical of tissue, the path length varies by less than 20% for a given background absorption. Another technique that features a known path length is differential path length spectroscopy (DPS).6, 7, 8, 9 The path length of photons contributing to the differential reflectance signal varies by less than 20% over a very broad range of both scattering and absorption coefficients.6, 7 This facilitates quantitative concentration measurements even for strong variations in either background absorption or scattering. However, as explained earlier, chromophore concentration measurements based on attenuation of elastically scattered light rely on (small) differences between large amounts of detected light with and without the target chromophore present. Therefore, accurate measurement of small concentrations of chromophores or measurements of chromophores with low absorption coefficients are difficult. This is particularly true for DPS, for which the average path length of the measured photons is very small, approximately equal to the fiber diameter.6, 7, 8, 9 Moreover, for fluorescing compounds such as photosensitizers, the concentration can be underestimated due to the presence of fluorescence, induced by the lower wavelengths of the white-light source, in the reflection spectra.4 For example, Johansson 4 used the OPS technique to estimate m-THPC concentration in a nonmelanotic skin tumor model and found a factor 2 underestimation in m-THPC concentration when not accounting for the presence of m-THPC fluorescence.
In contrast, measurements based on fluorescence contrast rely on the induced fluorescence of the fluorescing compound. Furthermore, the dynamic range for measurements based on fluorescence contrast is much larger than for scattering (absorption) measurements since the fluorescence is measured at a different wavelength than the excitation (scattered) light. Therefore, fluorescence-based concentration measurements are more sensitive and better capable of measuring very low fluorophore concentrations simply by increasing the integration time. However, there exists a complex relationship between the concentration of a chromophore and its absorption cross section and fluorescence emission intensity. In vivo fluorescence can be influenced by many factors that include changes in quantum yield induced by changes in the microenvironment,10 photobleaching,11 biological compartmentalization, and alteration in binding and aggregation.12, 13 In a turbid sample, the amount of fluorescence detected depends not only on the fluorophore concentration and quantum yield, but also on the scattering and absorption coefficients of the sample at the excitation and emission wavelengths. Various algorithms and measurement geometries have been developed to correct for the influence of tissue optical properties on a measured fluorescence spectrum. Photon migration techniques have been used to establish a general algorithm, applicable to any measurement geometry and for a broad range of scattering and absorption variations, to correct the measured fluorescence for the influence of tissue optical properties.14, 15 For this algorithm, the diffuse reflectance is measured in the same geometry as the fluorescence measurements and used to correct for differences in optical properties. However, elaborate probe-specific calibration procedures are required, and the correction algorithm itself is quite complex. Several other more simple correction algorithms based on specific probe geometries have been developed.16, 17, 18, 19 We have recently developed fluorescence differential path length spectroscopy (FDPS), which is based on the principles of DPS (the difference of two signals that contain the same contribution from long path length photons but different contributions from short path length photons, to obtain a well-defined, small measurement volume) but with the enhanced dynamic range of fluorescence measurements.5 The advantage of FDPS over other quantitative fluorescence measurements is its capability to deal with large variations in background absorption using a simple correction algorithm.
In this paper, we compare an optical concentration measurement technique based on quantitative fluorescence spectroscopy, FDPS, with chemical extraction.20 The photosensitiser m-THPC was chosen as the target chromophore to test the concept of FDPS in vivo. To test the strength of FDPS in vivo, we performed the measurements on highly absorbing tissue, the liver. Variations in m-THPC concentration in the liver are achieved by choosing different drug-light intervals based on the known pharmacokinetics of m-THPC in liver.21, 22 The distribution of m-THPC at the different time points within the liver was investigated using fluorescence microscopy.
Materials and Methods
Animal and Measurement Procedures
The experimental design for this study was approved by the animal experiment committee of the Erasmus MC. Two weeks before the start of the experiments, 25 normal adult male Wistar rats were placed on a diet of chlorophyll-free food to minimize the influence on autofluorescence centered at due to pheophorbide- . All rats were injected with m-THPC i.v., except for the control animals , which were injected with the solution (PEG400:ethanol:water, 2:3:5) not containing m-THPC. At either , , , or after injection ( animals per time point), the tissue overlying the liver was dissected, and optical concentration measurements were conducted on 10 randomly chosen positions across different lobes of the liver. Directly after the optical measurements, the main arteries and veins of the liver were clamped to minimize the loss of blood. The liver was then excised and snap-frozen in liquid nitrogen.
Concentration of m-THPC in the liver was measured in vivo using FDPS and ex vivo using chemical extraction. FDPS determines a concentration estimate based on the emitted photosensitizer fluorescence. Figure 1 shows a schematic diagram of the measurement setup. The concentration estimates measured by FDPS were compared to the concentration values determined by chemical extraction. Both methods, FDPS and chemical extraction, are described in more detail in the following sections.
The probe contained two fibers placed at minimum core-to-core distance, , in a specially adapted subminiature version A (SMA) connector. The SMA connector configuration ensured a reproducible fixed distance when calibrating the setup using a calibration lamp, as described elsewhere.5 The probe surface was polished under an angle of to minimize specular reflections at the probe-medium interface during FDPS measurements. The delivery-and-collection (dc) fiber is coupled into a bifurcated fiber, which contains a delivery and a collection leg. The delivery leg is coupled into a bifurcated fiber, of which one end is coupled into a xenon light source (HPX-2000, Ocean Optics, Duiven, The Netherlands) and the other end to a argon laser (Spectra Physics, Eindhoven, The Netherlands). The collection leg is also coupled into a bifurcated fiber, of which one end directly leads to the first channel of a temperature-regulated four-channel spectrograph setup (MC-2000-4-TR2, Ocean Optics, Duiven, The Netherlands) and the other end leads to a filter block containing a long-pass filter before being coupled into the second channel of the spectrograph. The collection (c) fiber is coupled to a bifurcated fiber, of which one end directly leads to the third channel and the other is again first filtered by the same long-pass filter before being coupled in the fourth spectrograph channel.
Tissue extraction was performed according to the chemical extraction method recently described by Kascáková 20 This is a modification of the original method described by Lilge 23 In short, small liver tissue samples ( or ) were randomly acquired from the liver. Note that we did not attempt to colocate the optical measurement sites with the tissue extraction sites. Instead, we avoided complicated experimental procedures associated with colocating the sites by averaging multiple random locations in both the optical and chemical concentration measurements. The liver samples were dissolved in of the ready-to-use tissue solvent Solvable™ (Perkin Elmer, Groningen, The Netherlands), which is a mixture of dodecyldimethylamine oxide (2.5 to 10%), secondary alcohol ethoxylate (2.5 to 10%), and sodium hydroxide in water. Subsequently, the tissue sample in Solvable was placed in a water bath of and agitated regularly for . The solubilized liver solution was then diluted with Solvable to an , to minimize absorption artifacts and to ensure homogenous illumination of the sample in path length quartz cuvettes in a fluorimeter (Perkin Elmer, Groningen, The Netherlands). The diluted samples were analyzed by using an excitation wavelength of (corresponding to the wavelength at which m-THPC in 100% Solvable absorbs the most20) and a spectral detection band of with a resolution of .
Frozen tissue samples of control and m-THPC administered animals were handled under subdued light conditions. Liver sections of thickness were sectioned and mounted on glass slides (Menzel, Braunschwig, Germany). Fluorescence images were acquired at a using a CCD camera (ORCA-ER, Hamamatsu, Herrsching am Ammersee, Germany) mounted on a fluorescence microscope (Leica, Leiden, The Netherlands) equipped with an N2.1 filter block with an additional bandpass detection filter, .
Before every measurement, the FDPS system was calibrated as described previously.5 A differential reflectance spectrum (DPS) is obtained by subtracting the spectral signal from the c-fiber, which collects long path length photons only, from the dc-fiber, which collects photons of both long and short path length. Hence, the differential spectrum contains the spectral contribution from short path length photons only. Differential reflectance spectra were fitted according to the following model6, 7, 8, 9, 24:and and wavelength dependencies and , respectively. Here, is a normalization wavelength where the signal is predominantly dependent on scattering, which we usually set to . is the fiber diameter , is the blood volume fraction, is the microvascular blood oxygenation, is the absorption coefficient of fully oxygenated whole blood, and is the absorption coefficient of fully deoxygenated whole blood.25 is a correction factor that accounts for the inhomogeneous distribution of blood in tissue and depends on the vessel diameter , and is a correction factor that accounts for the absorption dependence of the path length for highly vascularized tissue such as liver.26 A differential fluorescence spectrum is obtained by subtracting the fluorescence spectral signal measured by the c-fiber from the fluorescence spectral signal measured by the dc-fiber. The measured differential fluorescence signal is corrected for absorption by multiplying by the ratio of the reflectance at the excitation wavelength without and with absorption present, as follows5: and are the differential reflectance signals at the excitation wavelength measured with and without background absorber present, respectively. is the DPS signal at the excitation wavelength measured in vivo. The DPS signal at the excitation wavelength without absorption present, , cannot be measured, but is calculated from the fit of the in vivo DPS spectrum to Eq. 1, using the best estimates of the parameters and setting the exponent for the exponential term to 0. It was previously shown that the differential fluorescence signal is relatively insensitive to variations in scattering,5 and consequently no corrections were performed to account for scattering differences between tissue samples. The absorption-corrected FDPS spectra were analyzed as a linear combination of basis spectra and fitted using a singular value decomposition (SVD) algorithm.24, 27 The fluorescence was described by a combination of autofluorescence and m-THPC fluorescence. Basis spectra for these two components were extracted from spectra acquired in vivo. The autofluorescence basis spectrum is the normalized average of the control animals. For m-THPC, a basis spectrum, based on the spectra acquired in vivo corrected for the autofluorescence, is determined for each of the four time points to account for possible spectral changes in m-THPC fluorescence due to changes in environment and/or binding.
Fluorescence spectra acquired by the fluorimeter could be described as a linear combination of autofluorescence, Solvable fluorescence, and m-THPC fluorescence. The Solvable fluorescence basis spectrum was measured in the fluorimeter using pure Solvable. m-THPC was dissolved in Solvable and measured in the fluorimeter; the basis spectrum for m-THPC was acquired by subtracting the Solvable component. Last, the autofluorescence basis spectrum is the normalized average fluorescence spectrum of spectra acquired from dissolved liver samples of control animals after subtraction of the Solvable component. The absolute m-THPC concentration of the liver samples was derived from a calibration curve, which was constructed from measurements of known m-THPC concentrations mixed with dissolved control liver samples in Solvable.20
Statistics and Correlation
Confidence intervals on the individual parameters for the individual measurements were determined based on the covariance matrix generated for each fit as described by Amelink 28 Differences between groups were determined using the nonparametric Mann-Whitney test.
Figure 2 shows the data and fit for the three spectra acquired per animal for the different methods: DPS, FDPS, and chemical extraction. Figure 2a shows a typical differential reflectance spectrum acquired in vivo from rat liver with its fit and residual between fit and data from an animal after m-THPC injection. Figure 2b shows the fit of a differential fluorescence spectrum acquired in vivo under excitation of the rat liver after m-THPC injection. In addition to the fit and residual between fit and data, the individual components are also shown. Figure 2c shows a typical fluorescence spectrum and its fit and the individual components (m-THPC, autofluorescence, and Solvable fluorescence) of extracted liver tissue after m-THPC injection measured using the fluorimeter at excitation.
Figure 3 shows the m-THPC component of the absorption-corrected FDPS fluorescence versus the actual m-THPC concentration determined with chemical extraction. For the control animals, the FDPS spectrum was fully described by the autofluorescence component with negligible contribution from the m-THPC component, as expected. The smallest nonzero amount of m-THPC fluorescence (measured at the time point) corresponded to an actual m-THPC concentration of . Fitting a straight line forced through the origin shows an value of 0.87. Every measurement point represents the average of multiple fluorescence measurements at randomly chosen locations on the liver in a single animal. For these animals, the average blood volume fraction, measured with DPS, was . The two most prominent average deviations from the straight line, indicated by arrows and in Fig. 3, had an average blood volume fraction of and , respectively. Furthermore, all animals in the group are above the regression line in Fig. 4 . The three animals within this group that deviate from the regression line by more than one times the standard deviation show an increased blood volume fraction compared to the total average blood volume fraction for all animals . These observations indicate a possible relationship between measured m-THPC fluorescence and blood volume fraction. In Fig. 4, therefore, we have plotted the m-THPC fluorescence intensity as a function of blood volume fraction for each animal. Indeed a strong correlation between m-THPC fluorescence and blood volume fraction is observed for the early time points, 3 and . A decrease in correlation coefficients between m-THPC fluorescence and blood volume fraction with increasing drug-light intervals is observed.
Another interesting feature to be noticed in Fig. 3 is the difference in standard deviations between FDPS intensity and m-THPC concentration determined through chemical extraction. The large standard deviations in FDPS intensity are caused by intra-animal variations in m-THPC fluorescence in the liver, most likely related to a heterogenous distribution of m-THPC on a scale resolved by the FDPS technique but averaged out in the extraction. Therefore, we investigated the m-THPC fluorescence distribution at the different time points in liver sections using fluorescence microscopy. Figure 5 shows representative fluorescence microscopy images at of liver sections for the 3-, 24-, 48-, and time points. The time point clearly shows intense clusters of m-THPC fluorescence randomly spread throughout the section. At , m-THPC fluorescence is measured in the whole section, and more intense m-THPC fluorescence is observed around the bigger vessels, which appear black in the image due to blood absorption. The animal shows similar m-THPC fluorescence distribution as on the time point, with the difference that the overall m-THPC fluorescence intensities are lower. The time point shows m-THPC fluorescence more evenly distributed throughout the section than on the other time points.
The aim of this study was to test the concept of optical concentration measurements based on quantitative fluorescence spectroscopy (FDPS) in vivo. We have chosen to validate the FDPS concentration measurements in an in vivo environment on highly vascularized and thus highly absorbing tissue (liver) using m-THPC as an exogenous chromophore. Different drug-light intervals were chosen based on the pharmacokinetics of m-THPC in the liver21, 22 to vary the in vivo tissue concentrations by an order of magnitude. FDPS concentration estimates for the different time points were compared with chemical extraction.
Based on our measurements, we found that FDPS is capable of measuring m-THPC concentrations as low as in the liver at the drug-light interval. We expect to be able to measure even lower concentrations by optimizing the setup and increasing the integration time. The measured m-THPC concentration with FDPS showed good linear correlation with the extracted m-THPC concentration, . The correlation coefficient could be improved to 0.96 when the outliers from the linear regression line in Fig. 3, identified as and , are omitted. However, these outliers yield important information about in vivo m-THPC localization. The animals with the two most prominent deviations from the straight line, indicated by arrows and , were shown to have blood volume fractions of and , respectively. These are significantly different from the average blood volume fraction of the m-THPC animals, . (The blood volume fraction of the control animals was , which is not significantly different from the m-THPC animals.) Based on this observation, we investigated the correlation between m-THPC concentration measured using FDPS and blood volume fraction. For the two shortest drug-light intervals, we found a strong correlation ( values of 0.97 and 0.98 for the 3-and drug-light intervals). For longer drug-light intervals, there was a decrease in the correlation between m-THPC fluorescence intensity and blood volume fraction. The drug-light interval dependence of the correlation between fluorescence and blood volume suggests that m-THPC is predominantly localized in or near the tissue vasculature for short drug-light intervals and less so for longer drug-light intervals. This is in agreement with a range of m-THPC pharmacokinetic studies in rats showing high concentrations of m-THPC in the plasma directly after i.v. injection, followed by an initial rapid exponential decrease followed by one or two exponential decays with lower elimination rates.21, 22
Another interesting observation is that the intra-animal variations in FDPS signals are up to a factor of 5 larger than those of chemical extraction. The source for these larger variations in FDPS concentration estimates is potentially related to (intra-animal) differences in tissue scattering, since the FDPS signal is dependent on scattering. The scattering dependence of the FDPS signal depends on the probe geometry. For an FDPS probe, it has been shown in a phantom study that within biological relevant scattering values, the FDPS signal can vary by a factor of 2.2 (Ref. 5). Since in these experiments the overall variation in the scattering parameter was small, 16%, it is safe to assume that scattering had no significant influence on the FDPS signal and hence does not contribute to the variation in the data, inter-or intra-individual. It is most likely that the differences in standard deviations between FDPS and chemical extraction are related to intra-animal variability in m-THPC concentration on a microscopic scale and are a result of the different interrogation volumes of the techniques. For chemical extraction, tissue samples of are used, whereas FDPS probes only of tissue [corresponding to the volume of a cylinder with a diameter equal to the fiber and height of half the path length ]. Fluorescence microscopy on sections at for the four different time points (Fig. 5) shows a heterogeneous m-THPC fluorescence distribution throughout the sections. This heterogeneous distribution of m-THPC is on a submillimeter spatial scale and can be picked up only by techniques that sample small tissue volumes. Obviously, the tissue volumes used for chemical extraction are too large to pick up this submillimeter spatial heterogeneity, and standard deviations in m-THPC concentrations are small since multiple regimes of high and low fluorescence are present in each individual tissue volume used for chemical extraction. However, the measured m-THPC fluorescence intensity using FDPS depends heavily on probe placement on the liver; some measurements will contain bright spots of fluorescence, and other measurements on the same liver will contain smaller amounts of m-THPC, leading to large intra-animal variations in fluorescence intensity.
The spatial m-THPC distribution in the liver at different time points using fluorescence microscopy [Fig. 5a] illustrates the wide variations in spatial distribution of m-THPC in rat liver after the administration of m-THPC. It is clear that the localization of m-THPC is not coincident with the whole liver vasculature and that depending on probe placement, the volume interrogated by our optical technique contains areas of very high or low m-THPC fluorescence intensities. The spatial distribution of m-THPC is likely to be dominated by the role of the liver in the elimination of m-THPC.29, 30 A number of studies have illustrated the complexity of m-THPC pharmacokinetics in vivo.21, 31, 32 These studies have shown the formation of m-THPC aggregates and the importance of binding to plasma proteins. Jones 21 postulated that m-THPC could disaggregate and redistribute to lipoproteins in the liver before further distribution to other tissues. It is therefore not surprising that m-THPC fluorescence is not homogeneously distributed within the liver vasculature after the administration of m-THPC. In the liver, we observe increased m-THPC fluorescence around the vascalature at both intermediate and long drug-light intervals ( and ). Note that m-THPC fluorescence is observed throughout the whole section, although in a lower intensity than around the vasculature.
Another important consideration is that the measured fluorescence signal by FDPS is the product of the photosensitizer concentration and the quantum yield. The quantum yield of a photosensitizer can change due to changes in environment and binding10, 12, 13 and might give a possible indication on(sub)cellular localization of the photosensitizer. We find a linear correlation between FDPS measured fluorescence and extracted concentration, which suggests that the quantum yield is relatively constant over the drug-light intervals that we have investigated. This observation is in agreement with the fact that we found only small differences in the shape of the basis spectra for different m-THPC drug-light intervals (data not shown). It seems that these binding effects are not sufficiently large to affect the m-THPC concentration estimate. We note that there may be subtle differences in quantum yield with respect to drug-light interval in the liver and that other organs might show significant variations in quantum yield. It should also be noted that steady-state fluorescence measurements are rather insensitive to the effects of binding and variations in quantum yield and that time-resolved spectroscopy would be much more appropriate to determine the magnitude of these effects.33, 34 The possible subtle differences in fluorescence quantum yield and the differences in scattering properties for different tissue types strongly suggest the necessity to determine a calibration curve (such as Fig. 3 for liver) for each tissue type separately. This is a topic currently under investigation.
In conclusion, we compared an optical concentration measurement technique based on quantitative fluorescence spectroscopy (FDPS) with chemical extraction in an in vivo model. FDPS showed good correlation with chemical extraction and an ability to measure m-THPC values as low as . Moreover, for short drug-light intervals, a correlation was observed between blood volume fraction and measured m-THPC fluorescence. A larger intra-animal variability was measured with FDPS compared to chemical exctraction due to its smaller interrogation volume and heterogenous distribution of m-THPC on the scale of the FDPS sampling volume.