2.1.

Experimental Setup

The experimental noncontact FMT setup used [Fig. 1(a)] employed a continuous-wave argon-ion laser source (LaserPhysics, Reliant 1000m, West Jordan, Utah) emitting at 457, 488, and 514 nm and enclosed in a custom-built aluminum chamber coated in antireflective black coating (deep black optical paint, Gerd Neumann, Hamburg, Germany). The source was directed across three fixed mirrors (High Energy Argon-Ion Laser Mirrors, Edmund Optics, Barrington, Illinois) and a UV–NIR neutral density filter (Edmund Optics) into the FMT chamber and onto an optical scanner employing galvo-mirrors (Scanlab, SCANcube 7, Munich, Germany). Incident light power was measured before entering the optical scanner using a laser power meter (PH100-Si-OD2, Gentec Electro-Optics). The setup was designed to operate in both transmission and reflection geometries by repositioning a mirror (First Surface mirror, Edmund Optics) mounted on a travel linear translation stage (Edmund Optics). The sample holder was mounted on an electronically controlled $x-y-z$ positioning stage (Standa, Vilnius, Lithuania). A custom-built filter wheel accommodating up to five filters was aligned to a 50 mm Macro $\mathrm{f}/2.8$ objective (SIGMA Corporation, Tokyo, Japan). Light collection was performed using a $510/10$-, $540/40$-, $593/40$-, or $615/90\text{-}\mathrm{nm}$ interference bandpass filters (Andover Corporation, Salem, New Hampshire) to isolate fluorescence from excitation light. A 16-bit, $1024\times 1024\text{pixel}$ charge-coupled device (CCD) (DV 434, Andor Technology, Belfast, Northern Ireland), thermoelectrically cooled down to $-65°\mathrm{C}$, was used for the detection of signals. The lens was focused on the surface of the sample, and the image scaled from pixel dimensions to metric units by the use of metric fiducials. Stage calibration was performed to convert the CCD field of view to degrees of rotation of the galvo-mirrors. For all experiments, an image was obtained with white light illumination before exposure to the laser source and was used as a reference image for source pattern selection. Additionally, a background image in the absence of an illuminating source was acquired to account for any external light entering the FMT chamber. Illumination sources were distributed symmetrically to the target location for both reproducibility and calibration experiments. Exposure time used was 0.2 s with 0.8 mW excitation power. Identical source/detector parameters were used for the fluorophores Atto590 (excitation max 594 nm, emission max 624 nm; ATTO-TEC Gmbh, Germany) and carboxyfluorescein succidimyl ester (CFSE) (excitation max 492 nm, emission max 517 nm; Thermo Fisher Scientific Inc.) placed in a 2-mm capillary glass tube in a phantom at a depth of 3 mm from the surface. A slab geometry phantom was used with a combination of 20 ppm India ink and 1% Intralipid-20% to match tissue-like optical properties at 520 nm (scattering coefficient ${\mu }_{\mathrm{s}}=16{\mathrm{cm}}^{-1}$ and absorption coefficient ${\mu }_{\mathrm{a}}=0.3{\mathrm{cm}}^{-1}$) and at a depth of 12 mm. An isoflurane vaporizer was used to deliver anesthetic to the FMT chamber and to the induction chamber, and a scavenging system was used to remove excess anesthetic gas (Fluovac systems, Harvard Apparatus, Hollison, Massachusetts).

Fig. 1

Horizontal noncontact FMT imaging system. (a) The FMT setup is illustrated, where the argon-ion source directs the beam into the FMT chamber via two fixed mirrors and into a scan cube that directs the beam via galvo-mirrors onto different user-selected source positions on the sample. The laser source can be directed onto the sample in reflection or transmission geometry by the use of a sliding mirror. Light is collected by a CCD camera, where wavelength is selected by the use of bandpass filters placed on a filter wheel. The data are recorded by a PC. The FMT imager was used to image a phantom containing a glass capillary tube filled with $10\text{-}\mu \mathrm{M}$ CFSE. (b) 3-D reconstructed image of the capillary tube was obtained with 100 iterations; the tube was clearly visible and geometrically correctly reconstructed. (c) The $x-y$ plane showed the reconstructed tube in line with its true location, visible in the background image, and 2 mm below the surface. (d) The $y-z$ plane and (e) $x-z$ plane images demonstrated that the FMT software correctly reconstructed the tube as a cylindrical object with a homogeneous fluorescent signal.

2.2.

Tomographic Data Acquisition and Reconstruction

Tomographic imaging was performed by scanning the laser source into selected illumination points.²³ The optimum excitation source pattern found for the tomographic scans was an $8\times 8$ grid covering a field of view of $12\times 12\mathrm{mm}$. For each illumination point, two measurements (excitation and emission) were recorded sequentially with the appropriate bandpass filters placed in front of the CCD. An image stack was created for all illumination points creating two sets of raw data (excitation and emission). Excitation and emission stacks were then resampled to a $14\times 14$ detector grid covering the target area and used for the tomographic reconstructions. Data from the excitation and emission stacks were used to create the normalized Born ratio¹⁸ as shown in the following equation:

Table 1

Comparative statistical analysis for quantification experiments in reflection (R) and transmission (T) modalities. Phantoms with increasing concentrations of CFSE and Atto590 were imaged with the FMT and emission quantified for each dataset. The correlation between the linear regression model used and the experimental data points is illustrated by the R2 and SDM values. The slope values were used as means to compare reproducibility between modalities. Increasing the number of iterations from 100 to 1000 marginally improves the fits (bold) and the slope. Small differences in slope values can be noticed between reflection and transmission experiments, indicating that a quantitative comparison of values between modalities is possible but may be affected by the intensity range.

2.3.

Fluorescence Molecular Tomography Calibration

Fluorophore quantum yield (QY) defines the efficiency with which absorbed light is converted to emitted light. Published QYs, however, are recorded at excitation and emission maxima. Such conditions often fail to match experimental conditions due to the wavelengths available and also because experimentally the QY is affected by concentration range and solvent properties. Commercial QY values therefore could not be used for FMT imaging calibration; we used the linear quantification data from CFSE and Atto590 to calculate the FMT-fluorescence yield (FMT-FY) described for our samples and experimental parameters. A plot of FMT-recorded intensities ($F$) ($y$-axis) against measured sample absorbance $A$ ($x$-axis) (FluoroMax, Jobin Yvon, Horiba Scientific, Kyoto, Japan) was obtained by multiplying the known fluorophore concentrations ($c$) by their published extinction coefficient values ($ϵ$) and measured light path length ($l$) following Beer–Lambert’s law:

The absorbance values were then plotted and fitted to a linear regression model, as shown in Fig. 2. The slope of the fits ($m$) is proportional to the QY of the fluorophore, where $b$ is the intercept on the $y$-axis:

FMT-FY values were calculated using a standard (st) solution as reference; ${\mathrm{FMT}\text{-}\mathrm{FY}}_x$ is thus always expressed as relative to $\mathrm{FMT}\text{-}{\mathrm{FY}}_{\mathrm{st}}$ as follows:

The calculated FMT-FY for CFSE and Atto590 was

The ratio of the calculated FMT-FYs ($\phi$) was then compared with the ratio between the slopes ($m$):

Fig. 2

FMT calibration. FMT-FY was calculated by converting CFSE and Atto590 concentrations into absorbance values. FMT intensity values were plotted against measured absorbance value ($A=ϵ*c*l$) for four concentrations of (a) CFSE and (b) Atto590. The points were fitted to a linear regression model, and the slope and intercept points were used to calculate the relative FMT-FY value.

The calculated slopes were proportional to the FMT-FYs and consequently to the fluorophores’ QYs (within 10% error). The linear relationship between fluorescence emission intensity and concentration [Eq. (4)] therefore becomes:

Table 2

Conversion table. The molar concentrations of CFSE and Atto590 used and the intensity values (a.u.) recovered from the 3D-FMT data analysis are shown. FMT concentration values represent the converted a.u. units to molarity obtained by the FMT calibration step.

2.4.

Cell Culture

Stable HeLa cell lines expressing enhanced yellow fluorescent protein (EYFP), super green fluorescent protein (SGFP), enhanced green fluorescent protein (EGFP), Katushka,²⁹ or Cardinal³⁰ red fluorescent protein were generated and characterized as described by Weidenfeld et al.²⁶ In brief, HeLa Tet-ON advanced cells (line EM2-11ht) were stably transfected with DNA coding for the fluorescent proteins under control of a tetracycline/doxycycline inducible promoter (Ptet). The gene of interest was stably integrated into a defined genomic locus (5q31), which allows tight regulation of the doxycycline-inducible expression. Constructs were inserted by Flippase Recombinase-Mediated Cassette Exchange (Flp-RMCE), and clonal lines were isolated. The expression characteristics of the derived cell lines were directly comparable as the transgenes were directionally integrated as single copies at the same locus. HeLa cells were cultured in DMEM supplemented with 10% FBS, 2 mM glutamine, and 1% penicillin/streptomycin. Expression of SGFP, EGFP, EYFP, Katushka, or Cardinal was induced by doxycycline, supplied to the media at $200\mathrm{ng}/\mathrm{ml}$. For FMT imaging of HeLa monolayers, 24-well tissue culture plates were used.

2.5.

Animals

Rag1−/−,^31,32 CD2,³³ and DsRed³⁴ transgenic animals were maintained in the Institute of Molecular Biology and Biotechnology colony. For the FMT imaging, the animals ($n=4$) were anesthetized with 1.5% isoflurane, initially delivered at 2.5% in a tranquilizing chamber. Temperature and breathing of each animal were monitored during the experimental procedure. Mesenteric nodes (MNs) were detected after feeding the mice for 2 weeks with alfalfa-free food (Labdiet), and hair was removed using depilatory cream. All animal experimental protocols were conducted in accordance with and under the approval of the Foundation for Research and Technology Ethics Committee and the General Directorate of Veterinary Services, Region Crete (permit numbers: EL 91BIO-02 and EL91-BIOexp-02).

2.6.

Cell Culture Experimental Protocol

A 24-well cell culture plate containing HeLa-wt and stable HeLa clones expressing either EGFP, EYFP, SGFP, Katushka, or Cardinal ($n=3$) was imaged using a two-dimensional (2-D) raster scan, ensuring homogeneous excitation across samples. The EGFP-, SGFP-, and EYFP-positive cells were excited using the 488-nm laser line, and emission was recorded with $510/10$-nm and a $540/40\text{-}\mathrm{nm}$ filters. Katushka- and Cardinal-positive cells were excited with the 514-nm laser line, and $593/40$-nm and $615/90\text{-}\mathrm{nm}$ filters were used for emission. SGFP-positive cells were measured with all filter sets. To mimic the high absorbance, freshly heparinated mouse blood was added to the culture wells to a final concentration of 12% (assuming a molar extinction coefficient of 24202.4 [${\mathrm{cm}}^{-1}/(\text{moles}/\mathrm{L})$] at 520 nm, matching ${\mu }_{\mathrm{a}}=16{\mathrm{cm}}^{-1}$). ROI areas (identical for all samples) corresponding to the width of the wells were used to quantify FP emission. The data were normalized for filter width, excitation, and emission wavelength and for cell number. Fluorimeter data were experimentally measured for each population at $1\times {10}^6\text{cells}/\mathrm{mL}$.

2.7.

In Vivo Experimental Protocol

Initially, a 2-D scan was performed on each animal to locate the target LN using 514-nm excitation and $615/90\text{-}\mathrm{nm}$ emission (1 mW excitation power and 6 s exposure time). These images were used to determine the scan pattern position: a $10\times 10$ source grid was chosen to cover a wide field of view ($2\times 2\mathrm{cm}$) with 25 mW excitation power and 0.2- to 0.6-s exposure time for the superficial and deep targets, respectively. Tomographic data were recorded using 514-nm excitation with $615/90$-nm and a $690/30\text{-}\mathrm{nm}$ emission filters for fluorescence measurement and a $510/10\text{-}\mathrm{nm}$ filter to measure the excitation field. The data were processed with in-house developed software using a $10\times 10$ detector pattern.

3.1.

In Vitro Quantification

In order to assess the capabilities of the FMT system, a set of experiments was designed to address its sensitivity, dynamic range, and resolution. Each query was dependent on the SNR and was therefore application dependent. Given that the optical properties of the fluorescent object of interest and its immediate surroundings significantly affected the SNR, each experiment here reported was acquired using settings where the SNR was experimentally maximized. A typical 3-D-reconstructed image is shown in Fig. 1. The FMT imager was tested in reflection and transmission geometry modes at different wavelengths. Initially, response was assessed with phantoms containing 2, 4, 8, and $10\mu \mathrm{M}$ of CFSE in reflection geometry. To compare the quantification accuracy at different spectral regions, CFSE was replaced with Atto590. Atto590 has a high molecular absorption and a high QY (0.80); however, the 514-nm source achieved approximately 10% excitation efficiency. This resulted in a 60% weaker Atto590 emission compared with CFSE (excitation max 489 nm). Atto590 concentrations (5, 10, 15, and $20\mu \mathrm{M}$) were chosen to match the intensity range used for CFSE. Similarly, a set of experiments assessed the quantification capabilities of the FMT imager in transmission geometry. Quantification of mean intensity values in transmission geometry was achieved using the same reconstruction and ROI parameters used for reflection and were therefore directly comparable. The results from the quantification analysis for CFSE and Atto590 in reflection and transmission modes (Fig. 3) were fitted to a linear regression model (Table 1). The quantification data showed the reconstructed fluorescence mean intensity values to be linearly proportional to fluorescence concentration.

Fig. 3

Quantification of FMT fluorescent signal in reflection and transmission modalities at different wavelengths. Increasing concentrations of (a) CFSE and (b) Atto590 were measured; fluorescence was detected using the FMT imager in reflection (black) and transmission (red) modalities. The mean intensity values for each experiment were then plotted against the known concentration values and fitted to a linear model. $R^2>0.98$ for all fits (Table 1).

3.2.

In Vitro Reproducibility

The FMT imager’s reproducibility was then assessed by designing a set of in vitro experiments carried out in reflection geometry using $2\text{-}\mu \mathrm{M}$ CFSE. Data acquisition, processing, ROI selection, and quantification were obtained (excitation 488 nm, emission $540/40\mathrm{nm}$; $8\times 8$ source/detector pattern, 100 iterations) for four independent measurements performed as technical repeats. Reproducibility was assessed by standard deviation of the mean (SDM) and standard error of the mean (SEM), $1.61334\times {10}^{-5}$ and $8.0667\times {10}^{-6}$, respectively, 2 and 3 orders of magnitude smaller than the mean (0.00204 a.u.), with a coefficient of variance of 0.00792 indicating a systemic error $<0.8\%$. Conversion using the calibration factor in Eq. (4) recovered a value of $2.69\mu \mathrm{M}$.

3.3.

Optimal Fluorescent Protein Selection for Fluorescence Molecular Tomography

The intrinsic properties of fluorescent proteins dictate whether or not they are suitable for an application; however, these are seldom explicitly tested. The relative intensities of the emission displayed by identical numbers of HeLa cells expressing YFP, SGFP, EGFP, Katushka, or Cardinal were obtained by quantifying the mean FMT reconstructed values. The mean intensity values recorded [Figs. 4(a) and 4(b)] were corrected for filter width. These normalized data give a more accurate intensity value for each fluorophore considered; more precisely, they represent a weighted average across the filter wavelength range.

Fig. 4

Fluorescent protein emission comparison. A 24-well cell culture plate, each containing $1\times {10}^6\text{cells}$ expressing EGFP, SGFP, SYFP, Katushka, and Cardinal, was imaged using the FMT imager with or without addition of 12% heparinated blood. Excitation was performed using 488- and 514-nm laser lines, and fluorescence was recorded with $510/10$-, $540/40$-, $593/40$-, and $615/90\text{-}\mathrm{nm}$ filters. (a) Intensity values for each fluorophore were recorded with the optimal filter combination. The intensity values for red emitters are expanded in (b); SGFPRed indicates SGFP-expressing cells detected with the red filter for comparative purposes. The intensity values were normalized to take into account the fluorophore-specific excitation/emission efficiency. The measured normalized values (Norm) and calculated potential values (Pot) are shown for the (c) green and (d) red channels.

For increased spectral resolution, a dedicated spectral imager² would be required. Green emitters were approximately 1 order of magnitude brighter than red emitters. The data were further corrected for the “excitation efficiency” term achieved by the available laser lines (488 and 515 nm). To address the nonlinear relationship between excitation wavelength and emission intensity, the values were corrected by an experimentally defined “efficiency factor” as follows:

${\mathrm{Ex}}_{\max }$, ${\mathrm{ex}}_{488}$, and ${\mathrm{ex}}_{515}$ intensity values were obtained using a fluorimeter, where spectral data were measured using each cell line. Figure 4 shows how, even by exciting at the excitation peak, red emitters still display weak emission and GFP emission is still clearly detectable using a $>600\text{-}\mathrm{nm}$ filter. The data were then corrected for the “emission efficiency” achieved: the emission spectral profiles obtained for the cells were used to calculate the integrals for the whole emission curve and, separately, the integrals for the wavelengths covered by each filter used to image the sample with the FMT as follows:

The ratio of the “whole emission curve”/“detected emission” represents the portion of fluorescent signal actually detected by the FMT:

The “corrected” values [Figs. 4(c) and 4(d), dashed lines] represent the achievable values by exciting the fluorophores at their excitation maximum and detecting the whole of the emission curve. A final correction that could be made to these values is defined by the QY. This correction should, in theory, equalize the values for the different fluorophores at identical concentrations. Unfortunately, QY information for the specific fluorescent proteins used here was unavailable at the time of writing.

3.4.

In Vivo Small Animal Imaging

LNs represent highly desirable targets for in vivo imaging due to their functional importance to the immune system. An immune response is in fact a localized process with LNs acting synergistically while remaining independent from one another. To test whether the FMT could resolve fluorescence from anatomically diverse LNs, the inguinal and mesenteric LNs of a CD2/DsRed mouse were targeted. The inguinal LN is located subcutaneously at the height of the groin, while the MNs are found bunched (usually five to six nodes) deep within the mesentery of the intestine. Figure 5 shows the raw fluorescence data (a) and the 3-D reconstructed image (b) for the right inguinal LN of a CD2/DsRed mouse. The FMT software correctly located the origin of the fluorescent signal, and the reconstructed image matched the dimensions and anatomical conformation of the inguinal LN. The mesenteric LNs of a CD2/DsRed and a nonfluorescent control mouse were then targeted (Fig. 6). The morphology and location of the MNs make target recognition a difficult task; however, the DsRed-positive reconstructed image displayed three times as much fluorescent signal than the control sample. The bright autofluorescent object visible in both the control and DsRed animals was identified ex vivo as the gallbladder. The DsRed signal located at 0.5 to 1 cm below the gallbladder is consistent with the MNs.

Fig. 5

Subcutaneous localization and FMT rendering of the inguinal LN of a CD2/DsRed mouse. (a) Fluorescence tomography raw data (514 nm excitation; $615/90\mathrm{nm}$ emission), and (b) FMT 3-D reconstruction shows how the rendering process correctly localizes the shape and location of the LN.

Fig. 6

FMT localization and rendering of the mesenteric LNs of a CD2/DsRed mouse. 2-D homogeneous illumination images of the ventral area of (a) a CD2/DsRed and (c) a control mouse show the spatial spread of fluorescent and autofluorescent objects. The area delimited by the red boxes represents the area selected for the 3-D FMT rendering (b and d) for each mouse. The difference in anatomical location of nontarget autofluorescent objects illustrates the challenges faced in the FMT reconstructions.