2.1.

Phantom Design and Fabrication

2.1.1.

Experimental design

In Fig. 1(a), we show a pulsatile flow bioreactor developed for the preconditioning of a synthesized vascular graft.¹⁶ As shown in the figure, the vascular graft is enclosed in a sealed bioreactor and cannot be easily imaged using traditional optical imaging methods. Ultimately, we intend to use the scanning-fiber-based imaging method to assess lumen endothelialization, where a MIC is directly embedded into the scaffold wall as shown in Fig. 1(b). However, before applying this novel imaging method for any in vitro or in vivo studies, we need to first validate system performance through optical phantom studies.

Fig. 1

(a) A pulsatile flow bioreactor for in vitro incubation of bioengineered carotid artery scaffolds developed by one of the authors. Bioreactors often require a hermetically enclosed chamber that is incompatible with standard optical imaging methods. (b) A vascular scaffold embedded with a micro-imaging channel (MIC) for non-destructive, scanning-fiber-based imaging. (c) and (d) Depict design of a planar optical phantom that imitates a tubular carotid artery scaffold graft for future in vitro (no neck skin) or in vivo (with neck skin) studies. As shown in (c), an MIC is directly embedded within the wall of the scaffold. Through the MIC, we can deliver highly localized excitation light to a region of interest on scaffold lumen and generate a fluorescent signal. Part of the fluorescent signal is captured by an external detector for image reconstruction. (d) An optical phantom model was designed to mimic the experimental configuration in (c). The phantom is designed such that we can verify our fluorescence mapping results using the direct-line-of-sight images obtained by a control camera.

As illustrated in Fig. 1(c), fluorescent labeled ECs exist only on the innermost layer (i.e., lumen) of the tubular scaffold. Consequently, it is difficult to apply direct-line-of-sight optical microscopy to visualize luminal fluorophore distributions through the optically opaque scaffold. Yet in order to validate our imaging method, we need to compare the results obtained through fiber scanning with a common standard such as direct-line-of-sight microscopy. To resolve this quandary, we created an equivalent phantom by “flattening” the tubular vessel and converting it to a planar structure, as illustrated in Fig. 1(d). Because ECs cover only the innermost surface of a blood vessel, they will exist only on one side of the “flat” vessel surface, which is referred to as the “luminal” surface. Note that the objective lens and all other instruments required for scanning-fiber-based imaging should be placed outside of the animal body as indicated by the “detector” in Fig. 1(c) and 1(d). Hence we denote the surface opposite of the luminal surface as the “exterior” surface. With these considerations, the optical phantom used in this study is composed of a planar tissue scaffold with an embedded MIC, a piece of porcine skin, and multiple fluorophores placed on the luminal surface. With the configuration depicted in Fig. 1(d), we can easily obtain the direct-line-of-sight images as control images that accurately depict the distributions of fluorophores on scaffold lumen. Physical properties of the phantom such as scaffold porosity and optical coefficients were kept equivalent to the vessel scaffolds used for carotid artery engineering.¹⁷

The presence of the 3-mm thick porcine skin serves two purposes. First, it mimics in vivo conditions,¹⁸ where the presence of additional obstructive biological tissues, such as the skin of an animal, must be included in order to account for additional photon scattering and autofluorescence. Additionally, the porcine skin also enables us to evaluate the performance of our imaging system as we significantly increase imaging depth.

We used two types of fluorophores in our studies. To evaluate the resolution and depth dependence of the imaging system, we used 28-μm-diameter green fluorescent microspheres (FP-30052-5, Spherotech Inc., Lake Forest, IL) to simulate green fluorescent protein (GFP)-labeled ECs. For a preliminary live cell study, we used GFP-labeled ECs seeded on the luminal surface of a flat 500 μm thick scaffold.

2.1.2.

Scaffold fabrication

Electrospinning was used to fabricate a scaffold to construct the phantom.¹⁹ Briefly, bioabsorbable poly-(D, L-lactide) (PDLLA) ($M_w=80,000\mathrm{g}/\mathrm{mol}$, SurModics Pharmaceuticals, Birmingham, AL) was suspended in a $22\%\mathrm{w}/\mathrm{v}$ solution with a $3:1$ ratio of tetrahydrofuran:dimethylformamide (Fisher Scientific, Fair Lawn, NJ) under gentle stirring for 4 h. Next, the polymer solution was delivered at a flow rate of $5\mathrm{ml}/\mathrm{hr}$ through an 18 G blunt-tip needle attached to the end of a syringe. A 13 kV charge was then applied between the needle tip and a 2-in. diameter aluminum mandrel using a direct current power supply (Gamma High Voltage Research, Ormond Beach, FL). The mandrel was placed 10 cm away from the needle tip and set to rotate at a constant 60 rpm. The high voltage difference between the needle tip and the spinning mandrel drew the charged polymer solution towards the mandrel. The rapid evaporation of the solvent then generated thin strands of PDLLA polymer fibers ($\sim 1\mathrm{\mu m}$ in diameter), which formed a finely woven scaffold sheet on the spinning mandrel as shown up close by the SEM image in Fig. 2(a). Once the scaffold sheet reached its desired thickness, it was removed from the mandrel and placed in a desiccator for 10 h to remove any residual solvent.

Fig. 2

(a) A thinly woven PDLLA scaffold mat was electrospun and then cut into $3\mathrm{cm}\times 2\mathrm{cm}$ rectangular mats. The optically turbid scaffold architecture is shown in the scanning electron microscope image. The PDLLA phantom was fabricated by placing micro-imaging channels (MICs) between two scaffold mats and heat sintering them together. (b) A microscope image of a fiber micro-mirror inserted into a MIC. (c) The 90 deg reflection of the excitation light at the polished fiber tip is used for local delivery and scanning of excitation light within the region of interest.

2.2.

Excitation Light Delivery

Delivery of pump light for fluorescence excitation was achieved by inserting an angle-polished fiber micro-mirror into the transparent MIC as shown in the image in Fig. 2(b). The mirror was fabricated by polishing the tip of a standard single mode fiber (SMF430, Nufern Inc., East Granby, CT) at a 45 deg angle with a 0.1-μm grit diamond lapping film (Pace Technologies, Tucson, AR). Excitation light was coupled into the optical fiber and perpendicularly redirected by the 45 deg air-silica interface via total internal reflection as shown in Fig. 2(c). After inserting the micro-mirror into the MIC, the propagation direction of the excitation light was controlled through the translational and angular position of the inserted fiber micro-mirror.

2.3.

Incorporation of Fluorescent Sources

The phantom studies required placing fluorescent sources on the scaffold lumen at fixed locations. We used 28 μm diameter microspheres coated with a green fluorescent dye (FP-30052-5, Spherotech Inc., Lake Forest, IL) to mimic GFP-labeled ECs. First, the microspheres were suspended in deionized water at a $1:10$ volume ratio. Next, we pipetted 1 ml of the solution onto the lumen of the phantom, which lead to a random dispersion of the microspheres. To securely attach the microsphere to the scaffold surface, a thin $\sim 10\mathrm{\mu m}$ layer of additional PDLLA was electrospun on top of the microspheres. The added layer was thin enough to be optically transparent, yet sufficiently strong to eliminate any change in microsphere pattern during extended handling of the phantom.

2.4.

Measuring the Scaffold Optical Properties

To quantify the optical characteristics of the electrospun PDLLA scaffold, a spectrophotometer (Cary 5000, Agilent Technologies, Santa Clara, CA) coupled with an integrating sphere (Labsphere, North Sutton, NH) was used to measure the reflectance and transmittance values from 450 to 750 nm. The optical measurements were repeated on three scaffold mats having the same thickness as the phantom ($\pm 25\mathrm{\mu m}$ std.dev.). Prior to the measurements, the scaffolds were immersed and saturated in Endothelial Growth Medium-2 (Lonza Biomedical, Walkersville, MD), the same cell media used for EC culturing and phantom imaging. From the reflectance and transmittance values, the absorption coefficient ${\mu }_a$, and scattering coefficient ${\mu }_s$, were calculated using the inverse adding-doubling algorithm developed by Prahl.²¹ For the calculations, we used commonly accepted values for the refractive index ($n=1.38$) and anisotropy number ($g=0.9$) of the scaffold.^9,22 We calculated the MFP distance of the PDLLA by using

2.5.

Imaging System

The scanning-fiber-based imaging method requires local excitation of the fluorophores using the fiber mirror and the detection of fluorescent signals generated at each mirror location. A schematic and a photograph of the imaging platform that can accommodate this design is shown in Fig. 3(a) and 3(b), respectively. A 473-nm laser light was coupled into an optical fiber and delivered to the sample’s ROI by the fiber micro-mirror within the MIC. The laser was operated at a continuous 1 mW, with a fiber injection efficiency of $\sim 15\%$. The movement of the fiber micro-mirror was controlled by a custom-built two-axis motorized scanning system consisting of a 0.1-μm-resolution translation stage (UTM100PP.1HL, Newport, Irvine, CA) and a $20\mathrm{deg}/\sec$ rotation stage (URM80PE, Newport). A fiber clamp was mounted to the scanner that held the fiber in place. The distance from the fiber micro-mirror to the clamp was 15 cm. This system enabled the control of both the angular and the translational forward/backward movement of the fiber micro-mirror using a custom Labview program (National Instruments, Austin TX). The fluorescent responses generated by the fluorophores were collected by a $2\times$ long-working distance lens (M Plan Apo 2, Mitutoyo) and captured by the electron multiplying CCD camera (EM-CCD) (iXon, Andor Inc., Belfast). The distance between the lens and the phantom was 10 cm. For fluorescence mapping, the camera was set to a full-binning mode where the EM-CCD chip’s pixels were internally summed together to provide the total fluorescence intensity. In principle, we can replace the camera with a single detector such as a photomultiplier tube. However, a camera is required to quantify fluorescence distributions on the scaffold exterior surface that will be shown later. A bandpass filter ($525/45$ BrightLine, Semrock, Rochester, NY) was used to remove the excitation light from fluorescence signals.

Fig. 3

(a) Schematic and (b) photograph of the scanning-fiber-based imaging system. (c) Diagram of the imaging procedure. Using the fiber mirror, we can locally deliver excitation light to a point within the region of interest (ROI) (excitation spot). The excitation spot is moved within the ROI by rotating and translating the fiber mirror. By scanning the excitation spot according to a pixel grid, we can map the intensity responses into a digital grid to obtain fluorophore distribution.

2.6.

Fiber-Scanning and Fluorescence-Mapping Procedure

The key feature of the scanning-fiber-based method is the localized fluorophore excitation. More specifically, after using the fiber mirror to deliver excitation light into the scaffold, we can assume all fluorescent signals are generated within this highly localized light spot on the luminal surface. This local light spot is referred to as an “excitation spot” and its location on the lumen is controlled by the fiber mirror position within the MIC. The illustration in Fig. 3(c) shows the excitation spot as it appears on the lumen.

The scanning system possesses two degrees of freedom: one is the forward/backward translation $x$ and the other is angular rotation $\theta$ of the fiber inside the MIC. As the excitation spot is scanned across the lumen, a fluorescence response is generated if the spot overlaps with a fluorophore. A portion of the fluorescent signal travels through the optically opaque phantom and is captured by the detector. Since all fluorescent signals are produced within the spatially-localized excitation spot, we can “reconstruct” the fluorophore distribution by using the intensity of the fluorescence signal captured by the detector. This reconstruction process is referred to as “fluorescence mapping”, and is described in detail below.

First, we selected a ROI on the lumen and divided it into a pixel grid of $5\times 5{\mathrm{\mu m}}^2$ imaging pixels (IP) as illustrated in Fig. 3(c). Every IP in the grid can be selectively illuminated by the excitation spot by establishing a one-to-one correspondence between the center of the spot (e.g., $R$ axis and $T$ axis) and the corresponding fiber mirror position ($x$, $\theta$). In Fig. 3(c), we define the $R$ axis as parallel to the MIC and the $T$ axis as perpendicular to the MIC. Note that the coordinate $R$ is a function of the fiber rotation angle $\theta$ and $T$ is directly given by the linear translation $x$ of the fiber mirror. Furthermore, $\theta =0$ denotes the case where the excitation light is launched directly towards the lumen.

To begin an experiment, the excitation spot was first positioned to $\mathrm{IP}=1$. The resulting fluorescence signal response value was collected by the detector and assigned to $\mathrm{IP}=1$. This process was repeated for each IP in the pixel grid by discretely scanning the excitation spot across the luminal surface. By plotting the response intensities of each IP in the pixel grid as a 2-D intensity array, we obtained a mapped image of the fluorophore distribution on the luminal surface.

To intuitively understand the validity of this imaging method, let us consider an ideal case that satisfies the following assumptions: (1) the excitation spot is contained entirely within any given IP, (2) the excitation light intensity remains constant across the lumen surface for all fiber mirror locations, and (3) the scaffold does not generate any background fluorescence (i.e., autofluorescence) as “noise.” In this ideal case, the fluorescent response assigned to each IP should be directly proportional to the brightness of the fluorophores within the corresponding IP. As a result, the image obtained through fluorescence mapping should accurately reflect the spatial distributions of fluorophores over the lumen.

This intuitive analysis also identifies three factors that may limit the performance of the fluorescence mapping method including: (1) the excitation spot may exceed the size of an IP; (2) the excitation light intensity may not remain constant over the luminal surface; and (3) the scaffold may generate autofluorescence that overwhelms the fluorescent signals produced by the fluorophores. The impacts of these three factors will be discussed in Sec. 3.

2.7.

Excitation Spot Characterization

The intensity profile of the excitation spot was characterized using a control camera (XCD-X710, Sony, Japan) as depicted in Fig. 2(b). The camera lens was focused on the luminal surface of the phantom and pictures were taken of the excitation spot. After inserting the fiber mirror into the MIC, the excitation light was launched towards the lumen, producing a different spot profile at a given launching angle $\theta$, and then captured by the camera as an image. The results are described in Sec. 3.1.

2.8.

Spectrum Measurement

The spectra of fluorescent signals as well as “noises” generated by scaffold or porcine skin autofluorescence were measured by replacing the EM-CCD camera with a spectrometer (USB2000, OceanOptics, Dunedin, FL). The imaging system remains the same otherwise.

2.9.

Cell Culture Protocol

A human microvascular endothelium cell line (American Type Culture Collection (ATCC), Manassas, VA) labeled with enhanced GFP was used to demonstrate that our imaging method is suitable for in vitro and in vivo tissue engineering. All cells were cultured in Endothelial Growth Medium-2 (EGM-2) (Lonza Biomedical, Walkersville, MD). Before cell seeding, the scaffold with embedded MICs was sterilized using 70% ethanol for 30 min, followed by three sterile phosphate buffered saline (PBS) washes for 10 min each. The ECs were then suspended in 100 μL of media and seeded onto the scaffold at a density of $1\times {10}^4\mathrm{cells}/{\mathrm{cm}}^2$. The scaffold was then placed in the incubator for two hours to allow cell attachment and then was gently washed with PBS to remove any unattached cells.

3.1.

Excitation Spot Characterization

The spatial resolution of our imaging method is largely determined by the size of the excitation spot on the lumen. Therefore, it is important to quantify the properties of the excitation spot as a function of the fiber mirror launching angle $\theta$. The configuration described in Sec. 2.8 was used to obtain the results shown in Fig. 4(a)–4(c). The angle $\theta$, defined in Fig. 3(c), was swept from $\theta$ equals to $-50\mathrm{deg}$ to $+50\mathrm{deg}$ in 1 deg increments on five different locations on the $T$ axis. The characteristic data of the excitation spot presented in Fig. 4 shows both the average as well as the standard deviation of the five distinct $T$ axis locations.

Fig. 4

Excitation spot characterization. The plot lines are in 1 deg increments and the error is shown at every 4th point to prevent overcrowding. Error bars represent—one std. dev. centered at the mean of the five trials. (a) The full-width-half-maximum of the excitation spot intensity profile on scaffold lumen is shown with respect to launching angle $\theta$. The insets depict the actual excitation spot profile with $|\theta |$ equal to 0, 20, and 40 deg, respectively. (b) The intensity of the profile (summed pixels) shows a diminishing excitation spot strength at increasing angles $|\theta |$. (c) The excitation spot profile center position on the $R$ axis is shown to behave nearly linearly with respect to $|\theta |$. From the results, we find that $R(\theta )=3.33\times \theta$ based on a linear fit (red).

Figure 4(a) shows the full-width-half-maximum (FWHM) of the excitation spot size as a function of the launching angle $\theta$. Several intensity profiles of the excitation spot on the luminal surface are also shown in the figure as insets. It is clear that the FWHM increased as the launching angle deviated from $\theta =0\mathrm{deg}$. This phenomenon can be explained by the fact that at the angle of $\theta =0\mathrm{deg}$, excitation photons encountered the least number of scattering events as they traveled through the scaffold to the lumen. As the angle $|\theta |$ increased, excitation photons traveled a longer distance to the lumen, thereby experiencing more scattering within the scaffold. As a result, the FWHM of the excitation spot increased as a function of the launching angle $\theta$. For the results in Fig. 4(a), the excitation spot FWHM was at $21\pm 0.8\mathrm{\mu m}$ at $\theta =0\mathrm{deg}$ and increased by roughly 2.5 times to $50\pm 8.2\mathrm{\mu m}$ at $\theta =\pm 50\mathrm{deg}$.

In Fig. 4(b), we show that the total intensity of the excitation spot decreased as $|\theta |$ increased. The intensity value was calculated by summing all CCD camera pixel counts within the excitation spot [i.e., inset in Fig. 4(a)]. A possible explanation for this behavior is that at a larger launching angle $|\theta |$, the excitation photons traveled a longer distance, therefore experiencing more absorption before reaching scaffold lumen. Since the fluorescence response has a linear dependence on excitation light intensity, the fluorescence signals captured during fluorescence mapping must be renormalized as follows: At each $|\theta |$ value, the magnitude of the fluorescent signal was boosted according to the curve in Fig. 4(b) so that the “renormalized” excitation intensity remains constant for all pixels.

Figure 4(c) shows that along the $R$ axis, the center position of the excitation spot depends almost linearly on the fiber mirror launching angle $\theta$. Using a linear fit, we can relate the position of the excitation spot along the $R$ axis versus the launching angle as $R(\theta )=3.33\times \theta$. This result indicates that for this phantom, the excitation spot can scan across a distance of 400 μm (200 μm on either side of $\theta =0$) on the lumen along the $R$ axis, with a FWHM ranging from 21 to 50 μm. The scanning range along the $T$ axis is unlimited.

3.2.

Phantom Optical Properties

The optical properties of electrospun PDLLA and porcine skin (dermis and epidermis) were measured between 450 to 700 nm to determine their absorption and scattering coefficients ${\mu }_a$ and ${\mu }_s$, respectively. Such values quantitatively indicate how strongly the medium absorbs and scatters light. In Fig. 5(a) we see that optical scattering is significantly stronger than optical absorption by more than two orders of magnitude. This result suggests that the resolution of optical imaging is primarily limited by optical scattering in highly turbid biological media.

Fig. 5

(a) The scattering coefficient (${\mu }_s$) of PDLLA is found to be roughly double that of porcine skin over the 450 to 700 nm range. The results also show that scattering events (${\mu }_s$) dominate over absorption events (${\mu }_a$) by more than two orders of magnitude. (b) The mean free path for PDLLA and for porcine skin.

Using Eq. (1) from Sec. 2.5, we can calculate the MFP of both the PDLLA and the porcine skin. The same anisotropy factor ($g=0.9$) for the ${\mu }_a$ and ${\mu }_s$ calculation was used to calculate the MFP, which translates to $\mathrm{TMFP}=10\times \mathrm{MFP}$.²¹ Figure 5(b) shows that at the peak fluorophore emission wavelength (510 to 530 nm), the MFP is roughly 16 μm for PDLLA and 37 μm for porcine skin. Based on these values, the TMFP is 160 μm for PDLLA and 370 μm for porcine skin. We note that even for advanced modalities such as confocal and two-photon microscopes, the imaging depth is roughly limited to 1 to 2 photon TMFP,^9,23,24 which, in the case of our PDLLA scaffold and porcine skin phantom, is significantly less than their corresponding thickness: $\sim 0.5\mathrm{mm}$ for PDLLA scaffold and $\sim 3\mathrm{mm}$ for porcine skin.

3.3.

Phantom Imaging Results

In testing the accuracy of our imaging method, we first captured a control image of the fluorescent microsphere distribution on the phantom lumen surface. As described in Sec. 2.1, the control image was obtained using a standard optical microscope setup to provide an unobstructed, direct-line-of-sight, view of the luminal surface as illustrated in Fig. 6(a.1).

Fig. 6

Results of fluorescence mapping. (a.1) A schematic showing how we obtain a direct-line-of-sight control image of the scaffold lumen. (a.2) An example of a control image. (b.1) Configuration for fluorescence mapping through the 0.5 mm thick PDLLA scaffold. (b.2) Mapping result through 0.5 mm PDLLA. (b.3) The spatial distribution of fluorescence signals on the bottom surface of the phantom, as captured by the EM-CCD camera. The fluorescent signals were generated by the same region of interest in (b.2) under illumination by the external excitation light. (c.1) Configuration for fluorescence mapping through the same 0.5 mm thick PDLLA scaffold and a piece of 3 mm thick porcine skin. (c.2) Results of fluorescence mapping through 0.5 mm PDLLA $+3\mathrm{mm}$ skin. (c.3) Fluorescence image on the bottom surface of the porcine skin as captured by the EM-CCD camera. We notice further “blurring” of the fluorescent signal in (c.3), yet the result of fluorescence mapping in (c.2) remain the same as the result in (b.2), which was obtained using only PDLLA scaffold.

Prior to imaging, the sample was soaked with EGM-2. Next, the phantom was securely fastened on a glass slide. The slide with the phantom was then placed on the imaging platform and the fiber mirror was inserted into the MIC. Fiber scanning was carried out in the ROI that coincides with the control image shown in Fig. 6(a.2). After following the mapping procedure described in Sec. 2.7, we obtained the mapped image shown in Fig. 6(b.2). This configuration mimicked an in vitro environment of a bioengineered blood vessel with visual access to the outside surface of the vessel. When comparing the control image with the mapped image, we observe that the center position of each microsphere is in good agreement. Since the FWHM of the excitation spot is at times larger than the microsphere diameter, individual microspheres are blurred together.

Next, a 3-mm thick piece of porcine skin with an intact dermis and epidermis layer was placed under the phantom, thus further obstructing the lumen from the detector. This configuration is shown in the diagram of Fig. 6(c.1), which mimics an in vivo environment for a carotid artery imaging experiment. After the scanning algorithm was performed in the identical ROI, the fluorescence mapped image in Fig. 6(c.2) was produced. When comparing the fluorescence mapped image using the 0.5 mm PDLLA configuration versus the 0.5 mm PDLLA $+3\mathrm{mm}$ skin configuration, we observe that there is no significant degradation in image resolution. Therefore, the results in Fig. 6 directly demonstrate that the scanning-fiber-based method can decouple the link between imaging depth and image resolution. Fundamentally, this decoupling is due to the fact that our imaging system is not limited by the thickness of the turbid media between the lumen and the detector, but rather depends on the signal-to-noise (SNR) of fluorescent signals. For a detailed analysis of SNR, refer to Sec. 3.5.

To compare how a standard fluorescence microscope performs in terms of resolution, we use the EM-CCD camera to capture fluorescence images on the bottom surface of the phantom, where the entire ROI on scaffold lumen was illuminated using an external excitation source. The images in Fig. 6(b.3) and Fig. 6(c.3) show the fluorescence response after traveling through 0.5 mm PDLLA and 0.5 mm PDLLA $+3\mathrm{mm}$ skin, respectively. Both images show that it is impossible to deduce the original microsphere distribution, and that adding additional turbid medium (porcine skin) causes a significant spread in the spatial distributions of fluorescent signals.

3.4.

Imaging Resolution Analysis

We note that the result of fluorescence mapping can be modeled as a convolution of the control image with a point spread function (PSF), where the PSF describes the image “blurring” due to the finite size of the excitation spot. Mathematically, the spatial dimension of the PSF should correspond to the overall image resolution of our system.

Therefore, to quantify the overall image resolution of the fluorescence mapped image in Fig. 6, we carried out the following mathematical analysis. First, we convolved the control image with a variable-size Gaussian PSF. We note that the excitation spot profile can be closely approximated by a Gaussian PSF. By sweeping the FWHM of the Gaussian PSF from 0 to 50 μm, we obtained various theoretically predicted fluorescence mapped images with an image resolution varying from 0 to 50 μm. Then, the mean square error (MSE) was calculated between the theoretically predicted fluorescence mapped images versus the actual mapped images [i.e., the results shown in Fig. 6(b.2) or Fig. 6(c.2)]. The percentage of MSE versus the FWHM of the Gaussian PSF is plotted in Fig. 7, which shows that the smallest MSE occurs at around a 24 μm FWHM for both with or without additional porcine skin. This matches very well with the experimental results shown at in Fig. 4(a) from $|\theta |\sim 0$ to 30 μm. The inserts in Fig. 7 show the experimental mapped images (through 0.5 mm PDLLA or 0.5 mm PDLA $+3\mathrm{mm}$ skin) as well as the theoretically predicted image using a 24 μm FWHM Gaussian PSF. With the result in Fig. 7, we conclude that the resolution of our imaging system can reach the level of 20 to 30 μm with an imaging depth corresponding to 0.5 mm PDLLA scaffold plus 3 mm porcine skin.

Fig. 7

The resolution of the scanning-fiber-based-method is modeled by convolving the control image with a variable Gaussian point spread function creating a theoretical mapped image. By finding the least mean square error of the difference between the theoretical and experimental results, we find the approximate resolution of the system. The result suggests that the imaging resolution is between 20 to 30 μm at an imaging depth corresponding to 0.5 mm PDLLA plus 3 mm porcine skin.

3.5.

Signal Versus Noise

Figure 8 shows the spectral components of the fluorescent signals and noises generated by the microspheres and the two phantoms, respectively. These results were obtained by replacing the EM-CCD camera with a spectrometer. Specifically, the microsphere signal was measured by positioning the excitation spot to the center of a single standing microsphere and capturing the fluorescence emission spectrum. Then, we applied the same procedure to characterize noises generated by the optical phantoms. To ensure that only “noise” was captured by the spectrometer, we positioned the excitation spot on a luminal surface location that was void of any microspheres. (We used the control camera to ensure no fluorescent microspheres exist within the excitation spot.) The results are shown in Fig. 8, where we normalized the intensity of all emission spectra such that the peaks of the spectral noise were set to be one.

We define the SNR of the imaging system as the ratio between the microsphere signal and the background noise. For the 0.5 mm PDLLA experiment, the SNR is around 4 in the 510 to 540 nm range. After adding the 3-mm thick skin, the SNR dropped to two. Although a SNR of two is relatively small, it is sufficient to separate the signal from the noise to obtain the fluorescence mapped image in Fig. 6(c.2). However, if we place a thicker tissue between the phantom and the detector such that the SNR approaches unity, it would be very difficult to separate the microsphere signals from background “noises” generated by the scaffold as well as the surrounding tissue.

Fig. 8

Spectral responses of microsphere signals as well as autofluorescence noises. The microsphere signal was obtained by centering the excitation spot on a single microsphere placed on the phantom lumen. The autofluorescence noise was obtained by moving the excitation spot to a location on the lumen that was free of microspheres. The signal-to-noise (SNR) is calculated as the microsphere signal divided by the autofluorescence. (a) The SNR through 0.5 mm PDLLA is around four between 510 to 545 nm. (b) The SNR through 0.5 mm PDLLA $+3\mathrm{mm}$ porcine skin is around two between 510 to 545 nm.

The results in Fig. 8 suggest that the main limitation on fluorescence mapping lies in making sure the intensity of fluorescence signals is greater than the background noise. In other words, the spatial profile of the fluorescent signal captured on the exterior surface of the scaffold or porcine skin plays no role in fluorescence mapping—only the total strength of the fluorescent signal does. More specifically, after adding the porcine skin, the fluorescence light was distributed within a much wider spatial region [Fig. 6(c.3)] compared to the case without any porcine skin [Fig. 6(b.3)]. Yet the images obtained through fluorescence mapping did not show any significant difference. Consider the following two observations: (1) for most biological tissues, optical scattering significantly exceeds optical absorption as shown in Fig. 5, and (2) the primary impact of photon scattering is the blurring of the fluorescent signal without significantly changing its total strength. With these considerations, it is clear that the resolution is no longer limited by the scattering of the fluorescent signal. As a result, the imaging resolution of the scanning-fiber-based method is largely “decoupled” from the total imaging depth.

3.6.

Endothelial Cell Imaging

Figure 9(a) shows the direct-line-of-sight control image of the GFP-labeled ECs on PDLLA scaffold lumen. The same ROI was then used for fiber scanning followed by fluorescence mapping. Following the process described in Secs. 2.7 and 3.5, we obtained the fluorescence mapped image shown in Fig. 9(b). Comparing the mapped image to the control image, it is clear that the spatial distribution of ECs obtained through fluorescence mapping is in good agreement with the control image. This result confirms that the scanning-fiber-based method can image through a 0.5-mm thick tissue scaffold and reveal the spatial distribution of ECs with single-cell-level resolution. Figure 9(c) shows that the SNR of a single GFP-labeled EC is around two for the 0.5 mm thick PDLLA phantom, which also confirms the reliability of our fluorescence mapping results.

Fig. 9

(a) Control image showing the actual endothelial cell (EC) distribution on scaffold lumen. (b) A fluorescence mapped image of EC distribution that corresponds to the image in (a). Comparison between the control image and the fluorescence mapped image indicates that our method can “see” through a 0.5 mm thick PDLLA scaffold with single-cell-level resolution. (c) signal-to-noise measurement for a single green fluorescent protein (GFP)-labeled EC on scaffold lumen. The SNR is around two for a 0.5 mm thick PDLLA phantom.