2.1.

Dual-Channel Optical Imaging System

A custom-built optical set-up provides dual-channel imaging of both high-speed bright-field video and fluorescence images simultaneously (Fig. 1). This is achieved through optically dividing the microscope light path into two bands, one for fluorescence (495–550 nm) and the other for bright-field ($>560\mathrm{nm}$). Two light sources are used to illuminate the vessel. A halogen light source built into the microscope (AxioScope, Carl Zeiss Microscopy, Thornwood, NY) offers transmission illumination and a mercury arc lamp (X-Cite, Lumen Dynamics, Ontario, Canada) provides reflective illumination. A band pass excitation filter centered at $475/40\mathrm{nm}$ is positioned in the filter cube within the AxioScope (Zeiss). A 495 nm long pass dichroic (Zeiss), also within the cube, allows for reflected light to pass through while restricting the excitation wavelength. A dual phototube adapter (Zeiss) allows us to divide the light path between two ports by using a 560 nm long pass dichroic (T555LPXR, Chroma, Bellows Falls, VT). A $530/40\mathrm{nm}$ emission band pass filter (HQ530/40m, Chroma, Bellows Falls, VT) is placed before the fluorescence camera (PIXIS 1024 B, Princeton Instruments, Trenton, NJ). An adjustable 60 N to C-mount adapter (Zeiss) provides us with the flexibility of aligning the camera in the plane perpendicular to the light path in addition to adjusting focus and angular rotation. A 580 nm long pass filter (HQ580lp, Chroma, Bellows Falls, VT) with an optical density (OD) of 5 intercepts the halogen light path and only allows wavelengths greater than 580 nm to pass. A 10x water immersion objective (Zeiss) with a numerical aperture (NA) of 0.3 is used to achieve the required magnification.

Fig. 1

A dual-channel optical system. Both a fluorescence and halogen light source are used to illuminate the vessel. A long pass filter (580 nm LP) is used to attenuate wavelengths below 580 nm. An excitation band-pass filter ($475/40\mathrm{nm}$ BP) is used for the fluorescence light source. A dichroic (550 nm LP) effectively splits the wavelengths into two channels; $>550\mathrm{nm}$ for the bright-field channel and $<550\mathrm{nm}$ for fluorescence. An emission band pass filter ($530/40\mathrm{nm}$) is placed in front of the fluorescence camera. An adjustable adapter allows focusing of the two cameras independently. (a) Representative bright-field image from high-speed video of the vessel. (b) Representative fluorescence image of the same vessel. BODIPY $C_{16}$, an orally delivered fluorescent long chain fatty acid analogue, is used as our fluorophore.

A high-speed CMOS video camera (Falcon Dalsa VGA300 HG, Teledyne Dalsa, Billerica, MA) allows a frame capturing rate of up to 300 fps with a resolution of $640\times 480$ and provides images of individual lymphocytes flowing in the lymph. The 12-bit fluorescence camera utilizes a back-illuminated CCD that is cooled to $-70°\mathrm{C}$ which eliminates thermal noise and provides high sensitivity, allowing the detection of small changes in fluorescence intensity.

2.2.

Tissue Phantom Preparation

A 147 μm diameter channel fabricated in polydimethylsiloxane (PDMS; SYLGARD 184, Dow Corning, Midland, MI) served as a mock lymphatic vessel to quantify the minimum detectable concentration of BODIPY FL ${\mathrm{C}}_{16}$ (Life Technologies, Grand Island, NY) with the system and the fluorescence camera’s linearity within a given concentration range of BODIPY (Excitation: 490 nm, Emission: 520 nm) in a $10\mathrm{mg}/\mathrm{mL}$ bovine albumin (MP Biomedicals, Auckland, New Zealand) solution. A copper wire running through two holes in a polystyrene petri-dish was used as a PDMS mold. A $10:1$ (elastomer to base) PDMS mixture was poured into the mold after removing air bubbles and cured overnight at 60°C. The wire was then pulled out to create a hollow cylindrical channel, thus mimicking a collecting lymphatic vessel in both dimensions and optical clarity.

2.3.

Integrated Image Acquisition Platform

Using third-party toolkits (R Cubed Software, Lawrenceville, NJ and BitFlow, Woburn, WA) for both cameras, an integrated image acquisition application was written using LabVIEW (National Instruments, Austin, TX) to streamline the acquisition process with minimal user input. The interface provides a live feed of the high speed video and fluorescence images throughout the experiment. The user can specify the duration of a high-speed video segment, the integration time of the fluorescence camera, and the interval at which to capture for both cameras. Both video sequences and fluorescence images are time-stamped for later processing.

High-speed video is captured at 250 fps using a Neon-CLB PCIe frame grabber (Bitflow, Woburn, MA) and is saved as an uncompressed AVI file. The program uses four memory buffers which together with RAID 0 hard disks and an 8-core central processing unit (CPU) configuration allows direct streaming of high-speed video frames to the hard drive without the RAM limitation of the camera or the computer reported previously.³⁵ This allows the user to capture an unlimited duration of high-speed video that is only limited by available hard disk space. Fluorescence images are captured at an interval of 5 s with an integration time of 100 ms, which provides enough sensitivity to image low levels of fluorescence while minimizing blur due to motion artifacts. Images are stored as uncompressed 16-bit TIFF files.

2.4.

Animal Preparation

A male Sprague-Dawley (SD) rat (Charles River, Wilmington, MA) was chosen to facilitate comparative studies of lymphatic contractility to previous studies performed on the same strain. The animal was housed in an American Association for Accreditation of Laboratory Animal Care facility. At 9 weeks of age, a rat weighing 311 g was fasted the night before the experiment for 15 h while water was available ad libitum. After fasting, a solution of 0.5 mL of olive oil (Great Value, Walmart, GA) and 100 μg of BODIPY FL ${\mathrm{C}}_{16}$ reconstituted in 20 μL of Dimethyl Sulfoxide (DMSO; Fisher Scientific, Pittsburgh, PA) was delivered via gavage.

After waiting 1.5 h to allow for digestion, the rat was sedated with an intramuscular (IM) injection of Diazepam ($2.5\mathrm{mg}/\mathrm{Kg}$, Hospira, Lake Forest, IL) and then anesthetized through an IM injection of a cocktail containing $0.12\mathrm{mL}/\mathrm{kg}$ Fentanyl (Sigma Aldrich, St. Louis, MO) and $6\mathrm{mL}/\mathrm{kg}$ Droperidol (Sigma Aldrich, St. Louis, MO) which has been previously observed to have minimal effect on lymphatic vessel contractility. Supplemental IM booster doses at half the initial dose were administered as needed. After preparing a surgical area around the abdominal cavity, a 2 cm incision was made at the midline starting at 1 cm below the Xiphoid process. A segment of the small intestine distal to the duodenum was exteriorized and stabilized in a groove between two acrylic plates, thus exposing the mesentery over an imaging window covered with a glass slide (Fig. 2). An albumin physiological salt solution (APSS; in mM: 145.0 NaCl, 4.7 KCl, 2.0 ${\mathrm{CaCl}}_2$, 1.2 ${\mathrm{MgSO}}_4$, 1.2 ${\mathrm{NaH}}_2$ ${\text{PO}}_4$, 5.0 glucose, 2.0 sodium pyruvate, 0.02 EDTA, 3.0 MOPS, and $10\mathrm{g}/\mathrm{L}$ BSA) (all reagents from Sigma, St. Louis, MO and BSA from ICP Bio, New Zealand) with pH adjusted to $7.4\pm 0.1$ at 38°C was temperature controlled at 36°C to 39°C and flowed at a rate of $12\mathrm{mL}/\min$ to bathe the mesentery. The APSS bath recapitulates the oncotic extracellular environment found around the mesentery. The temperature of the rat was maintained through circulating hot water flowing in silicone tubing underneath the animal within the custom designed imaging board while body temperature was monitored and recorded with a rectal thermometer (Kent Scientific, Torrington, Connecticut). A lymphatic vessel was then located and placed over the imaging window allowing the imaging session to begin. Imaging was performed for a total of 70 min. All animal procedures were performed in accordance with the Georgia Institute of Technology Internal Animal Care and Use Committee and complied with the National Institutes of Health Guide for the Care and Use of Laboratory Animals. At the end of the experiment, the rat was euthanized.

Fig. 2

The surgical set-up. (a) The small intestine is stabilized in a loop via a two-piece clamp thus exposing the mesentery. The base of the platform is a glass slide which forms the imaging window. (b) A custom designed imaging board that allows us to image the mesentery while bathing it in a circulating albumin physiological salt solution (APSS). The animal sits on a heated platform, which maintains the animal’s core body temperature. The board is screwed into the microscope stage to insure long term field-of-view stability by limiting slight board movements.

2.5.

Post-Acquisition Image Processing

2.5.3.

Diameter tracings

For quantifying lymphatic pump metrics, an accurate diameter tracing algorithm was developed. In addition to the inherent low contrast, adipocytes accumulate around lymphatic vessels causing the vessel wall to become obscure and in most cases lose its sharp edge characteristics; thus, common automatic edge detection algorithms did not prove to be accurate. This led us to use a 2D CC method based on previously published techniques³³ [Fig 3(a)]. The user manually selects the two vessel walls in the first image of the sequence. The algorithm then draws a window around each of the vessel walls and sets the two windows as reference templates. To track the movement of these windows, the template windows (solid green line) in a frame were correlated to search windows (dashed red line) in a subsequent frame and the maximum correlation coefficient calculated indicates the new position of the wall. The template window was centered on the current location of the vessel wall while the search window was larger and centered on the same coordinates in a subsequent frame. Typically, the template window is $40\times 40\text{pixels}$, while the search window is $80\times 80\text{pixels}$. The dimensions of these windows can be adjusted dynamically in the program in order to decrease computational time (by making the windows smaller) or to account for high contraction amplitudes in highly contractile vessels (by making the search windows larger). The diameter of the vessel was the distance separating the centers of the two windows and is tracked in every frame to give the diameter tracings over time.

Fig. 3

Post-acquisition image processing algorithms. (a) Diameter tracing algorithm. Green boxes (solid line) represent the template windows. Red boxes (dashed line) are the correlation search windows. The diameter d is the distance separating the centers of the two template windows as they are located across sequential frames. (b) Lymphocyte velocity tracking algorithm. The green box (solid line) is the template window which is cross-correlated with the search window, yellow box (dashed line), the red box is the new template window location. $\mathrm{\Delta }t$ is the time separating two frames. The average velocity of lymphocytes is $V^{*}=\mathrm{\Delta }x/\mathrm{\Delta }t$.

2.6.

Quantifying Correlation Between Triglyceride Concentration and BODIPY $C_{16}$ Fluorescence in Lymph

2.7.

Quantitative Descriptors for Lymphatic Pump Function

From the diameter and velocity tracings the following metrics were calculated:

3.1.

Optical System Sensitivity to BODIPY

Our characterization experiments confirm the quantum yield of BODIPY exhibits a 7-fold increase when mixed with albumin (Fig. 4). The increase in quantum yield quickly plateaus at an albumin concentration below that typically measured in lymph⁴⁸ suggesting fluctuations in fluorescence due to changes in albumin concentration are minimized. This increase in quantum yield is most often caused by alteration of the fluorophore de-excitation pathway, essentially increasing the probability of a radiative event.⁴⁹ Considering the limitations of this method, we calculate the minimum detectable concentration of BODIPY to be $24\mathrm{ng}/\mathrm{mL}$ at 100 ms integration time (Fig. 5) with the primary limiting factor being light leakage from the transmission halogen light source through the 580 nm LP filter with OD of 5. A 100 ms integration time was used for all the experiments presented in this study.

Fig. 4

Fluorescence intensity in the presence of albumin. BODIPY fluorescence intensity increased by approximately 7 fold when bound to albumin. Once bound, fluorescence is stable with the increase in albumin concentration. Error bars represent mean standard deviation (SD).

Fig. 5

Performance characteristics of the fluorescence camera, the PIXIS. (a) A calibration curve shows the linearity of the PIXIS fluorescence camera and allows it to be used for quantitative fluorescence. (b) Minimum detectable BODIPY concentration at 3 dB signal-to-noise ratio (SNR) is $24\mathrm{ng}/\mathrm{mL}$ in $10\mathrm{mg}/\mathrm{mL}$ albumin solution.

3.2.

Correlation of BODIPY ${\mathrm{C}}_{16}$ Fluorescence and Triglyceride Concentration

In order to quantify the extent to which BODIPY ${\mathrm{C}}_{16}$ might be indicative of actual in vivo Triglyceride (TG) concentration, we collected lymph from rats ($n=7$) over a 4-h period. Rats were infused with a lipid emulsion along with BODIPY ${\mathrm{C}}_{16}$. It was found that the fluorescence trend correlates well with actual TG concentration (Fig. 6) with a linear regression ($R^2$) value of approximately 0.83.

Fig. 6

BODIPY ${\mathrm{C}}_{16}$ fluorescence correlates well with TG concentration. (a) TG concentration and BODIPY fluorescence in rat lymph. Lymph samples were collected at 30 min intervals for 4 h. TG concentration was quantified using a commercially available kit and fluorescence intensity values were obtained using a fluorescence plate reader. TG and fluorescence peak at around 2 h after the start of intraduodenal lipid infusion. (b) BODIPY fluorescence versus TG concentration with a linear regression ($R^2$) value of almost 0.83. $n=7$. Error bars represent mean standard deviation (SD).

3.3.

Image Processing Performance

3.3.1.

Motion compensation

The motion compensation algorithm significantly stabilized the high-speed video captured during intestinal peristalsis (Fig. 7). A randomly chosen 60-s video segment was used to obtain performance characteristics. The standard deviation for the displacement of the original unstabilized video was 9 pixels with a maximum displacement of 45 pixels while that of the stabilized video was 0.4 and 3.5 pixels respectively [Fig. 7(a)]. The normalized correlation index of a window that was fixed in the FOV was calculated for the video segment. The standard deviation for the displacement of the original unstabilized video was 0.27 with a minimum correlation index of 0 (the contents of the window completely leave the area), while that of the stabilized video was 0.05 and 0.63, respectively [Fig. 7(b)]. The motion compensation algorithm developed can be easily applied to any video sequence.

Fig. 7

Motion compensation algorithm performance metrics. (a) Original versus stabilized pixel displacement. The displacement of a template window was tracked as it moved in the field of view using 2D cross correlation. The standard deviation for the original unstabilized video was 9 pixels while that of the stabilized was 0.4 pixels. (b) Original versus stabilized normalized cross correlation values. The correlation index was tracked over time for a template window fixed in the field of view. The standard deviation of the normalized correlation index for the original unstabilized image was 0.28 while that of the stabilized was 0.05.

3.3.2.

Diameter tracings

Manual measurements were carried out every one second of video by the user drawing a line connecting the vessel walls and measuring that distance. The manual measurements were then compared to the automated tracings (Fig. 8). The average error rate between manual and algorithmic tracings was found to be around 3.3% and is likely a result of user subjectivity on the manual selection of where a vessel wall starts or ends. Diameter tracings obtained provide the basis for various parameters used to quantify lymphatic pump function (Table 1).

Fig. 8

Verification of diameter tracing algorithm. Two different vessels with varying morphology and sizes are displayed. Black markers indicate manual measurements where the user drew a line connecting the vessel walls and the distance was measured. Error rate between manual versus algorithmic tracings was 3.3%.

Table 1

Diameter related quantifiable parameters for characterizing BODIPY uptake and lymphatic pump function.

Time (min)	BODIPY (Normalized a.u.)	AD (μm)	CF (Hz)	DC (μm)	EDD (μm)	ESD (μm)	CA (%)	CWV ($\mathrm{\mu m}/\mathrm{s}$)	DWV ($\mathrm{\mu m}/\mathrm{s}$)
1	3.01	144	0.26	11	150	139	7	7	5
3	3.22	138	0.24	13	146	133	8	8	6
4	3.49	137	0.22	19	147	129	12	9	11
6	3.25	141	0.24	13	148	133	10	8	9
8	3.23	133	0.16	17	138	123	10	9	8
10	3.26	148	0.16	11	153	142	7	7	6
12	2.89	148	0.18	8	151	142	5	5	4
28	3.75	153	0.24	5	156	151	2	5	3
41	1.00	144	0.12	7	147	140	4	3	4
43	1.30	142	0.24	4	145	140	3	2	3
46	2.06	144	0.26	6	147	141	4	3	5
53	1.76	143	0.18	13	150	138	7	3	8
57	1.95	128	0.16	10	136	125	7	3	7
60	1.26	157	0.24	3	159	156	2	1	3

Note: AD: average diameter, CF: contraction frequency, DC: diameter change, EDD: end-diastolic diameter, ESD: end-systolic diameter, CWV: constriction wall velocity, DWV: dilation wall velocity.

3.3.3.

Velocity tracking

The algorithm has a 97% accuracy for measuring particle velocity in the range of lymphocyte velocities in the mesentery lymphatics reported in literature⁴¹ (Fig. 9). The motorized stage being used produced some inherently small jerky movements when moving at low speeds, this accounted for the somewhat jumpier than expected algorithm accuracy verification readings. Volume flow rates (VFR) and wall shear stress (WSS) can be calculated from lymphocyte velocities as described previously⁴¹ assuming Poiseuille flow in a cylindrical tube (Table 2).

Fig. 9

Accuracy of the lymphocyte velocity tracking algorithm. Validation measurements were carried out by placing 15 μm beads on a slide and a motorized stage was programmed to move at certain velocities. Within the velocity range previously published the algorithm has close to a 97% accuracy rate in determining the velocity.

Table 2

Lymphocyte velocity related quantifiable parameters for characterizing BODIPY uptake and lymphatic pump function.

Time (min)	BODIPY (Normalized a.u.)	MLV ($\mathrm{\mu m}/\mathrm{s}$)	Max. LV ($\mathrm{\mu m}/\mathrm{s}$)	Min. LV ($\mathrm{\mu m}/\mathrm{s}$)	VFR ($\mathrm{\mu l}/\mathrm{hr}$)	Avrg. WSS ($\mathrm{dyn}/{\mathrm{cm}}^2$)	Max. WSS ($\mathrm{dyn}/{\mathrm{cm}}^2$)	FPF (/min)	EF	SV ($\mathrm{\mu L}$)	LO ($\mathrm{\mu L}/\mathrm{hr}$)	VFR/LO	ELO
1	3.01	43	1928	$-1512$	17	0.06	2.00	2.14	0.14	0.02	22.77	1.10	0.84
3	3.22	240	2394	$-1503$	87	0.21	2.21	2.46	0.17	0.03	24.70	5.26	4.65
4	3.49	289	2111	$-1578$	103	0.24	1.84	3.12	0.24	0.04	32.09	4.79	5.96
6	3.25	377	2404	$-1465$	143	0.32	2.03	2.74	0.19	0.03	28.52	7.51	7.74
8	3.23	392	1933	$-1378$	132	0.35	1.89	1.98	0.21	0.03	17.98	11.03	7.11
10	3.26	396	1916	$-1034$	164	0.32	1.52	1.33	0.14	0.03	14.78	16.69	8.94
12	2.89	527	1845	$-846$	219	0.43	1.55	1.19	0.11	0.02	12.87	25.48	10.51
28	3.75	504	2024	$-1407$	224	0.40	1.68	0.78	0.05	0.01	8.95	37.61	14.03
41	1.00	441	2312	$-1275$	173	0.37	1.96	0.68	0.09	0.02	6.99	37.25	2.89
43	1.30	326	2665	$-1736$	125	0.27	2.35	0.93	0.06	0.01	9.19	20.38	2.71
46	2.06	439	2929	$-1578$	174	0.36	2.57	1.23	0.08	0.01	12.66	20.57	5.97
53	1.76	435	2670	$-1557$	170	0.35	2.21	1.65	0.15	0.03	17.52	14.53	4.97
57	1.95	202	2753	$-1866$	63	0.19	2.66	1.46	0.15	0.02	12.81	7.40	2.05
60	1.26	399	2559	$-1456$	187	0.30	2.06	0.67	0.05	0.01	8.04	34.84	3.91

NOTE: MLV: Measured Lymphocyte Velocity, LV: Lymphocyte Velocity, VFR: Volume Flow Rate, WSS: Wall Shear Stress, FPF: Fractional Pump Flow, EF: Ejection Fraction, SV: Stroke Volume, LO: Lymphatic Output, ELO: Effective Lipid Output.

All image processing algorithms and instructions for use are available upon request.

4.1.

Alternative Imaging Systems

Miura et al. measured relative changes in lipid concentration in the mesentery lymph using gray level ratios obtained by analyzing video images and were able to correlate them to an increase in lymphatic contraction frequency.¹⁷ While some qualitative conclusions can be made, the sensitivity to changes in lipid concentration falls into a few discrete gray level values. The system is also limited by the fact that initial small changes in lipid uptake would not be detectable. However, using a back-illuminated 12-bit CCD along with BODIPY allows us to quantify changes in lipid concentrations as low as $24\mathrm{ng}/\mathrm{mL}$. With regard to quantifying lymphatic function, several systems are currently being used;^45,50–53 however, our set-up provides us with the capability of capturing an unlimited duration of high-speed video allowing us to carry out measurements without any blind spots if the experimentalist wishes to do so. In addition, our motion compensation algorithm provides an integral tool for studies in the rat mesentery model, as unlike other systems, we do not need to fast our animal before an imaging experiment. This is also important since peristalsis is thought to provide an extrinsic mechanism for driving lymph flow,⁵⁴ thus studies designed that intentionally minimize motion artifact by limiting peristalsis might actually be underestimating lymph flow rates in the mesentery. The system presented in this paper is both sensitive and able to provide us with various quantifiable data (Tables 1 and 2) that comprehensively describe lymphatic pump function and lymph flow in the context of lipid uptake and transport.

4.2.

Determining Intrinsic versus Extrinsic Factors

Lymph flow is a consequence of various active (intrinsic) and passive (extrinsic) forces. The phasic contraction of lymphangions accounts for the dominant intrinsic pumping mechanism. Extrinsic factors include the driving force of lymph formation, influences of cardiac and arterial pulsations, contractions of skeletal muscles in proximity to the lymphatic vessels, central venous pressure fluctuations, gastrointestinal peristalsis, and respiration.⁵⁵ Because of this complexity, the velocity peaks due to the actions of passive lymph pumps often are not synchronized with intrinsic contractile activity of lymphangions [Figs. 10(a), 10(b), and 10(c)], flow profiles in lymphatic vessel are extremely variable and bidirectional.⁵⁶ By tracking both flow and contraction simultaneously during the absorptive process, we can quantity the significance of both the extrinsic and intrinsic pump on lymph flow. One such indicator for describing the dominant pumping is the volume flow rate to lymphatic output ratio (VFR/LO). The VFR is the measured flow in the vessel obtained through lymphocyte tracking, while the LO is what is expected due to the intrinsic contractility of the lymphangion. In fasted rats, this average ratio was 0.71,⁴¹ while for the lipid fed rat shown here, the average ratio was 11.64, indicating a dominance of extrinsic factors. This is most likely due to lymph formation serving as a dominant extrinsic factor,¹⁷ but more studies are warranted to determine the exact mechanism. Our system does, however, have the ability to distinguish between the expected flow rate due to vessel pumping and the actual flow rate, even in the context of lipid absorption and substantial intestinal peristalsis. In addition, obtaining a frequency spectrum of the underlying velocity and contraction frequencies (Fig. 11) clearly shows that the fundamental frequencies of contraction and flow are independent, with flow having a higher fundamental frequency than contraction, further showing that extrinsic factors play a major role.

Fig. 10

Correlating lipid uptake with lymphatic pump function. (a, b, c) Diameter tracings superimposed on velocity profiles for three time points at minutes 12, 28 and 57. (d) Estimated BODIPY ${\mathrm{C}}_{16}$ concentration plot over a 68 minute period giving us relative lipid concentrations in the lymphatic vessel. (e) Sample fluorescence image used for pixel intensity measurements. (f) A single frame from a bright-field high-speed video segment used to extracting diameter and velocity data.

Fig. 11

Fourier analysis of representative diameter and velocity tracings. (a) at 12 min [Fig. 10(a)]. (b) at 28 minutes [Fig. 10(b)] at 57 min [Fig. 10(c)]. Fundamental frequencies for diameter and velocity tracings are different (see numerical labels), indicating that extrinsic factors might potentially be the dominant mechanism of transport as opposed to lymphatic contraction.

4.3.

Quantifying Intestinal Uptake

We have chosen BODIPY FL ${\mathrm{C}}_{16}$ (4,4-Difluoro-5,7-Dimethyl-4-Bora-3a,4a-Diaza-s-Indacene-3-Hexadecanoic acid), a fluorescently labeled 16-carbon-chain fatty acid, to quantify lipid uptake. BODIPY is an ideal choice due to having a high quantum yield and solvent photostability. The lymphatic transport characteristics of BODIPY ${\mathrm{C}}_{16}$ have been previously validated using a coculture lacteal in vitro model^18,57 and have also been previously reported to be taken up into lymphatics in vivo after administration via gavage.^14,18 Because this fluorescent lipid analogue is a long-chain free fatty acid (LCFA), it is absorbed by the villi lining the small intestine and packaged along with the triglycerides present in the olive oil cocktail to form fluorescent chylomicrons and correlates well with actual TG concentrations in lymph (Fig. 6). BODIPY is exclusively taken up by lymphatics and is not detectable in the mesenteric blood circulation¹⁸ and is metabolized as an 18-carbon fatty acid due to the presence of two extra carbons in the fluorophore.⁵⁸ Once the chylomicrons enter the mesenteric lymphatic, an increase in fluorescence intensity is observed [Fig. 10(d)]. While BODIPY was chosen for this particular application, any fluorophore in the green fluorescent protein (GFP) excitation/emission range can be used to quantify uptake by the mesentery lymphatics.

There has been growing interest in targeting lymphatics with orally delivered drugs or vaccines as such a route would avoid first-pass metabolism by the liver and could also provide access to mesenteric lymph nodes.^59,60 Fluorescently labeling these delivery systems would allow investigators to not only access lymphatic absorption of the drug, but would also provide insight into whether or not the delivery results in unwanted consequences on lymphatic function, thus limiting its delivery to the systemic circulation. It could also provide insight into the mechanisms behind the enhancement of lymphatic uptake seen when drugs are delivered to a subject with elevated system levels of triglyceride rich lipoproteins.⁶¹ Understanding the effects of metabolic differences between patients on oral drug absorption are essential for developing proper dosing strategies for these individuals.

4.4.

Significance in Studying Disease

Malformations of mesentery lymphatics result in various clinical pathologies.⁶² Protein-losing enteropathies, for example, are characterized by the progressive loss of protein from bowel due to elevated lymphatic pressure, lymphatic congestion, and nonulcerative mucosal disease as well as inflammatory and ulcerative diseases. Primary intestinal lymphangiectasia (PIL) is one important form of protein-losing enteropathy. PIL is a disorder characterized by dilated intestinal lacteals which presumably cause lymph leakage into the small bowel lumen. Comparing VFR and BODIPY fluorescence in this diseased state to a healthy state will provide quantitative data to the extent of leakage, and potentially disease severity. A low-fat diet associated with medium-chain triglyceride supplementation is the cornerstone of PIL medical management. The absence of fat in the diet prevents chyle engorgement of the intestinal lymphatic vessels thereby preventing their rupture with its ensuing lymph loss. Medium-chain triglycerides are absorbed directly into the portal venous circulation and avoid lacteal overloading.⁶³ Using a long chain fluorescent fatty acid analogue such as BODIPY ${\mathrm{C}}_{16}$ can be used to better understand how the contribution of loading the lacteals contributes to the disease by investigating the active role that the collecting lymphatic vessel plays to clear the extra load. Even before PIL symptoms develop, patients have shown delayed transport of lipid from the intestine, suggesting that lymphatic lipid transport function is compromised at an early stage of the disease.⁶²

In addition, inflammatory bowl diseases such as Crohn’s disease (CD) present themselves with several lymphatic abnormalities.⁶⁴ Lymphatic contractile activity was shown to be impaired in an isolated vessel model of gut inflammation, suggesting that lymphatic function might be compromised in inflammatory diseases such as CD.⁶⁵ While alleviating the lipid burden on lymphatics is clinically beneficial in many of these intestinal disorders, the exact mechanisms of lymphatic failure and the interplay between the lipid absorption process and lymphatic function is unclear. The imaging system described here has the capability to address many of these issues in a unique fashion. The parameters obtainable in Tables 1 and 2, along with Fourier analysis and further signal processing analysis (Fig. 11) will pave the way to understanding various disease states and quantitatively elucidating how mesentery lymphatic function changes in response to disease.