In vivo visualization and quantification of collecting lymphatic vessel contractility using near-infrared imaging

Techniques to image lymphatic vessel function in either animal models or in the clinic are limited. In particular, imaging methods that can provide robust outcome measures for collecting lymphatic vessel function are sorely needed. In this study, we aimed to develop a method to visualize and quantify collecting lymphatic vessel function in mice, and to establish an in vivo system for evaluation of contractile agonists and antagonists using near-infrared fluorescence imaging. The flank collecting lymphatic vessel in mice was exposed using a surgical technique and a near-infrared tracer was infused into the inguinal lymph node. Collecting lymphatic vessel contractility and valve function could be easily visualized after the infusion. A diameter tracking method was established and the diameter of the vessel was found to closely correlate to near-infrared fluorescence signal. Phasic contractility measures of frequency and amplitude were established using an automated algorithm. The methods were validated by tracking the vessel response to topical application of a contractile agonist, prostaglandin F2α, and by demonstrating the potential of the technique for non-invasive evaluation of modifiers of lymphatic function. These new methods will enable high-resolution imaging and quantification of collecting lymphatic vessel function in animal models and may have future clinical applications.


Matlab software code for automated analysis of contractile parameters of CLVs
The Matlab code enables the identification of peaks and troughs in the recorded time series by using an automatic multiscale-based peak detection (AMPD) algorithm 1 . AMPD performs an automatic peak detection of non-stationary multiscale time series based on the analysis of the local maxima scalogram, a matrix comprising the scale-dependent occurrences of local maxima.
The Matlab program also determines the upper and lower envelopes by interpolating between the peaks and troughs and calculates the average value of these envelopes as the instantaneous mean.
For the interpolation, a piecewise cubic Hermite interpolating polynomial was used in order to ensure a smooth determination of the envelopes 2, 3 . Raw amplitude was calculated as an instantaneous measure of the difference between the upper and lower envelopes. This value was adjusted to a percent value of the mean to take into account differences in vessel size or brightness. For frequency (f) assessment, the number of peaks (N) in the selected interval was determined using AMPD and then the mean value of time intervals between consecutive peaks (∆N) was calculated. Finally, the frequency was determined according to f=1/∆N. Quantifications of the median percent amplitude and frequency in contractions per min were performed for the periods excluding the first and last 15 s of the movies. The exclusion of the beginning and end of the time series was performed since the applied peak-detection algorithm needed the beginning and end of the time series for the auto-tuning of parameters while not giving peak information for these time intervals.

Supplementary Movie 2 | Prox1-GFP CLV before and after infusion of lymphatic tracer.
Video shows GFP visualization of the same vessel and lymphatic valve before (1 st 8 s) and after (2 nd 8 s) infusion into the lymph node of P20D680 as in Video 1. Note that the contraction amplitude of the vessel is increased and that the valve function is activated by the infusion. Video is displayed at 10x normal speed.

Supplementary Movie 3 | High magnification imaging of Prox1-GFP CLV contractility.
Video at 63x magnification of GFP signal in a 6 week old Prox-GFP mouse of a flank collecting lymphatic vessel after infusion of P20D680. Video is displayed at 10x normal speed.  Figure 4B and is displayed at 30x normal speed.

Supplementary Movie 7 | Representative video of a P20D680 perfused CLV response to
addition of 10 µmol/L PGF2α. NIR video at 63x magnification before (up to 2 min on time scale) and after (from 2 to 8 min on time scale) treatment of 40 µL of 10 µmol/L PGF2α. Video corresponds to the data shown in Figure 4C and is displayed at 30x normal speed.
Supplementary Movie 8 | Representative video of a P20D680 perfused CLV response to addition of 60 µmol/L PGF2α. NIR video at 63x magnification before (up to 2 min on time scale) and after (from 2 to 8 min on time scale) treatment of 40 µL of 60 µmol/L PGF2α. Video corresponds to the data shown in Figure 4D and is displayed at 30x normal speed.
Supplementary Movie 9 | Representative video of a quiescent CLV after P20D680 perfusion and the response to addition of PGF2α. NIR video at 63x magnification before (up to 2 min on time scale) and after (from 2 to 6 min on time scale) treatment of 40 µL of 60 µmol/L PGF2α.
Video is displayed at 20x normal speed. Representative of n=5 independent experiments with PGF2α.
Supplementary Movie 10 | Representative video of a non-perfused Prox1-GFP CLV response to addition of 0.1% DMSO. GFP video at 63x magnification before (up to 2 min on