Vascular patterning of subcutaneous mouse fibrosarcomas expressing individual VEGF isoforms can be differentiated using angiographic optical coherence tomography

Abstract

Subcutaneously implanted experimental tumors in mice are commonly used in cancer research. Despite their superficial location, they remain a challenge to image non-invasively at sufficient spatial resolution for microvascular studies. Here we evaluate the capabilities of optical coherence tomography (OCT) angiography for imaging such tumors directly through the murine skin in-vivo. Data sets were collected from mouse tumors derived from fibrosarcoma cells genetically engineered to express only single splice variant isoforms of vascular endothelial growth factor A (VEGF); either VEGF120 or VEGF188 (fs120 and fs188 tumors respectively). Measured vessel diameter was found to be significantly (p<0.001) higher for fs120 tumors (60.7 ± 4.9μm) compared to fs188 tumors (45.0 ± 4.0μm). The fs120 tumors also displayed significantly higher vessel tortuosity, fractal dimension and density. The ability to differentiate between tumor types with OCT suggests that the visible abnormal vasculature is representative of the tumor microcirculation, providing a robust, non-invasive method for observing the longitudinal dynamics of the subcutaneous tumor microcirculation.

Keywords: (100.2000) Digital image processing; (110.4500) Optical coherence tomography; (170.2655) Functional monitoring and imaging; (170.3880) Medical and biological imaging.

Figures

Fig. 1

Experimental setup within a plastic chamber which was heated to 32°C internal temperature. A) Rodent facemask for administration of isoflurane gaseous anesthesia. B) CD-1 Nude mouse. C) Plastic standoff which gently contacts the skin around the subcutaneous tumor. D) The OCT imaging probe (Vivosight). E) Feedback controlled heated mat. F) Rectal temperature probe (Feeds back to the heated mat). G) Mobile clamp for repositioning of the OCT imaging probe.

Fig. 2

En-face svOCT images of an fs188 tumor before (Left) and after (Right) wavelet/FFT filtering was performed using a Daubechies wavelet to a decomposition level of 5. The colors correspond to the depth of the detected vessels, red vessels are 0-300μm and green vessels are 300-600μm beneath the skin surface.

Fig. 3

Processing steps for the quantification of svOCT data. A) En-face svOCT image captured from a subcutaneous fs-120 tumor 17 days post-implantation. Dashed box shows zoomed section from B-G. B) Zoomed section of the en-face svOCT image. C) The result of the hessian-based filtering algorithm. D) The result of B*C, improved vascular contrast against the background. E) Binary threshold in green overlaid on the original image. F) Skeleton in blue overlaid on the original image. G) Map of vessel diameter calculated using the binary threshold and the skeleton data from E and F.

Fig. 4

A selection of 6x6mm en-face svOCT images. A-D) Images of baseline murine skin vasculature without the presence of a tumor. E-L) Images of established subcutaneous tumor vasculature, each image is of a separate tumor captured once the largest tumor diameter exceeded 10mm. Middle row (E-H) shows tumors expressing only the VEGF120 isoform (fs120) and bottom row (I-L) shows tumors expressing only the VEGF188 isoform (fs188). All images were captured from different animals. The colors correspond to the depth of the detected vessels, red vessels are 0-400μm and green vessels are 400-800μm beneath the skin surface. E-L) Number of days post-implantation > 14 days.

Fig. 5

Top and middle rows) Depth encoded short-term longitudinal svOCT images of both an fs120 and an fs188 tumor over a period of 5 days. Images have been elastically registered together using UnwarpJ [23] such that the same vessels align on subsequent frames. Bottom row) 4x4mm (Zoomed) en-face svOCT images showing long-term longitudinal vascular progression from pre- tumor implantation to 15-days post- tumor implantation. Each separate row represents longitudinal data that was captured from one unique animal. The colors correspond to the depth of the detected vessels, red vessels are 0-400μm and green vessels are 400-800μm beneath the skin surface. The white number in the lower left corner of each image corresponds to the number of days post-tumor implantation that the image was captured.

Fig. 6

Line plots showing the variation in measured vessel length per square mm as a function of time within subcutaneous tumors expressing either the VEGF120 isoform (blue) or the VEGF188 isoform (red). The standard deviation in the measured mean vessel length for each animal is calculated as a function of time, and represents how much variance is visible within the measurement. The average of these standard deviations across all four fs120 mice (1.4mm−1) is higher than those in the fs188 cohort (0.4mm−1), however this result does not reach statistical significance (p = 0.063).

Fig. 7

Comparing the depth penetration of OCT against histological sections of murine rear-dorsum skin. A) H&E stained section of healthy skin. B) OCT B-scan of healthy skin (Different animal to A). C) H&E stained section of the skin above an fs120 tumor, showing the lack of the muscular layer. D) OCT B-scan of the skin above an fs120 tumor (Same animal as C). E) H&E stained section of skin with an fs188 tumor visible beneath the muscular (panniculus carnosus) layer of the skin. F) OCT B-scan of the skin above an fs188 tumor (Same animal as E).

Fig. 8

Variation in the thickness of the hypodermis (fat) layer within healthy skin compared to that of the skin encapsulating ~12mm diameter fs188 and fs120 tumors. The fatty layer is significantly thicker in healthy skin than both fs188 and fs120 skin, furthermore this layer is also significantly thicker in fs188 skin than fs120 skin. A thicker fat layer appears to correlate with an increase in the number of hair follicles present, reducing the depth penetration of the OCT imaging beam. (columns, mean; bars, standard deviation; crosses, datapoints). All groups contain n = 7 samples, significance calculated using a one-way ANOVA followed by a Tukey-Kramer HSD test.

Fig. 9

CD31 immunohistochemistry demonstrating the presence of endothelial cells lining the vessels within the rear-dorsum skin of CD1 nude mice. A-C) H&E stained serial sections of healthy, fs120 and fs188 skin respectively. D-F) CD31 immunostained serial sections of healthy, fs120 and fs188 skin respectively. Endothelial cells are stained in brown. Red arrows represent the largest visible vessel lumen. Red boxes represent the zoomed sections from G-I. G-I) Zoomed view of vessels within the hypodermis of the CD31 stained sections. The fs120 tumor shown here was excised 14 days post-implantation and is a different tumor to the one shown in Fig. 9. The fs188 tumor shown here was excised 20 days post-implantation, and is the same tumor shown in Fig. 9.

Fig. 10

The variation in quantitative vessel parameters between fs120 tumors (n = 9) and fs188 tumors (n = 8) at the study endpoint. Columns: The average value of each respective quantitative parameter across the entire fs120 or fs188 group. (bars, standard deviation). Statistical significance calculated using an independent two-sample t-test between the fs120 and fs188 data sets.