Quantification of Entire Tumor Vascular Normalization in Response to A VEGF Inhibitor Vascular Normalization in Response

A comprehensive vascular analysis is crucial for extending our understanding of angiogenesis and to evaluate the efficacy of anti-angiogenic therapies in cancer. No analysis based upon the entire tumor vasculature has been established. We have developed several morphological imaging markers to analyze entire vascular structures from a human non-small cell lung carcinoma subcutaneous xenograft using micro-computed tomography. The imaging markers aim to condense complicated three-dimensional vascular structures to simple numbers and tables. The design of the imaging markers was motivated by the physiology and function of vascular systems. We tested the markers on 30 mice in four groups: one-week and two-week vehicle groups; one-week and two-week Stent administration groups. Vascular normalization after anti-angiogenic treatment was quantified. The imaging markers verified that micro-vessel sprouting followed by dilation and large-vessel segment enlargement occurred in tumor progression. This methodology can assist researchers to objectively and quantitatively validate the efficacy of antiangiogenic compounds and combinational therapies..


Introduction
Angiogenesis is associated with numerous diseases and physiological processes in the body [1][2][3]. Recent discoveries also elucidate the connection and common mechanisms between angiogenesis and other networks [3][4][5][6]. Tumor-induced pathological angiogenesis dictates the growth of many solid tumors. Uncontrolled tumor cells require excessive nutrient and oxygen supply to survive and metastasize [7]. When normal physiological vascular networks around tumors cannot compensate for the demand, unregulated growth factors from tumor cells trigger abnormal nascent vessel sprouting and irregular pruning leading to over vascularization. The immature vessel networks are heterogeneous and leaky, resulting in low delivery efficiency to surrounding tissues compared to normal vascular structures [8].
Targeting tumor angiogenesis as cancer therapy was proposed by Folkman in 1971. The Vascular Endothelial Growth Factor (VEGF) family and receptors have proved to be essential to physiological and pathological angiogenesis [9]. VEGF administration also induces lymph angiogenesis [10][11][12][13]. Clinical studies showed that antiangiogenic therapy combined with other cancer therapies (such as cytotoxic drugs and radiation therapy) yielded better survival rates than monotherapy [13][14][15][16]. The vascular normalization hypothesis supplies an explanation of why combinational therapy results in better overall survival than monotherapy. It also suggests that the degree of vascular normalization due to anti-angiogenic therapy may dictate the efficacy of the following cytotoxic therapy. In order to yield better survival rates from the combinational therapy paradigm, quantification of vascular morphology during the antiangiogenic regimen is critical [16,17].
We used Sutent in this study as an anti-angiogenic compound to quantify the vascular normalization in response to two regimens. Sutent (SU11248, sunitinib malate, Pfizer, Inc., New York, NY, USA) is a small-molecule, multi-target tyrosine kinase inhibitor with high affinity for the PDGF and VEGF receptors [18]. Dual delivery of VEGF and PDGF-BB returned more mature vessel formation than either single growth factor. Sutent has demonstrated anti-tumor activity and inhibition of angiogenesis in clinical trials [19,20].
It was approved by the FDA in January of 2006 to treat renal cell carcinoma and imatigib-resistant Gastrointestinal Stromal Tumors (GIST). Imaging technology has advanced significantly over the last decade for drug research and clinical diagnoses. Various imaging modalities with proper imaging analysis methods have been utilized to reveal the function and anatomy of vascular structures in differing spatial and temporal resolutions [21,22]. Contrastenhanced CT is able to reconstruct three-dimensional (3-D) vascular structures with resolution of a few microns. In this study, the isotropic voxel dimension of all images in the vehicle and the   This study aimed to develop imaging parameters to objectively quantify entire 3-D vascular configurations and to differentiate the vascular remodeling due to treatment with anti-angiogenic agents.
The hope is that the imaging markers can differentiate vascular evolution during tumor progression and during treatment with different anti-angiogenic therapies. The imaging markers can be used to characterize the response to anti-angiogenic therapies not only for cancer but also for other angiogenesis-related diseases into different aspects of vascular structure. Furthermore, correlation between the molecular interactions and entire vasculature morphological remodeling via imaging markers can be established.

Tumor Xenograft
Female CB-17 SCID mice, 6-7 weeks old, (Charles River, Wilmington, MA) were acclimated for one week prior to the study.

Contrast Agent Perfusion
Nude mice carrying intradermal tumor xenografts of A549 human lung cancer cells were used in this experiment. The mice were anesthetized with 3% isoflurane inhalation and local hair was removed with Nair hair remover. The animals were placed on a drainage tray and the core temperature was maintained between 37°C and 39°C. Thoracotomy was performed, and a 23-g needle was immediately inserted into the left ventricle, while the right atrium was cut for drainage. Systemic perfusion was performed with a pre-

Micro-CT Scanning
Each tumor xenograft with surrounding tissue was cut off and placed in a 15-mm tube (without medium) and scanned with the explore Locus SP Micro-CT Scanner (GE Healthcare). The scan parameters used included a tube voltage of 80 kVp, 400 views acquired with an angle increment of 0.5o, a total tube current-time product of 110 mAs, 0.020" aluminum filtration, and a 33-minute scan time. Calibration was performed with air-, water-, and bonemimicking materials in a calibration phantom. Bright and dark fields were collected for correction of the acquired images. The twodimensional projections were reconstructed into a 3D volume with 16-m isotropic voxels using the explore Reconstruction Utility.

Imaging Analysis
The raw 16-bit volumetric tumor images were loaded into the workspace of Analyze 7.0 (Mayo Clinic, Rochester MN) in unsigned 8-bit format. High spatial-frequency noise was removed by using a 3x3x3 low-pass filter. The 3-D vascular structure extraction was completed using the Tree Analysis module of Analyze 7.0 [23]. The intensity threshold ranged from 130 to the highest voxel intensity.
The shortest skeleton branch was set to be either 4 or 7, while the minimum tree length was 25. Commonly, more than one tree was generated. The first tree, however, was extensive enough to represent the whole vascular structure. We tested the performance of the imaging markers based upon one tree and all the trees, and the outcomes were close. In the study, we considered all trees if the computation time for the imaging marker calculations was not demanding. A single vessel in this study was defined to be from the root to an end node of the tree. Accordingly, the number of end nodes defined the number of vessels of a vascular tree.
Segments of a vessel were defined between two branch points or

Vessel Length Distribution of Vehicle and Sutent-treated Groups
Excessive vessel sprouting from a pre-existing vascular network is a vital hallmark of angiogenesis in tumors. Vessel length calculation from a 3-D vasculature image is a direct approach to quantify angiogenesis. Our vessel length imaging marker measures the normalized vessel length distribution, defined as the distance from the root of a vascular tree to the end nodes (Supplementary

Vessel Tortuosity Distribution
During the progression of the tumor, the vascular network becomes chaotic and tortuous. Direct or indirect anti-angiogenic therapies prune immature vessels to reduce the vascular tortuosity.
The normalized network should deliver drugs and nutrients to tumor cells with better efficiency. We applied a simple formula to determine the modification of the entire vascular tortuosity distribution during tumor growth and the response to the Sutent regimens (Supplemental Figure 1, Supplementary Methods).
More low tortuosity vessels were found in the Sutent-treated groups than in the vehicle groups ( Figure 3). In contrast, Figure   3 shows that the vehicle groups had a higher population of more tortuous vessels than the Sutent-treated groups. Table 1 lists the details of the tortuosity distributions in Figure 3 grouped into three domains (low tortuosity, high tortuosity, and ultra-high tortuosity).
The vessels with tortuosity between 3 and 12 were categorized as low tortuosity; the vessels belonging to the high tortuosity domain had tortuosity between 13 and 70; the ultrahigh tortuosity domain contained the vessels with tortuosity beyond 71. The quantitative alteration of the tortuosity in the three domains was compared between groups (Table 1).

Figure 3:
Vessel tortuosity histograms of vehicle and Sutent-treated groups. Tortuosity is a dimensionless parameter. The tortuosity histogram of a group is normalized by the total number of vessels from the group as with the vessel length histogram. The bin size of the tortuosity histogram is one. More than 76 percent of the vessels in the one-week Sutent  Figure 4A). In the week two comparison, the median vehicle-group volume was enlarged to 82.5 mm 3 while the median volume of the treated group shifted to 30.5 mm 3 . Since the notch of vehicle and treated groups did not overlap, the median volume difference between vehicle and treated groups evaluated at the same time point should be above 95% confidence ( Figure 4A).
Although the two-week treated vascular volume was greater than the one-week treated group, the median volume ratio of the treated to the vehicle group at week two was less than the ratio at week one. The significant volume increase of the two-week vehicle group over the one-week vehicle group could be the consequence of both angiogenic sprouting and vessel dilation during tumor growth.

Micro-Vessel Lumen Surface Area
We designed a micro-vessel lumen surface area marker to investigate the change of lumen surface area between the vehicle and treated groups (Supplementary Methods). Three diameter thresholds were defined to evaluate the total lumen surface area contributed by vessel segments (Supplementary Figure 1) in a 3-D vascular structure with diameters less than the assigned threshold. This analysis also leads to the diameter distribution.  Figure 4B). The average lumen surface areas using the 50m and 70m thresholds for the one- week vehicle group were less than those for the two-week vehicle group. The average lumen area for the one-week vehicle group using the 107m threshold, however, became greater than that for the two-week vehicle group. Figure 4B: Average micro-vessel lumen surface area.
Column heights indicate the average micro-vessel area contributed from vessel segments with diameters less than thresholds of 50, 70, and 107m. The error bars are the standard deviations of the groups. One outlier was removed in the analysis.
Since more sprouting was observed according to the vessel length marker, we had expected that the lumen surface area of the two-week vehicle group would be larger than that of the one-week vehicle group. One possible explanation for this result is that the majority of the tumor-induced micro vessels may have been dilated in the two-week vehicle group. Therefore, the surface area contributed by vessel segments with average diameters less than 50 and DOI: 10.26717/BJSTR.2020. 24.004054 70m was less than that of the one-week vehicle group. However, when the diameter threshold was large enough to consider the most dilated micro vessels, the lumen surface area of the two-week vehicle group exceeded that of the one-week vehicle group.

Large Vessel Segment Diameter of Vehicle Groups
To further investigate dilation during tumor progression, we    Figure 4A. The notches of Sutent-treated groups do not lie over the notches of vehicle groups. This suggests that the true median difference between the Sutent-treated groups and the vehicle groups is with 95% confidence.

Discussion
We week one to week two. In contrast to our intuition and the above observation, the micro-vessel lumen surface area of the two-week vehicle group was less than that of the one-week vehicle group when considering vessel segments with diameters less than 70m.
Further micro-vessel sprouting in the two-week vehicle group was illustrated by the vessel length distribution.
When the larger diameter threshold (107m) was applied, the lumen surface area became larger than that of the one-week vehicle group. This counterintuitive observation can be explained by vessel dilation during tumor progression, which explains the contrasting observations revealed by the lumen surface area marker and the vessel length/vascular volume markers. The results of this study also suggest that micro-vessel dilation after two weeks was more intense than after one week. Dilation in the large vessel realm was also observed. This indicates that tumorinduced angiogenesis remodels the whole vasculature in tumors and suggests that sprouting and dilation mechanisms alternatively dominate at different stages. It is tempting to speculate that tumorinduced angiogenesis is a damped cycle of sprouting and dilation mechanisms. When dilation following sprouting cannot satisfy the demand from tumor cells, another excessive sprouting cycle begins.
Tumor-induced angiogenesis also triggers the dilation of largevessel segments to compensate for the growth of micro vessels.
However, how the vessel dilation signal propagates from micro vessels to upstream large vessel segments is unknown.
Angiogenesis is essential not only in cancer but also in other diseases. Unlike conventional micro-vessel density parameters from 2-D microscopy images of local tissue, our 3-D imaging markers consider the entire vasculature and supply more comprehensive analyses on vascular remodeling during tumor progression and in response to anti-angiogenic therapy. Micro-vessel density can be used as a prognostic marker, not as an efficacy marker for antiangiogenic treatments [36,37]. Although many imaging markers in this study could be associated with functions of vascularity, the correlation between morphological markers and functional markers should be further investigated.