Micro-CT imaging of tumor angiogenesis: quantitative measures describing micromorphology and vascularization

Abstract

Angiogenesis is a hallmark of cancer, and its noninvasive visualization and quantification are key factors for facilitating translational anticancer research. Using four tumor models characterized by different degrees of aggressiveness and angiogenesis, we show that the combination of functional in vivo and anatomical ex vivo X-ray micro-computed tomography (μCT) allows highly accurate quantification of relative blood volume (rBV) and highly detailed three-dimensional analysis of the vascular network in tumors. Depending on the tumor model, rBV values determined using in vivo μCT ranged from 2.6% to 6.0%, and corresponds well with the values assessed using IHC. Using ultra-high-resolution ex vivo μCT, blood vessels as small as 3.4 μm and vessel branches up to the seventh order could be visualized, enabling a highly detailed and quantitative analysis of the three-dimensional micromorphology of tumor vessels. Microvascular parameters such as vessel size and vessel branching correlated very well with tumor aggressiveness and angiogenesis. In rapidly growing and highly angiogenic A431 tumors, the majority of vessels were small and branched only once or twice, whereas in slowly growing A549 tumors, the vessels were much larger and branched four to seven times. Thus, we consider that combining highly accurate functional with highly detailed anatomical μCT is a useful tool for facilitating high-throughput, quantitative, and translational (anti-) angiogenesis and antiangiogenesis research.

Copyright © 2014 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Figures

Figure 1. Study design

Four tumor models (A431, Calu-6, MLS, and A549) with differing degrees of angiogenesis were used to demonstrate the potential of combining in vivo and ex vivo μCT for highly accurate functional and ultra-high-resolution anatomical imaging of tumor angiogenesis. Using contrast-enhanced in vivo μCT, the rBV in tumors approximately 6 × 6 mm in size was determined noninvasively. The rBV values were then compared with those obtained with IHC by quantifying the area fraction of CD31+ blood vessels on three different sections for each tumor; both congruence and correlation were highly significant. After ex vivo imaging with Microfil perfusion, the three-dimensional micromorphology of tumor blood vessels was visualized at a resolution of approximately 3.4 μm; this allowed a highly detailed and quantitative analysis of the anatomical properties of the vascular network in tumors, as well as correlation of vessel size, vessel distribution, and vessel branching with the degree of angiogenesis by quantifying the amount of αSMA+ (mature) blood vessels using IHC.

Figure 2. Characterization of tumor growth and angiogenesis

A and B: Representative histological and immunofluorescence images of A431, Calu-6, MLS, and A549 tumors with H&E staining for histology (A) or with immunofluorescence staining (B) for CD31 (green) as a marker of blood vessels, for αSMA (red) as a marker of pericytes, and for Hoechst nuclear dye (blue). C and D: Differences in tumor growth (C) and blood vessel density and maturity (D) characterize the four models. Data are expressed as means±SD. n = 5 tumors per model. *P<0.05, **P<0.01, and ***P<0.001, two-tailed t-test. Original magnification: ×100 (B, insets).

Figure 3. In vivo and ex vivo μCT imaging of tumor angiogenesis

A-D: Contrast-enhanced in vivo μCT was used for anatomical and functional visualization and quantitative characterization of tumor angiogenesis. Numbers represent the vessel branching order. In the xenograft models with large numbers of mature blood vessels (MLS and A549), blood vessel branches up to the third order could be visualized; in models characterized by more angiogenic and less mature blood vessels (A431 and Calu-6), only first- and second-order blood vessel branches could be identified. The numbers within the images exemplify the rising order of vascular branches. E-H: After Microfil perfusion and vascular casting, ultra-high-resolution ex vivo μCT was performed with three-dimensional volume rendering, enabling the visualization and quantitative characterization of blood vessels with diameters as small as 3.4 μm, and blood vessel branches up to the seventh order. I-L: Two-dimensional cross-sectional images (x, y, and z planes) provide highly detailed information on blood vessel diameter, blood vessel density, and blood vessel distribution; tumors are the same as in panels E-H.

Figure 4. Congruence and correlation of functional in vivo μCT with IHC

A: Comparison of the model-dependent tumor rBV values determined using in vivo μCT and IHC. To properly assess the rBV in IHC, the vessel lumen was semiautomatically filled and quantified in six different FOVs (three for the core and three for the periphery) in three representative sections from each of five tumors per tumor model. B: Correlation of the rBV values obtained on in vivo μCT and IHC after semiautomatic vessel filling. For the 20 tumors, the correlation was highly significant (P < 0.0001), and the linear regression (α = 47 degrees) indicates a highly accurate and congruent determination of the rBV by in vivo μCT versus IHC. C: Correlation of the rBV values determined used in vivo μCT versus IHC was significant for all four tumor models (P < 0.05). D: Quantification of nonfilled CD31+ area fractions in IHC, exemplifying that, compared with filled vessel structures and to in vivo μCT, no significant differences were observed between the four tumor models used and that absolute rBV values are strongly underestimated. E and F: Correlation of nonfilled CD31+ area fractions in IHC with rBV values determined using in vivo μCT (E) and with semiautomatically filled CD31 area fractions (F), exemplifying poor congruence and correlation. Data are expressed as box plots ± SD (A, C, and D).

Figure 5. Quantitative ex vivo μCT imaging of tumor angiogenesis

A and B: Quantification of vessel diameters in the core and periphery of the four tumor models using IHC (A) and ex vivo μCT (B), exemplifying that vessels in more aggressive tumors (A431 and Calu-6), which are characterized by a more angiogenic and less mature vasculature, are smaller than vessels in less angiogenic and more mature tumors (MLS and A549). C: Correlation of vessel diameters determined using ex vivo μCT and IHC. D: Quantification of blood vessel diameter distribution within a particular size range, confirming that vessels in more aggressive and more angiogenic tumors were smaller and more homogeneous in size than in less aggressive and less angiogenic tumors. E and F: Ex vivo μCT-based quantification of the total number of blood vessel branches (E) and of the percentage of branches by increasing order (F), exemplifying that less aggressive and more mature tumors (MLS and A549) contained more branches and higher order branches per vessel than less mature tumors (A431 and Calu-6). Data are expressed as means ± SD (A, B, and D-F). **P < 0.01, ***P < 0.001.

Figure 6. Qualitative and quantitative comparison of tumor blood vessels in corresponding ex vivo μCT and IHC data sets

A and B: Immunofluorescence images and corresponding two-dimensional cross-sectional images from high-resolution ex vivo μCT imaging after Microfil perfusion and vascular casting of moderately vascularized A549 (A) and highly vascularized MLS (B) tumors. Boxed regions in the whole-tumor images (top row) are shown at higher magnification in the middle and bottom rows. Immunohistochemical staining was performed using antibodies against CD31 (blood vessels; red), αSMA (pericytes; green), and Hoechst nuclear dye (blue). C and D: Correlation of vessel diameters determined using corresponding IHC and ex vivo μCT data sets, exemplifying a highly significant correlation (P < 0.0001) and linear regression α values close to 45 degrees for both A549 (C) and MLS (D) tumors.