Morphologic changes of mammary carcinomas in mice over time as monitored by flat-panel detector volume computed tomography

Abstract

Noninvasive methods are strongly needed to detect and quantify not only tumor growth in murine tumor models but also the development of vascularization and necrosis within tumors. This study investigates the use of a new imaging technique, flat-panel detector volume computed tomography (fpVCT), to monitor in vivo tumor progression and structural changes within tumors of two murine carcinoma models. After tumor cell inoculation, single fpVCT scans of the entire mice were performed at different time points. The acquired isotropic, high-resolution volume data sets enable an accurate real-time assessment and precise measurements of tumor volumes. Spreading of contrast agent-containing blood vessels around and within the tumors was clearly visible over time. Furthermore, fpVCT permits the identification of differences in the uptake of contrast media within tumors, thus delineating necrosis, tumor tissues, and blood vessels. Classification of tumor tissues based on the decomposition of the underlying mixture distribution of tissue-related Hounsfield units allowed the quantitative acquisition of necrotic tissues at each time point. Morphologic alterations of the tumor depicted by fpVCT were confirmed by histopathologic examination. Concluding, our data show that fpVCT may be highly suitable for the noninvasive evaluation of tumor responses to anticancer therapies during the course of the disease.

Figure 1

Growth rate of an orthotopically implanted tumor depicted in vivo by 3D reconstructions of fpVCT data sets. (A) Representations of volume rendering of skin in the tumor area after virtual removal of fur. Visualization of the enlargement of a representative mammary carcinoma by repeated fpVCT scans in combination with contrast agent 21, 28, 35, and 42 days after MDA-MB-231 cell implantation. (B) Corresponding semiautomatically segmented tumors. The indicated volumes were automatically determined. (C) Growth rates of five MDA-MB-231 tumors for 3 weeks. (D) Comparison of automatically determined tumor volumes using fpVCT data sets (rhombuses) with caliper measurements postmortem (squares). Although tumor volumes were underestimated by caliper measurements, the data show the proportionality between both methods.

Figure 2

Tumor vessel development over time visualized in vivo using 3D fpVCT data sets. (A) Depiction of contrast agent-containing tumor vessels and their distribution and bifurcations both in the periphery and within a developing orthotopic mammary tumor by repeated fpVCT scans of a representative SCID mouse. Tumor vessels possessed small diameters on day 21 and their density increased by day 28. Tumor vessels appeared most enlarged after 35 days, followed by a decrease in the number of vessels with high density 1 week later. The tumor is framed. (B) In an MIP presentation of the final scan, blood vessels within the tumor were not visible, suggesting the loss of central blood vessels due to necrotic tissue after this period (left). One kidney is indicated (K). (C) Tumor vessel formation of a representative subcutaneous mammary carcinoma in combination with contrast agent (right). Tumor vessels were hardly visible 20 days after R30C tumor cell implantation and appeared after 25 days. The density of vessels around the tumor increased after 28 days and even more after 31 days. (B) An MIP presentation of vessel densities within the tumor indicates that a diffuse lattice of vessels infiltrated the tumor tissue (right). (D) Visualization of a single blood vessel supplying the orthotopic tumor (framed) and (E) the venous port of the subcutaneous tumor. The tumor is framed. (D) In the dorsal aspect of a tumor-bearing mouse after orthotopic implantation of MDA-MB-231 cells, a blood vessel (black arrow) coming from the tumor (white arrow) can be traced to the kidneys (K). In a higher magnification and after subtraction of the spine, a connection (arrowhead) between the tumor vessel (arrow) and the upper lumbar artery is visible. Aorta (A) and vena cava (V) are depicted as parallel running structures. (E) A large efferent vessel (white arrow) of the subcutaneous tumor (black arrow) discharges in the brachiocephalic vein (arrows) as shown in detail (right).

Figure 3

Quantitative and qualitative analyses of the density ratios within an orthotopic tumor in vivo using fpVCT. (A) A 3D volume-rendering image of the tumor in situ (arrow) 42 days after orthotopic implantation of MDA-MB-231 cells. Superficial layers were subtracted. (B) A 2D fpVCT image of the same mouse in a coronal view; note that the tumor is framed. (C) Semiautomatic segmentation of the tumor after subtraction of all additional data sets of the mouse. (D) Histogram of the percentage of tumor tissue within the tumor volume versus its density in HU measured by fpVCT. (E) Inflection points of the curve were determined automatically. Density values between two inflection points (divided by black marks) belong to a specific density portion, marked with different colors. The blue distribution indicates a fraction of low density, red indicates a portion of an intermediate-density range, and white fraction indicates the portion of highest density. (F) These density portions within the tumor volume were assumed to be three overlapping Gaussian distributions that possessed their specific peaks in different density regions of the histogram. (G–I) Volume-rendering images of the tumor in three serial median slices. Distribution of the colors corresponds to the colors of the histogram and suggests to represent the central necrotic area in blue as a low-density region, the surrounding tumor tissue in red, and the contrast agent-containing blood vessels in white with the highest density on the surface of the tumor. Scale bar in (I), 5 mm.

Figure 4

Comparison of images generated by fpVCT with both macroscopic and histopathologic examinations. (A) A 3D fpVCT image of an orthotopic mammary tumor (arrow) 6 weeks after tumor cell implantation in situ. (B) Macroscopic appearance of the tumor (arrow) in situ at the time of dissection. (C) An fpVCT-generated representative 3D central section depicts the halves of the tumor with their density profile: the central necrotic area (blue, black arrow) and intact tumor tissue, including densely packed mammary gland tissue (red, white arrow). (D) Macroscopic appearance of a central slice of the dissected tumor confirmed the existence of necrotic tissue (black arrow) between the intact tumor and mammary gland tissues (white arrow). Note that the analog distribution of these features in the fpVCT image is indicated with arrows in (C). (E) An fpVCT volume-rendering presentation of a different mouse bearing an orthotopic mammary tumor (blue). (E, detailed view, left) Serial sections of the tumor virtually cut off the fpVCT data sets that were generated with contrast agent on the day of dissection. Visualization of densities within tumor sections demonstrates a distinct central necrotic region (blue), surrounding tumor tissue (red), and a cross section of a blood vessel (top left, arrow). (E, detailed view, top right) Median paraffin section of the same tumor stained with H&E closely corresponds to the predicted distribution of the morphologic features necrosis (N), intact tumor tissue (T), and a vessel (V, arrow) depicted by the fpVCT data sets as shown in (E, top left). At a 2.5-fold higher magnification (E, bottom right), the display window according to the frame in (E, bottom left) shows the occurrence of intact tumor tissue (T) between an area of central necrosis (N). Scale bars: bottom and top left, 4 mm; top right, 3 mm; bottom right, 800 µm.

Figure 5

Comparison of growth kinetics and morphologic changes in both necrotic and nonnecrotic tumors analyzed by fpVCT imaging in vivo. (A) Graphic representations of density distributions within a tumor with developing necrosis over time. The state of vascularization of this tumor is depicted in Figure 2A. At 21 days after implantation, a wide Gaussian curve in a negative HU range indicates a lack of blood vessels in the mammary fat pad. After 4 weeks, a small bell-shaped curve with a homogeneous distribution of only one density portion in a positive HU range is detectable. During days 35 and 42, the Gaussian distribution divides into two components, one of low density (developing necrosis) and one of higher density (tumor tissue and contrast agent-containing blood vessels). (B) Corresponding serial sections of the 3D visualization of the tumor were generated using fpVCT. Similar to the corresponding histograms (A), necrotic tissue developed regularly (blue) and displaced intact tumor tissue (red). Surrounding blood vessels (white) detected by contrast agent only occur in the tumor periphery (B, bottom). (C) The histograms for the nonnecrotic tumor showed no movement into the negative HU range between days 20, 25, 28, and 31, although the curve spreads at the latest time point because of an increase of different density portions. (D) Corresponding serial sections of the 3D visualization of the tumor are shown. As depicted in the corresponding histograms, no central area of necrosis was observed in this tumor over time.

Figure 6

Morphologic structures of both tumor types depicted by fpVCT compared with histopathologic analysis. (A and B) Overlays of the histograms over time allowed the comparison of the shift of the curves during tumor development. (A) Necrotic tumor: 21 days after orthotopic implantation of MDA-MB-231 cells, the tumor volume primarily consisted of low density, which is explained by its lack of receptivity toward the contrast agent. After 28 days, the histogram depicts the characteristic shift to the positive HU sector. At this time point, the tumor consisted primarily of intact tumor tissue and had a threefold greater volume than the previous week. After days 35 and 42, the curve shifts progressively into the negative HU sector, suggestive of the development of necrosis. (B) Nonnecrotic tumor: 20 days after subcutaneous implantation of R30C cells, the tumor volume primarily consisted of an area of relatively low density similar to the necrotic tumor in (A) at the first time point. After 25 days, the tumor volume increased nearly twofold. Until day 28, a clear shift of the graph to the positive HU sector remained throughout the peak of the curve; after 31 days, it shifts broadly in a negative direction. (C–H) fpVCT-generated images of the necrotic tumor (C and E) and the homogeneous nonnecrotic tumor in situ (F and H). H&E-stained paraffin sections of the tumors depict the distinct central area of necrosis of the orthotopically implanted tumor (D) and the generally intact tumor tissue of the subcutaneous tumor (G). Note that the latter tumor grew in multiple lobes (F, arrow) and that only one lobe was analyzed in detail (G and H). The predicted distributions of necrosis as illustrated in blue and the intact tissue as depicted in red within the tumors are determined using fpVCT (E and H). Scale bars: D, 3 mm; E, 6 mm; G, 800 µm; H, 1600 µm.