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THORACIC IMAGING

Tumor Angiogenesis and Dynamic CT in Lung Adenocarcinoma: Radiologic–Pathologic Correlation

Tateishi, Ukihide; Nishihara, Hiroshi; Watanabe, Satoshi; Morikawa, Toshiaki; Abe, Kazuhiro; Miyasaka, Kazuo

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Journal of Computer Assisted Tomography: January-February 2001 - Volume 25 - Issue 1 - p 23-27
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Abstract

Dynamic CT of pulmonary nodules provides quantitative information about blood flow pattern and is a diagnostic method in the differential diagnosis (1,2). Malignant neoplasms enhance more significantly than granulomas and benign neoplasms (1). The blood supply of malignant pulmonary nodules is qualitatively and quantitatively different from that of benign nodules (2). The peak attenuation (APA) of tumor reflects intratumoral microvessel densities (MVDs) in small peripheral lung carcinomas on dynamic CT (3).

Angiogenesis is a complex process, critical to the growth and metastasis of malignant tumors. Angiogenesis is mediated by factors released by tumors and/or tumor-associated inflammatory cells (4–7). Vascular endothelial growth factor (VEGF), a 34 to 42 kDa heparin-binding, dimeric, disulfide-bonded glycoprotein, is known as a vascular permeability factor and plays an important role in tumor angiogenesis (4–7). MVD measurements with immunohistochemical staining techniques are used to measure angiogenic activity (4,5). MVD correlates with clinical stage and acts as an independent prognostic factor in many types of tumors (4–9). VEGF expression was significantly associated with MVD of non-small cell lung cancer, especially in lung adenocarcinoma (10–13).

The correlation between dynamic CT imaging and tumor angiogenesis has not been described before. In this study, we investigated the VEGF-related neovascularization in lung adenocarcinomas and evaluated the correlation between dynamic CT and pathologic findings.

MATERIALS AND METHODS

Patients

Thirty-five consecutive patients with lung adenocarcinoma (18 men, 17 women; age range 37–76 years, mean age 58.7 years) were evaluated retrospectively (Table 1). All patients underwent surgery, and tissue samples were available to be studied immunohistochemically in our institute. The duration between dynamic CT and surgery was within a week. No patients received any therapy before surgery, such as chemotherapy.

TABLE 1
TABLE 1:
Characteristics of lung adenocarcinoma

Dynamic CT Scan

Dynamic CT scans were obtained from the best demonstrated level of lung adenocarcinoma with use of an Aquilion CT scanner (Toshiba, Tokyo, Japan; 120 kVp, 150 mA). Iodinated nonionic contrast material (iopamidol 300, Iopamiron; Nihon Schering, Osaka, Japan) was administered at a rate of 3 ml/s for a total of 100 ml with an autoinjector (Auto Enhance A250; Nemoto Kyourindou, Tokyo, Japan). The section thickness was 2 mm, and scanning time was 1 s. The APA (i.e., the maximum value of the time-attenuation curve) was defined as peak attenuation minus baseline precontrast attenuation. With an injection rate of 3 ml/s, average transit time in the thoracic vasculature is within 30 s and average time of arrival of APA is within 60 s (1). Changes of the time-attenuation curve within the first 2 min have clinical importance. Patients underwent dynamic CT with breath-holding for 20 s. Three scan times were conducted after injection of contrast material: 0–20, 35–55, and 120–140 s for each patient. A normal reconstruction algorithm without edge enhancement was used for dynamic scanning (window width 350 HU, window level 40 HU).

Time-attenuation curves were created with circular regions of interest (ROIs) drawn over the tumor, aorta (or left subclavian artery if the aorta was not included in the section), and pulmonary artery. The ROI was drawn as large as possible to minimize noise but with care to avert partial volume effect. The diameter of the ROI was ≈70% of the diameter of tumors with this criterion. If the proper scan level was not attained because of inadequate respiration, the image was eliminated from the data analysis.

Pathologic Study

Tumor tissue specimens were fixed with 10% buffered formalin and embedded in paraffin. Five-micron-thick sections were mounted on silanized slides (Dako Japan, Kyoto, Japan) and deparaffinized with xylene and ethanol. Sections were pretreated in 10 m M citrate buffer (pH 6.0) for 15 min at room temperature before the immunohistochemical staining of CD34 and VEGF to retrieve the antigen. To remove endogenous peroxidase activity, the sections were soaked in absolute ethanol containing 0.3% hydrogen peroxide for 15 min at room temperature. To suppress nonspecific binding, the sections were incubated with 1.5% nonimmune goat serum for 20 min. The sections were then incubated with mouse monoclonal antibody of CD34 (5 μg/ml; Histofine, Nichirei, Japan) and with rabbit polyclonal antibody to the N-terminus of VEGF (5 μg/ml; anti-VEGF rabbit IgG affinity purified; IBL, Japan) for 24 h at room temperature. After being washed with phosphate-buffered solution (PBS), the sections were incubated with avidin-biotin-peroxidase complex (Histofine) for 30 min and washed once more with PBS. The sections were finally incubated with 3,3-diaminobenzidine (Simplestain DAB; Nichirei). Negative controls were carried out by omitting the primary antibody and substituting the primary antibody with an irrelevant antibody. No significant immunohistochemical reaction occurred in the control sections. Counterstaining was performed with hematoxylin. To assess intratumoral MVD, immunohistochemical reactivity for CD34 was evaluated (4–13). We assessed delineated CD34-positive cells as microvessels (size 0.02–0.10 mm). Stained vessels were counted in a ×200 microscopic field, and the averages of MVDs counted in 10 fields were calculated.

We used a score system described by Mattern et al. (10). We evaluated immunohistochemical expression of VEGF corresponding to the sum of both staining intensity (0 = negative, 1 = weak, 2 = intermediate, 3 = strong) and percentage of positive cells (0 = 0% positive cells, 1 = <25% positive cells, 2 = 26–50% positive cells, 3 = >50% positive cells). The sum of staining intensity plus percentage of positive cells reached a maximum score of 6. A score of >3 was the value of a positive immunohistochemical survey (10).

Statistical Analysis

Data are expressed as means ± SD. The Student t test was used for analysis of two unpaired samples. An a priori level of significance was set at a p value of <0.05.

RESULTS

Mean size, MVD, and APA of dynamic CT of lung adenocarcinoma are shown in Table 1. The MVDs were assessed in the most intense areas of neovascularization by immunohistochemical analysis of CD34. Delineated CD34-positive cells were counted as microvessels within tumors (Fig. 1C).

FIG. 1.
FIG. 1.:
Case of a 73-year-old woman with well differentiated adenocarcinoma. A: Dynamic CT image 140 s after administration of contrast agent reveals APA of 50 HU. B: Hematoxylin-eosin-stained specimen demonstrates well differentiated adenocarcinoma. C: Immunohistochemical staining of anti-CD34 antibody is shown. Delineated CD34-positive cells are counted as microvessels (arrow). D: Immunohistochemical staining of anti-vascular endothelial growth factor (anti-VEGF) antibody is shown. There are positive findings for VEGF in the cytoplasm of adenocarcinoma cells (arrow).
Figure 1
Figure 1:
Continued
Figure 1
Figure 1:
Continued
Figure 1
Figure 1:
Continued

The APA of lung adenocarcinoma correlated positively with MVD (r = 0.689, p < 0.0001).

Vascular Endothelial Growth Factor

The immunoreactivities of VEGF were found within tumor cells (Fig. 1D). A part of fibroblasts and smooth muscle cells within tumors have positivity for VEGF as well. Positiveness of VEGF expression was 63% of lung adenocarcinoma. The mean APA of VEGF-positive tumors was statistically higher than that of VEGF-negative tumors (p < 0.05) (Table 1). The mean APA of 22 VEGF-positive adenocarcinomas correlated positively with MVD (r = 0.707, p < 0.0001), whereas that in 13 VEGF-negative lung adenocarcinomas did not (r = 0.261, p = 0.3987) (Fig. 2). There were significant differences in the mean MVD between VEGF-positive and -negative lung adenocarcinomas (p < 0.05).

FIG. 2.
FIG. 2.:
Relationship between APA of dynamic CT and microvessel density (MVD) in vascular endothelial growth factor (VEGF)-positive lung adenocarcinoma.

DISCUSSION

Dynamic CT analyses of pulmonary nodules have been performed for differential diagnosis (1–3). Contrast enhancement of malignant pulmonary nodules is higher than that of benign nodules (1). There are large, dilated lacunae derived from bronchial arteries in primary pulmonary tumors (14). These histologic findings are considered to have a relationship with dynamic CT images of pulmonary nodules (1–3).

Transport time after injection reveals contrast material beginning to enter the intravascular space in the lung in about 10 s via the pulmonary arteries and in 11–19 s via the bronchial arteries (15). More than half of the injected dose had reached the extravascular space 60 s after injection in most tissues, including lung (15). All the tumors in our cases reached APA within 60 s after injection of contrast material, regardless of different size.

The APA of the time-attenuation curve reflects relatively good tumoral vascularity (1). The APA of incremental dynamic CT correlated with the number of tumoral small vessels (0.02–0.10 mm) in pathologically proven specimens (3). This evidence was consistent with our results.

The process of neovascularization is thought to be mediated by a tumor angiogenic factor produced by the neoplastic cells (4). Although numerous angiogenic molecules have been identified, VEGF is thought to be one of the most important (4,5). VEGF expression correlated with MVD in lung adenocarcinomas in previous reports (5,10). In this study, VEGF expression of 35 lung adenocarcinomas was evaluated immunohistochemically. The rate of VEGF-positive lung cancers was 63%. This evidence was in accordance with previous results (4–7).

The APA of dynamic CT correlated with MVD in VEGF-positive lung adenocarcinomas, whereas in VEGF-negative carcinomas, it did not. This result demonstrated that tumor angiogenesis is different between VEGF-positive and -negative lung adenocarcinoma. Angiogenesis assessed by MVD is a significant prognostic factor (6,7). Our study emphasizes the need for considering lung adenocarcinoma in further evaluation of prognostic factors with regard to tumor angiogenesis.

The collimation of the CT beam was always less than half the diameter of the tumors. Variations in breath-holding will change the readable density of the tumor image (1). We excluded four patients from the current study because of misregistration during dynamic CT scan. Artifacts will be produced by heart motion, lack of breath-holding, and contrast material in the superior vena cava and subclavian vein. We avoided artifacts by administering contrast material in the opposite side.

We conclude that the APA of dynamic CT correlates with MVD in VEGF-positive lung adenocarcinoma. The APA of dynamic CT might be a useful index for VEGF-related tumor angiogenesis in lung adenocarcinoma.

Acknowledgment:

The authors thank Tsukasa Sasaki for radiologic assistance.

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Keywords:

Lungs, cancer; Lungs, adenocarcinoma; Vascular endothelial growth factor; Computed tomography

© 2001 Lippincott Williams & Wilkins, Inc.