The purpose of this study was to investigate the clinical usefulness of the color Doppler vascularity index (CDVI) in patients with colon cancer before surgery. Forty-four patients with sonographically visible tumor mass of colon cancer were investigated. The CDVI of each tumor was determined using transabdominal color Doppler ultrasound. The CDVI was defined as the ratio of the number of the colored pixels within a tumor section to the number of total pixels in that specific tumor section and was calculated by using Encomate software (Electronic Business Machine Co. Ltd., Taipei, Taiwan). The correlation between the CDVI and clinicopathological factors, mode of recurrence, and patient survival was studied. For comparison, microvessel density (the mean number of microvessels in three areas of highest vascular density at×200 magnification) of the tumors of these 44 patients was also evaluated by using immunohistochemical staining of surgical specimens with anti-CD34. The microvessel density was not correlated with Dukes’classification, clinicopathological factors, and survival. The CDVI was significantly higher in the patients with lymph node metastases and vascular invasion than in those without such metastases and invasion(P = 0.006 and P = 0.0098, respectively). Moreover, in patients with a high CDVI(>15%) and positive vascular invasion, survival was significantly poorer than in those with low CDVI (≤15%) and negative invasion(P = 0.0037 and 0.0039, respectively). Multivariate analysis indicated that liver metastasis, vascular invasion, and CDVI are independent prognostic factors in the patients with colon cancer. According to the mode of recurrence in 36 patients who underwent curative resection, the frequency of the distant organ recurrence was significantly higher in the high CDVI group (40%) than in the low CDVI group (0%). The CDVI is a good preoperative indicator of recurrence and patient survival in colon cancer. Thus, the CDVI may be helpful in stratifying patients for adjuvant therapy.

Angiogenesis is essential for the growth of solid tumors measuring more than a few millimeters (1). It permits rapid tumor growth and potential presence of tumor metastasis (2, 3). Several studies have reported an association between the degree of angiogenesis and the clinicopathological factors and prognosis of patients with various solid tumors, such as breast (4, 5, 6),lung (7), prostate (8), head and neck(9), and gastrointestinal cancer (10, 11). All these studies were accomplished on tissue sections retrospectively obtained from surgical specimens. However, an “in vivo “method to assess tumor angiogenesis is highly desirable for diagnostic purpose, treatment planning, and follow-up.

With the current technique of color Doppler sonography, tumor vascularity can be assessed in vivo(12). The correlation of the color Doppler vascular signals with the angiographic and histological findings has also been shown in tumors of various human organs (13, 14). Incremental angiogenesis could be demonstrated in the tumorigenesis of ovarian and endometrial malignancies with color Doppler ultrasound (15, 16). Vascularity index is a new ultrasound parameter for evaluating in vivo angiogenesis. Several reports have revealed that the vascularity index could be used to differentiate the nature of neck lymph node (17) and had a good correlation with status of lymph node metastasis in cervical carcinoma (18).

Conventional transabdominal sonography has become increasingly important not only in evaluating diseases of solid organ but also in diagnosis of the gastrointestinal diseases, such as colon cancer(19, 20, 21, 22). Therefore, tumoral vascularity may also be assessed by transabdominal color Doppler ultrasound. Combining transabdominal color Doppler ultrasound and the concept of the vascularity index, we defined a new parameter for tumor angiogenesis,CDVI3.

To investigate the clinical usefulness of the CDVI in colon cancer,this study was conducted to evaluate the correlation between the CDVI and clinicopathological factors, recurrence, and survival in patients with sonographically visible tumor. For comparison, MVD, determined immunohistochemically, was also evaluated.

Patients.

A total of 56 patients with colon cancer, who had undergone colectomy at our institution from January 1996 to February 1999, were included in this study. They were all proved to have adenocarcinomas by colonofibroscopic biopsies. Abdominal ultrasound was performed before operation to evaluate liver and other i.p. metastases routinely without hydrocolonic preparation after overnight fasting. The tumor mass of colon cancer could be delineated by trans-abdominal ultrasound in 44 patients (79%) who constituted the population of this study. These 44 patients ranged in age from 41–82 yr (average age,64.4 yr); there were 30 men and 14 women (Table 1). No patient had received chemotherapy and radiotherapy before surgery. Tumors were divided into two histological subgroups: differentiated and undifferentiated types. Depth of invasion (within the wall or through the wall), lymph node metastasis (negative or positive), and liver metastasis (negative or positive) were also evaluated. They were staged according to Dukes’ classification. Thirty-six patients received curative surgery, whereas the remaining eight patients underwent palliative resection only. All patients staged Dukes’ B2 or later received postoperative chemotherapy with the same regimen of 5-fluorouracil and leucovorin. The patients were followed up from 6–34 months after surgery. The follow-up intervals were calculated as survival intervals after surgery. Different modes of metastasis were confirmed by diagnostic imaging and surgery.

Sonographic Technique and Quantification of Vascular Density in Color Doppler Images (17, 18).

The scanner we used was a color Doppler ultrasound unit (HDI 3000;Advanced Technology Laboratories, Bothell, WA) with a 2–5-MHz curved array and a 5–10-MHz broad band linear array transducers. Settings of the color Doppler ultrasound were standardized for the highest sensitivity in the absence of apparent noise by using a medium wall filter, pulsed repetition frequency of 1000 Hz, moderate-to-long persistence, and a slow sweep technique. Under these conditions, the lowest possible measurable velocity was claimed below 5 cm/s. Focusing depth was set between 1.5 and 4 cm. The 2–5-MHz curved array transducer was used to search the site of colon cancer after routine abdominal sonographic examination, then changed the transducer to the 5–10-MHz linear one for color Doppler evaluation of the tumor. Each tumor was scanned thoroughly, and tangential scanning was made to avoid the intraluminal air interference. The color window was set to cover the whole tumor on the screen. The tumor of the colon cancer was then scanned carefully in all directions, and the tumor section with subjectively maximal color signals was captured and stored for later analysis. Each tumor was scanned three times, thus three tumor sections with maximal color signals were available for quantitative analysis. After the examination, the previously stored images were retrieved and displayed on the monitor. The tumor margin was contoured using a cursor(Fig. 1). Quantification of the vascular color signals within the demarcated tumor area was then automatically performed by a special software(Encomate; Electronic Business Machine Co., Ltd., Taipei, Taiwan). The results were expressed as the “CDVI” (the number of colored pixels within the tumor section/the number of total pixels in that particular tumor section). For each tumor, the mean of the CDVI of three representative tumor sections was used for statistical analysis.

Microvessel Staining and Evaluation.

The paraffinized tumor blocks of 44 patients whose colon cancers could be visualized by ultrasound were stained for endothelial cell CD34 antigen using the labeled streptavidin-biotin after antigen retrieval(Fig. 2). Briefly, deparaffinized sections were heated in a pressure cooker. After endogenous peroxidase was blocked with 3% hydrogen peroxide in the section, each section was incubated with nonimmune horse serum. The sections were incubated in anti-CD34 monoclonal antibody (Santa Cruz Biotechnology, Santa Cruz, CA) at a dilution of 1:20 or the control nonimmune serum at 4°C overnight. The sections were incubated with link antibodies, followed by peroxidase-conjugated streptavidin complex (LSAB kit; DAKO Corporation, Carpinteria, CA). The peroxidase activity was visualized with diaminobenzidine tetrahydroxychioride solution (DAKO Corporation) as the substrate. The sections were lightly counterstained with hematoxylin. After screening the areas with intense neovascularized spots at low power field (×100), microvessels in the area with the highest number of discrete microvessels were counted in a×200 field. Three separate intense neovascularized areas were assessed, and the mean was calculated as the MVD of each tumor evaluated.

Statistics.

The relationship between MVD, CDVI, and the various clinicopathological factors was examined by χ2 test. One-way ANOVA was used to test the correlation among different Dukes’ stages. Survival curves were calculated using the Kaplan-Meier method and analyzed by the log-rank test. The CDVI and clinicopathological variables influencing survival were assessed by the Cox proportional hazards model. The mode of recurrence was examined by Fisher’s exact test. Statistical significance was defined as P < 0.05.

The CDVI of the 44 sonographically visible colon cancers ranged from 2.0–34%, with a mean value of 15.4%, whereas the MVD ranged from 38.7–150.0, with a mean value of 81.5. Table 2 shows the correlation between the CDVI and the MVD, with various clinicopathological factors. There was no statistically significant association between the MVD and clinicopathological factors as tested in this study. However, the CDVI in the patients with lymph node metastases and vascular invasion was significantly higher than in those without lymph node metastases (P = 0.006) and vascular invasion (P = 0.0098). The CDVI of undifferentiated tumors was also significantly higher than that of differentiated tumors (P = 0.0022).

Fig. 3 shows the correlation between MVD, CDVI, and Dukes’ stages. Both MVD and CDVI showed no statistically significant difference among different Dukes’ stages.

The prognosis of the 44 patients was then analyzed. Because the mean MVD of these patients was 81.5, we, therefore, classified them into two subgroups: one group of MVD >82 and one group of MVD ≤82. The mean CDVI of these patients was 15.4%. Accordingly, the patients were divided into two subgroups: one group of high CDVI (>15%) and one group of low CDVI (≤15%). The survival rates were calculated using the Kaplan-Meier method. The survival of the group with high MVD and that with low MVD was not significantly different (Fig. 4). On the contrary, the survival of the group with high CDVI was significantly (P = 0.0037) worse than that with low CDVI (Fig. 5). The effects of variables presumably associated with patient survival were studied by multivariate analysis using a Cox model. As a result,liver metastasis, vascular invasion, and vascularity index were independent prognostic factors (Table 3).

Among the 36 patients who underwent curative resection, 10 experienced disease recurrence. The relationship between CDVI and recurrence is shown in Table 4 . The recurrence rate in the high CDVI group was 45%, which was significantly higher than the rate in the low CDVI group (6.3%). As to the mode of recurrence, the frequency of distant organ recurrence such as liver, lung, and bone marrow after curative resection was significantly higher in the high CDVI group (40%) than in the low CDVI group (0%; P = 0.005).

In this study, the CDVI was significantly associated with tumor differentiation, lymph node metastasis, and tumor vascular invasion and was also an independent prognostic factor. Furthermore, according to the mode of recurrence, distant organ recurrence was significantly more frequent in the high CDVI group. However, the MVD of colon cancer was not correlated with tumor differentiation, tumor invasion depth, lymph node metastasis, liver metastasis, tumor vascular invasion, and patient survival.

Current ultrasound technology is not capable of detecting tumor neovascularization itself (approximately 15 μm or less in diameter),which was usually demonstrated immunohistochemically(23). The color Doppler signals seen within tumor represented the larger vessels (approximately 100 μm or more in diameter), possibly intratumoral arterioles, venules, and arteriole-vanule shunting (23, 24). We hypothesized that the more neovascularization exists, the more supplying intratumoral arterioles and draining venules will be present. Thus, the CDVI, by quantitatively depicting the larger supplying arterioles and draining venules, can reflect the extent of global neovascularization of a tumor.

Liotta et al.(25, 26) developed a tumor perfusion study with C57BL/6J male mice to determine the dynamics of tumor growth, density, and size distribution of perfused tumor vessels,entry rate of tumor cells and tumor cell clumps, and number of pulmonary metastases. They found that the tumor vessel size and density are important determinants of the size of tumor cell clumps and concentration of effluent tumor cells released into the circulation. The number of intratumoral vessels of diameter ≥100 μm was important for passage of tumor cell clumps, which produced a significantly greater number of metastases than did the same number of cells with single cell form (27). Therefore, increased density of larger vessels may facilitate distant metastases by allowing the intravasation and transportation of larger cancer cell clumps. In the present study, patients with a high CDVI have a higher incidence of distant metastasis after curative resection than patients with a low CDVI (40% versus 0%, P = 0.005). This in vivo observation in human is in line with that of Liotta et al.(25, 26) in mice.

The large intratumoral vessels collapse and dramatically decrease their sizes from a living status to a fixed specimen (28) and are seldom seen histologically, even when specifically sought(29). Color Doppler ultrasound was reported to be able to depict larger vessels of approximately 100 μm or larger in diameter in vivo(23, 24). Therefore, the CDVI can then provide better information on macrovessel density in living state, which is not usually detectable in surgical-fixed specimens. As a result, the CDVI can better reflect the tumor invasiveness,recurrence, and prognosis.

Currently, MVD assessed with immunohistochemistry using antibodies against various endothelial cell-related antigens such as factor VIII, CD31, CD34 and so forth are widely used for assessing angiogenesis in colorectal cancer (10, 11, 30, 31, 32). However, the results are inconsistent. Some studies (10, 11, 30) showed a significant association between the high MVD of primary tumors and recurrence, metastasis, and survival. The study by Bossi et al.(31) and our present study didn’t show any significant association. Surprisingly, Abdalla et al.(32) reported that high MVDs were associated with a better prognosis in colorectal cancer. There seem to be some problems to be resolved in MVD study. At first at laboratory level,standardization of technique in MVD needs to be determined before clinical application. Second, the inability of panendothelial antibodies to distinguish between preexisting and newly formed blood vessels could be an important factor in the assessment of true tumor angiogenesis (33, 34). Third, recent study has shown that tumor cells themselves could substitute endothelial cells in tumor tissue and panendothelial antibodies may not demonstrate this type of neovascularization. Fourth, distribution of angiogenesis is usually uneven and heterogenous, and the MVD represented microvessel counts in tiny portions of tumor.

Colon cancer staging is still mostly performed according to the Dukes’classification. However, the predictive value of tumor stage,especially in the Dukes’ B and C categories (which are the stages most patients belong to in this study), is rather limited (35). This may be the reason why the CDVI was significantly associated with lymph node metastasis, positive vascular invasion, and poor prognosis but was not correlated with Dukes’ stages in this study.

Vascular invasion is a well known factor for hematogenous metastasis and also an independently prognostic factor in colorectal cancer(36). Local shedding of cancer cells into the tumor vascular stream that can commence at the onset of angiogenesis is quantitatively related to the surface area of intratumoral vessels(25, 37). The CDVI as a measure of global vascularity of the tumor might reflect the surface area of intratumoral vessels. In the present study, the patients with vascular invasion had a significantly higher CDVI than those without. This may also explain why hematogenous recurrence was more frequent in patients with a higher CDVI and patients with a higher CDVI had poorer prognosis. Vascular invasion is usually accompanied with lymphatic invasion that is directly related to lymph node metastasis in colorectal cancer(30, 36). In the present study, the CDVI, which was correlated with vascular invasion, was also associated with lymph node metastasis.

Various adjuvant therapies have been given to patients with advanced colorectal cancer, including neoadjuvant and postoperative chemotherapy or radiotherapy. The patients who need adjuvant therapies should be selected by using some indicator affecting recurrence and prognosis. The CDVI was shown to be an excellent prognostic indicator in colon cancer patients. Thus, the CDVI in colon cancer patients obtained before operation may help to identify patients with poor prognosis and stratify patients for appropriate neoadjuvant therapy. Other than chemotherapy or radiotherapy, TNP-470, an analogue of fumagillin derived from Aspergillus jumigatus, has been shown to inhibit angiogenesis and the growth of some tumors(38, 39, 40). Such agents may be valuable in the adjuvant therapy of colon cancer patients with high CDVI tumors.

Fig. 1.

CDVI assessment within the colon cancer. A,the color window was set to cover the whole tumor on the screen and stored for later quantitative analysis. B, the tumor margin was contoured using a cursor. Quantification of the vascular color signals within the demarcated tumor was then automatically executed by special software called Encomate (Electronic Business Machine Co., Ltd., Taipei, Taiwan). C, the results were expressed as the “CDVI” (the number of colored pixels within the tumor section/the number of total pixels in that particular tumor section).

Fig. 1.

CDVI assessment within the colon cancer. A,the color window was set to cover the whole tumor on the screen and stored for later quantitative analysis. B, the tumor margin was contoured using a cursor. Quantification of the vascular color signals within the demarcated tumor was then automatically executed by special software called Encomate (Electronic Business Machine Co., Ltd., Taipei, Taiwan). C, the results were expressed as the “CDVI” (the number of colored pixels within the tumor section/the number of total pixels in that particular tumor section).

Close modal
Fig. 2.

Immunohistochemical staining for CD34 in colon cancer tissues (original magnification, ×200). Microvessels are represented by brown clusters, which stand out sharply from other tissues.

Fig. 2.

Immunohistochemical staining for CD34 in colon cancer tissues (original magnification, ×200). Microvessels are represented by brown clusters, which stand out sharply from other tissues.

Close modal
Fig. 3.

A, correlation between microvessel counts and Dukes’ stages. B, correlation between CDVI and Dukes’ stages.

Fig. 3.

A, correlation between microvessel counts and Dukes’ stages. B, correlation between CDVI and Dukes’ stages.

Close modal
Fig. 4.

Survival curves of patients with high microvessel counts(>82) and low microvessel counts (≤82).

Fig. 4.

Survival curves of patients with high microvessel counts(>82) and low microvessel counts (≤82).

Close modal
Fig. 5.

Survival curves of patients with high CDVI(>15%) and low CDVI (≤15%).

Fig. 5.

Survival curves of patients with high CDVI(>15%) and low CDVI (≤15%).

Close modal

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Supported by Grant 88F0001 from National Taiwan University Hospital.

The abbreviations used are: CDVI, color Doppler vascularity index; MVD, microvessel density.

Table 1

Characteristics of 44 patients studied

Age (yr)  
Range 41–82 
Mean 64.4 
Sex (no. of patients)  
Men 30 
Women 14 
Localization of tumor  
Ascending colon 
Transverse colon 
Descending colon 12 
Sigmoid colon 21 
Stage (no. of patients)  
Dukes’ A 
Dukes’ B1 
Dukes’ B2 17 
Dukes’ C 11 
Dukes’ D (liver metastasis) 13 
Operative (no. of patients)  
Curative (including complete resection of liver metastasis) 36 
Noncurative 
Age (yr)  
Range 41–82 
Mean 64.4 
Sex (no. of patients)  
Men 30 
Women 14 
Localization of tumor  
Ascending colon 
Transverse colon 
Descending colon 12 
Sigmoid colon 21 
Stage (no. of patients)  
Dukes’ A 
Dukes’ B1 
Dukes’ B2 17 
Dukes’ C 11 
Dukes’ D (liver metastasis) 13 
Operative (no. of patients)  
Curative (including complete resection of liver metastasis) 36 
Noncurative 
Table 2

Correlation between clinicopathologic factors and MVD, and vascularity index

VariablesMVD (no.)CDVI (%)
Patients (no.)Mean ± SDPPatients (no.)Mean ± SDP
Histologic type       
Differentiated 37 84.0 ± 31.0 0.7388 37 15.1 ± 7.5 0.0022 
Undifferentiated 88.7 ± 30.3  25.5 ± 5.9  
Depth of invasion       
Through the wall 39 81.5 ± 28.2 0.1777 39 16.3 ± 7.7 0.4703 
Within the wall 101.0 ± 40.1  19.5 ± 9.6  
Lymph node metastasis       
Negative 25 78.6 ± 28.9 0.1932 25 13.8 ± 7.2 0.0060 
Positive 19 91.2 ± 30.7  19 20.2 ± 7.3  
Liver metastasis       
Negative 31 88.7 ± 30.5 0.9162 31 16.3 ± 8.2 0.7007 
Positive 13 84.8 ± 30.1  13 17.3 ± 7.1  
Vascular invasion       
Negative 25 78.9 ± 27.8 0.2148 26 14.1 ± 7.2 0.0098 
Positive 19 90.9 ± 32.3  18 20.2 ± 7.4  
VariablesMVD (no.)CDVI (%)
Patients (no.)Mean ± SDPPatients (no.)Mean ± SDP
Histologic type       
Differentiated 37 84.0 ± 31.0 0.7388 37 15.1 ± 7.5 0.0022 
Undifferentiated 88.7 ± 30.3  25.5 ± 5.9  
Depth of invasion       
Through the wall 39 81.5 ± 28.2 0.1777 39 16.3 ± 7.7 0.4703 
Within the wall 101.0 ± 40.1  19.5 ± 9.6  
Lymph node metastasis       
Negative 25 78.6 ± 28.9 0.1932 25 13.8 ± 7.2 0.0060 
Positive 19 91.2 ± 30.7  19 20.2 ± 7.3  
Liver metastasis       
Negative 31 88.7 ± 30.5 0.9162 31 16.3 ± 8.2 0.7007 
Positive 13 84.8 ± 30.1  13 17.3 ± 7.1  
Vascular invasion       
Negative 25 78.9 ± 27.8 0.2148 26 14.1 ± 7.2 0.0098 
Positive 19 90.9 ± 32.3  18 20.2 ± 7.4  
Table 3

Significantly clinicopathologic factors affecting overall survival rate determined by Cox proportional hazards model

VariablesPHazard ratio
Liver metastasis 0.0007 15.801 
Negative positive   
Vascular invasion 0.0166 4.571 
Negative positive   
CDVI (%) 0.0192 5.040 
≤15 >15   
VariablesPHazard ratio
Liver metastasis 0.0007 15.801 
Negative positive   
Vascular invasion 0.0166 4.571 
Negative positive   
CDVI (%) 0.0192 5.040 
≤15 >15   
Table 4

Recurrent cases after curative resectiona

CDVIRate of recurrence (%)Location of recurrence (%)
  Liver 25 (5/20) 
>15 (n = 20) 45 (9/20) Lung 10 (2/20) 
  Bone 5 (1/20) 
  Peritoneum 5 (1/20) 
  Liver 0 (0/16) 
≦15 (n = 16) 6.3 (1/16) Lung 0 (0/16) 
  Bone 0 (0/16) 
  Peritoneum 6.3 (1/16) 
CDVIRate of recurrence (%)Location of recurrence (%)
  Liver 25 (5/20) 
>15 (n = 20) 45 (9/20) Lung 10 (2/20) 
  Bone 5 (1/20) 
  Peritoneum 5 (1/20) 
  Liver 0 (0/16) 
≦15 (n = 16) 6.3 (1/16) Lung 0 (0/16) 
  Bone 0 (0/16) 
  Peritoneum 6.3 (1/16) 

Statistically significant differences were calculated by Fisher’s exact test.P= 0.022 40 (8/20) 0 (0/16)P= 0.005

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