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- Subjects and methods
- Supporting Information
Both benign and malignant tumors are composed of ‘tumor cells’ and supporting tissues: blood vessels, fibrous supporting tissue, lymphatic vessels and sometimes nerve fibers1, 2. An increase in the cell population of tumors must be preceded by the production of new vessels—angiogenesis3. Usually newly formed vessels pierce the tumor from various directions from the surrounding tissue of the organ. Tumor vascular networks are tortuous and do not follow the regular structural hierarchy seen in normal tissue4. Vessels in malignant tumors are not well differentiated, manifest heterogeneity of structure5, are often densely distributed, dilated and saccular and may contain tumor cells within their endothelial lining6, 7. Malignant tumors may also harbor giant capillaries and arteriovenous shunts without intervening capillaries7, 8. Such haphazard branching patterns and larger, less regular diameters of vessels in tumors contribute to the non-uniform perfusion of cancer cells, expressed as chaotic tumor blood flow, with high flow rates in some vessel segments and stagnation in others7. These patterns can change within hours or even minutes9.
Tumor vascularity has been examined by microscopy10, 11, polymer casting techniques12, 13, contrast angiography14–16, color and power Doppler ultrasound17–24 and using ultrasound contrast25. Both two-dimensional (2D) and three-dimensional (3D) power Doppler ultrasound has been used to try to quantify the color content of tumor scans objectively19, 21, 26. Using 3D power Doppler ultrasound, a 3D image of the vessel tree of tumors can be created. However, we know of no publications providing a systematic description of the morphology of vessels in ovarian tumors, as assessed by 3D power Doppler ultrasound. Testa and coworkers27 briefly mention, in a study on computerized quantitative analysis of the color content of tumor volumes obtained by 3D ultrasound, that the ‘presence of irregular and randomly dispersed vessels with complex branching was considered suggestive of malignancy’. They found this vessel pattern to be more common in malignant than in benign tumors, but the difference was not statistically significant. The reproducibility of assessment of the vessel tree was not tested27.
The aims of this study were: to determine whether subjective evaluation of the morphology of the vessel tree of ovarian tumors, as depicted by 3D power Doppler ultrasound, is reproducible; whether the vascular morphology, as assessed by 3D power Doppler ultrasound, differs between benign and malignant ovarian tumors; and whether 3D power Doppler ultrasound adds anything to gray-scale ultrasound imaging in an ordinary population of tumors.
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- Subjects and methods
- Supporting Information
Of the 131 consecutive women examined, 24 were excluded because of an unequivocal ultrasound diagnosis of dermoid cyst (n = 14), tubal disease (n = 7), paraovarian cyst (n = 2) or peritoneal pseudocyst (n = 1). The ultrasound diagnosis was correct in 23 of these 24 cases (one ultrasound diagnosis of dermoid cyst was incorrect, the histopathology of the tumor being endometrioma). Three women were excluded because of technical problems or power Doppler artifacts that made evaluation of the vascular tree of the tumor unreliable. Thus, 104 tumors were included.
Among these 104 tumors there were 77 (74%) benign tumors and 27 (26%) malignancies. Histological diagnoses are presented in Table 1. The mean ( ± SD) age of the women with a benign tumor was 45 ± 17.4 years, and the mean age of those with a malignant tumor was 56 ± 17.6 years; 35% (27/77) and 56% (15/27), respectively, were postmenopausal; and 30% in both groups (23/77 vs. 8/27) were nulliparous. The most important gray-scale ultrasound features of the tumors are shown in Table 2. Power Doppler signals were detected in all tumors.
Table 1. Histopathological diagnoses
| Mucinous cyst(aden)oma||17|
| Unspecified cyst||10|
| Serous cyst(aden)oma||9|
| Functional cyst||3|
| Mixed serous and mucinous cystadenoma||1|
| Struma ovarii||1|
| Simple cyst + hydrosalpinx||1|
| Paraovarian cyst||1|
| Borderline ovarian tumor (all Stage 1)||6|
| Primary invasive ovarian cancer*||18|
| Stage 1||5|
| Stage 2||3|
| Stage 3||7|
| Stage 4||3|
| Metastatic cancer (gastrointestinal cancer)||3|
Table 2. Gray-scale ultrasound morphology of benign and malignant tumors
|Parameter||Malignant (n = 27)||Benign (n = 77)||P*|
|Bilateral tumor (n (%))||10 (37)||18 (23)||0.177|
|Ascites (n (%))||2 (7)||0 (0)||0.019|
|Type of tumor|| || ||< 0.0001|
| Unilocular (n (%))||0 (0)||22 (29)|| |
| Unilocular solid (n (%))||2 (7)||7 (9)|| |
| Multilocular (n (%))||0 (0)||25 (33)|| |
| Multilocular solid (n (%))||14 (52)||20 (26)|| |
| Solid (n (%))||11 (41)||3 (4)|| |
|Lesion diameter† (mm, median (range))||92 (41–216)||58 (14–176)||< 0.0001|
|Largest solid component† (mm, median (range))|| || || |
| All tumors||53 (14–114)||0 (0–76)||< 0.0001|
| Tumors with solid components||53 (14–114)||15 (5–76)||< 0.0001|
|Papillation (n (%))||9 (33)||16 (21)||0.199|
|Irregular wall (n (%))||21 (78)||22 (29)||< 0.0001|
Interobserver agreement with regard to the assessment of the vascular tree was moderate to good (κ = 0.44–0.78; Table 3). The highest κ values were achieved for density of vessels (κ = 0.70) and branching of vessels in the whole tumor (κ = 0.70) and for bridges between vessels (κ = 0.78) and color splashes (κ = 0.76) in the 5-cm3 sample.
Table 3. Interobserver agreement in the assessment of the morphology of the vascular tree of tumors
|Morphological characteristic||κ||Agreement (%)|
|Whole tumor|| || |
| Color splashes||0.69||86|
| Caliber changes||0.44||79|
|Sample from the most vascularized|| || |
| area of the tumor|| || |
| Color splashes||0.78||90|
| Caliber changes||0.62||83|
The diagnostic performance of the features of the vascular tree is summarized in Table 4. All vascular features differed significantly between benign and malignant tumors. Of the malignant tumors, 48% (13/27) had dense vessels in the whole tumor vs. 5% (4/77) of the benign tumors, 30% (8/27) vs. 10% (8/77) had areas with dense vessels, and 22% (6/27) vs. 85% (65/77) had widely dispersed vessels (P < 0.0001). The diagnostic performance of the features of the vascular tree was at most moderate. The areas under the ROC curves varied between 0.61 and 0.83, the largest areas being 0.83 for density of vessels in the whole tumor and 0.77 for bridges between vessels in the 5-cm3 sample. Branching of vessels in the 5-cm3 sample did not seem to have any discriminative power at all, the lower 95% confidence limit of the area under the ROC curve being 0.49. The strongest predictor of malignancy was the presence of dense vessels in the whole tumor, which increased the odds of malignancy five-fold. The strongest predictor of benignity was the absence of branching vessels in the whole tumor, which decreased the odds of malignancy 10-fold. The vascular features in the 5-cm3 sample did not change the likelihood of malignancy at all or only little, the positive LRs varying between 1.3 and 3.8 and the negative LRs between 0.3 and 0.7.
Table 4. Diagnostic performance of the morphology of the vascular tree
|Morphological characteristic||Area under ROC curve||Sensitivity (% (n))||False-positive rate* (% (n))||LR+||LR−||P†|
|Vascular morphology in the whole tumor|| |
| Density||0.83||0.73–0.93||78 (21/27)‡||16 (12/77)‡||5.0||0.26||< 0.0001|
| Caliber changes||0.73||0.61–0.85||67 (18/27)||21 (16/77)||3.2||0.42||< 0.0001|
| Tortuosity||0.71||0.59–0.83||56 (15/27)||14 (11/77)||4.0||0.52||< 0.0001|
| Color splashes||0.70||0.58–0.82||59 (16/27)||20 (15/77)||3.0||0.51||< 0.0001|
| Branching||0.70||0.59–0.80||96 (26/27)||57 (44/77)||1.7||0.09||< 0.0001|
|Vascular morphology in 5-cm3 sample|| |
| Bridges||0.77||0.66–0.88||74 (20/27)||20 (15/77)||3.8||0.32||< 0.0001|
| Caliber changes||0.75||0.64–0.86||74 (20/27)||23 (18/77)||3.2||0.34||< 0.0001|
| Color splashes||0.74||0.63–0.86||67 (18/27)||18 (14/77)||3.7||0.41||< 0.0001|
| Tortuosity||0.64||0.51–0.77||44 (12/27)||16 (12/77)||2.9||0.67||0.003|
| Branching||0.61||0.49–0.73||85 (23/27)||64 (49/77)||1.3||0.41||0.029|
All vascular features except splashes in the whole tumor and branching in the 5-cm3 sample added information to the logistic regression model containing only gray-scale variables. The performance of the models is shown in Table 5. The gray-scale model correctly identified all 27 malignancies and 69 of the 77 benign tumors. One of the best models was obtained by adding branching of vessels in the whole tumor to the gray-scale model. The mathematical formula of this model is shown in the footnote to Table 5. Its area under the ROC curve was 0.99, with all malignancies and 73 of the 77 benign tumors being correctly classified, i.e. an additional four benign tumors were correctly classified compared to when using the gray-scale model without any added Doppler variable (comparison based on the use of the optimal cut-offs of both models).
Table 5. Diagnostic performance of logistic regression models
|Parameter||Area under ROC curve||Optimal cut-off value*||Sensitivity (% (n))||False-positive rate† (% (n))||LR+||LR−|
|Gray-scale model‡||0.98||0.96–1.0||0.12||100 (27/27)||10 (8/77)||9.6||—|
| ||0.25||96 (26/27)||8 (6/77)||12.4||0.04|
|Gray-scale variables with the following Doppler variables added|
|In whole tumor|| |
| Branching§||0.99||0.98–1.0||0.16||100 (27/27)||5 (4/77)||19.8||—|
| ||0.35||96 (26/27)||4 (3/77)||24.7||0.04|
| Density of vessels||0.99||0.97–1.0||0.12||100 (27/27)||9 (7/77)||11.0||—|
| ||0.41||93 (25/27)||5 (4/77)||17.8||0.08|
| Caliber changes||0.99||0.97–1.0||0.09||100 (27/27)||10 (8/77)||9.6||—|
| ||0.25||96 (26/27)||5 (4/77)||18.5||0.04|
| Tortuous vessels||0.99||0.97–1.0||0.16||100 (27/27)||9 (7/77)||11.0||—|
| ||0.31||93 (25/27)||4 (3/77)||23.7||0.08|
|In 5-cm3 sample|| |
| Bridges||0.99||0.98–1.00||0.09||100 (27/27)||12 (9/77)||8.5||—|
| ||0.37||96 (26/27)||4 (3/77)||24.7||0.04|
| Splashes||0.99||0.97–1.00||0.10||100 (27/27)||9 (7/77)||11.0||—|
| ||0.27||96 (26/27)||5 (4/77)||18.5||0.04|
| Caliber changes||0.99||0.97–1.00||0.08||100 (27/27)||16 (12/77)||6.4||—|
| ||0.29||96 (26/27)||5 (4/77)||18.5||0.04|
| Tortuous vessels||0.99||0.97–1.00||0.10||100 (27/27)||9 (7/77)||11.0||—|
| ||0.27||96 (26/27)||5 (4/77)||18.5||0.04|
- Top of page
- Subjects and methods
- Supporting Information
Depiction of the morphology of tumor vessels using 3D power Doppler ultrasound may be regarded as a new ultrasound modality. We wanted to determine whether subjective evaluation of the ultrasound morphology of tumor vessels, as depicted by 3D power Doppler ultrasound, is reproducible, and whether the morphology of the vessel tree so evaluated contains any clinically useful information. It is not possible to describe the morphology of the vessel tree using 2D color or power Doppler ultrasound. The only vascular feature that can possibly be evaluated using 2D ultrasound is vessel density, subjective evaluation of the color content of a 2D tumor scan probably being related to vessel density in a 3D power Doppler image of the vessel tree. However, the two are not directly comparable. The area under the ROC curve of vessel density, as assessed by 3D ultrasound in the current series of tumors, was similar to that of the color content of the tumor scan as evaluated using 2D ultrasound in (virtually) the same series of tumors26 (area under the ROC curve 0.83 vs. 0.80). It is interesting to note that the density of vessels was the single best vascular predictor of malignancy, because the density of vessels is likely to be reflected in the total color content of the tumor scan, and the color content of the tumor scan has been shown to be one of the best 2D Doppler ultrasound variables for discriminating between benign and malignant adnexal masses17. Others, too, have found, using methods other than ultrasound, that vessels are more densely packed in malignant than in benign tumors34–36.
Our results show that subjective evaluation of the morphology of the vessel tree of ovarian tumors, as depicted by 3D power Doppler ultrasound, manifest moderate to good interobserver reproducibility. The vessel features most difficult to reproduce were caliber changes and tortuosity. We have also shown that the morphology of the vascular tree of benign and malignant ovarian tumors, as depicted by 3D power Doppler ultrasound, does differ. This was perhaps to be expected, because the vessels of benign and malignant tumors have been described to be different when using methods other than ultrasound to describe them15, 16, 37. On the other hand, our study could just as well have shown that the 3D power Doppler method was too crude to detect the differences. Earlier studies found a wide heterogeneity of vessel distribution in different parts of tumors38, 39 and in different types of tumor37, 40, 41. Such heterogeneity may explain some of the false-positive and false-negative diagnoses using our technique.
In all previous studies evaluating the value of adding Doppler ultrasound information to gray-scale imaging, gray-scale ultrasound findings were available to the person evaluating the Doppler information because it was technically impossible to conceal it28, 42–48. Therefore, in the studies cited, Doppler results may have been biased. Because it was the aim of our study to determine the diagnostic performance of vessel morphology as depicted by 3D ultrasound, it is a methodological strength that vessel morphology was evaluated by observers having no clinical information, no information on histology, and no information on gray-scale ultrasound morphology. The AVI files contained no gray-scale information and had been prepared by a third person. Thus, our results of the evaluation of the vessel tree are completely unbiased and reflect the true capacity of vessel morphology to discriminate between benign and malignant adnexal masses.
Potential weaknesses of our study are that the very largest tumors could not be included in their entirety in the volume acquired, and that the site of the 5-cm3 sample was chosen on the basis of subjective evaluation of which area of the tumor was most vascularized. We do not believe that a small part (5–10% in most cases) of the very largest tumors missing invalidates our results, or that choosing the place of the 5-cm3 sample using subjective evaluation does. Any selection of a ‘representative’ part of a tumor must necessarily be subjective. Alcazar et al.19 used subjective evaluation to find the most ‘suspicious’ part of a tumor in a volume acquired by 3D ultrasound and quantified the color content of that part using the VOCAL™ software.
It is a weakness of our study that the logistic regression models including vascular morphology were not tested prospectively on a test set. However, it would be of limited interest to test our risk calculation models, including vessel morphology variables, prospectively in an ordinary tumor population because the gray-scale model itself performed extremely well in our study population (area under ROC curve 0.98), and it also performed very well (area under ROC curve 0.89) when tested prospectively in a test population of more than 1000 patients49, both study populations representing ordinary tumor populations. Five42–46 of seven studies42–48 evaluating prospectively whether adding Doppler ultrasound examination to gray-scale imaging improved discrimination between benign and malignant masses showed that the contribution of Doppler ultrasound examination to a correct diagnosis was very limited. In concordance, the results of our study on the vessel tree of tumors suggest that, in an ordinary population of ovarian tumors, 3D Doppler ultrasound examination adds little to gray-scale imaging. An experienced ultrasound examiner can usually correctly and confidently discriminate between benign and malignant adnexal tumors on the basis of gray-scale imaging alone, using pattern recognition28, 45. However, approximately 10% of adnexal tumors are difficult to classify correctly as benign or malignant, even for an experienced examiner45, 50. The difficult tumors are often borderline tumors, papillary cystadeno(fibro)mas or struma ovarii, and at ultrasound examination they are often seen to have papillary projections or to be multilocular cysts with a very large number of locules50. It is for these types of difficult tumor that gray-scale imaging needs to be supplemented by additional diagnostic methods. It would be interesting to test the value of adding evaluation of the morphology of the vascular tree, as assessed by 3D power Doppler ultrasound, to gray-scale imaging in a very large series of difficult tumors. The problem is that such tumors are rare, and it would require a large multicenter study to collect enough data within a reasonable time. One could design such a study as a randomized trial, where women with difficult tumors were assigned to have either a 2D gray-scale ultrasound examination alone, or a 2D gray-scale examination supplemented by conventional 2D color or power Doppler ultrasound, or by 3D power Doppler examination of the morphology of the vessel tree, and then to compare the diagnostic performance of the three strategies.