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Correlation Between Maximum Intensity and Microvessel Density for Differentiation of Malignant From Benign Thyroid Nodules on Contrast-Enhanced Sonography Jue Jiang, MD, Xu Shang, MD, Hongli Zhang, MM, Wenqi Ma, MM, Yongbo Xu, MM, Qi Zhou, MD, Ya Gao, MD, Shanshan Yu, MD, Yanhua Qi, MD Objectives—The purpose of this study was to retrospectively evaluate contrastenhanced sonography for differentiation of benign and malignant thyroid nodules by analyzing the correlation between maximum intensity and microvessel density. Methods—From February 2010 to May 2012, 122 patients (85 female and 37 male; mean age ± SD, 45 ± 9.1 years) with thyroid nodules (62 papillary thyroid carcinomas, 30 nodular goiters, and 30 adenomas) that underwent routine thyroid sonography and were diagnosed by surgery were included in this study. Contrast-enhanced sonography was performed, and enhancement patterns were classified into 3 groups: high, equal, and low enhancement. As a time-intensity curve parameter, the correlation of maximum intensity with CD31 and CD34 microvessel density counts was analyzed. Results—On contrast-enhanced sonography, most patients with papillary thyroid carcinomas showed a heterogeneous low enhancement pattern, whereas most patients with nodular goiters showed an equal enhancement pattern, and patients with adenomas showed a high enhancement pattern. The detection of papillary thyroid carcinomas with low enhancement had sensitivity of 96.8%, specificity of 95.0%, and accuracy of 95.9%. Compared with the papillary thyroid group, the mean microvessel density counts were significantly higher in the nodular goiter and adenoma groups (P < .05). We also found that the maximum intensity was significantly associated with CD31 and CD34 counts (CD31, r = 0.963; P < .01; CD34, r = 0.968; P < .01). Conclusions—Maximum intensity has a significant relationship with microvessel density. Contrast-enhanced sonography is a practical and convenient means for differentiating benign from malignant thyroid nodules. Received July 25, 2013, from the Department of Ultrasound, Second Affiliated Hospital, Medical School of Xi’an Jiaotong University, Xi’an, China. Revision requested August 23, 2013. Revised manuscript accepted for publication October 23, 2013. Drs Jiang and Zhou should be regarded as joint first authors. Address correspondence to Qi Zhou, MD, Department of Ultrasound, Second Affiliated Hospital, Medical School of Xi’an Jiaotong University, 710004 Xi’an, China. E-mail: [email protected] doi:10.7863/ultra.33.7.1257
Key Words—benign and malignant thyroid nodules; contrast-enhanced sonography; maximum intensity; microvessel density; superficial structures
T
hyroid nodules are common clinical problems, but an accurate clinical diagnosis is always difficult to make.1 The prevalence of thyroid nodules in adults is about 10% to 67% as detected with sonography.2 In general, thyroid nodules are divided into 2 categories: benign nodules, such as nodular goiters and adenomas, and malignant nodules, mainly including papillary thyroid carcinomas, follicular carcinomas, encephaloid carcinomas, and anaplastic carcinomas. Nowadays, many researchers have focused
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on the study of papillary thyroid carcinomas, which are the most common type of well-differentiated thyroid cancer3,4 and account for more than 70% of all malignant nodules.5 It is generally known that pathologic angiogenesis is a key marker for tumor growth and cancer,6 and microvessel density is a predictive index for identification of angiogenesis.7,8 Since microvessel density counting can only be used for evaluating tumor vessels and prognoses in surgical and biopsy specimens, the impact of sonography for assessing nodular thyroid disease has increased recently.9,10 Furthermore, the evaluation and management of thyroid nodules remain uncertain in some aspects11; therefore, a relatively new technique, contrast-enhanced sonography, has been shown to be promising for detecting and characterizing lesions in clinical applications.12–14 According to the literature, some investigators suggest that the secondgeneration sulfur hexafluoride microbubble contrast agent SonoVue (Bracco SpA, Milan, Italy) may have the ability to show some specific contrast enhancement patterns in lesions.15 However, the utility of contrast-enhanced sonography for categorizing thyroid nodules has not been fully evaluated.16 In addition, although correlations between maximum intensity and microvessel density have been demonstrated in mouse cancer models17,18 and patients with meningioma,19 the correlation in patients with thyroid nodules remains unknown. Hence, the purpose of our study was to clarify the correlation between maximum intensity and microvessel density for differentiation of malignant from benign thyroid nodules on contrast-enhanced sonography. The quantitative parameter maximum intensity and microvessel density markers CD31 and CD34 were used for characterizing the microvascular angiogenesis of thyroid nodules in Chinese patients. A deeper understanding of this relationship may contribute to determining the potential of contrastenhanced sonography for differentiating malignant from benign thyroid nodules.
Materials and Methods Patients From February 2010 to May 2012, the thyroid glands of 122 patients (85 female and 37 male; age range, 20–61 years; mean ± SD, 45 ± 9.1 years) were retrospectively analyzed. They underwent contrast-enhanced sonography and were scheduled to undergo thyroidectomy for previously diagnosed thyroid nodules, including papillary thyroid carcinomas (62 patients; size range, 5.1–23.1 mm; mean, 8.3 ± 3.7 mm), nodular goiters (30 patients; size range, 6.9–
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29.8 mm; mean, 17.9 ± 4.2 mm), and adenomas (30 patients; size range, 15.4–27.5 mm; mean, 21.3 ± 3.9 mm). The study was approved by the local Ethics Committee, and all patients gave their full informed consent. Contrast-Enhanced Sonography An Acuson Sequoia 512 color Doppler diagnostic ultrasound system (Siemens Medical Solutions, Mountain View, CA) with a 7-MHz linear array probe and a mechanical index of 0.32 was used for contrast-enhanced sonography. The contrast agent was SonoVue, injected intravenously as a bolus at a dose of 2.4 mL, followed by 5 mL of physiologic saline, via a 22-gauge peripheral intravenous cannula. To obtain the best imaging plane, the thyroid nodules were initially observed with sonography. Patients were instructed not to swallow during the procedure. Then SonoVue was injected. Each scan lasted 2 minutes and was digitally stored as raw data on the hard drive of the ultrasound machine. All contrast-enhanced sonographic examinations were performed within 10 minutes by 2 experienced physicians at our hospital (at least 2 years of professional experience). One physician was in charge of the SonoVue injections, and another operated the ultrasound machine to scan and capture images. The images were analyzed with SonoLiver software (TomTec Imaging Systems, Unterschleissheim, Germany) according to previous publications.20,21 Three regions of interest were drawn with this software. The border regions of interest (blue) represented the imaging acoustic window to be analyzed, including the thyroid nodule and the surrounding tissue. The nodule regions of interest (green) covered no less than 90% of the whole thyroid nodules. The reference regions of interest (yellow) were defined as the normal peripheral thyroid parenchyma near the same depth as the nodules. A quantitative time-intensity curve was drawn (Figure 1) to obtain the following indices: rise time (seconds), time to peak (in seconds), mean transit time (seconds), and maximum intensity (percentage of peak enhancement to peripheral tissue). The mean total examination time was 40 minutes, including contrastenhanced sonography and postprocessing. The contrastenhanced sonographic patterns were classified as high, equal, and low enhancement. A high enhancement pattern showed higher perfusion in the lesion than the surrounding parenchymal tissue after contrast agent injection; equal enhancement showed the same perfusion in the lesion as the surrounding parenchymal tissue; and low enhancement showed lower perfusion in the lesion than the surrounding parenchymal tissue. Immunohistochemical Analysis
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Gross specimens as well as 4-μm-thick hematoxylin-eosin– stained histologic sections of all cases were reviewed, and the tumor tissues obtained from the most representative paraffin blocks were mounted on poly-L-lysine–coated slides for immunostaining. Mouse antihuman CD31 and CD34 monoclonal antibodies (Maixin-BIO Corporation, Fujian, China) were used to label the vascular endothelial cytoplasm. Microvessel density was obtained by counting the microvessels in each tissue slide. Microvessels labeled with the CD31 and CD34 antibodies were counted by 2 experienced pathologists (double blinded) during pathologic diagnosis and quantified by the counting procedure of Weidner et al.22 Put simply, the 5 most vascular areas (ie, hot spots) with the highest numbers of microvessel profiles were chosen subjectively from each tumor section under a low-power lens (×100), and their microvessel numbers were counted under a high-power lens (×400). The mean microvessel number was the microvessel density of the tumor. Statistical Analyses Statistical analyses were performed with SPSS version 16.0 software (IBM Corporation, Armonk, NY). All quantitative data were reported as mean ± standard deviation. The microvessel density values between thyroid nodules and peripheral parenchyma were compared by a Student t test, and differences among the 3 groups were compared by analysis of variance. A χ2 test and a Fisher exact test were used for comparison of categorical variables. Pearson correlation analysis was used to determine the correlation between maximum intensity and microvessel density. P < .05 was considered statistically significant.
Results Enhancement Patterns on Contrast-Enhanced Sonography The contrast-enhanced sonographic patterns of the 122 patients were as follows: In the papillary thyroid carcinoma group, 60 patients showed a heterogeneous low enhancement pattern, and 2 patients showed a slightly high enhancement. In the nodular goiter group, 23 patients showed an equal enhancement pattern, whereas 4 patients showed high enhancement, and 3 showed low enhancement. In the adenoma group, 29 patients showed high enhancement (Figure 1), and 1 showed equal enhancement. The diagnostic performance of contrast-enhanced sonography was measured by using pathologic findings as the diagnostic standard. Low enhancement had sensitivity of 96.8% (60 of 62), specificity of 95.0% (57 of 60), accuracy of 95.9% (117 of 122), a positive predictive value of 95.2% (60 of 63), and a negative predictive value of 96.6% (57 of 59) for the detection of papillary thyroid carcinoma. Microvessel Density Analysis Figure 2 shows microvessel density counts of thyroid nodules of different pathologic types. Both the mean CD31 and CD34 microvessel density counts for adenomas (71.5 ± 6.7 and 72.5 ± 8.3, respectively) and nodular goiters (55.7 ± 8.8 and 56.0 ± 9.3) were significantly higher than those for papillary thyroid carcinomas (37.9 ± 5.1 and 38.0 ± 6.1; P < .05). There were no significant differences between CD31 and CD34 microvessel density counts in all groups (all P > .05).
Figure 1. A–C, Contrast-enhanced sonograms of thyroid nodules. A, Papillary thyroid carcinoma. B, Nodular goiter. C, Thyroid adenoma. D–F, Time-intensity curves of thyroid nodules (green lines) and peripheral tissue (yellow lines). D, Papillary thyroid carcinoma. E, Nodular goiter. F, Thyroid adenoma.
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Correlation Analysis of Maximum Intensity and Microvessel Density Compared with papillary thyroid carcinomas, the maximum intensities of nodular goiters and adenomas were significantly higher (P < .05). The maximum intensity of papillary
thyroid carcinomas was lowest, followed by nodular goiters and adenomas (Table 1). Both the CD31 and CD34 microvessel density counts were lower in the papillary thyroid carcinoma group than the other groups. The correlation analysis showed a strong correlation between CD31
Figure 2. Microvessel staining of thyroid nodules. A and D, Surgical specimens showing low microvessel density (thyroid papillary carcinoma cells immunostained brown and CD31 [A] and CD34 [D] immunostaining, original magnification ×200). B and E, Surgical specimens showing high microvessel density (nodular goiter cells immunostained brown and CD31 [B] and CD34 [E] immunostaining, original magnification ×200). C and F, Surgical specimens also showing high microvessel density (adenoma cells immunostained brown and CD31 [C] and CD34 [F] immunostaining, original magnification ×200).
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microvessel density, CD34 microvessel density, and maximum intensity in thyroid nodules (Figure 3), which was statistically significant (CD31, r = 0.963; P < .01; CD34, r = 0.968; P < .01).
Discussion Contrast-enhanced sonography is a useful screening tool for detection of organ nodules,23–25 but little information concerning differentiation of malignant from benign thyroid nodules is available. In our study, we differentiated benign and malignant thyroid nodules by contrastenhanced sonography with application of a second-generation contrast agent (SonoVue). In total, 60 papillary thyroid carcinomas in 62 patients showed heterogeneous low enhancement, whereas most patients with nodular goiters showed equal enhancement, and 29 patients with adenomas showed high enhancement pattern. The time-intensity curve (Figure 1) was analyzed by TomTec software, and microvessels in vascular hot spots were quantified by immunohistochemistry and vascular markers (CD31 and CD34) in these 3 groups. Finally, we found a significant Table 1. Comparison of Maximum Intensity and Microvessel Density in Thyroid Lesions by Pathologic Type Pathologic Type
Maximum Intensity, %
Papillary thyroid carcinoma Nodular goiter Adenoma
61.9 ± 11.8 102.9 ± 16.1a 128.8 ± 8.3a
Microvessel Density CD31 CD34 37.9 ± 5.1 55.7 ± 8.8a 71.5 ± 6.7a
aP < .05 compared with papillary thyroid carcinoma.
38.0 ± 6.1 56.0 ± 9.3a 72.5 ± 8.3a
correlation between maximum intensity and microvessel density, which were lower in the papillary thyroid group than the benign groups. Accordingly, this result conveys the fact that maximum intensity has a significant relationship with microvessel density, and contrast-enhanced sonography plays an important role in distinguishing benign from malignant thyroid nodules before surgery. Preoperative differentiation of malignant from benign thyroid nodules still represents an unsolved problem in endocrinology. Our findings support a previous study, which suggested that the contrast-enhanced sonographic parameters mean and peak intensity had a significant relationship with microvessel density. Thus, contrastenhanced sonography could be directed at distinguishing benign from malignant thyroid nodules.26 Nemec et al27 compared the relative peak enhancement (ratio of peak enhancement to baseline intensity) and the relative enhancement during the wash-out curve between benign and malignant nodules at different time points, and they concluded that contrast-enhanced sonography may become an adjunctive tool for assessing thyroid nodules. It has been reported that contrast-enhanced sonography was a highly sensitive method for detecting the microvascularization of thyroid carcinomas. By comparing the area under the curve of contrast between the middle and margin of suspicious lesions, it has been applied as a standard diagnostic procedure in the preoperatively evaluation of suspicious thyroid nodules.28 Some investigators reported that with histopathologic assessment, small benign and malignant liver lesions in a humanized tumor mouse model could be detected by a combination of contrast-enhanced sonography and other technologies.29 Other investigators found that contrast-enhanced sonographic patterns associated
Figure 3. Significant correlations between maximum intensity (IMAX) and microvessel density of thyroid nodules.
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with microvessel density counts were statistically significant in benign and malignant breast lesions, which indicated the contrast-enhanced sonography could serve as an effective tool for identifying malignancy or benignity of breast mass by evaluating angiogenesis.30 The most meaningful finding from our study is that contrast-enhanced sonography can be used for differentiating papillary thyroid carcinomas from solitary thyroid nodules and adenomas. Microvessel density has become the reference standard for quantification of blood vessels.31 However, with lagging guidance, it only applies to postoperative specimens for retrospective assessment. Therefore, it is necessary to explore a correlation with a noninvasive imaging method to predict tumor angiogenesis before surgery. In our study, we found a positive correlation between the maximum intensity and microvessel density of thyroid nodules, which implies that maximum intensity on contrastenhanced sonography can reflect microvessel density to some extent. The results indirectly reflected the blood perfusion of the lesions. Our work emphasizes the finding that the heterogeneous low contrast-enhanced sonographic patterns in papillary thyroid carcinomas are distinctly different from the homogeneous low patterns in benign thyroid nodules. Similarly, Bartolotta et al15 reported that the enhancement of thyroid nodules were associated with the diameter of the nodule. In short, tumor vascularity in papillary thyroid carcinomas can be evaluated by contrast-enhanced sonography. To establish this method as an efficient tool for identifying thyroid nodules, a large-scale prospective study may be conducted in the near future to confirm our findings. In conclusion, enhancement patterns on contrastenhanced sonography are different in malignant and benign thyroid nodules. Notably, there is a positive correlation between maximum intensity and microvessel density in thyroid nodules. Furthermore, contrast-enhanced sonography is useful for distinguishing malignant from benign thyroid nodules. Our work may provide clinically valuable information for diagnosis and treatment of thyroid nodules.
References 1.
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Cooper DS, Doherty GM, Haugen BR, et al. Management guidelines for patients with thyroid nodules and differentiated thyroid cancer. Thyroid 2006; 16:109–142. Cronan JJ. Thyroid nodules: is it time to turn off the US machines? Radiology 2008; 247:602–604. Hu MI, Vassilopoulou-Sellin R, Lustig R, Lamont JP. Thyroid and parathyroid cancers. In: Pazdur R, Wagman LD, Camphausen KA, Hoskins WJ (eds). Cancer Management: A Multidisciplinary Approach. 11th ed. London, England: UBM; 2008.
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Lee SH, Lee SJ, Jin SM, et al. Relationships between lymph node metastasis and expression of CD31, D2-40, and vascular endothelial growth factors A and C in papillary thyroid cancer. Clin Exp Otorhinolaryngol 2012; 5:150–155. Kim SH, Kim BS, Jung SL, et al. Ultrasonographic findings of medullary thyroid carcinoma: a comparison with papillary thyroid carcinoma. Korean J Radiol 2009; 10:101–105. Carmeliet P, Jain RK. Angiogenesis in cancer and other diseases. Nature 2000; 407:249–257. Shivakumar S, Prabhakar BT, Jayashree K, Rajan MG, Salimath BP. Evaluation of serum vascular endothelial growth factor (VEGF) and microvessel density (MVD) as prognostic indicators in carcinoma breast. J Cancer Res Clin Oncol 2009; 135:627–636. Zhuang H, Yang ZG, Chen HJ, Peng YL, Li L. Time-intensity curve parameters in colorectal tumours measured using double contrastenhanced ultrasound: correlations with tumour angiogenesis. Colorectal Dis 2012; 14:181–187. Bastin S, Bolland MJ, Croxson MS. Role of ultrasound in the assessment of nodular thyroid disease. J Med Imaging Radiat Oncol 2009; 53:177–187. Lee YH, Kim DW, In HS, et al. Differentiation between benign and malignant solid thyroid nodules using an US classification system. Korean J Radiol 2011; 12:559–567. Giuffrida D, Gharib H. Controversies in the management of cold, hot, and occult thyroid nodules. Am J Med 1995; 99:642–650. Clevert DA, D’Anastasi M, and Jung EM. Contrast-enhanced ultrasound and microcirculation: efficiency through dynamics—current developments. Clin Hemorheol Microcirc 2013; 53:171–186. Greis C. Quantitative evaluation of microvascular blood flow by contrastenhanced ultrasound (CEUS). Clin Hemorheol Microcirc 2011; 49:137–149. Horvath E, Majlis S, Rossi R, et al. An ultrasonogram reporting system for thyroid nodules stratifying cancer risk for clinical management. J Clin Endocrinol Metab 2009; 94:1748–1751. Bartolotta TV, Midiri M, Galia M, et al. Qualitative and quantitative evaluation of solitary thyroid nodules with contrast-enhanced ultrasound: initial results. Eur Radiol 2006; 16:2234–2241. Zhang B, Jiang YX, Liu JB, et al. Utility of contrast-enhanced ultrasound for evaluation of thyroid nodules. Thyroid 2010; 20:51–57. Lee HJ, Hwang SI, Chung JH, Jeon JJ, Choi JH, Jung HS. Evaluation of tumor angiogenesis in a mouse PC-3 prostate cancer model using dynamic contrast-enhanced sonography. J Ultrasound Med 2012; 31:1223–1231. Pysz MA, Foygel K, Panje CM, Needles A, Tian L, Willmann JK. Assessment and monitoring tumor vascularity with contrast-enhanced ultrasound maximum intensity persistence imaging. Invest Radiol 2011; 46:187–195. Yrjänä SK, Tuominen H, Karttunen A, Lähdesluoma N, Heikkinen E, Koivukangas J. Low-field MR imaging of meningiomas including dynamic contrast enhancement study: evaluation of surgical and histopathologic characteristics. AJNR Am J Neuroradiol 2006; 27:2128– 2134.
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20. Hirata K, Pulerwitz T, Sciacca R, et al. Clinical utility of new real time threedimensional transthoracic echocardiography in assessment of mitral valve prolapse. Echocardiography 2008; 25:482–488. 21. Yuan Z, Quan J, Yunxiao Z, Jian C, Zhu H, Liping G. Diagnostic value of contrast-enhanced ultrasound parametric imaging in breast tumors. J Breast Cancer 2013; 16:208–213. 22. Weidner N, Semple JP, Welch WR, Folkman J. Tumor angiogenesis and metastasis: correlation in invasive breast carcinoma. N Engl J Med 1991; 324:1–8. 23. Houtzager S, Wijkstra H, de la Rosette JJ, Laguna MP. Evaluation of renal masses with contrast-enhanced ultrasound. Curr Urol Rep 2013; 14:116– 123. 24. Molinari F, Mantovani A, Deandrea M, Limone P, Garberoglio R, Suri JS. Characterization of single thyroid nodules by contrast-enhanced 3-D ultrasound. Ultrasound Med Biol 2010; 36:1616–1625. 25. Pei XQ, Liu LZ, Zheng W, et al. Contrast-enhanced ultrasonography of hepatocellular carcinoma: correlation between quantitative parameters and arteries in neoangiogenesis or sinusoidal capillarization. Eur J Radiol 2012; 81:e182–e188. 26. Wei X, Li Y, Zhang S, Li X, Luo J, Ming G. Evaluation of microcirculation of thyroid cancer in Chinese females with breast cancer using contrastenhanced ultrasound (CEUS) combined with VEGF and microvessel density (MVD) [published online ahead of print March 11, 2013; withdrawn]. Clin Hemorheol Microcirc. doi:10.3233/CH-131712. 27. Nemec U, Nemec SF, Novotny C, Weber M, Czerny C, Krestan CR. Quantitative evaluation of contrast-enhanced ultrasound after intravenous administration of a microbubble contrast agent for differentiation of benign and malignant thyroid nodules: assessment of diagnostic accuracy. Eur Radiol 2012; 22:1357–1365. 28. Hornung M, Jung EM, Georgieva M, Schlitt HJ, Stroszczynski C, Agha A. Detection of microvascularization of thyroid carcinomas using linear high resolution contrast-enhanced ultrasonography (CEUS). Clin Hemorheol Microcirc 2012; 52:197–203. 29. Wege AK, Schardt K, Schaefer S, Kroemer A, Brockhoff G, Jung EM. High resolution ultrasound including elastography and contrast-enhanced ultrasound (CEUS) for early detection and characterization of liver lesions in the humanized tumor mouse model. Clin Hemorheol Microcirc 2012; 52:93–106. 30. Xi W, Ying L, Ying Z, Sheng Z. Microvascularity of breast lesions evaluated by contrast-enhanced ultrasound imaging combined with pathologic basis of angiogenesis. Chin J Clin 2011; 5:120–124. 31. Laforga J, Aranda FI. Angiogenic index: a new method for assessing microvascularity in breast carcinoma with possible prognostic implications. Breast J 2000; 6:103–107.
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Correlation Between Maximum Intensity and Microvessel Density for Differentiation of Malignant From Benign Thyroid Nodules on Contrast-Enhanced Sonography Jue Jiang, MD, Xu Shang, MD, Hongli Zhang, MM, Wenqi Ma, MM, Yongbo Xu, MM, Qi Zhou, MD, Ya Gao, MD, Shanshan Yu, MD, Yanhua Qi, MD Objectives—The purpose of this study was to retrospectively evaluate contrastenhanced sonography for differentiation of benign and malignant thyroid nodules by analyzing the correlation between maximum intensity and microvessel density. Methods—From February 2010 to May 2012, 122 patients (85 female and 37 male; mean age ± SD, 45 ± 9.1 years) with thyroid nodules (62 papillary thyroid carcinomas, 30 nodular goiters, and 30 adenomas) that underwent routine thyroid sonography and were diagnosed by surgery were included in this study. Contrast-enhanced sonography was performed, and enhancement patterns were classified into 3 groups: high, equal, and low enhancement. As a time-intensity curve parameter, the correlation of maximum intensity with CD31 and CD34 microvessel density counts was analyzed. Results—On contrast-enhanced sonography, most patients with papillary thyroid carcinomas showed a heterogeneous low enhancement pattern, whereas most patients with nodular goiters showed an equal enhancement pattern, and patients with adenomas showed a high enhancement pattern. The detection of papillary thyroid carcinomas with low enhancement had sensitivity of 96.8%, specificity of 95.0%, and accuracy of 95.9%. Compared with the papillary thyroid group, the mean microvessel density counts were significantly higher in the nodular goiter and adenoma groups (P < .05). We also found that the maximum intensity was significantly associated with CD31 and CD34 counts (CD31, r = 0.963; P < .01; CD34, r = 0.968; P < .01). Conclusions—Maximum intensity has a significant relationship with microvessel density. Contrast-enhanced sonography is a practical and convenient means for differentiating benign from malignant thyroid nodules. Received July 25, 2013, from the Department of Ultrasound, Second Affiliated Hospital, Medical School of Xi’an Jiaotong University, Xi’an, China. Revision requested August 23, 2013. Revised manuscript accepted for publication October 23, 2013. Drs Jiang and Zhou should be regarded as joint first authors. Address correspondence to Qi Zhou, MD, Department of Ultrasound, Second Affiliated Hospital, Medical School of Xi’an Jiaotong University, 710004 Xi’an, China. E-mail: [email protected] doi:10.7863/ultra.33.7.1257
Key Words—benign and malignant thyroid nodules; contrast-enhanced sonography; maximum intensity; microvessel density; superficial structures
T
hyroid nodules are common clinical problems, but an accurate clinical diagnosis is always difficult to make.1 The prevalence of thyroid nodules in adults is about 10% to 67% as detected with sonography.2 In general, thyroid nodules are divided into 2 categories: benign nodules, such as nodular goiters and adenomas, and malignant nodules, mainly including papillary thyroid carcinomas, follicular carcinomas, encephaloid carcinomas, and anaplastic carcinomas. Nowadays, many researchers have focused
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on the study of papillary thyroid carcinomas, which are the most common type of well-differentiated thyroid cancer3,4 and account for more than 70% of all malignant nodules.5 It is generally known that pathologic angiogenesis is a key marker for tumor growth and cancer,6 and microvessel density is a predictive index for identification of angiogenesis.7,8 Since microvessel density counting can only be used for evaluating tumor vessels and prognoses in surgical and biopsy specimens, the impact of sonography for assessing nodular thyroid disease has increased recently.9,10 Furthermore, the evaluation and management of thyroid nodules remain uncertain in some aspects11; therefore, a relatively new technique, contrast-enhanced sonography, has been shown to be promising for detecting and characterizing lesions in clinical applications.12–14 According to the literature, some investigators suggest that the secondgeneration sulfur hexafluoride microbubble contrast agent SonoVue (Bracco SpA, Milan, Italy) may have the ability to show some specific contrast enhancement patterns in lesions.15 However, the utility of contrast-enhanced sonography for categorizing thyroid nodules has not been fully evaluated.16 In addition, although correlations between maximum intensity and microvessel density have been demonstrated in mouse cancer models17,18 and patients with meningioma,19 the correlation in patients with thyroid nodules remains unknown. Hence, the purpose of our study was to clarify the correlation between maximum intensity and microvessel density for differentiation of malignant from benign thyroid nodules on contrast-enhanced sonography. The quantitative parameter maximum intensity and microvessel density markers CD31 and CD34 were used for characterizing the microvascular angiogenesis of thyroid nodules in Chinese patients. A deeper understanding of this relationship may contribute to determining the potential of contrastenhanced sonography for differentiating malignant from benign thyroid nodules.
Materials and Methods Patients From February 2010 to May 2012, the thyroid glands of 122 patients (85 female and 37 male; age range, 20–61 years; mean ± SD, 45 ± 9.1 years) were retrospectively analyzed. They underwent contrast-enhanced sonography and were scheduled to undergo thyroidectomy for previously diagnosed thyroid nodules, including papillary thyroid carcinomas (62 patients; size range, 5.1–23.1 mm; mean, 8.3 ± 3.7 mm), nodular goiters (30 patients; size range, 6.9–
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29.8 mm; mean, 17.9 ± 4.2 mm), and adenomas (30 patients; size range, 15.4–27.5 mm; mean, 21.3 ± 3.9 mm). The study was approved by the local Ethics Committee, and all patients gave their full informed consent. Contrast-Enhanced Sonography An Acuson Sequoia 512 color Doppler diagnostic ultrasound system (Siemens Medical Solutions, Mountain View, CA) with a 7-MHz linear array probe and a mechanical index of 0.32 was used for contrast-enhanced sonography. The contrast agent was SonoVue, injected intravenously as a bolus at a dose of 2.4 mL, followed by 5 mL of physiologic saline, via a 22-gauge peripheral intravenous cannula. To obtain the best imaging plane, the thyroid nodules were initially observed with sonography. Patients were instructed not to swallow during the procedure. Then SonoVue was injected. Each scan lasted 2 minutes and was digitally stored as raw data on the hard drive of the ultrasound machine. All contrast-enhanced sonographic examinations were performed within 10 minutes by 2 experienced physicians at our hospital (at least 2 years of professional experience). One physician was in charge of the SonoVue injections, and another operated the ultrasound machine to scan and capture images. The images were analyzed with SonoLiver software (TomTec Imaging Systems, Unterschleissheim, Germany) according to previous publications.20,21 Three regions of interest were drawn with this software. The border regions of interest (blue) represented the imaging acoustic window to be analyzed, including the thyroid nodule and the surrounding tissue. The nodule regions of interest (green) covered no less than 90% of the whole thyroid nodules. The reference regions of interest (yellow) were defined as the normal peripheral thyroid parenchyma near the same depth as the nodules. A quantitative time-intensity curve was drawn (Figure 1) to obtain the following indices: rise time (seconds), time to peak (in seconds), mean transit time (seconds), and maximum intensity (percentage of peak enhancement to peripheral tissue). The mean total examination time was 40 minutes, including contrastenhanced sonography and postprocessing. The contrastenhanced sonographic patterns were classified as high, equal, and low enhancement. A high enhancement pattern showed higher perfusion in the lesion than the surrounding parenchymal tissue after contrast agent injection; equal enhancement showed the same perfusion in the lesion as the surrounding parenchymal tissue; and low enhancement showed lower perfusion in the lesion than the surrounding parenchymal tissue. Immunohistochemical Analysis
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Gross specimens as well as 4-μm-thick hematoxylin-eosin– stained histologic sections of all cases were reviewed, and the tumor tissues obtained from the most representative paraffin blocks were mounted on poly-L-lysine–coated slides for immunostaining. Mouse antihuman CD31 and CD34 monoclonal antibodies (Maixin-BIO Corporation, Fujian, China) were used to label the vascular endothelial cytoplasm. Microvessel density was obtained by counting the microvessels in each tissue slide. Microvessels labeled with the CD31 and CD34 antibodies were counted by 2 experienced pathologists (double blinded) during pathologic diagnosis and quantified by the counting procedure of Weidner et al.22 Put simply, the 5 most vascular areas (ie, hot spots) with the highest numbers of microvessel profiles were chosen subjectively from each tumor section under a low-power lens (×100), and their microvessel numbers were counted under a high-power lens (×400). The mean microvessel number was the microvessel density of the tumor. Statistical Analyses Statistical analyses were performed with SPSS version 16.0 software (IBM Corporation, Armonk, NY). All quantitative data were reported as mean ± standard deviation. The microvessel density values between thyroid nodules and peripheral parenchyma were compared by a Student t test, and differences among the 3 groups were compared by analysis of variance. A χ2 test and a Fisher exact test were used for comparison of categorical variables. Pearson correlation analysis was used to determine the correlation between maximum intensity and microvessel density. P < .05 was considered statistically significant.
Results Enhancement Patterns on Contrast-Enhanced Sonography The contrast-enhanced sonographic patterns of the 122 patients were as follows: In the papillary thyroid carcinoma group, 60 patients showed a heterogeneous low enhancement pattern, and 2 patients showed a slightly high enhancement. In the nodular goiter group, 23 patients showed an equal enhancement pattern, whereas 4 patients showed high enhancement, and 3 showed low enhancement. In the adenoma group, 29 patients showed high enhancement (Figure 1), and 1 showed equal enhancement. The diagnostic performance of contrast-enhanced sonography was measured by using pathologic findings as the diagnostic standard. Low enhancement had sensitivity of 96.8% (60 of 62), specificity of 95.0% (57 of 60), accuracy of 95.9% (117 of 122), a positive predictive value of 95.2% (60 of 63), and a negative predictive value of 96.6% (57 of 59) for the detection of papillary thyroid carcinoma. Microvessel Density Analysis Figure 2 shows microvessel density counts of thyroid nodules of different pathologic types. Both the mean CD31 and CD34 microvessel density counts for adenomas (71.5 ± 6.7 and 72.5 ± 8.3, respectively) and nodular goiters (55.7 ± 8.8 and 56.0 ± 9.3) were significantly higher than those for papillary thyroid carcinomas (37.9 ± 5.1 and 38.0 ± 6.1; P < .05). There were no significant differences between CD31 and CD34 microvessel density counts in all groups (all P > .05).
Figure 1. A–C, Contrast-enhanced sonograms of thyroid nodules. A, Papillary thyroid carcinoma. B, Nodular goiter. C, Thyroid adenoma. D–F, Time-intensity curves of thyroid nodules (green lines) and peripheral tissue (yellow lines). D, Papillary thyroid carcinoma. E, Nodular goiter. F, Thyroid adenoma.
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Correlation Analysis of Maximum Intensity and Microvessel Density Compared with papillary thyroid carcinomas, the maximum intensities of nodular goiters and adenomas were significantly higher (P < .05). The maximum intensity of papillary
thyroid carcinomas was lowest, followed by nodular goiters and adenomas (Table 1). Both the CD31 and CD34 microvessel density counts were lower in the papillary thyroid carcinoma group than the other groups. The correlation analysis showed a strong correlation between CD31
Figure 2. Microvessel staining of thyroid nodules. A and D, Surgical specimens showing low microvessel density (thyroid papillary carcinoma cells immunostained brown and CD31 [A] and CD34 [D] immunostaining, original magnification ×200). B and E, Surgical specimens showing high microvessel density (nodular goiter cells immunostained brown and CD31 [B] and CD34 [E] immunostaining, original magnification ×200). C and F, Surgical specimens also showing high microvessel density (adenoma cells immunostained brown and CD31 [C] and CD34 [F] immunostaining, original magnification ×200).
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microvessel density, CD34 microvessel density, and maximum intensity in thyroid nodules (Figure 3), which was statistically significant (CD31, r = 0.963; P < .01; CD34, r = 0.968; P < .01).
Discussion Contrast-enhanced sonography is a useful screening tool for detection of organ nodules,23–25 but little information concerning differentiation of malignant from benign thyroid nodules is available. In our study, we differentiated benign and malignant thyroid nodules by contrastenhanced sonography with application of a second-generation contrast agent (SonoVue). In total, 60 papillary thyroid carcinomas in 62 patients showed heterogeneous low enhancement, whereas most patients with nodular goiters showed equal enhancement, and 29 patients with adenomas showed high enhancement pattern. The time-intensity curve (Figure 1) was analyzed by TomTec software, and microvessels in vascular hot spots were quantified by immunohistochemistry and vascular markers (CD31 and CD34) in these 3 groups. Finally, we found a significant Table 1. Comparison of Maximum Intensity and Microvessel Density in Thyroid Lesions by Pathologic Type Pathologic Type
Maximum Intensity, %
Papillary thyroid carcinoma Nodular goiter Adenoma
61.9 ± 11.8 102.9 ± 16.1a 128.8 ± 8.3a
Microvessel Density CD31 CD34 37.9 ± 5.1 55.7 ± 8.8a 71.5 ± 6.7a
aP < .05 compared with papillary thyroid carcinoma.
38.0 ± 6.1 56.0 ± 9.3a 72.5 ± 8.3a
correlation between maximum intensity and microvessel density, which were lower in the papillary thyroid group than the benign groups. Accordingly, this result conveys the fact that maximum intensity has a significant relationship with microvessel density, and contrast-enhanced sonography plays an important role in distinguishing benign from malignant thyroid nodules before surgery. Preoperative differentiation of malignant from benign thyroid nodules still represents an unsolved problem in endocrinology. Our findings support a previous study, which suggested that the contrast-enhanced sonographic parameters mean and peak intensity had a significant relationship with microvessel density. Thus, contrastenhanced sonography could be directed at distinguishing benign from malignant thyroid nodules.26 Nemec et al27 compared the relative peak enhancement (ratio of peak enhancement to baseline intensity) and the relative enhancement during the wash-out curve between benign and malignant nodules at different time points, and they concluded that contrast-enhanced sonography may become an adjunctive tool for assessing thyroid nodules. It has been reported that contrast-enhanced sonography was a highly sensitive method for detecting the microvascularization of thyroid carcinomas. By comparing the area under the curve of contrast between the middle and margin of suspicious lesions, it has been applied as a standard diagnostic procedure in the preoperatively evaluation of suspicious thyroid nodules.28 Some investigators reported that with histopathologic assessment, small benign and malignant liver lesions in a humanized tumor mouse model could be detected by a combination of contrast-enhanced sonography and other technologies.29 Other investigators found that contrast-enhanced sonographic patterns associated
Figure 3. Significant correlations between maximum intensity (IMAX) and microvessel density of thyroid nodules.
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with microvessel density counts were statistically significant in benign and malignant breast lesions, which indicated the contrast-enhanced sonography could serve as an effective tool for identifying malignancy or benignity of breast mass by evaluating angiogenesis.30 The most meaningful finding from our study is that contrast-enhanced sonography can be used for differentiating papillary thyroid carcinomas from solitary thyroid nodules and adenomas. Microvessel density has become the reference standard for quantification of blood vessels.31 However, with lagging guidance, it only applies to postoperative specimens for retrospective assessment. Therefore, it is necessary to explore a correlation with a noninvasive imaging method to predict tumor angiogenesis before surgery. In our study, we found a positive correlation between the maximum intensity and microvessel density of thyroid nodules, which implies that maximum intensity on contrastenhanced sonography can reflect microvessel density to some extent. The results indirectly reflected the blood perfusion of the lesions. Our work emphasizes the finding that the heterogeneous low contrast-enhanced sonographic patterns in papillary thyroid carcinomas are distinctly different from the homogeneous low patterns in benign thyroid nodules. Similarly, Bartolotta et al15 reported that the enhancement of thyroid nodules were associated with the diameter of the nodule. In short, tumor vascularity in papillary thyroid carcinomas can be evaluated by contrast-enhanced sonography. To establish this method as an efficient tool for identifying thyroid nodules, a large-scale prospective study may be conducted in the near future to confirm our findings. In conclusion, enhancement patterns on contrastenhanced sonography are different in malignant and benign thyroid nodules. Notably, there is a positive correlation between maximum intensity and microvessel density in thyroid nodules. Furthermore, contrast-enhanced sonography is useful for distinguishing malignant from benign thyroid nodules. Our work may provide clinically valuable information for diagnosis and treatment of thyroid nodules.
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