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Predicting lymph node metastasis in papillary thyroid carcinoma patients by vascular index on power doppler US

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dc.contributor.author이지혜-
dc.date.accessioned2019-12-26T08:21:39Z-
dc.date.available2019-12-26T08:21:39Z-
dc.date.issued2017-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/173585-
dc.description.abstractBackground: Angiogenesis plays a crucial role in tumor growth and the metastatic spread of cancer. For patients with papillary thyroid carcinoma (PTC), lymph node metastasis (LNM) is associated with an increased recurrence rate. The purpose of this study was to investigate whether the vascular endothelial growth factor (VEGF), microvessel density (MVD), and vascular index (VI) can predict LNM in patients with PTC. Methods: From January 2011 to October 2011, 202 patients with PTCs underwent preoperative staging ultrasound (US) evaluation. To evaluate vascularity, we measured the VI, VEGF expression and MVD. Results: The VI was significantly correlated with MVD (P = 0.009). On multivariate analysis, young age showed a significant correlation with LNM (OR = 0.957, P = <0.001; OR = 0.955, P = <0.001; OR = 0.957, P = <0.001) and extrathyroidal extension had a marginal correlation with LNM (OR = 1.897, P = 0.058; OR = 2.155, P = 0.029; OR = 1.935, P = 0.053). However, the other clinicopathologic features, VEGF, MVD and VI failed to show any significant correlations with LNM. Conclusions: Although the VI showed significant correlation with MVD, it was not significantly correlated to LNM.-
dc.description.statementOfResponsibilityopen-
dc.publisher연세대학교-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titlePredicting lymph node metastasis in papillary thyroid carcinoma patients by vascular index on power doppler US-
dc.title.alternative파워도플러 초음파의 혈관 지수와 미세혈관 밀도 그리고 혈관내피성장인자를 이용하여 유두갑상샘암종 환자에서의 림프절 전이의 예측에 대한 유용성-
dc.typeThesis-
dc.contributor.collegeGraduate School, Yonsei University-
dc.contributor.departmentDept. of Medicine-
dc.contributor.localIdA05168-
dc.description.degree박사-
dc.contributor.alternativeNameLee, Ji Hye-
dc.contributor.affiliatedAuthor이지혜-
dc.type.localDissertation-
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