甲状腺结节超声征象分级评估与报告系统的临床研究

发布时间：2018-06-04 10:49

  本文选题：甲状腺 + 甲状腺肿瘤　； 参考：《福建医科大学》2014年硕士论文

【摘要】：目的探讨灰阶超声、多普勒血流成像及弹性成像鉴别甲状腺良恶性结节的价值，并尝试用一种简便易行的分类方法制定甲状腺结节恶性危险度分类报告方案，并验证其临床应用价值。 方法第一部分:纵/横比回顾性分析785例甲状腺手术患者的1012个甲状腺结节的声像图，用t检验比较良、恶性结节的最大径，用卡方检验或Fisher精确概率法比较结节数目、、边缘、边界、晕环、结构成份、回声水平、钙化类型、血流模式、弹性评分、结节与被膜关系及周围淋巴结转移情况等。用Logistic回归(逐步法)获得恶性相关征象的OR值，据此赋予有鉴别价值的征象不同的分值。统计各分值结节的恶性比例及由回归方程计算的预测概率。 第二部分:根据预测概率及恶性比例对不同分值的结节进行初步分类。并结合文献报道及单因素分析结果对初步分类方法进行调整，建立一个分良恶性两种模式的甲状腺结节分类诊断方案：Ⅰ类“良性结节”、Ⅱ类“可能良性”、ⅢA“低度可疑恶性”、ⅢB“中度可疑恶性”、ⅢC“高度可疑恶性”、Ⅳ类“较确定恶性”。应用该方案对术前患者的甲状腺结节进行前瞻性分类评估，并以手术病理诊断为金标准分析此方案的应用价值。 结果第一部分:单纯胶质囊肿及海绵样结节为良性结节的特异性表现；结节内“暴风雪”样簇状微钙化、结节突破腺体被膜、甲状腺周围淋巴结转移征象为恶性结节的特异征象；中央型血流、低回声、边缘不光滑、纵/横比大于1、厚薄不均晕环、散在微钙化及极低回声这7个声像特征与恶性有不同程度的相关性，其OR值分别为2、7、8、11、16、58、72。 第二部分:回顾性资料中Ⅰ类结节均为良性，其余类别的恶性比例随着分类级别的提高而增高，该分类方案预测恶性的ROC曲线下面积为0.964。前瞻性资料中，术前分类为Ⅰ类的结节均为良性，Ⅱ类、ⅢA、ⅢB、ⅢC、Ⅳ类结节的恶性比例同样随着级别的提高而增高，并且各类结节恶性比例与回顾性资料相比，差异均无统计学意义，，其预测恶性的ROC曲线下面积为0.970。 结论本研究对甲状腺结节超声评估指标进行分类并评分，分良恶性两种模式对结节进行TI-RADS (Thyroid Imaging Reporting and Data System,甲状腺影像报告与数据系统)分类，有助于预测结节的恶性危险度。
[Abstract]:Objective to study the value of gray scale ultrasound, Doppler flow imaging and elastic imaging in differentiating benign and malignant thyroid nodules, and to make a classification and report scheme of thyroid nodule malignant risk by a simple and convenient classification method. Its clinical application value was verified. Methods the first part: the longitudinal / transverse ratio of 1012 thyroid nodules in 785 patients undergoing thyroid surgery was analyzed retrospectively. The maximum diameter of benign and malignant nodules was compared by t test, and the number and edge of nodules were compared by chi-square test or Fisher accurate probability method. Boundary, halo ring, structural composition, echo level, calcification type, blood flow pattern, elastic score, the relationship between nodule and capsule and lymph node metastasis. The OR value of malignant correlation signs was obtained by Logistic regression (stepwise method). The malignancy ratio of nodule and the prediction probability calculated by regression equation were calculated. Part two: according to the probability of prediction and the proportion of malignancy, the nodules with different scores are preliminarily classified. According to the results of literature report and univariate analysis, the preliminary classification method was adjusted to establish a classification and diagnosis scheme of thyroid nodule classified into benign and malignant models: type 鈪

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