本文選題：超聲檢查 + 甲狀腺結(jié)節(jié)�。� 參考：《中國(guó)介入影像與治療學(xué)》2017年12期

【摘要】：目的探討Logistic回歸分析在常規(guī)超聲及CEUS診斷甲狀腺良惡性結(jié)節(jié)中的價(jià)值。方法選取經(jīng)超聲引導(dǎo)下穿刺活檢或術(shù)后病理證實(shí)的甲狀腺結(jié)節(jié)患者218例,其中惡性結(jié)節(jié)74例,良性結(jié)節(jié)144例,觀察結(jié)節(jié)邊界、形態(tài)、縱橫比、微鈣化、回聲類型、血流分級(jí)以及CEUS增強(qiáng)模式等超聲特征,并對(duì)其行單因素分析,以有統(tǒng)計(jì)學(xué)意義的指標(biāo)為因變量,行多因素Logistic回歸分析,建立ROC曲線。結(jié)果單因素分析顯示低回聲、形態(tài)不規(guī)則、邊界不清、縱橫比≥1、微鈣化、血流分級(jí)(Ⅰ、Ⅱ級(jí))、不均勻增強(qiáng)及低增強(qiáng)是診斷甲狀腺惡性結(jié)節(jié)的重要指標(biāo)(P均0.01)。多因素分析顯示形態(tài)不規(guī)則、微鈣化、不均勻增強(qiáng)及低增強(qiáng)是甲狀腺惡性結(jié)節(jié)的獨(dú)立預(yù)測(cè)指標(biāo)(P均0.05)。以Logistic回歸模型預(yù)測(cè)甲狀腺惡性結(jié)節(jié)的準(zhǔn)確率為82.57%,ROC曲線下面積為0.906。結(jié)論根據(jù)甲狀腺結(jié)節(jié)邊界、形態(tài)、縱橫比、微鈣化、回聲類型、血流分級(jí)以及CEUS增強(qiáng)特征建立的Logistic回歸模型有助于診斷甲狀腺惡性結(jié)節(jié)。
[Abstract]:Objective to evaluate the value of Logistic regression analysis in the diagnosis of benign and malignant thyroid nodules by conventional ultrasound and CEUS. Methods 218 patients with thyroid nodules confirmed by ultrasound guided biopsy or postoperative pathology were selected, including 74 malignant nodules and 144 benign nodules. The boundary, shape, aspect ratio, microcalcification and echo type of thyroid nodules were observed. Ultrasound features such as blood flow grading and CEUS enhancement mode were analyzed by univariate analysis. The multivariate Logistic regression analysis was performed to establish the ROC curve. Results univariate analysis showed that hypoechoic, irregular shape, unclear boundary, aspect ratio 鈮，

本文編號(hào)：1849084