中国医学影像学杂志
中國醫學影像學雜誌
중국의학영상학잡지
CHINESE JOURNAL OF MEDICAL IMAGING
2013年
6期
447-450
,共4页
陈晓然%唐少珊%于冬梅%刘站
陳曉然%唐少珊%于鼕梅%劉站
진효연%당소산%우동매%류참
胆囊肿瘤%超声检查,多普勒,彩色%诊断,鉴别%Logistic模型
膽囊腫瘤%超聲檢查,多普勒,綵色%診斷,鑒彆%Logistic模型
담낭종류%초성검사,다보륵,채색%진단,감별%Logistic모형
Gallbladder neoplasms%Ultrasonography,Doppler,color%Diagnosis,differential%Logistic models
目的通过建立直径≥1 cm胆囊隆起样病变超声诊断的Logistic回归模型，筛选有助于鉴别此类病变良、恶性的超声特征。资料与方法回顾性分析165例经病理证实的直径≥1 cm胆囊隆起样病变的超声特征，包括病灶数目、大小、形态及基底宽窄，是否合并胆囊结石，胆囊壁是否连续，彩色多普勒血流显像是否检出血流信号等，通过多因素回归分析建立二分类Logistic回归模型，评价Logistic回归模型预报此类病变良、恶性的效能。结果经过二分类Logistic回归分析，病变形态、基底宽窄、彩色多普勒血流显像是否检出血流信号3个特征变量进入Logistic回归模型，是鉴别诊断胆囊隆起样病变良、恶性的敏感指标。二分类Logistic回归模型预报直径≥1 cm胆囊隆起样病变良、恶性的准确度、敏感度、特异度分别为97.0%、93.8%、97.3%，ROC曲线下面积为0.979。结论二分类Logistic回归分析能够筛选出对鉴别诊断直径≥1 cm胆囊隆起样病变良、恶性有意义的超声特征，病变形态、基底宽窄及血流信号对鉴别诊断病变的良、恶性有重要价值。
目的通過建立直徑≥1 cm膽囊隆起樣病變超聲診斷的Logistic迴歸模型，篩選有助于鑒彆此類病變良、噁性的超聲特徵。資料與方法迴顧性分析165例經病理證實的直徑≥1 cm膽囊隆起樣病變的超聲特徵，包括病竈數目、大小、形態及基底寬窄，是否閤併膽囊結石，膽囊壁是否連續，綵色多普勒血流顯像是否檢齣血流信號等，通過多因素迴歸分析建立二分類Logistic迴歸模型，評價Logistic迴歸模型預報此類病變良、噁性的效能。結果經過二分類Logistic迴歸分析，病變形態、基底寬窄、綵色多普勒血流顯像是否檢齣血流信號3箇特徵變量進入Logistic迴歸模型，是鑒彆診斷膽囊隆起樣病變良、噁性的敏感指標。二分類Logistic迴歸模型預報直徑≥1 cm膽囊隆起樣病變良、噁性的準確度、敏感度、特異度分彆為97.0%、93.8%、97.3%，ROC麯線下麵積為0.979。結論二分類Logistic迴歸分析能夠篩選齣對鑒彆診斷直徑≥1 cm膽囊隆起樣病變良、噁性有意義的超聲特徵，病變形態、基底寬窄及血流信號對鑒彆診斷病變的良、噁性有重要價值。
목적통과건립직경≥1 cm담낭륭기양병변초성진단적Logistic회귀모형，사선유조우감별차류병변량、악성적초성특정。자료여방법회고성분석165례경병리증실적직경≥1 cm담낭륭기양병변적초성특정，포괄병조수목、대소、형태급기저관착，시부합병담낭결석，담낭벽시부련속，채색다보륵혈류현상시부검출혈류신호등，통과다인소회귀분석건립이분류Logistic회귀모형，평개Logistic회귀모형예보차류병변량、악성적효능。결과경과이분류Logistic회귀분석，병변형태、기저관착、채색다보륵혈류현상시부검출혈류신호3개특정변량진입Logistic회귀모형，시감별진단담낭륭기양병변량、악성적민감지표。이분류Logistic회귀모형예보직경≥1 cm담낭륭기양병변량、악성적준학도、민감도、특이도분별위97.0%、93.8%、97.3%，ROC곡선하면적위0.979。결론이분류Logistic회귀분석능구사선출대감별진단직경≥1 cm담낭륭기양병변량、악성유의의적초성특정，병변형태、기저관착급혈류신호대감별진단병변적량、악성유중요개치。
Purpose To establish Logistic regression model of gallbladder lesions of≥1 cm in diameter diagnosed by ultrasound, and to filter benign and malignant sonographic features. Materials and Methods The sonographic features were retrospectively analyzed in 165 patients with gallbladde apophysis lesions of≥1 cm in diameter which confirmed by pathology, including the number of lesions, size, shape and basal width, gallstones, continuous gallbladder wall continuous, blood flow signals detected by color Doppler flow imaging. Logistic regression model with bipartition was established by multivariate Logistic regression analysis, and the efficiency of Logistic regression model was evaluated to predict benign or malignant of these lesions. Results Three characteristic variables, including lesion morphology, basal width and flow signals, were took into the Logistic regression model by binary Logistic regression analysis, which was the sensitive indicators can differentiate the benign or malignant gallbladder lesions. The accuracy, sensitivity and specificity of this model were 97.0%, 93.8%and 97.3%for predicting the benign or malignant gallbladder apophysis lesions≥1 cm in diameter, respectively. Area under ROC was 0.979. Conclusion Binary Logistic regression analysis can filter the sonographic features which can differentiate the benign or malignant gallbladder apophysis lesions≥1 cm in diameter, and lesion morphology, basal width and flow signals are of important differential diagnosis value of benign lesions or malignant lesions.
