螺旋CT对黏液性软组织肿瘤良恶性鉴别的价值

doi:10.6040/j.issn.1671-7554.0.2021.0109

摘要/Abstract

摘要： 目的探讨螺旋动态增强CT检查对黏液性软组织肿瘤良恶性的鉴别诊断价值。方法选取2016年8月至2020年3月在山东大学齐鲁医院诊治的147例(男52例,女95例)经病理诊断为黏液性软组织肿瘤患者的临床和CT资料进行回顾性分析。根据病理分为良性组(n=59例)和恶性组(n=88例)。由两名放射科医生评估并记录肿瘤的平扫及三期动态增强CT特征:病灶的长/短径、边界、形状,以及瘤内黏液、实性、钙化和液化坏死成分的分布和数量,有无增强的血管,黏液和实性成分在平扫和各增强期的CT值。分析患者的年龄、性别和病灶部位与上述CT特征对鉴别肿瘤良恶性的价值,根据方差膨胀系数(VIF)检验筛选变量,并建立含不同变量的多因素Logistic 回归预测模型,包括基于分段多项式模式(MFP)的模型0,具完整变量的模型1和基于赤池信息准则(AIC)的模型2,绘制受试者工作特征(ROC)曲线评价模型效能。结果患者年龄、病灶的部位、长/短径、边界、形状、瘤内钙化、三期增强的血管、平扫时实性成分CT值在良性和恶性肿瘤之间均差异具有统计学意义(P<0.05); 基于上述临床资料和CT特征变量的Logistic回归模型对良、恶性肿瘤的鉴别具有一定价值(模型0: OR=29.714 3, AUC=0.867 8; 模型1: OR=37.142 9, AUC=0.874 6; 模型2: OR=9.730 8, AUC=0.833 6)。结论利用螺旋CT特征和患者临床资料联合建立的Logistic 回归预测模型可对黏液性软组织肿瘤进行良恶性的鉴别。

关键词: 常规螺旋CT, 黏液样变性, 肿瘤, 良恶性, 预测模型

Abstract: Objective To explore the value of spiral dynamic enhanced CT in differentiating benign and malignant myxoid soft tissue tumors. Methods The clinical and CT data of 147 patients(52 males and 95 females)with myxoid soft tissue tumors diagnosed by pathology in Qilu Hospital of Shandong University from August 2016 to March 2020 were retrospectively analyzed. The patients were divided into the benign group(n=59)and malignant group(n=88). The plain and tri-phasic dynamic enhanced CT features of tumors were evaluated and recorded by two radiologists, including the maximum/minimum diameter, boundary and shape of lesions, distribution and amount of myxoid or solid part, calcification and liquefaction necrosis within the tumor, enhanced blood vessel, and CT values of myxoid and solid components during the plain and enhanced CT phases. Patients age, gender, location of lesions, and CT features were analyzed to assess the differential diagnostic value. After variables were screened with the variance inflation coefficient(VIF), a multivariable Logistic regression prediction model was established, including the model 0 based on multiple fractional polynomial(MFP)model, model 1 with all variables and model 2 based on akakike information criteria(AIC), the receiver-operating characteristic(ROC)curve was drawn to evaluate the effectiveness of the models. Results Patients age, location of lesions, maximum/minimum diameter, tumor boundary, tumor shape, tumor calcification, enhanced vessels in tri-phasic scanning and solid part on plain CT were statistically different between benign and malignant tumors(P<0.05). The Logistic regression prediction model had certain value in the differentiation of benign and malignant tumors(Model 0: OR=29.714 3, AUC=0.867 8; Model 1: OR=37.142 9, AUC=0.874 6; Model 2: OR=9.730 8, AUC=0.833 6). Conclusion The Logistic regression prediction model based on spiral CT features and clinical data of patients can be used to differentiate benign and malignant myxoid soft tissue tumors.

Key words: Spiral CT, Myxoid degeneration, Tumor, Benign or malignant, Prediction model

中图分类号:

R574

赵洁,李岩,李明,于德新. 螺旋CT对黏液性软组织肿瘤良恶性鉴别的价值[J]. 山东大学学报 (医学版), 2021, 59(4): 100-107.

ZHAO Jie, LI Yan, LI Ming, YU Dexin. Spiral CT in differentiating benign and malignant tumors with myxoid degeneration[J]. Journal of Shandong University (Health Sciences), 2021, 59(4): 100-107.

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