摘要
目的探讨Kaiser评分在乳腺病变良恶性鉴别中的应用及其提高乳腺癌诊断效能的价值。方法收集我院2018年1月至2021年5月进行术前乳腺1.5TMRI检查的患者资料,以病理结果为金标准,分别计算并比较Kaiser评分及BI-RADS分类对乳腺病变良恶性的诊断效能。结果共纳入199个病灶,良性病变95个(47.7%),恶性病变104个(52.3%)。Kaiser评分诊断的敏感性、特异性、阳性预测值、阴性预测值和准确性分别为94.2%、84.2%、86.7%、93.0%、89.4%;BI-RADS分类诊断的敏感性、特异性、阳性预测值、阴性预测值和准确性分别为93.3%、65.3%、74.6%、89.9%、79.9%。Kaiser评分和BI-RADS分类对乳腺病变良恶性诊断的ROC曲线下面积分别为0.937和0.885。Kaiser评分对肿块和非肿块的ROC曲线下面积分别为0.952和0.883。结论Kaiser评分对于乳腺良恶性病变的诊断效能优于BI-RADS分类,并且可以为乳腺病变的诊断提供流程化、结构化的思路,对于肿块样病变诊断的准确性更高。
Objective To explore the value of Kaiser score in the differential diagnosis between benign and malignant breast lesions and it’s ability in improving the diagnostic efficiency of breast cancer.Methods The clinical data of patients who underwent preoperative breast 1.5T MRI examination in our hospital from January 2018 to May 2021 were collected.Using pathological results as the golden standard,the diagnostic efficacy of Kaiser score and BI-RADS classification for benign and malignant breast lesions was calculated and compared respectively.Results A total of 199 lesions were included,including 95 benign lesions(47.7%)and 104 malignant lesions(52.3%).For diagnosis of the lesions,the sensitivity,specificity,positive predictive value,negative predictive value and accuracy of Kaiser Score were 94.2%、84.2%、86.7%、93.0%、89.4%,as compared with 93.3%、65.3%、74.6%、89.9%、79.9%of MRI BI-RADS,respectively.The areas under the ROC curve of Kiaser score and Bi-RADS classification for benign and malignant breast lesions were 0.937 and 0.885 respectively.Conclusion Kaiser score was more effective than BI-RADS in the differential diagnosis in benign and malignant breast lesions.In addition,it can provide a streamlined and structured way of thinking for the diagnosis.The Kaiser score has a higher diagnostic accuracy for mass lesions.
作者
冯琳琳
冯小会
闫锐
陈欣
FENG Lin-lin;FENG Xiao-hui;YAN Rui;CHEN Xin(Department of Imaging,The second affiliated hospital of Xi'an Jiaotong university,Xi'an 710004,Shaanxi Province,China;Medical Imaging Center,Northwest Women's and Children's Hospital,Xi'an710061,Shaanxi Province,China)
出处
《中国CT和MRI杂志》
2023年第3期93-95,共3页
Chinese Journal of CT and MRI
基金
陕西省重点研发计划项目(2020SF-042)。
