目的 探讨非对称回波最小二乘估算法迭代水脂分离序列(iterative decomposition of water and fat with echo asymmetrical and least-squares estimation quantitation sequence,IDEAL-IQ)来源的R2*值在乳腺良恶性肿瘤鉴别诊断中的价值,并与传统多回波T2*梯度回波(gradient recalled echo,GRE)序列来源的R2*值进行比较.材料与方法 回顾性分析2021年9月至2023年10月在中国医科大学附属第一医院连续收治的42名患者的50个良性肿瘤病灶,在本院影像归档和通信系统(picture archiving and communication systems,PACS)中使用倾向性评分匹配方法匹配肿瘤所在最大层面的最长径,按1:3的比例纳入150名患者的150个恶性肿瘤病灶.将恶性肿瘤根据预后因子[雌激素受体(estrogen receptor,ER)、孕激素受体(progesterone receptor,PR)以及人表皮生长因子受体2(human epidermal growth factor receptor 2,HER-2)]的阳性/阴性表达情况进行分组.所有患者均接受包含IDEAL-IQ和多回波T2*GRE序列的多参数MRI,测量以下定量参数:IDEAL-IQ序列R2*值(R2*IDEAL)、多回波T2*GRE序列R2*值(R2*GRE)、表观扩散系数(apparent diffusion coefficient,ADC)及肿瘤长径.根据原始资料类型的不同,分别利用单因素分析(独立样本t检验、Mann-Whitney U检验等方法)对比分析各参数的差异.采用Spearman相关性分析R2*IDEAL与R2*GRE及二者与ADC的相关性.采用配对样本t检验比较R2*IDEAL与R2*GRE的差异.采用logistic回归分析建立联合诊断模型,并使用受试者工作特征(receiver operating characteristic,ROC)曲线及曲线下面积(area under the curve,AUC)分析单独及联合参数鉴别乳腺肿瘤良恶性的效能.结果 相关性分析显示乳腺肿瘤患者的R2*IDEAL与R2*GRE呈中度相关(r=0.763,P＜0.001),二者与 ADC值均呈负性弱相关[r=-0.300(R2*IDEAL),-0.306(R2*GRE),P＜0.001].良性组与恶性组中,R2*IDEAL与R2*GRE均呈中度相关(r=0.745、0.680,P＜0.001),二者与ADC均无相关性.两种序列所得的R2*值差异有统计学意义(P＜0.001).R2*IDEAL在良恶性组间差异有统计学意义(P＜0.001),管腔HER-2阴性型R2*值最高.对于单一参数,ADC值鉴别良恶性的AUC最高(0.857);对于联合参数,R2*IDEAL+ADC鉴别良性组与管腔阴性组的AUC最高(0.927);差异均有统计学意义(P＜0.05).结论 IDEAL-IQ序列生成的R2*值可用于区分良恶性乳腺肿块,可能成为除ADC外辅助乳腺肿瘤良恶性鉴别的又一无需对比剂参数.
Application value of IDEAL-IQ sequence in differential diagnosis of benign and malignant breast masses
Objective:To investigate the diagnostic significance of R2*values obtained from iterative decomposition of water and fat with echo asymmetrical and least-squares estimation quantitation sequence(IDEAL-IQ)in distinguishing between benign and malignant breast tumors,and compare these values with those obtained from traditional multiple echo T2*gradient recalled echo(GRE)series.Materials and Methods:A total of 50 cases of benign tumors in 42 patients admitted to the First Hospital of China Medical University from September 2021 to October 2023 were retrospectively analyzed.The propensity score matching was used to match the longest diameter of the largest plane of the tumor in picture archiving and communication systems(PACS),and 150 cases of malignant tumors in 150 patients were included according to the 1:3 ratio.Malignant tumors were grouped based on the positive/negative expression of prognostic factors such as estrogen receptor(ER),progesterone receptor(PR),and human epidermal growth factor receptor 2(HER-2).All patients underwent multi-parameter MRI with IDEAL-IQ and multi-echo T2*GRE sequences,and the following quantitative parameters were measured:R2*IDEAL from IDEAL-IQ sequence,R2*GRE from multi-echo T2*GRE sequence,apparent diffusion coefficient(ADC),and tumor diameter.The intra-class correlation coefficient(ICC)was used to evaluate the consistency between the researchers.Depending on the type of raw data,the differences of each parameter were compared and analyzed using one-way analysis(independent samples t-test,Mann-Whitney U-test,etc.).Spearman correlation analysis was used to analyze the correlation between R2*IDEAL and R2*GRE,as well as their correlation with ADC.The difference between R2*IDEAL and R2*GRE was compared by paired sample t-test.A joint diagnostic model was established by using logistic regression analysis,and the receiver operating characteristic(ROC)curve and the area under the curve(AUC)were used to analyze the efficacy of single and combined parameters in differentiating benign and malignant breast tumors.Results:Correlation analysis showed that R2*IDEAL and R2*GRE in patients with breast tumors were moderately strongly correlated(r-0.763,P＜0.001),and both were weakly negatively correlated with ADC values[r=-0.300(R2*IDEAL),-0.306(R2*GRE),P＜0.001].In benign group and malignant group,R2*IDEAL and R2*GRE showed moderate correlation(r=0.745,0.680,P＜0.001),and there was no correlation between them and ADC.The R2*values obtained by the two sequences were statistically different(P＜0.05).There was a significant difference in R2*IDEAL between benign and malignant groups(P＜0.001),and the R2*value of luminal HER-2 negative group was the highest.For a single parameter,ADC value had the largest AUC(0.857)in differentiating benign and malignant groups.For the combined parameters,R2*IDEAL+ADC had the largest AUC(0.927)in differentiating benign group from luminal negative group.The differences were statistically significant(P＜0.05).Conclusions:The R2*value generated by IDEAL-IQ sequence can be used to distinguish benign and malignant breast tumors,and may be another non-contrast parameter in addition to ADC to assist the differentiation of benign and malignant breast tumors.
breast neoplasmsdistinguish between benign and malignantmolecular subtypeiterative decomposition of water and fat with echo asymmetrical and least-squares estimation quantitation sequencediffusion weighted imagingmagnetic resonance imaging
万方数据
维普
