扩散加权成像与乳腺浸润性导管癌分子生物标记的相关性研究

Correlation between diffusion weighted imaging and molecular biomarkers in breast invasive ductal carcinomas

目的:研究表观扩散系数(apparent diffusion coefficient,ADC)与乳腺浸润性导管癌分子生物学标记之间的关系,以指导临床判断预后及选择治疗方案。方法:对67例乳腺浸润性导管癌患者进行磁共振扩散加权成像(diffusion weighted imaging,DWI)检查,并测量病灶ADC值。术后免疫组化分析人表皮生长因子受体2(human epidermal growth factor receptor 2,HER-2)、雌激素受体(estrogen receptor,ER)、孕激素受体(progesterone receptor,PR)、Ki-67,统计学分析ADC值与ER、PR、HER-2、Ki-67的相关性,并研究不同分子分型病灶之间ADC值的差别。结果:Spearman相关性分析表明,ADC值与Ki-67之间无相关性(P>0.05);ER、PR、HER-2阴性表达者ADC值高于阳性者(P<0.05);三阴性病灶ADC值明显高于Luminal A型、Luminal B型、HER-2过表达型(P<0.05);HER-2过表达型病灶ADC值高于Luminal B型。结论:ADC值与乳腺浸润性导管癌分子生物标记及分子分型具有相关性,可辅助指导临床选择治疗方案及判断预后。

Objective： To investigate the relationship between apparent diffusion coefficient （ADC） value and molecular biomarkers in breast invasive ductal carcinomas （IDCs）, which may facilitate the optimal treatment and prognosis prediction. Methods： A total of 67 patients with IDC were enrolled in this study. All the patients underwent breast diffusion weighted magnetic resonance imaging （DW-MRI） before treatment. The ADC values of IDCs were calculated. The expressions of estrogen receptor （ER）, progesterone receptor （PR）, Ki-67, human epidermal growth factor receptor 2 （HER-2） were analyzed by immunohistochemistry. The relationships between ADC values and ER, PR, HER-2 and ki-67 expressions were statistically evaluated while the ADC values in different subtypes were also studied. Results： The ADC values of IDCs did not correlate significantly with Ki-67 by Spearman＇s correlation analysis （P〉0.05）; The mean ADC value was higher in IDCs with negative ER, PR and HER-2 expressions than that with positive expressions （P〈0.05）; The triple-negative IDC had higher mean ADC value than Luminal A, Luminal B and HER-2 overexpressing IDCs （P〈0.05）; The mean ADC value in HER-2 overexpressing IDC was significantly higher than that in Luminal B type IDC （P〈0.05）. Conclusion： The ADC value could be used to evaluate the expressions of molecular biomarkers and IDC subtype, which could help determine individual treatment and predict prognosis.