摘要
目的:研究分析不同分子亚型乳腺癌患者DCE-MRI定量参数及其与血管生产指标的关系。方法:选取2020年3月至2022年12月期间在我院接受治疗的乳腺癌患者共计102例,通过对患者进行乳腺DCE-MRI扫描,手术后对切除病变实施临床病理与免疫组织化学检验,结合免疫组织化学结果,进行不同分子亚型划分,分析不同分子亚型患者DCE-MRI定量参数变化情况。结果:在102例乳腺癌患者中,通过免疫组化检验显示,Luminal A型共有14例,Luminal B型共有57例,HER-2过表达型共有21例,三阴型共有10例;根据速率常数对比结果显示,Luminal A型<Luminal B型<三阴型<HER-2过表达型,有明显统计学意义(P<0.05);相较于PR阴性,阳性容量转移常数、速率常数水平较低,计算结果有统计学差异,P<0.05。结论:不同分子亚型乳腺癌患者DCE-MRI定量参数组间对比差异明显,能够提高不同分子亚型乳腺癌的诊断有效性。
Objective:To study and analyze the relationship between quantitative parameters of DCE-MRI and vascular production in patients with different molecular subtypes of breast cancer.Methods:A total of 102 patients with breast cancer who were treated in our hospital from March 2020 to December 2022 were selected.The patients were scanned by DCE-MRI,and the resected lesions were examined by clinicopathology and immunohistochemistry after surgery.Combined with the immunohistochemical results,different molecular subtypes were classified,and the changes of quantitative parameters of DCE-MRI in patients with different molecular subtypes were analyzed.Results:(1)Among 102 cases of breast cancer patients,immunohistochemistry results showed that there were 14 cases of Luminal A type,57cases of Luminal B type,21 cases of HER-2 overexpression type,and 10 cases of triple negative type;(2)According to the results of rate constant comparison,Luminal A typeLuminal B typetriple negative typeHER-2 overexpression type,which was statistically significant(P<0.05);(3)Compared to PR negative,the level of positive volume transfer constant and rate constant is lower,and the statistical results are P<0.05.Conclusion:The quantitative parameters of DCE-MRI in patients with different molecular subtypes of breast cancer are significantly different between groups,which can improve the diagnostic effectiveness of different molecular subtypes of breast cancer.
作者
熊益敏
卜学勇
敬宗玉
石长勇
XIONG Yi-min;BU Xue-yong;JING Zong-yu;SHI Chang-yong(Longgang District Maternal and child health hospital(Longgang Clinical College of Women and Children,Shantou University Medical College),Guangdong 518172,China)
出处
《影像技术》
CAS
2023年第3期4-8,19,共6页
Image Technology
基金
深圳市龙岗区科技发展专项资金(医疗卫生科技计划项目)(LGKCYLWS2020110)。