乳腺癌不同分子亚型的动态对比增强MRI影像学特征分析及ADC特点研究

Analysis of dynamic contrast-enhanced MRI image and apparent diffusion coefficient features of different molecular subtypes of breast cancer

    摘要
  • 摘要:
    目的 探讨乳腺癌不同分子亚型的动态对比增强磁共振成像（DCE-MRI）影像学征象及表观扩散系数（ADC）特点。
    方法 回顾性分析2018年1月至2020年1月于内蒙古医科大学附属人民医院就诊并经免疫组织化学染色法检查证实的138例乳腺癌女性患者的临床资料，患者年龄27~71（56.1±5.6）岁。所有患者均于术前行乳腺常规MRI扫描，根据乳腺影像报告和数据系统分析乳腺癌不同分子亚型的DCE-MRI特征；测量 ADC并分析其特点。术后采用免疫组织化学染色法将乳腺癌分为不同分子亚型。采用卡方检验或 Fisher确切概率法分析DCE-MRI特征与乳腺癌分子亚型的关系。采用单因素方差分析比较各分子亚型的ADC。
    结果 138 例乳腺癌患者的免疫组织化学染色法检测结果显示， Luminal A 型 14 例 、 Luminal B 型 62 例、HER-2 过表达型 33 例、基底细胞样型 29 例。4种乳腺癌分子亚型中，基底细胞样型较其他3种类型体积大( χ2=0.70、15.21、6.87，均P<0.01)；Luminal A型多边缘光滑，其他3种类型边缘多不规则( χ2=26.41、7.23、7.88，均P<0.01)；基底细胞样型乳腺癌多呈边缘强化，而Luminal A型乳腺癌多呈均匀强化，且其动态增强扫描时间-信号曲线（TIC）类型以Ⅱ型居多，其他3种类型的TIC类型以Ⅲ型为主( χ2=12.325，P<0.01)。所有患者病灶的ADC为（0.497×10−3~1.367×10−3）mm2/s（0.865±0.021）×10−3 mm2/s。HER-2过表达型乳腺癌的ADC最高（1.023±0.027）×10−3 mm2/s，基底细胞样型和Luminal A型乳腺癌次之（0.957±0.025）×10−3 mm2/s和（0.902±0.033）×10−3 mm2/s，Luminal B型乳腺癌最低（0.852±0.013）×10−3 mm2/s。HER-2过表达型乳腺癌的ADC与基底细胞样型及Luminal B型之间的差异均有统计学意义(F=11.80、12.40，均P<0.01)，Luminal B型与Luminal A型之间的差异有统计学意义(F=25.50，P<0.01)。
    结论 乳腺癌各分子亚型的DCE-MRI影像学征象及ADC具有一定的特征性，可为乳腺癌患者术前预测、治疗方案的制定及预后评估提供参考依据。

     

    Abstract:
    Objective To explore the characteristics of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coefficient (ADC) of different molecular subtypes of breast cancer.
    Methods The clinical data of one hundred thirty-eight women aged 27–71 (56.1±5.6) years and diagnosed with breast cancer, which was confirmed via immunohistochemical examination, at the Affiliated People's Hospital of Inner Mongolia Medical University were retrospectively analyzed from January 2018 to January 2020. All patients underwent routine breast MRI scanning before operation. DCE-MRI features of different molecular subtypes of breast cancer were analyzed using the breast imaging report and data system. ADC was measured and its characteristics were analyzed. The breast cancer was divided into non molecular subtypes via immunohistochemical staining after operation. Chi-square test and Fisher test was used to analyze the relationship between DCE-MRI features and molecular subtypes of breast cancer. The ADC of each molecular subtype was compared using one-way ANOVA.
    Results The immunohistochemical results showed that 138 cases of breast cancer are composed of 14 cases of Luminal A, 62 cases of Luminal B, 33 cases of HER-2 overexpression, and 29 cases of Basal-like subtypes. Among the four molecular subtypes of breast cancer, Basal-like subtype is the largest type of tumor (χ2=0.70, 15.21, 6.87; all P<0.01). Edges of Luminal A type are smooth, and those of the other types are irregular (χ2=26.41, 7.23, 7.88; all P<0.01). Basal-like subtype breast cancer showed ring enhancement, while Luminal A type breast cancer presented homogeneous enhancement. The dynamic enhanced scan time signal intensity curve (TIC) was mostly type Ⅱ, while the three other types of TIC were mainly type Ⅲ (χ2=12.325, P<0.01). The ADC range of lesions in all patients was (0.497×10−3–1.367×10−3) mm2/s (0.865±0.021)×10−3 mm2/s. HER-2 overexpressing breast cancer presented the highest ADC at (1.023±0.027)×10−3 mm2/s, followed by Basal-like subtype breast cancer at (0.957±0.025)×10−3 mm2/s) and Luminal A type breast cancer at (0.902±0.033)×10−3 mm2/s, Luminal B type breast cancer had the lowest at (0.852±0.013)×10−3 mm2/s. ADC demonstrated a significant difference between HER-2 overexpressing and Basal-like subtype and Luminal B type breast cancers (F=11.80,12.40; both P<0.01). A significant difference was also observed between Luminal B and Luminal A type breast cancers (F=25.50, P<0.01).
    Conclusion DCE-MRI imaging signs and ADC of each molecular subtype of breast cancer have certain characteristics, which can provide reference basis for preoperative prediction, treatment plan formulation and prognosis evaluation of breast cancer patients.

     

    • HTML全文
    • 参考文献(21)
    • 相关文章
    • 施引文献
  • 资源附件(0)

/

返回文章
返回