| 梁园园,李昌帅,赵文静,张敏,郭荣,聂家秋,于艳妮,耿海.多模态影像学术前评估浸润性乳腺癌组织学分级[J].中国介入影像与治疗学,2021,18(10):617-621 |
| 多模态影像学术前评估浸润性乳腺癌组织学分级 |
| Multimodal imaging for preoperational prediction of histologic classification of invasive breast cancer |
| 投稿时间：2021-05-13 修订日期：2021-08-13 |
| DOI：10.13929/j.issn.1672-8475.2021.10.010 |
| 中文关键词: 乳腺肿瘤 超声检查 磁共振成像 乳腺X射线摄影 组织学分级 |
| 英文关键词:breast neoplasms ultrasonography magnetic resonance imaging mammography histological grading |
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| 中文摘要: |
| 目的 观察多模态影像学术前评估浸润性乳腺癌组织学分级的价值。方法 回顾性分析69例术前接受乳腺X射线摄影、超声及MR检查，并经病理证实的单发浸润性乳腺癌女性患者，对比不同组织学分级病灶的影像学表现及相关影像学参数；采用受试者工作特征（ROC）曲线评估影像学参数对乳腺癌组织学分级的诊断效能。结果 69例浸润性乳腺癌中，组织学分级为Ⅰ级4例、Ⅱ级28例、Ⅲ级37例，均表现为肿块样强化。Ⅰ+Ⅱ级与Ⅲ级浸润性乳腺癌之间，可疑微小钙化及毛刺征、腋窝淋巴结转移及表观弥散系数（ADC）、平均弥散率（MD）、平均峰度（MK）值差异均有统计学意义（P均<0.05），其余影像学表现差异均无统计学意义（P均>0.05）。MK、MD及ADC预测浸润性乳腺癌组织学分级的AUC分别为0.93、0.88及0.80（P均<0.05）。结论 多模态影像学技术可用于术前评估浸润性乳腺癌的组织学分级。 |
| 英文摘要: |
| Objective To explore the value of multimodal imaging for preoperational prediction of histological grading of invasive breast cancer. Methods Totally 69 females who underwent mammography, ultrasound and MR examination with single invasive breast cancer confirmed by pathology were retrospectively analyzed before operation. The imaging manifestations and parameters of lesions were compared among different histological grades. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacies of imaging parameters for histological grading of breast cancer. Results Among 69 cases of invasive breast cancer, there were 4 cases of grade Ⅰ, 28 cases of grade Ⅱ and 37 cases of grade Ⅲ, all showed mass-like enhancement. Statistically significant differences of suspected micro-calcification, burr sign, axillary lymph node metastasis, apparent dispersion coefficient (ADC), mean dispersion (MD) and mean kurtosis (MK) were found between grade Ⅰ+Ⅱ and grade Ⅲ invasive breast cancer (all P<0.05), while there was no statistical difference of other imaging findings (all P>0.05). The AUC of MK, MD and ADC for predicting histological grade of invasive breast cancer was 0.93, 0.88 and 0.80, respectively (all P<0.05). Conclusion Multimodal imaging could be used to predict histological grading of invasive breast cancer. |
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