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| 多模态影像技术对乳腺导管原位癌与导管原位癌伴微浸润的鉴别诊断 |
| Differential diagnosis of breast ductal carcinoma in situ and ductal carcinoma in situ with microinvasion by multimodal imaging technology |
| 投稿时间：2025-01-06 修订日期：2025-02-05 |
| DOI： |
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| 中文关键词: 乳腺X线摄影 MRI B超 乳腺导管原位癌 乳腺导管原位癌伴微浸润 |
| 英文关键词:Mammography MRI B-ultrasound Breast ductal carcinoma in situ Breast ductal carcinoma in situ with microinvasion |
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| 中文摘要: |
| 【摘要】目的 比较乳腺导管原位癌(DCIS)与乳腺导管原位癌伴微浸润(DCISM)的MG、B超和MRI的影像及临床特征,旨在提高对DCIS与DCISM的精确鉴别诊断水平。方法 回顾性分析浙江省肿瘤医院经手术病理证实的DCIS和DCISM 共147例患者,151个病灶(DCIS=87、DCISM=64),术前均行B超、MG和MRI增强检查。用χ2检验对两组患者的临床及影像学特征进行分析。运用单因素及多因素logistic回归分析鉴别DCIS与DCISM的预测因素,并分别构建临床模型、影像特征、联合诊断模型。采用受试者工作特征(ROC)曲线评估各个模型的预测能力。结果 在MG中,DCIS主要表现为团簇状分布钙化(38.6%,22/57),DCISM主要表现为区域性(42.0%,21/50)及段样分布钙化(39.0%,19/50)(P=0.014)。在B超中,DCSIM非肿块病变(31.2%,20/64)比例要高于DCIS(14.9%,13/87)(P=0.014)。在MRI中,DCISM段样非肿块样强化(NME)(85.1%,40/87)要多于DCIS(56.9%,29/64)(P=0.002)。DCISM灶周水肿及血管增粗比例要高于DCIS(P=0.003)。临床模型、影像模型及联合诊断模型AUC分别为0.681(95%CI:0.596-0.766)、0.793(95%CI:0.722-0.863)、0.841(95%CI:0.780-0.902)。结论 核级别及B超肿块型病灶是DCIS与DCISM鉴别诊断的独立预测因子。MG结合MRI可以显著提高DCIS与DCISM的鉴别诊断效能。本研究建立的临床与影像模型对鉴别DCIS与DCISM有一定的预测价值,两者联合建立的联合模型预测价值更高。 |
| 英文摘要: |
| [Objective ]To compare the imaging and clinical features of breast ductal carcinoma in situ (DCIS) and breast ductal carcinoma in situ with microinvasion (DCISM) with MG, B-ultrasound and MRI, in order to improve the accurate differential diagnosis of DCIS and DCISM. [Methods] A retrospective analysis of 147 patients with DCIS and DCISM confirmed by surgery and pathology in zhejiang cancer hospital, 151 lesions ( DCIS = 87, DCISM = 64 ). All patients underwent B-ultrasound, MG and MRI enhancement before operation. The clinical and imaging features of the two groups were analyzed byχ2 test. Univariate and multivariate logistic regression analysis were used to identify the predictors of DCIS and DCISM, and clinical models, imaging features, and combined diagnostic models were constructed respectively. The receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of each model.[Results] In MG, DCIS mainly showed clustered calcification (38.6 %, 22/57), while DCISM mainly showed regional calcification (42.0 %, 21/50) and segmental calcification (39.0 %, 19 / 50) (P= 0.014). The proportion of non-mass lesions in DCSIM (31.2 %, 20/64) was higher than that in DCIS (14.9 %, 13/87) (P= 0.014). In MRI, DCISM segment-like non-mass-like enhancement (NME) (85.1 %, 40/87) was more than DCIS (56.9 %, 29/64) (P= 0.002). The proportion of perifocal edema and vascular thickening in DCISM was higher than that in DCIS (P= 0.003). The AUC values of clinical model, imaging model and combined diagnosis model were 0.681 (95%CI:0.596-0.766), 0.793 (95%CI:0.722-0.863) and 0.841 (95%CI:0.780-0.902), respectively.[Conclusion] Nuclear grade and B-ultrasound mass lesions are independent predictors of differential diagnosis of DCIS and DCISM. The combination of MG and MRI can significantly improve the differential diagnosis efficiency of DCIS and DCISM. The clinical and imaging models established in this study have certain predictive value for differentiating DCIS from DCISM, and the combined model established by the two has higher predictive value. |
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