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中华介入放射学电子杂志

中华介入放射学电子杂志 ›› 2024, Vol. 12 ›› Issue (03) : 234 -243. doi: 10.3877/cma.j.issn.2095-5782.2024.03.008

影像诊断

磁共振DWI及其ADC对乳腺导管原位癌伴微浸润腋窝淋巴结转移的诊断价值
姜超1,†(), 夏旭东1, 王功夏1, 何向宇1, 王海彬1, 李媛1   
  1. 1. 455000　河南安阳，河南省安阳市肿瘤医院影像科
  • 收稿日期:2023-12-22 出版日期:2024-08-25
  • 通信作者: 姜超

Diagnostic value of magnetic resonance DWI and ADC in breast ductal carcinoma in situ with axillary lymph node metastasis

Chao Jiang1,†(), Xudong Xia1, Gongxia Wang1, Xiangyu He1, Haibin Wang1, Yuan Li1   

  1. 1. Department of Imaging, Anyang Cancer Hospital, Henan Anyang 455000, China
  • Received:2023-12-22 Published:2024-08-25
  • Corresponding author: Chao Jiang
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引用本文：

姜超, 夏旭东, 王功夏, 何向宇, 王海彬, 李媛. 磁共振DWI及其ADC对乳腺导管原位癌伴微浸润腋窝淋巴结转移的诊断价值[J]. 中华介入放射学电子杂志, 2024, 12(03): 234-243.

Chao Jiang, Xudong Xia, Gongxia Wang, Xiangyu He, Haibin Wang, Yuan Li. Diagnostic value of magnetic resonance DWI and ADC in breast ductal carcinoma in situ with axillary lymph node metastasis[J]. Chinese Journal of Interventional Radiology(Electronic Edition), 2024, 12(03): 234-243.

目的

探讨磁共振扩散加权成像（diffusion weighted imaging，DWI）及其表观扩散系数（apparent diffusion coefficient，ADC）对乳腺导管原位癌（ductal carcinoma in situ，DCIS）伴微浸润（micro-invasio，Mi）腋窝淋巴结（axillary lymph nodes，ALN）转移的诊断价值。

方法

选取2018年2月至2021年3月于河南省安阳市肿瘤医院行磁共振成像（magnetic resonance imaging，MRI）常规平扫、DWI且经术后病理结果均为DCIS-Mi的女性患者120例纳入训练集，另将2018年11月至2019年8月收治的女性DCIS-Mi患者51例纳入验证集。根据术后病理诊断结果将训练集患者分别分为阳性组（ALN转移）与阴性组（无ALN转移）。训练集中，阳性组17例，阴性组103例。收集患者的一般临床资料及ADC图中ALN纹理特征，比较训练集中阳性组和阴性组纹理特征及一般临床资料；采用LASSO回归及Logistic回归分析筛选影响因素。基于筛选的影响因素构建列线图模型，并对模型进行评价。各独立因素与DCIS-Mi患者发生ALN转移风险的相关性采用Spearman相关性分析。

结果

变异度、偏度、峰度、1%ADC值、10%ADC值、能量、和方差、和熵、熵是影响DCIS-Mi患者发生ALN转移的独立影响因素（P < 0.05）。1%ADC值与DCIS-Mi患者发生ALN转移风险呈明显负相关（P < 0.05），变异度、偏度、峰度、10%ADC值、能量、和方差、和熵、熵与DCIS-Mi患者发生ALN转移风险呈明显正相关（P < 0.05）。基于独立影响因素构建的Nomogram模型具有较高的特异性和灵敏度，临床适用性较高。

结论

基于ADC图纹理参数构建的列线图模型预测DCIS-Mi患者ALN转移具有较好的预测效能。

关键词: 乳腺导管原位癌伴微浸润, 腋窝淋巴结转移, 磁共振成像, 扩散加权成像, 表观扩散系数
Objective

To investigate the diagnostic value of DWI and ADC in axillary lymph node (ALN) metastasis of breast ductal carcinoma in situ (DCIS) with micro-invasion (Mi).

Method

A total of 120 female patients who underwent conventional magnetic resonance imaging (MRI) scan, DWI and postoperative pathological results of DCIS-Mi in Anyang Cancer Hospital of Henan Province from February 2018 to March 2021 were included in the training set. In addition, 51 female DCIS-Mi patients admitted from November 2018 to August 2019 were included in the validation set. According to the results of postoperative pathological diagnosis, the patients in the training set were divided into the positive group (ALN metastasis) and the negative group (no ALN metastasis). In the training set, there were 17 cases in the positive group and 103 cases in the negative group. The patient's general clinical data and the ADC ALN texture feature in the figure were collected and compared between positive group and negative group. LASSO regression and Logistic regression analysis were used to screen the influencing factors. A nomogram model was constructed and evaluated based on the selected influencing factors. The correlation between independent factors and the risk of ALN metastasis in DCIS-Mi patients was analyzed using Spearman correlation analysis.

Result

Variation, skewness, kurtosis, 1%ADC value, 10%ADC value, energy, variance of sum, entropy of sum and entropy were independent factors affecting ALN metastasis in patients with DCIS-Mi (P < 0.05). The 1%ADC value was negatively correlated with the risk of ALN metastasis in DCIS-Mi patients (P < 0.05), while variation, skewness, kurtosis, 10%ADC value, energy, variance of sum, entropy of sum and entropy were positively correlated with the risk of ALN metastasis in DCIS-Mi patients (P < 0.05). The Nomogram model based on independent factors has high specificity, sensitivity and clinical applicability.

Conclusion

The Nomogram model based on ADC texture parameters is effective in predicting ALN metastasis in DCIS-Mi patients.

Key words: DCIS-Mi, Axillary lymph node metastasis, Magnetic resonance imaging, Diffusion weighted imaging, Apparent diffusion coefficient
图1 DCIS-Mi伴左侧ALN转移（阳性组）1A：增强MRI T1WI显示ALN边缘毛糙，不均匀强化；1B：于增强T1WI中勾画ALN的ROI（红色区域）；1C：ADC图显示ALN呈不均匀低信号；1D：于ADC图中勾画ALN的ROI（红色区域）。MRI为磁共振成像；ALN为腋窝淋巴结；ROI为感兴趣区；ADC为表观扩散系数；DCIS-Mi为乳腺导管原位癌伴微浸润。
图2 DCIS-Mi伴左侧ALN增生（阴性组）2A：增强MRI T1WI显示ALN边缘光滑，均匀强化；2B：于增强T1WI中勾画ALN的ROI（红色区域）；2C：ADC图显示ALN呈稍高信号；2D：于ADC图中勾画ALN的ROI（红色区域）。MRI为磁共振成像；ALN为腋窝淋巴结；ROI为感兴趣区；ADC为表观扩散系数；DCIS-Mi为乳腺导管原位癌伴微浸润。
表1 阳性组和阴性组的一般临床资料及纹理参数比较（±s）
指标 阳性组（17例） 阴性组（103例） F/t/χ2值 P值
年龄[例（%）]     0.403 0.526
< 45岁 9 46    
≥45岁 8 57    
组织学分级[例（%）]     4.199 0.123
低级别 2 22    
中级别 6 52    
高级别 9 29    
原发灶肿瘤大小[例（%）]     0.235 0.628
< 2.5 cm 9 48    
≥2.5 cm 8 55    
浸润病灶数目[例（%）]     4.143 0.042
单个 8 74    
≥2个 9 29    
粉刺样坏死[例（%）]     0.840 0.360
是 2 22    
否 15 81    
脉管瘤栓[例（%）]     5.032 0.025
有 3 4    
无 14 99    
ER状态[例（%）]     3.996 0.046
阳性 11 40    
阴性 6 63    
PR状态[例（%）]     0.100 0.752
阳性 4 28    
阴性 13 75    
HER-2 [例（%）]     0.157 0.692
阳性 13 74    
阴性 4 29    
Ki-67指数[例（%）]     3.861 0.049
<20% 1 29    
≥20% 16 74    
变异度 286.51±30.36 205.83±25.81 11.642 < 0.001
均值 125.22±41.82 170.64±52.52 3.389 0.001
偏度 0.84±0.50 -0.25±0.63 6.781 < 0.001
峰度 0.23±0.07 -0.70±0.10 36.821 < 0.001
1%ADC值 75.52±29.31 127.24±35.14 5.742 < 0.001
10%ADC值 107.81±20.92 92.74±15.09 3.597 < 0.001
50%ADC值 130.79±31.05 115.86±25.27 2.183 0.031
90%ADC值 150.85±32.44 138.06±21.84 2.074 0.040
99%ADC值 162.56±34.86 145.62±29.13 2.159 0.033
能量（×10-3） 30.86±7.29 14.85±5.33 10.851 < 0.001
对比度 9.43±3.72 11.32±4.15 1.763 0.080
相关 0.78±0.26 0.69±0.21 1.581 0.117
平方和 28.04±9.31 21.82±8.95 2.640 0.009
逆差距 0.28±0.13 0.34±0.16 1.467 0.145
均和 64.20±17.26 78.40±20.21 2.735 0.007
和方差 103.77±18.51 39.28±12.95 17.805 < 0.001
和熵 1.48±0.27 1.30±0.15 4.015 < 0.001
熵 1.96±0.33 1.44±0.26 7.342 < 0.001
差方差 3.87±0.95 4.22±1.23 1.118 0.266
差熵 0.80±0.22 0.76±0.15 0.947 0.345
图3 特征筛选3A：表示λ（最优参数值）= 0.020时绘制垂直线，选取17个变量关系图；3B：表示调整λ后，各个特征系数与log(λ)的关系图。
图4 影响DCIS-Mi患者发生ALN转移的Logistic回归分析森林图注：DCIS-Mi为乳腺导管原位癌伴微浸润；ALN为腋窝淋巴结；ADC为表观扩散系数。
图5 DCIS-Mi患者发生ALN转移的Nomogram预测模型注：DCIS-Mi为乳腺导管原位癌伴微浸润；ALN为腋窝淋巴结；ADC为表观扩散系数。
图6 列线图模型的校正曲线验证图
图7 列线图模型的ROC曲线验证图注：ROC曲线为受试者工作特征曲线；AUC为曲线下面积。
图8 列线图模型的决策曲线图
图9 ADC纹理参数与DCIS-Mi患者发生ALN转移的相关性分析注：DCIS-Mi为乳腺导管原位癌伴微浸润；ALN为腋窝淋巴结；ADC为表观扩散系数。
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