Wang Bin, Yang Juan, Tang Yu-Long, Chen Yu-Yuan, Luo Jia, Cui Xin-Wu, Dietrich Christoph F, Yi Ai-Jiao
Department of Medical Ultrasound, Yueyang Central Hospital, Yueyang, China.
Department of Thyroid Surgery, The Second Xiangya Hospital of Central South University, Changsha, China.
Quant Imaging Med Surg. 2024 Jan 3;14(1):408-420. doi: 10.21037/qims-23-445. Epub 2023 Nov 24.
The status of the axillary lymph node (ALN) in patients with breast cancer can critically inform clinical decision-making and prognosis. Preoperative evaluation of limited nodal burden (0-2 metastatic ALNs) and high nodal burden (≥3 metastatic ALNs) is vital for individual treatment in patients with breast cancer. Thus, this study aimed to evaluate the value of Angio-PLUS (AP; Aixplorer, SuperSonic Imagine) and the qualitative and quantitative shear-wave elastography (SWE) of breast lesions to predict limited or high axillary nodal burden and to develop a model for predicting limited or high axillary nodal burden.
From March 2020 to November 2022, a total of 232 consecutive patients with breast cancer comprising 232 breast lesions were enrolled retrospectively from Yueyang Central Hospital. The sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV), accuracy, and area under the receiver operating characteristic curve (AUC) of AP, qualitative SWE, quantitative SWE, and the predictive model for evaluating limited or high axillary nodal burden were compared.
There was no significant difference in AP patterns between the limited nodal burden group and high nodal burden group. The best cutoff values of Emin (the minimal value of the first Q-box), Emean (the mean value of the first Q-box), Emax (the maximum value of the first Q-box), Eratio (ratio of the first Q-Box and the second Q-Box) and standard deviation for predicting limited or high nodal burden were 80.85 KPa, 133.45 KPa, 153.40 KPa, 9.95, and 19.25 KPa, respectively. The Emax had the highest AUC, and its sensitivity, specificity, PPV, NPV, accuracy, and AUC were 71.64%, 56.36%, 40.00%, 83.04%, 60.78%, and 0.640 [95% confidence interval (CI): 0.575-0.702], respectively. The sensitivity, specificity, PPV, NPV, accuracy, and AUC of seven color patterns for qualitative SWE were 71.64%, 74.55%, 53.33%, 86.62%, 73.71%, and 0.731 (95% CI: 0.669-0.787), respectively, which was significantly higher than all the other quantitative SWE parameters. ALN evaluation in ultrasound and qualitative SWE were independent risk factors for predicting limited or high nodal burden according to a binary logistics regression analysis. The AUC of the predictive model based on independent risk factors was 0.820 (95% CI: 0.765-0.867), which was significantly higher than that of the other independent risk factors.
The seven color patterns in the qualitative SWE of breast lesions were valuable for predicting limited or high nodal burden for patients with breast cancer. Compared with quantitative SWE, qualitative SWE exhibited a better diagnostic performance. Breast lesions present no findings, vertical stripes, and spot patterns were important indicators for limited nodal burden. The predictive model developed in this study could be a simple, noninvasive, and convenient method for predicting limited or high nodal burden, which would be beneficial for clinical decision-making and individual treatment to improve prognosis.
乳腺癌患者腋窝淋巴结（ALN）的状态对临床决策和预后至关重要。术前评估有限淋巴结负荷（0 - 2个转移腋窝淋巴结）和高淋巴结负荷（≥3个转移腋窝淋巴结）对于乳腺癌患者的个体化治疗至关重要。因此，本研究旨在评估Angio - PLUS（AP；Aixplorer，SuperSonic Imagine）以及乳腺病变的定性和定量剪切波弹性成像（SWE）对预测有限或高腋窝淋巴结负荷的价值，并建立一个预测有限或高腋窝淋巴结负荷的模型。
2020年3月至2022年11月，从岳阳市中心医院回顾性纳入了232例连续的乳腺癌患者，共232个乳腺病变。比较了AP、定性SWE、定量SWE以及评估有限或高腋窝淋巴结负荷的预测模型的敏感性、特异性、阴性预测值（NPV）、阳性预测值（PPV）、准确性和受试者操作特征曲线下面积（AUC）。
有限淋巴结负荷组和高淋巴结负荷组之间的AP模式无显著差异。预测有限或高淋巴结负荷的Emin（第一个Q框的最小值）、Emean（第一个Q框的平均值）、Emax（第一个Q框的最大值）、Eratio（第一个Q框与第二个Q框的比值）和标准差的最佳截断值分别为80.85千帕、133.45千帕、153.40千帕、9.95和19.25千帕。Emax的AUC最高，其敏感性、特异性、PPV、NPV、准确性和AUC分别为71.64%、56.36%、40.00%、83.04%、60.78%和0.640 [95%置信区间（CI）：0.575 - 0.702]。定性SWE的七种颜色模式的敏感性、特异性、PPV、NPV、准确性和AUC分别为71.64%、74.55%、53.33%、86.62%、73.71%和0.731（95% CI：0.669 - 0.787），显著高于所有其他定量SWE参数。根据二元逻辑回归分析，超声和定性SWE中的ALN评估是预测有限或高淋巴结负荷的独立危险因素。基于独立危险因素的预测模型的AUC为0.820（95% CI：0.765 - 0.867），显著高于其他独立危险因素。
乳腺病变定性SWE中的七种颜色模式对预测乳腺癌患者的有限或高淋巴结负荷有价值。与定量SWE相比，定性SWE表现出更好的诊断性能。乳腺病变无表现、垂直条纹和斑点模式是有限淋巴结负荷的重要指标。本研究建立的预测模型可能是一种简单、无创且方便的预测有限或高淋巴结负荷的方法，这将有利于临床决策和个体化治疗以改善预后。
