UNASSIGNED: A retrospective analysis of 169 patients with cervical lymph node enlargement who attended Hangzhou Red Cross Hospital from March 2020 to October 2022. All patients underwent conventional ultrasound (CUS), contrast-enhanced ultrasound (CEUS), and real-time elastography (RTE), and were divided into training set and validation set. Univariate analysis was applied to screen out statistically significant parameters, and CUS model and MMUS model were constructed by multifactorial logistic regression analysis. The receiver operator characteristic (ROC) curve was established, and the area under the curve (AUC) was used to compare CUS model with MMUS model to assess the value of MMUS.
UNASSIGNED: Of the cervical 169 lymph nodes in 169 patients included in the study. The 169 enrolled patients were divided into a training set (132 patients) and a validation set (37 patients). In the training set, univariate analysis showed statistically significant differences in long diameter/short diameter(L/S), border, margin, hilus, dermal medulla boundary, blood flow type, enhancement mode, enhancement type, and RTE score (all p< 0.05). Multifactor logistic analysis showed that L/S, blood flow type, enhancement mode and enhancement type were correlates of malignant lymph nodes (all p< 0.05). The comparison of AUC demonstrated that the discriminative ability of the MMUS model was superior to using the CUS model, both in the training set(p = 0.004) and validation set (p<0.001).
UNASSIGNED: In this study, MMUS shows higher diagnostic efficiency than CUS. Ultrasound features such as L/S, blood flow type, mode of enhancement, type of enhancement are helpful in distinguishing benign and malignant lymphadenopathy. The addition of CEUS can greatly improve the sensitivity and specificity of ultrasonic diagnosis of malignant cervical lymph nodes. RTE score is of limited value in the diagnosis of malignant cervical lymph nodes.
■回顾性分析了2020年3月至2022年10月在杭州红十字会医院就诊的169例颈部淋巴结肿大患者。所有患者均接受常规超声检查(CUS),超声造影(CEUS),和实时弹性成像(RTE),分为训练集和验证集。应用单变量分析筛选出具有统计学意义的参数,通过多因素Logistic回归分析构建CUS模型和MMUS模型。建立受试者操作特征(ROC)曲线,曲线下面积(AUC)用于比较CUS模型和MMUS模型以评估MMUS的值。
■纳入研究的169例患者的颈部169个淋巴结。169名入选患者被分为训练集(132名患者)和验证集(37名患者)。在训练集中,单因素分析显示长径/短径(L/S)差异有统计学意义,边界,margin,hilus,真皮髓质边界,血流类型,增强模式,增强类型,和RTE评分(均p<0.05)。多因素Logistic分析表明,L/S,血流类型,增强方式和增强类型与恶性淋巴结相关(均p<0.05)。AUC的比较表明,MMUS模型的判别能力优于CUS模型,在训练集(p=0.004)和验证集(p<0.001)中。
■在这项研究中,MMUS显示出比CUS更高的诊断效率。超声特征,如L/S,血流类型,增强模式,增强类型有助于区分良性和恶性淋巴结病。超声造影可大大提高颈部恶性淋巴结超声诊断的敏感性和特异性。RTE评分对颈部恶性淋巴结的诊断价值有限。