Guo Wenjuan, Wang Tong, Li Fan, Jia Chao, Zheng Siqi, Zhang Xuemei, Bai Min
Department of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China.
Department of Pathology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China.
Diagnostics (Basel). 2022 Nov 23;12(12):2923. doi: 10.3390/diagnostics12122923.
Objective: To develop a prediction model for discriminating malignant from benign breast non-mass-like lesions (NMLs) using conventional ultrasound (US), strain elastography (SE) of US elastography and contrast-enhanced ultrasound (CEUS). Methods: A total of 101 NMLs from 100 patients detected by conventional US were enrolled in this retrospective study. The characteristics of NMLs in conventional US, SE and CEUS were compared between malignant and benign NMLs. Histopathological results were used as the reference standard. Binary logistic regression analysis was performed to identify the independent risk factors. A multimodal method to evaluate NMLs based on logistic regression was developed. The diagnostic performance of conventional US, US + SE, US + CEUS and the combination of these modalities was evaluated and compared. Results: Among the 101 lesions, 50 (49.5%) were benign and 51 (50.5%) were malignant. Age ≥45 y, microcalcifications in the lesion, elasticity score >3, earlier enhancement time and hyper-enhancement were independent diagnostic indicators included to establish the multimodal prediction method. The area under the receiver operating characteristic curve (AUC) of US + SE + CEUS was significantly higher than that of US (p < 0.0001) and US + SE (p < 0.0001), but there was no significant difference between the AUC of US + SE + CEUS and the AUC of US + CEUS (p = 0.216). Conclusion: US + SE + CEUS and US + CEUS could significantly improve the diagnostic efficiency and accuracy of conventional US in the diagnosis of NMLs.
利用传统超声(US)、超声弹性成像的应变弹性成像(SE)和对比增强超声(CEUS)开发一种用于鉴别乳腺非肿块样病变(NMLs)良恶性的预测模型。方法:本回顾性研究纳入了100例患者经传统超声检测出的101个NMLs。比较了良恶性NMLs在传统超声、SE和CEUS中的特征。组织病理学结果作为参考标准。进行二元逻辑回归分析以确定独立危险因素。开发了一种基于逻辑回归评估NMLs的多模态方法。评估并比较了传统超声、US + SE、US + CEUS以及这些模式组合的诊断性能。结果:在101个病变中,50个(49.5%)为良性,51个(50.5%)为恶性。年龄≥45岁、病变内微钙化、弹性评分>3、增强时间早和高增强是建立多模态预测方法所纳入的独立诊断指标。US + SE + CEUS的受试者操作特征曲线下面积(AUC)显著高于US(p < 0.0001)和US + SE(p < 0.0001),但US + SE + CEUS的AUC与US + CEUS的AUC之间无显著差异(p = 0.216)。结论:US + SE + CEUS和US + CEUS可显著提高传统超声诊断NMLs的诊断效率和准确性。