Fu Naiqin, Li Junkang, Wang Bo, Jiang Ying, Li Shiyu, Niu Ruilan, Wang Zhili
Department of Ultrasound, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Department of Ultrasound, Chinese PLA 63820 Hospital, Mianyang, China.
Gland Surg. 2023 Dec 26;12(12):1654-1667. doi: 10.21037/gs-23-223. Epub 2023 Dec 22.
Previous studies show the size of lesions could affect the diagnostic accuracy of contrast-enhanced ultrasound (CEUS). It is unclear whether CEUS has good diagnostic performance for lesions ≤2.0 and ≤1.0 cm. It is beneficial for the early diagnosis to explore the application of CEUS in breast lesions of different sizes. This study aims to analyze the diagnostic performance of CEUS and explore diagnostic models better suited to breast lesions of different sizes.
A total of 1,059 lesions (656 benign and 403 malignant) examined by ultrasound and CEUS with definite pathological results were included in this retrospective study and divided into training (n=847) and validation (n=212) sets. All lesions were divided into three groups according to size. Diagnostic models (M: all lesions; M: ≤1.0 cm, M: >1.0-2.0 cm, and M: >2.0 cm) were developed through logistic regression analyses of CEUS features from the training set. Diagnostic performance was evaluated using the area under the receiver operating characteristic curve (AUC) and validated in the validation set.
The median age of patients was 45±11 years (range, 18-80 years). The AUC values of M combined with the Breast Imaging Reporting and Data System (BI-RADS) in the training and validation sets were 0.921 and 0.922, respectively (P=0.893). The AUC values of M combined with BI-RADS in the three groups were 0.844, 0.936 and 0.928 respectively. M was less effective in diagnosing lesions ≤1.0 cm (0.844 0.921, P=0.029). The AUC of M combined with BI-RADS for lesions ≤1.0 cm was higher than that of M (0.893 0.844, P=0.047), and M and M had no statistical difference in diagnostic performance when compared with M (P=0.243; P=0.246).
The diagnostic performance of CEUS was closely related to lesion size. Establishing a new diagnostic model for lesions ≤1.0 cm can improve the CEUS diagnostic performance for breast lesions ≤1.0 cm.
既往研究表明,病变大小可能会影响超声造影(CEUS)的诊断准确性。目前尚不清楚CEUS对于≤2.0 cm和≤1.0 cm的病变是否具有良好的诊断性能。探索CEUS在不同大小乳腺病变中的应用,有助于早期诊断。本研究旨在分析CEUS的诊断性能,并探索更适合不同大小乳腺病变的诊断模型。
本回顾性研究纳入了1059例经超声和CEUS检查且病理结果明确的病变(656例良性病变和403例恶性病变),并将其分为训练集(n = 847)和验证集(n = 212)。所有病变根据大小分为三组。通过对训练集CEUS特征进行逻辑回归分析,建立诊断模型(M:所有病变;M:≤1.0 cm,M:>1.0 - 2.0 cm,M:>2.0 cm)。使用受试者操作特征曲线下面积(AUC)评估诊断性能,并在验证集中进行验证。
患者的中位年龄为45±11岁(范围:18 - 80岁)。训练集和验证集中M联合乳腺影像报告和数据系统(BI - RADS)的AUC值分别为0.921和0.922(P = 0.893)。三组中M联合BI - RADS的AUC值分别为0.844、0.936和0.928。M在诊断≤1.0 cm的病变时效果较差(0.844 0.921,P = 0.029)。M联合BI - RADS对≤1.0 cm病变的AUC高于M(0.893 0.844,P = 0.047),M和M与M相比,诊断性能无统计学差异(P = 0.243;P = 0.246)。
CEUS的诊断性能与病变大小密切相关。建立针对≤1.0 cm病变的新诊断模型可提高CEUS对≤1.0 cm乳腺病变的诊断性能。