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索纳造影剂增强超声联合剪切波弹性成像定量分析在鉴别和诊断乳腺肿瘤特征中的临床价值

Clinical value of quantitative analysis of Sonazoid-contrast enhanced ultrasound combined with shear wave elastography in discriminating and diagnosing breast tumor characteristics.

作者信息

Wang Gang, Ouyang Yingmei, Ruan LiTao

机构信息

Ultrasound Imaging Department, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.

Department of Ultrasound Medicine, The Shaoyang Central Hospital of Hunan Province, Shaoyang, Hunan, China.

出版信息

Front Oncol. 2025 May 20;15:1485671. doi: 10.3389/fonc.2025.1485671. eCollection 2025.

Abstract

OBJECTIVE

This research intends to probe the clinical value of combining Sonazoid-contrast-enhanced ultrasound (S-CEUS) quantitative analysis with shear wave elastography (SWE) for discriminating and diagnosing the nature of breast tumors.

METHODS

A total of 108 breast tumor patients (comprising 120 breast lesions) who were classified as category 4 breast tumor cases and underwent routine ultrasound examinations (June 2022-June 2023) were selected for this study. S-CEUS and SWE examinations were conducted on these breast lesions. The morphological characteristics of S-CEUS were assessed, including morphology (regular, irregular), boundary (clear, unclear), and internal enhancement (no enhancement, homogeneous enhancement, heterogeneous enhancement), along with dynamic enhancement features. Additionally, the maximum Young's modulus (Emax) from SWE examinations was recorded, and the results were compared to the gold standard in pathology. The diagnostic efficacy of S-CEUS quantitative analysis, SWE alone, or their combined assessment in determining the nature of breast tumors was evaluated.

RESULTS

Among the cohort of 108 patients, a total of 120 category 4 breast lesions were analyzed, revealing 68 cases (56.67%) of pathologically confirmed malignant breast tumors and 52 cases (43.33%) of benign breast tumors. Malignant breast tumors exhibited irregular morphology, unclear boundaries, heterogeneous internal enhancement, high enhancement levels, increased enhancement ranges, perfusion defects, and predominantly washout-type time-signal intensity curve patterns. These characteristics were significantly more prevalent in malignant tumors compared to benign tumors (p<0.05). Furthermore, quantitative assessment denoted that malignant breast tumors showcased higher CEUS quantitative scores than benign tumors (p<0.05). The Emax for malignant breast tumors was (91.36 ± 24.15) kPa, which was considerably higher than that for benign breast tumors [(49.86 ± 20.31) kPa] (=9.981, p<0.05). Receiver operating characteristic (ROC) curve analysis demonstrated favorable diagnostic performance in evaluating the nature of breast tumors using S-CEUS quantitative analysis (AUC: 0.845) or SWE alone (AUC: 0.789). Particularly noteworthy was the optimal diagnostic efficacy achieved through the combined assessment of S-CEUS quantitative analysis and SWE (AUC: 0.916), yielding sensitivities and specificities of 95.59% and 80.77%, respectively.

CONCLUSION

Both S-CEUS quantitative analysis and SWE are valuable tools for the evaluation of benign and malignant characteristics in breast tumors. Particularly, their combined application demonstrates superior diagnostic efficacy.

摘要

目的

本研究旨在探讨声诺维增强超声(S-CEUS)定量分析联合剪切波弹性成像(SWE)对乳腺肿瘤性质鉴别诊断的临床价值。

方法

选取2022年6月至2023年6月期间经常规超声检查分类为4类乳腺肿瘤病例的108例乳腺肿瘤患者(共120个乳腺病灶)进行研究。对这些乳腺病灶进行S-CEUS和SWE检查。评估S-CEUS的形态学特征,包括形态(规则、不规则)、边界(清晰、不清晰)和内部增强情况(无增强、均匀增强、不均匀增强)以及动态增强特征。此外,记录SWE检查的最大杨氏模量(Emax),并将结果与病理金标准进行比较。评估S-CEUS定量分析、单独SWE或两者联合评估在确定乳腺肿瘤性质方面的诊断效能。

结果

在108例患者队列中,共分析了120个4类乳腺病灶,其中病理确诊为恶性乳腺肿瘤的有68例(56.67%),良性乳腺肿瘤52例(43.33%)。恶性乳腺肿瘤表现为形态不规则、边界不清、内部增强不均匀、增强程度高、增强范围增大、灌注缺损,且时间-信号强度曲线类型以廓清型为主。与良性肿瘤相比,这些特征在恶性肿瘤中更为常见(p<0.05)。此外,定量评估表明恶性乳腺肿瘤的CEUS定量评分高于良性肿瘤(p<0.05)。恶性乳腺肿瘤的Emax为(91.36±24.15)kPa,明显高于良性乳腺肿瘤[(49.86±20.31)kPa](t=9.981,p<0.05)。受试者操作特征(ROC)曲线分析表明,使用S-CEUS定量分析(AUC:0.845)或单独SWE(AUC:0.789)评估乳腺肿瘤性质具有良好的诊断性能。特别值得注意的是,S-CEUS定量分析和SWE联合评估具有最佳诊断效能(AUC:0.916),敏感性和特异性分别为95.59%和80.77%。

结论

S-CEUS定量分析和SWE均是评估乳腺肿瘤良恶性特征的有价值工具。特别是,它们的联合应用显示出卓越的诊断效能。

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