Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN, USA.
Department of Radiology, Mayo Clinic College of Medicine and Science, 200 1st Street SW, Rochester, MN, 55905, USA.
Eur Radiol. 2022 Nov;32(11):7448-7462. doi: 10.1007/s00330-022-08815-2. Epub 2022 Apr 29.
To overcome the limitations of power Doppler in imaging angiogenesis, we sought to develop and investigate new quantitative biomarkers of a contrast-free ultrasound microvasculature imaging technique for differentiation of benign from malignant pathologies of breast lesion.
In this prospective study, a new high-definition microvasculature imaging (HDMI) was tested on 521 patients with 527 ultrasound-identified suspicious breast masses indicated for biopsy. Four new morphological features of tumor microvessels, microvessel fractal dimension (mvFD), Murray's deviation (MD), bifurcation angle (BA), and spatial vascularity pattern (SVP) as well as initial biomarkers were extracted and analyzed, and the results correlated with pathology. Multivariable logistic regression analysis was used to study the performance of different prediction models, initial biomarkers, new biomarkers, and combined new and initial biomarkers in differentiating benign from malignant lesions.
The new HDMI biomarkers, mvFD, BA, MD, and SVP, were statistically significantly different in malignant and benign lesions, regardless of tumor size. Sensitivity and specificity of the new biomarkers in lesions > 20 mm were 95.6% and 100%, respectively. Combining the new and initial biomarkers together showed an AUC, sensitivity, and specificity of 97% (95% CI: 95-98%), 93.8%, and 89.2%, respectively, for all lesions regardless of mass size. The classification was further improved by adding the Breast Imaging Reporting and Data System (BI-RADS) score to the prediction model, showing an AUC, sensitivity, and specificity of 97% (95% CI: 95-98%), 93.8%, and 89.2%, respectively.
The addition of new quantitative HDMI biomarkers significantly improved the accuracy in breast lesion characterization when used as a complementary imaging tool to the conventional ultrasound.
• Novel quantitative biomarkers extracted from tumor microvessel images increase the sensitivity and specificity in discriminating malignant from benign breast masses. • New HDMI biomarkers Murray's deviation, bifurcation angles, microvessel fractal dimension, and spatial vascularity pattern outperformed the initial biomarkers. • The addition of BI-RADS scores based on US descriptors to the multivariable analysis using all biomarkers remarkably increased the sensitivity, specificity, and AUC in all size groups.
为了克服能量多普勒在血管成像方面的局限性,我们试图开发并研究一种新的无对比超声微血管成像技术的定量生物标志物,以区分乳腺病变的良恶性。
在这项前瞻性研究中,对 521 名因超声发现可疑乳腺肿块而需进行活检的患者的 527 个肿块进行了新的高清微血管成像(HDMI)检测。提取和分析了肿瘤微血管的 4 个新形态特征,即微血管分形维数(mvFD)、默里偏差(MD)、分叉角(BA)和空间血管模式(SVP)以及初始生物标志物,并将结果与病理相关联。多变量逻辑回归分析用于研究不同预测模型、初始生物标志物、新生物标志物以及新生物标志物和初始生物标志物联合在区分良恶性病变中的性能。
新的 HDMI 生物标志物,mvFD、BA、MD 和 SVP,在恶性和良性病变中无论肿瘤大小均有统计学差异。在>20mm 的病变中,新生物标志物的敏感性和特异性分别为 95.6%和 100%。将新生物标志物和初始生物标志物结合在一起,对于所有病变,无论肿块大小,AUC、敏感性和特异性分别为 97%(95%CI:95-98%)、93.8%和 89.2%。通过向预测模型中添加乳腺影像报告和数据系统(BI-RADS)评分,分类进一步得到改善,AUC、敏感性和特异性分别为 97%(95%CI:95-98%)、93.8%和 89.2%。
当作为常规超声的补充成像工具时,新的定量 HDMI 生物标志物的加入显著提高了乳腺病变特征的准确性。
从肿瘤微血管图像中提取的新型定量生物标志物提高了鉴别良恶性乳腺肿块的敏感性和特异性。
新的 HDMI 生物标志物默里偏差、分叉角、微血管分形维数和空间血管模式优于初始生物标志物。
将基于 US 描述符的 BI-RADS 评分添加到使用所有生物标志物的多变量分析中,显著提高了所有大小组的敏感性、特异性和 AUC。