Reproducibility and diagnostic performance of superb microvascular Imaging's vascular index in solid breast lesions

被引:0
作者
Abougazia, A. [1 ]
York, J. [1 ]
Erdelyi, G. [1 ]
Aryasomayajula, S. [1 ]
Evans, A. [1 ]
机构
[1] Univ Hosp Derby & Burton NHS Fdn Trust, Breast Unit, Uttoxeter Rd, Derby DE22 3NE, England
关键词
CANCER; ANGIOGENESIS;
D O I
10.1016/j.crad.2024.106773
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
AIM: Superb microvascular imaging (SMI) is a new ultrasound tool that can detect small blood vessels while cancelling out artefacts. It may be useful in detecting the vascularity associated with malignant breast lesions. This study evaluated the reproducibility and diagnostic performance of SMI's Vascular Index (VI) in differentiating benign from malignant solid breast lesions. MATERIALS AND METHODS: Solid breast lesions were prospectively assessed by two observers before core biopsy. Each lesion was given BIRADS score, and SMI VI was measured. The reproducibility and diagnostic performance of SMI VI were assessed by the intraclass correlation coefficient (ICC) and by the area under the receiver operating characteristics (AUROC) curve, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). RESULTS: 121 lesions in 115 patients were assessed, of which 53 were malignant and 68 benign. The ICC for SMI VI readings was 0.72. The SMI VI AUROC was 0.61, the sensitivity was 90.4%, specificity of 31.9%, PPV of 50% and NPV of 81.5%. The BIRADS scores in all lesions had an AUROC of 0.78, sensitivity of 100%, specificity of 55.1%, PPV of 62.7%, and NPV of 100%. CONCLUSION: This is the first study to assess the reproducibility and diagnostic performance of SMI VI in differentiating benign from malignant breast lesions in a European population. We have shown that SMI VI is poor at differentiating benign from malignant breast lesions, and therefore reproducibility is irrelevant in this context. Future studies may find other uses for SMI's depiction of lesion vascularity. (c) 2024 The Royal College of Radiologists. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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页数:6
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