Mohan Supraja Laguduva, Dhamija Ekta, Gauba Richa
Department of Radiodiagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India.
Department of Radiodiagnosis, National Cancer Institute - All India Institute of Medical Sciences, Jhajjar, Haryana, India.
Indian J Radiol Imaging. 2024 Feb 23;34(4):677-687. doi: 10.1055/s-0044-1779589. eCollection 2024 Oct.
Nonmass lesions in breast ultrasound (US) are areas of altered echogenicity without definite margins or mass effect. However, these lesions may show calcifications, associated architectural distortion, or shadowing just like masses. They vary in their echogenicity, distribution, ductal or nonductal appearance and the associated features that can be seen in variety of benign and malignant pathologies. With no uniform definition or classification system, there is no standardized approach in further risk categorization and management strategies of these lesions. Malignant nonmass lesions are not uncommon and few sonographic features can help in differentiating benign and malignant pathologies. US-guided tissue sampling or lesion localization can be preferred in the nonmass lesions identified on second look US after magnetic resonance imaging or mammography. This article aims to describe various imaging patterns and attempts to provide an algorithmic approach to nonmass findings on breast US.
乳腺超声(US)检查中的非肿块性病变是指回声发生改变的区域,没有明确的边界或肿块效应。然而,这些病变可能会出现钙化、相关的结构扭曲或声影,与肿块类似。它们在回声、分布、导管或非导管表现以及各种良性和恶性病变中可见的相关特征方面存在差异。由于没有统一的定义或分类系统,在对这些病变进行进一步的风险分类和管理策略方面没有标准化的方法。恶性非肿块性病变并不罕见,很少有超声特征能够有助于区分良性和恶性病变。在磁共振成像或乳腺钼靶检查后经二次超声检查发现的非肿块性病变中,超声引导下的组织取样或病变定位可能更受青睐。本文旨在描述各种成像模式,并尝试为乳腺超声检查中的非肿块性发现提供一种算法方法。