Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada.
Joint Department of Medical Imaging, University Health Network, Sinai Health System, Women's College Hospital, Toronto, Ontario, Canada.
Can Assoc Radiol J. 2022 Feb;73(1):107-120. doi: 10.1177/08465371211025229. Epub 2021 Jul 6.
Digital breast tomosynthesis (DBT) is gradually being implemented in routine clinical breast imaging practice. The technique of image acquisition reduces the confounding effect of overlapping breast tissue, which substantially affects cancer detection, abnormal recall, and interval cancer rates in a screening/ surveillance setting. In a diagnostic setting, tomosynthesis also allows for improved lesion localization and characterization over conventional imaging, which potentially improves the accuracy and improved workflow efficiency. To optimize the utility of tomosynthesis, imagers should be aware of the pertinent aspects of image acquisition as it relates to interpretation, the appearance of benign and malignant pathologies, and sources of possible misinterpretation. This article aims to provide a practical knowledge base of DBT and demonstrate its potential benefits when incorporated into routine clinical practice.
数字乳腺断层合成术（DBT）逐渐在常规临床乳腺成像实践中得到应用。该采集技术减少了重叠乳腺组织的混杂影响，这在筛查/监测环境中对癌症检测、异常召回和间隔期癌症发生率有显著影响。在诊断环境中，断层合成术还可以改善病变的定位和定性，优于常规成像，从而潜在地提高准确性和工作流程效率。为了优化断层合成术的应用，成像者应了解与解释相关的图像采集的相关方面、良性和恶性病变的表现，以及可能导致误解的来源。本文旨在提供 DBT 的实用知识库，并展示其在常规临床实践中的潜在益处。
