我们在乳腺癌筛查中实施数字乳腺断层合成术的历程：马尔默乳腺断层合成术筛查项目。

IF 1.9 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING Journal of Medical Imaging Pub Date : 2025-01-01 Epub Date: 2024-10-24 DOI:10.1117/1.JMI.12.S1.S13006

Anders Tingberg, Victor Dahlblom, Magnus Dustler, Daniel Förnvik, Kristin Johnson, Pontus Timberg, Sophia Zackrisson

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引用次数: 0

摘要

目的：旨在介绍马尔默乳腺断层合成筛查项目从开始到现在的情况，以及对未来的展望：我们将分两部分介绍我们的研究小组为通过引入数字乳腺断层合成技术（DBT）来改善乳腺癌筛查所做的努力，包括从最初的研究到大型前瞻性人群筛查试验及以后的工作：我们的研究表明，与欧洲目前乳腺癌筛查的金标准方法--数字乳腺 X 线断层摄影术（DM）相比，DBT 在许多方面都具有显著优势，但有一个主要问题除外--与 DM 相比，DBT 增加了放射科医生的工作量。可以预见，人工智能将是解决这一问题的可行方案：我们已经证明，就诊断效果而言，单视角 DBT 是一种高效的筛查方法。

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Our journey toward implementation of digital breast tomosynthesis in breast cancer screening: the Malmö Breast Tomosynthesis Screening Project.

Purpose: The purpose is to describe the Malmö Breast Tomosynthesis Screening Project from the beginning to where we are now, and thoughts for the future.

Approach: In two acts, we describe the efforts made by our research group to improve breast cancer screening by introducing digital breast tomosynthesis (DBT), all the way from initial studies to a large prospective population-based screening trial and beyond.

Results: Our studies have shown that DBT has significant advantages over digital mammography (DM), the current gold standard method for breast cancer screening in Europe, in many aspects except a major one-the increased radiologist workload introduced with DBT compared with DM. It is foreseen that AI could be a viable solution to overcome this problem.

Conclusions: We have proved that one-view DBT is a highly efficient screening approach with respect to diagnostic performance.

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来源期刊

Journal of Medical Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-

CiteScore

4.10

自引率

4.20%

发文量

期刊介绍： JMI covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal. The scope of JMI includes: Imaging physics, Tomographic reconstruction algorithms (such as those in CT and MRI), Image processing and deep learning, Computer-aided diagnosis and quantitative image analysis, Visualization and modeling, Picture archiving and communications systems (PACS), Image perception and observer performance, Technology assessment, Ultrasonic imaging, Image-guided procedures, Digital pathology, Biomedical applications of biomedical imaging. JMI allows for the peer-reviewed communication and archiving of scientific developments, translational and clinical applications, reviews, and recommendations for the field.