Simultaneous Digital Breast Tomosynthesis and Mechanical Imaging

Our project is motivated by a persistent challenge of underdiagnosis and false positives in breast cancer healthcare. The four most exciting innovations in breast cancer imaging that have recently emerged include: Digital Breast Tomosynthesis (DBT), MI, VCTs, and artificial intelligence (AI). In this project we utilize extensive experience of Lund University hosts, Prof. Zackrisson and Dr. Tingberg, and Dr. Bakic to interconnect these innovations efficiently and flexibly, enabling significant benefits. Within the two-year timeline, we have built a simultaneous DBT and MI (DBTMI) prototype system, and developped image processing and DBT reconstruction to maximize image quality. We have evaluated the prototype, first preclinically by VCTs and physical phantoms, followed by a pilot clinical trial. We would also explore introducing modern AI methods to improve DBTMI performance. Combined complementary experience, carefully designed knowledge-exchange activities, and Lund excellent institutional resources, guarantee the success of this application, and Dr. Bakic's successful reintegration into European research community.

“This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 846540”

Breast cancer is still one of the most frequent causes of cancer death, despite tremendous advances in breast screening and cancer therapy. The most challenging issues are cancers that are missed at screening, women recalled for additional diagnostic imaging who do not have breast cancer – so-called false positives – and distinguishing aggressive from non-aggressive tumors. Missed cancers and false positives cause significant financial and psychological burden. Our project combines digital breast toosynthesis (DBT), a three-dimensional imaging method that improves the visualization of breast tissue, with mechanical imaging (MI), a method to capture mechanical properties of the tissue – which provide complementary clinical information. In our previous studies where both digital mammography (DM) and MI were performed, we observed a 30%-40% reduction in false positives at screening and identified novel signatures of breast cancers. In this project, we have investigated integrating MI with DBT to allow both to be acquired simultaneously. A simultaneous exam means that patient experience would not differ from standard DBT, requiring no additional exam time or increased radiation dose. Our project has the potential to help all women who participate in breast screening programs by improving accuracy. Moreover, it could specifically help women with dense breasts, who are more prone to false positives and false negatives due to the risk of masking tumors in x-ray images by normal dense breast tissue. In addition to the important clinical benefits, our project will create great resources for research, including the infrastructure for future investigation of MI.