Impact of non-contrast-enhanced imaging input sequences on the generation of virtual contrast-enhanced breast MRI scans using neural network
Question How do different MRI sequences impact the performance of virtual contrast-enhanced (vCE) breast MRI? Findings The input combination of T1-weighted, T2-weighted, and diffusion-weighted imaging sequences with three b-values showed the best qualitative performance. Clinical relevance While in the future neural networks providing virtual contrast-enhanced images might further improve accessibility to breast MRI, the significant influence of input data needs to be considered during translational research.
Authors
- Frederik Bernd Laun (ORCID: https://orcid.org/0000-0002-9269-5609)
- Luise Brock (ORCID: https://orcid.org/0000-0002-4591-4354)
- Dominique Hadler (ORCID: https://orcid.org/0000-0002-7334-8855)
- Evelyn Wenkel
- Andrzej Liebert (ORCID: https://orcid.org/0000-0002-8450-3021)
- Sebastian Bickelhaupt (ORCID: https://orcid.org/0000-0003-1043-4462)
- Lorenz A. Kapsner (ORCID: https://orcid.org/0000-0003-1866-860X)
- Sabine Ohlmeyer (ORCID: https://orcid.org/0000-0001-9163-8840)
- Hannes Schreiter (ORCID: https://orcid.org/0000-0002-4373-6996)
- Michael Uder (ORCID: https://orcid.org/0000-0001-6238-4247)
- Jessica Eberle
- Julius Emons (ORCID: https://orcid.org/0000-0002-2520-4443)
- Ramona Erber (ORCID: https://orcid.org/0000-0003-0315-1229)
- Chris Ehring (ORCID: https://orcid.org/0009-0002-4910-0937)
Institutions
- German Cancer Research Center (DE)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- Heidelberg University (DE)
- Universitätsklinikum Erlangen (DE)
- München Klinik (DE)
- Comprehensive Cancer Center Erlangen (DE)
Publication Details
- Journal
- European Radiology
- Published
- 2024-10-25
- DOI
- https://doi.org/10.1007/s00330-024-11142-3
- Citations
- 5
- Primary Topic
- MRI in cancer diagnosis
- Type
- article
- Field-Weighted Citation Impact
- 2.02
Funders
- Deutsche Forschungsgemeinschaft
- Bayerisches Staatsministerium für Wissenschaft und Kunst