Portal de investigación
A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations
Fecha de publicación:
Autores de I3PT
Participantes ajenos a I3PT
- Garrucho, L
- Kushibar, K
- Reidel, CA
- Joshi, S
- Osuala, R
- Tsirikoglou, A
- Bobowicz, M
- Catanese, A
- Gwozdziewicz, K
- Cosaka, ML
- Abo-Elhoda, PM
- Tantawy, SW
- Sakrana, SS
- Shawky-Abdelfatah, NO
- Salem, AMA
- Kozana, A
- Divjak, E
- Ivanac, G
- Nikiforaki, K
- Klontzas, ME
- Garcia-Dosda, R
- Gulsun-Akpinar, M
- Lafci, O
- Mann, R
- Martin-Isla, C
- Prior, F
- Marias, K
- Starmans, MPA
- Strand, F
- Diaz, O
- Igual, L
- Lekadir, K
Grupos de Investigación
Abstract
Artificial Intelligence (AI) research in breast cancer Magnetic Resonance Imaging (MRI) faces challenges due to limited expert-labeled segmentations. To address this, we present a multicenter dataset of 1506 pre-treatment T1-weighted dynamic contrast-enhanced MRI cases, including expert annotations of primary tumors and non-mass-enhanced regions. The dataset integrates imaging data from four collections in The Cancer Imaging Archive (TCIA), where only 163 cases with expert segmentations were initially available. To facilitate the annotation process, a deep learning model was trained to produce preliminary segmentations for the remaining cases. These were subsequently corrected and verified by 16 breast cancer experts (averaging 9 years of experience), creating a fully annotated dataset. Additionally, the dataset includes 49 harmonized clinical and demographic variables, as well as pre-trained weights for a baseline nnU-Net model trained on the annotated data. This resource addresses a critical gap in publicly available breast cancer datasets, enabling the development, validation, and benchmarking of advanced deep learning models, thus driving progress in breast cancer diagnostics, treatment response prediction, and personalized care.
Datos de la publicación
- ISSN/ISSNe:
- 2052-4463, 2052-4463
- Tipo:
- Article
- Páginas:
- 453-453
- PubMed:
- 40108146
Scientific Data NATURE PORTFOLIO
Citas Recibidas en Web of Science: 5
Documentos
- No hay documentos
Filiaciones
Campos de Estudio
Financiación
Cita
Garrucho L,Kushibar K,Reidel CA,Joshi S,Osuala R,Tsirikoglou A,Bobowicz M,del Riego J,Catanese A,Gwozdziewicz K et al. A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations. Sci Data. 2025. 12. (1):p. 453-453. DOI: 10.1038/s41597-025-04707-4.
Garrucho L,Kushibar K,Reidel CA,Joshi S,Osuala R,Tsirikoglou A,Bobowicz M,del Riego J,Catanese A,Gwozdziewicz K,Cosaka ML,Abo PM,Tantawy SW,Sakrana SS,Shawky NO,Salem A,Kozana A,Divjak E,Ivanac G,Nikiforaki K,Klontzas ME,Garcia R,Gulsun M,Lafci O,Mann R,Martin C,Prior F,Marias K,Starmans M,Strand F,Diaz O,Igual L,Lekadir K. A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentations. Sci Data. 2025. 12. (1):p. 453-453. IF:6,900. (1).