Histological Hyperspectral Breast Cancer Recurrence Database (HistologyHSI-BC Recurrence)
Quintana-Quintana, Laura; Sauras-Colón, Esther; Fiorin, Alessio; Santana-Nunez, Javier; Ortega Sarmiento, Samuel; Gallardo-Borràs, Noèlia; Fischer-Carles, Alba; Sánchez-Alcántara, Tábata; Fabelo, Himar; Adalid-Llansa, Laia; Mata-Cano, Daniel; Bosch-Príncep, Ramon; Lejeune, Marylène; Callico, Gustavo M.; López-Pablo, Carlos
Summary
Abstract Metastasis occurs in nearly 1 out of 3 breast cancer (BC) patients and significantly reduces survival rates, particularly in cases of distant metastases. As most distant metastases develop after diagnosis (i.e., recurrence) and remain incurable, there is a critical need for prognostic biomarkers to assess recurrence risk. Multimodal data analysis has emerged as a promising approach to integrate diverse information, offering a more comprehensive perspective. This study introduces the Histology HSI-BC (hyperspectral imaging - breast cancer) Recurrence Database, the first publicly accessible multimodal database designed to advance BC distant recurrence prediction. The database comprises 47 histopathological whole-slide images, 677 hyperspectral (HS) images, and clinical and demographic data from 47 BC patients, of whom 22 (47%) experienced distant recurrence over a 12-year follow-up. Histopathological slides were digitized using a whole-slide scanner and annotated by expert pathologists, while HS images were acquired with an HS camera coupled to a bright-field microscope. This database provides a promising resource for studying BC recurrence prediction and personalized treatment strategies by integrating the aforementioned multimodal data.
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DOI
:
doi.org/10.1038/s41597-025-061...
NVA
:
hdl.handle.net/11250/5369607
Publication details
Journal : Scientific Data , 2025 , vol. 12 , no.1 , pp. 1–14
Publication type : Academic article
