Curated, Segmented, and Deep Learning-Optimized I-SPY 2 MRI Dataset for Prediction of pCR, HR, and HER2 Status (BreastDCEDL_ISPY2)

The BreastDCEDL_ISPY2 dataset is a curated, deep learning–ready resource that integrates pretreatment 3D Dynamic Contrast-Enhanced MRI (DCE-MRI) scans from 982 breast cancer patients enrolled in the I-SPY2 TRIAL, sourced from The Cancer Imaging Archive (TCIA). Imaging data has been standardized from raw DICOM to 3D NIfTI volumes, preserving signal integrity and spatial resolution.

The dataset includes extensive non-imaging supporting data, such as tumor annotations, DICOM metadata, and demographics.

To facilitate reproducible research, fixed benchmark train/validation/test splits are provided, stratified by biomarker subtypes and response outcomes.

This dataset enables diverse research applications, including the development of deep learning models for predicting treatment response, radiomics-based analyses, and hormone receptor (HR) and HER2 status classification. It also facilitates benchmarking of advanced architectures such as Vision Transformers, and supports clinical translation efforts in the field of precision oncology.