An Integrated Dataset of Metastatic Breast Cancer to the Brain with Imaging, Radiomics, and Tumor Genetics.
Authors
Affiliations (6)
Affiliations (6)
- Department of Neurosurgery, University of Minnesota, Minneapolis, Minnesota, USA. [email protected].
- Department of Radiation Oncology, Stanford University, Stanford, California, USA.
- Department of Radiology, University of Iowa, Iowa City, Iowa, USA.
- Department of Radiology, University of Minnesota, Minneapolis, Minnesota, USA.
- Department of Radiation Oncology, University of Minnesota, Minneapolis, Minnesota, USA.
- Department of Neurosurgery, University of Minnesota, Minneapolis, Minnesota, USA.
Abstract
This study introduces a unique magnetic resonance imaging dataset focusing on metastatic breast cancer to the brain, a significant clinical challenge in cancer treatment. Comprising 297 T1-weighted post-contrast images from 165 patients, this dataset from the University of Minnesota Medical Center is the first dedicated to breast cancer brain metastases. This collection includes expert-reviewed lesion segmentations with original image files, genetic markers, and an extensive array of tumor-derived radiomic features. The dataset's uniqueness lies in its detailed focus on metastatic breast cancer to the brain-offering a rich resource for advanced image-based tumor phenotyping and the vast potential for radiogenomic-based predictions based on machine learning model development. The inclusion of clinician-reviewed tumor segmentations and radiomic features, encompassing shape and texture characteristics, enhances the dataset's utility. This dataset aims to facilitate a deeper understanding of breast cancer metastasis to the brain, promote advancements in precision medicine, and improve patient care.