An Integrated Dataset of Metastatic Breast Cancer to the Brain with Imaging, Radiomics, and Tumor Genetics

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.

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Publication Details

Journal
Scientific Data
Published
2025-11-20
DOI
https://doi.org/10.1038/s41597-025-06066-6
Primary Topic
Brain Metastases and Treatment
Type
article
Field-Weighted Citation Impact
0.00
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article

An Integrated Dataset of Metastatic Breast Cancer to the Brain with Imaging, Radiomics, and Tumor Genetics

Luke Sabal, Andrew Sean Venteicher, Lindsey Sloan, Yoichi Watanabe et al.
Scientific Data
Brain Metastases and Treatment
article

An Integrated Dataset of Metastatic Breast Cancer to the Brain with Imaging, Radiomics, and Tumor Genetics

Luke Sabal, Andrew Sean Venteicher, Lindsey Sloan, Yoichi Watanabe, Matthew A. Hunt, Jianling Yuan, Birra Taha, David Darrow, B. Aika Shoo, Michael C. Park, Megan Kollitz, David Wu
article en

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.

Scientific DataVol. 12(1)
University of Iowa (US), University of Minnesota (US), University of Minnesota System (US), Stanford University (US)
Openalex Percentile: Top 49%
Brain Metastases and Treatment
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