Prediction of hormone receptor status in breast cancer brain metastases using an MRI-based multimodal deep learning framework
Qiqi Sun, Qiong Zhang, Yabo Xiao, Xiaohua Pei · 2026
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Description
Qiqi Sun and co-authors build a deep learning tool to read hormone status from brain scans in breast cancer in a 2026 study. Cancer spread to the brain needs hormone data to guide care, yet biopsy is risky and may miss varied lesions. Scan based reading could fill the gap if it joins image, texture, and place data.
Training used 268 scans from 165 patients in a public archive with expert tumor outlines. The model fused deep image traits, measured texture traits, and tumor place codes, and learned three receptor tasks at once. Scores for each receptor passed strong marks in tests. Lesion wise sampling guarded against data leaks.
Catalog record
| CREATOR | Qiqi Sun, Qiong Zhang, Yabo Xiao, Xiaohua Pei |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 77875 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |