Deciphering the biological underpinnings behind prognostic MRI-based imaging signatures in breast cancer: a systematic review
Nianshi Song, Chen Gao, Xinjing Lou, Ziqing Han, Shantian Wan, Yizhen He, Zhen Fang, Yongyu An, Linyu Wu, Changyu Zhou · 2025
Read Deciphering the biological underpinnings behind prognostic MRI-based imaging signatures in breast cancer: a systematic review by Nianshi Song, Chen Gao, Xinjing Lou, Ziqing Han, Shantian Wan, Yizhen He, Zhen Fang, Yongyu An, Linyu Wu, Changyu Zhou (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12709816.txt.
Description
Nianshi Song and co-authors review the biology behind MRI-based outlook signs in breast cancer in a 2025 systematic review. Scan-based scores from radiomics and deep learning can forecast outcomes, but what they mean in the body is less clear.
The search covered four big databases through early 2025 and kept sixteen studies. Most used supervised learning on patient groups of varied size. Links ran mostly to gene data, tumor surroundings, and multi-layer omics. Quality scores sat in the middle range, and bias risk was high overall by a standard check. The authors call for stronger methods and deeper biology checks. Scan model builders get a sober view of the field.
Catalog record
| CREATOR | Nianshi Song, Chen Gao, Xinjing Lou, Ziqing Han, Shantian Wan, Yizhen He, Zhen Fang, Yongyu An, Linyu Wu, Changyu Zhou |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 56 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |