Radiomics using contrast-enhanced T1-weighted imaging and clinical features for predicting response to EGFR-TKIs in EGFR-mutated non-small cell lung cancer patients with brain metastases
Lian-Yu Sui, Tian-Ye Zhang, Cheng Cheng, Li-Hong Xing, Huan Meng, Chong Liu, Qi Wang, Jia-Ning Wang, Tian-Shuo Zhang, Kun Liu, Xiao-Ping Yin · 2026
Read Radiomics using contrast-enhanced T1-weighted imaging and clinical features for predicting response to EGFR-TKIs in EGFR-mutated non-small cell lung cancer patients with brain metastases by Lian-Yu Sui, Tian-Ye Zhang, Cheng Cheng, Li-Hong Xing, Huan Meng, Chong Liu, Qi Wang, Jia-Ning Wang, Tian-Shuo Zhang, Kun Liu, Xiao-Ping Yin (2026) 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/PMC13523532.txt.
Description
Lian-Yu Sui and colleagues build, in a 2026 study, an imaging model to predict whether targeted drugs will work for lung cancer that has spread to the brain. Patients had non-small cell lung cancer with EGFR mutations and received EGFR-blocking drugs. The team combined clinical features with radiomics, numerical features extracted from contrast-enhanced MRI scans.
Data from 338 patients across three centers were analyzed, with features taken from inside tumors and from rings of tissue around them. Seven machine learning algorithms were compared, and random forest performed best. A combined clinical and radiomic model beat either alone in the test set, reaching an area under the curve near 0.76, with similar performance in external validation. The authors propose the model for forecasting one-year treatment benefit.
Catalog record
| CREATOR | Lian-Yu Sui, Tian-Ye Zhang, Cheng Cheng, Li-Hong Xing, Huan Meng, Chong Liu, Qi Wang, Jia-Ning Wang, Tian-Shuo Zhang, Kun Liu, Xiao-Ping Yin |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 61518 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |