MRI-based radiomics for noninvasive prediction of T790M resistance mutation in lung cancer spinal metastases: an exploratory study

Subregion-based MRI radiomics enables accurate, noninvasive prediction of T790M mutations in NSCLC spinal metastases. This subregion-based MRI radiomics model, to our knowledge, is the first to non-invasively predict T790M resistance mutations in spinal metastases by integrating spatial heterogeneity and SHAP interpretability. This subregion-based MRI radiomics model is exploratory and showed a consistent trend toward improved discrimination and net benefit.

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Publication Details

Journal
Frontiers in Cell and Developmental Biology
Published
2025-10-29
DOI
https://doi.org/10.3389/fcell.2025.1673498
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00

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article

MRI-based radiomics for noninvasive prediction of T790M resistance mutation in lung cancer spinal metastases: an exploratory study

Hua Ai, Yihua Sun, Jianghua Zheng, Chunna Yang et al.
Frontiers in Cell and Developmental Biology
Radiomics and Machine Learning in Medical Imaging
article

MRI-based radiomics for noninvasive prediction of T790M resistance mutation in lung cancer spinal metastases: an exploratory study

Hua Ai, Yihua Sun, Jianghua Zheng, Chunna Yang, Jiahui Wang, Lijun Jin, Xiaoya Zhou
article en

Abstract

Subregion-based MRI radiomics enables accurate, noninvasive prediction of T790M mutations in NSCLC spinal metastases. This subregion-based MRI radiomics model, to our knowledge, is the first to non-invasively predict T790M resistance mutations in spinal metastases by integrating spatial heterogeneity and SHAP interpretability. This subregion-based MRI radiomics model is exploratory and showed a consistent trend toward improved discrimination and net benefit.

Frontiers in Cell and Developmental BiologyVol. 13
First Hospital of China Medical University (CN), Jining Medical University (CN), China Medical University (CN)
Jining Medical University
Openalex Percentile: Top 54%
Radiomics and Machine Learning in Medical Imaging
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MRI-based radiomics for noninvasive prediction of T790M resistance mutation in lung cancer spinal metastases: an exploratory study — Hua Ai, Yihua Sun, et al. · Frontiers in Cell and Developmental Biology (2025) | TGRS Research Map | TGRS