A radiomics-based machine learning model and SHAP for predicting spread through air spaces and its prognostic implications in stage I lung adenocarcinoma: a multicenter cohort study

Our novel machine learning model, integrating imaging features from both tumor and peritumoral regions, preoperatively predicts tumor spread through air spaces in stage I lung adenocarcinoma. It outperforms traditional clinical models, highlighting the potential of quantitative imaging analysis in personalizing treatment. Future prospective studies and further optimization are warranted.

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Publication Details

Journal
Cancer Imaging
Published
2025-09-29
DOI
https://doi.org/10.1186/s40644-025-00935-4
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
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article

A radiomics-based machine learning model and SHAP for predicting spread through air spaces and its prognostic implications in stage I lung adenocarcinoma: a multicenter cohort study

Xiaojiang Zhao, Yuhang Wang, Zixiao Wang, Xufeng Liu et al.
Cancer Imaging
Radiomics and Machine Learning in Medical Imaging
article

A radiomics-based machine learning model and SHAP for predicting spread through air spaces and its prognostic implications in stage I lung adenocarcinoma: a multicenter cohort study

Xiaojiang Zhao, Yuhang Wang, Zixiao Wang, Xufeng Liu, Daqiang Sun, Xin Li
article en

Abstract

Our novel machine learning model, integrating imaging features from both tumor and peritumoral regions, preoperatively predicts tumor spread through air spaces in stage I lung adenocarcinoma. It outperforms traditional clinical models, highlighting the potential of quantitative imaging analysis in personalizing treatment. Future prospective studies and further optimization are warranted.

Cancer ImagingVol. 25(1)
Tianjin People's Hospital (CN), Tianjin Chest Hospital (CN), First Hospital of Qinhuangdao (CN)
Openalex Percentile: Top 60%
Radiomics and Machine Learning in Medical Imaging
DOIOpen Access PDFOpenAlex
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A radiomics-based machine learning model and SHAP for predicting spread through air spaces and its prognostic implications in stage I lung adenocarcinoma: a multicenter cohort study — Xiaojiang Zhao, Yuhang Wang, et al. · Cancer Imaging (2025) | TGRS Research Map | TGRS