Non-invasive prediction of invasive lung adenocarcinoma and high-risk histopathological characteristics in resectable early-stage adenocarcinoma by [18F]FDG PET/CT radiomics-based machine learning models: a prospective cohort study

PET/CT radiomics-based models enable accurate non-invasive prediction of invasiveness and high-risk pathology in early-stage LUAD, guiding optimal surgical resection.

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Publication Details

Journal
International Journal of Surgery
Published
2025-09-10
DOI
https://doi.org/10.1097/js9.0000000000003464
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36
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article

Non-invasive prediction of invasive lung adenocarcinoma and high-risk histopathological characteristics in resectable early-stage adenocarcinoma by [18F]FDG PET/CT radiomics-based machine learning models: a prospective cohort study

Ping Luo, Yice Sun, Jiatong Liu, Mengyuan Liang et al.
1 citations
International Journal of Surgery
Radiomics and Machine Learning in Medical Imaging
1.36
article

Non-invasive prediction of invasive lung adenocarcinoma and high-risk histopathological characteristics in resectable early-stage adenocarcinoma by [18F]FDG PET/CT radiomics-based machine learning models: a prospective cohort study

Ping Luo, Yice Sun, Jiatong Liu, Mengyuan Liang, Jingjing Deng, Xinghui Cao, Mengfei Guo, Xiaoli Lan, Qi Huang, Sufei Wang, Yuanyang Hu, Wenjing Xiao, Wei Geng, Jin Yang, Juanjuan Xu, Yan Li, Minglei Li, Zhilei Lv, Mei Zhou, Shengqing Hu, Xueyun Tan
article en
1 citations

Abstract

PET/CT radiomics-based models enable accurate non-invasive prediction of invasiveness and high-risk pathology in early-stage LUAD, guiding optimal surgical resection.

International Journal of SurgeryVol. 112(1)
Union Hospital (HK), Wuhan University (CN), State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (CN), Renmin Hospital of Wuhan University (CN), Union Hospital (CN), Huazhong University of Science and Technology (CN), Hubei University of Technology (CN), Hubei University (CN)
Openalex Percentile: Top 16%
Radiomics and Machine Learning in Medical Imaging
1.36
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