Quantitative analysis for identifying molecular subtypes of small cell lung cancer via two-dimensional and three-dimensional contrast-enhanced computed tomography images: a preliminary study

Quantitative analysis of CECT images via radiomics can noninvasively distinguish NE and non-NE molecular subtypes of SCLC. A simplified 2D radiomics approach performed comparably to 3D volumetric analysis for subtype classification and also demonstrated prognostic relevance. Radiomics could serve as a valuable adjunct for SCLC subtype identification and risk stratification, potentially guiding more personalized treatment decisions.

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Publication Details

Journal
Journal of Thoracic Disease
Published
2025-12-01
DOI
https://doi.org/10.21037/jtd-2025-1041
Primary Topic
Lung Cancer Research Studies
Type
article
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article

Quantitative analysis for identifying molecular subtypes of small cell lung cancer via two-dimensional and three-dimensional contrast-enhanced computed tomography images: a preliminary study

Jialiang Ren, M Li, S S Hu, Mengwen Liu et al.
Journal of Thoracic Disease
Lung Cancer Research Studies
article

Quantitative analysis for identifying molecular subtypes of small cell lung cancer via two-dimensional and three-dimensional contrast-enhanced computed tomography images: a preliminary study

Jialiang Ren, M Li, S S Hu, Mengwen Liu, Jiuming Jiang, Xu Jiang, Lin Yang, Li Zhang, Li Liu, Jian-Xin Zhang
article en

Abstract

Quantitative analysis of CECT images via radiomics can noninvasively distinguish NE and non-NE molecular subtypes of SCLC. A simplified 2D radiomics approach performed comparably to 3D volumetric analysis for subtype classification and also demonstrated prognostic relevance. Radiomics could serve as a valuable adjunct for SCLC subtype identification and risk stratification, potentially guiding more personalized treatment decisions.

Journal of Thoracic DiseaseVol. 17(12)
Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Shanxi Provincial Cancer Hospital (CN), Cancer Hospital of Chinese Academy of Medical Sciences (CN)
Good health and well-being
Openalex Percentile: Top 29%
Lung Cancer Research Studies
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