Quantifying Early-Stage Lung Adenocarcinoma Progression with a Radiomic Trajectory - Summary - MDSpire

Quantifying Early-Stage Lung Adenocarcinoma Progression with a Radiomic Trajectory

  • By

  • Zhen-Bin Qiu

  • Jiaqi Li

  • Shihua Dou

  • Qiuchen Meng

  • Meng-Min Wang

  • Hong-Ji Li

  • Chao Zhang

  • Hongsheng Xie

  • Ben-Yuan Jiang

  • Jun-Tao Lin

  • Jia-Tao Zhang

  • Fang-Ping Xu

  • Jin-Hai Yan

  • Lei Wei

  • Yi-Long Wu

  • Haibo Wang

  • Lin Yang

  • Xuegong Zhang

  • Wen-Zhao Zhong

  • November 17, 2025

  • 0 min

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Objective:

To quantify the progression of early-stage lung adenocarcinoma (esLUAD) using a deep learning framework that integrates both radiomic and pathological information for enhanced diagnostic accuracy.

Key Findings:
  • RadioTrace predicted tumor phenotypes such as spread through air spaces (STAS) and lymph node metastasis (LNM), demonstrating its clinical relevance.
  • It served as an independent prognostic factor with significant survival heterogeneity within the same pathological grade, indicating the limitations of current grading systems.
  • Genomic and transcriptomic analyses confirmed associations with progression-related molecular features, reinforcing the findings.
  • Longitudinal analysis showed consistency with continuous progression in patients, supporting the utility of RadioTrace in clinical settings.
Interpretation:

RadioTrace provides a quantitative and interpretable assessment of esLUAD progression, offering insights that surpass traditional histopathology methods.

Limitations:
  • The study relies on multi-center data, which may introduce variability that could affect the generalizability of the findings.
  • Further validation in larger, diverse populations is needed to ensure the robustness and applicability of the results.
Conclusion:

RadioTrace enhances the precision of esLUAD diagnosis and treatment by quantifying tumor progression beyond conventional grading systems.

Original Source(s)

Quantifying Early-Stage Lung Adenocarcinoma Progression with a Radiomic Trajectory

  • by Zhen-Bin Qiu, Jiaqi Li, Shihua Dou, Qiuchen Meng, Meng-Min Wang, Hong-Ji Li, Chao Zhang, Hongsheng Xie, Ben-Yuan Jiang, Jun-Tao Lin, Jia-Tao Zhang, Fang-Ping Xu, Jin-Hai Yan, Lei Wei, Yi-Long Wu, Haibo Wang, Lin Yang, Xuegong Zhang, Wen-Zhao Zhong

  • November 17, 2025

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