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Multicenter Study
. 2025 Aug;35(8):4861-4872.
doi: 10.1007/s00330-025-11397-4. Epub 2025 Feb 12.

Deciphering the intratumoral histologic heterogeneity of lung adenocarcinoma using radiomics

Jae Mo Koo #  1 , Jonghoon Kim #  2 , Junghee Lee  3 , Soohyun Hwang  4   5 , Hyo Sup Shim  6 , Tae Hee Hong  3 , Yu Jin Oh  2 , Hong Kwan Kim  2   3 , Chang Young Lee  7 , Byung Jo Park  8 , Ho Yun Lee  9   10
Affiliations
Multicenter Study

Deciphering the intratumoral histologic heterogeneity of lung adenocarcinoma using radiomics

Jae Mo Koo et al. Eur Radiol. 2025 Aug.

Abstract

Objective: To discern highly aggressive intratumoral areas among lung adenocarcinoma (LUAD) and its impact on occult nodal metastases and the recurrence rate with radiomic analysis.

Methods: This prospective dual-institution study analyzed clinical information and high-resolution preoperative CT of 528 patients from institution A and 249 patients from institution B. We extracted radiomic features and performed pathologic evaluations for resected tumors, based on the 2020 International Association for the Study of Lung Cancer (IASLC) classification. Prediction models were developed to discern micropapillary and solid patterns within LUAD using clinical and radiomic features from institution A through logistic analysis.

Results: Six selected CT radiomic features, sex, CTR (consolidation-to-tumor ratio), and solid diameter were selected to develop the prediction models. A composite model of radiomic and clinical characteristics outperformed radiomics-only and clinical-only models (AUC, 95% CI; the composite model: 0.84 [0.81-0.87]; the radiomics model: 0.82 [0.78-0.87]; the clinical model: 0.80 [0.76-0.83]) in institution A. External validation was performed with institution B cohort, showing even better results (AUC, 95% CI; the composite model: 0.91 [0.87-0.94]; the radiomics model: 0.89 [0.84-0.94]; the clinical model: 0.88 [0.84-0.92]).

Conclusions: Our study underscores the potential of radiomics to preoperatively predict aggressive histologic patterns in LUAD, enabling precise treatment planning and prognosis estimation.

Key points: Question Can any adjuvant methods address the limitations of core needle biopsies, which are invasive and may not capture the full heterogeneity of lung adenocarcinoma? Findings In a prospective study of 528 patients with cT1N0M0 lung adenocarcinoma, a composite model of clinical characteristics, conventional CT findings, and radiomics features predicted high-grade cancers. Clinical relevance Preoperative non-invasive diagnosis of histologically high-grade tumors using radiomics analysis offers crucial information for the treatment of lung adenocarcinoma with respect to occult lymph node metastasis and recurrence rate.

Keywords: Computed tomography; Lung adenocarcinoma; Metastasis; Radiomics.

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Conflict of interest statement

Compliance with ethical standards. Guarantor: The scientific guarantor of this publication is the corresponding author Ho Yun Lee. Conflict of interest: S.H. is currently affiliated with Lunit Inc. The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article. Statistics and biometry: J.K., a statistical analyst, participated as a co-author of this manuscript and performed statistical analysis for this manuscript. Informed consent: This study was approved by the Institutional Review Board of Samsung Medical Center (IRB No. 2017-09-045-015) with a waiver of informed consent. Ethical approval: Institutional Review Board approval was obtained. Study subjects or cohorts overlap: This study’s subjects or cohorts have not been previously reported. Methodology: Prospective Observational Multicenter study

References

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