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ArticleAnnals of surgical oncology2026

CT-based Intratumoral Heterogeneity Score for Preoperative Prediction of Lymphovascular Invasion and Prognosis in Lung Adenocarcinoma: A Multicenter Validation and Radiogenomic Interpretation.

Zhichao Zuo, Yunhua Li, Xuehong Long, Wanyin Qi, Sanhong Zhang

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Article in Annals of surgical oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

Zhichao Zuo *Department of Radiology, The Central Hospital of Xiangtan (The Affiliated Hospital of Hunan University), Xiangtan, 411100, Hunan, China. zuo_z@smail.xtu.edu.cn.
Yunhua Li *Department of Radiology, West China Hospital Sichuan University Jintang Hospital, Jintang First People's Hospital, Chengdu, 610400, Sichuan, China.
Xuehong LongHospital Infection Control Department, West China Hospital Sichuan University Jintang Hospital, Jintang First People's Hospital, Chengdu, 610400, Sichuan, China.
Wanyin QiDepartment of Radiology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646099, Sichuan, China.
Sanhong ZhangLiuyang Traditional Chinese Medicine Hospital, Changsha, 410300, Hunan, China.

Funding

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6 · The paper itself

Abstract

backgroundLymphovascular invasion (LVI) is a key determinant of recurrence and survival in lung adenocarcinoma (LUAD), but preoperative identification remains challenging. We developed and validated a CT-based intratumoral heterogeneity (ITH) score for LVI prediction, prognostic stratification, and exploratory radiogenomic interpretation.

methodsWe retrospectively included 1322 patients from three institutions and one public dataset. The discovery cohort was divided into training (n = 590) and internal validation (n = 253) sets; an independent cohort (n = 362) was used for external validation and prognostic analysis. A Stanford Radiogenomics set (n = 117) was used for exploratory transcriptomic analysis. Multiple machine learning algorithms were trained using the same feature matrix and cohort partitions.

resultsRandom forest was selected as the final classifier, with AUCs of 0.886 (95% confidence interval [CI] 0.842-0.923) in internal validation and 0.850 (95% CI 0.806-0.892) in external validation. The model showed acceptable calibration and positive net benefit across low-to-intermediate threshold probabilities. High ITH remained associated with worse recurrence-free survival (hazard ratio [HR] 12.92; 95% CI 3.90-42.78; P < 0.001) and overall survival (HR 26.47; 95% CI 3.52-198.76; P = 0.001). Exploratory radiogenomic analysis showed enrichment of hypoxia-, angiogenesis-, epithelial-mesenchymal transition-, and glycolysis-related pathways.

conclusionsThe CT-based ITH score may support preoperative risk stratification for LVI and prognosis in LUAD. Radiogenomic findings suggest potential biological correlates and should be considered hypothesis-generating.

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Intratumoral heterogeneityLung adenocarcinomaLymphovascular invasionPrognosisRadiogenomics

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