Preoperative CT-based radiomics prediction of tertiary lymphoid structures and prognostic integration with pathological microvascular invasion in resectable hepatocellular carcinoma: a multicenter study.
Authors
Affiliations (7)
Affiliations (7)
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
- Department of Radiology, Xinyu People's Hospital, Xinyu, China.
- Department of Radiology, Ganzhou People's Hospital, Ganzhou, China.
- Department of Stomatology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
- Department of Pathology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
- Department of Stomatology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China. Electronic address: [email protected].
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China. Electronic address: [email protected].
Abstract
Tertiary lymphoid structures (TLS) reflect the tumor immune microenvironment and may provide prognostic information in hepatocellular carcinoma (HCC), but assessment requires pathology. This study aimed to develop and externally validate a CT radiomics-based machine-learning model for preoperative prediction of TLS status and explore disease-free survival across pathological TLS/microvascular invasion (MVI) phenotypes. This multicenter retrospective study included 959 patients with HCC (training, n = 792; external validation, n = 167). Radiomic features and an intratumoral heterogeneity (ITH) score were extracted from contrast-enhanced CT images. A stacking ensemble model (ITH-Ensemble) incorporating clinicoradiological variables was developed to predict TLS status and compared with clinical and radiomics models. SHapley Additive exPlanations (SHAP) analysis was used for interpretation. Disease-free survival (DFS) was compared among four TLS/MVI phenotypes. Transcriptomic support was assessed using TCGA-LIHC data (n = 366). The ITH-Ensemble achieved an external-validation AUC of 0.842, versus 0.828 for the radiomics model and 0.732 for the clinical model. SHAP identified the Radscore and inflammatory markers, including monocyte count and alanine aminotransferase, as contributors. The four TLS/MVI phenotypes showed distinct DFS distributions (log-rank p < 0.0001); TLS+/MVI- had the most favorable and TLS-/MVI+ the least favorable outcome. In TCGA-LIHC, CD2 expression correlated with natural killer cell infiltration (Spearman ρ = 0.766, p < 0.001) and longer overall survival (p = 0.0247). The CT-based ITH-Ensemble provides a noninvasive preoperative estimate of TLS status in resectable HCC. Pathological TLS/MVI phenotypes were associated with DFS, although a fully preoperative dual-factor framework requires independent MVI prediction. 3 (retrospective multicenter cohort study).