CT-derived nested habitats score for preoperative IASLC grading in lung adenocarcinoma: cross-center validation and radiogenomic analysis

Introduction The 2020 International Association for the Study of Lung Cancer (IASLC) grading system integrates the predominant histologic pattern and the proportion of high-grade patterns, but preoperative CT assessment is limited by spatial averaging of heterogeneous tumor components. We aimed to develop a CT-derived nested habitats score (NHS) that recursively identifies grade-associated intratumoral CT subregions, evaluate its cross-center performance for preoperative IASLC grading, and explore its transcriptomic correlates. Methods This retrospective two-center study included 650 patients with surgically resected lung adenocarcinoma. Center 1 formed the development cohort (n = 390); Center 2 was stratified 1:1 into validation (n = 130) and locked test (n = 130) cohorts, both from the same external institution. The prespecified primary task was pathologic IASLC Grade 1 versus Grade 2/3. NHS was generated using five-fold out-of-fold estimation in development data. Clinical-radiological, whole-tumor radiomics, NHS, and integrated models were compared, with algorithm selection confined to validation before one-time test evaluation. An independent TCGA-LUAD/TCIA CT-RNA cohort (n = 88) underwent exploratory WGCNA and Hallmark gene-set enrichment analysis. Results The development/validation/test cohorts contained 41/14/14 Grade 1, 293/101/96 Grade 2, and 56/15/20 Grade 3 tumors. The selected random-forest integrated model yielded AUCs of 0.871 (95% CI, 0.784–0.936) in validation and 0.866 (95% CI, 0.784–0.935) in testing. NHS alone yielded AUCs of 0.828 and 0.854, compared with 0.620 and 0.497 for the clinical-radiological model and 0.703 and 0.775 for whole-tumor radiomics. NHS accounted for 76.3% of mean absolute SHAP contribution; removing NHS reduced AUC by 0.251 (95% CI, 0.079–0.439) in validation and 0.369 (95% CI, 0.200–0.553) in testing. Brier scores for NHS and the integrated model (0.074–0.077) were below the non-informative reference (0.096), but calibration slopes exceeded 1, and decision curves showed no net benefit over treating all patients as Grade 2/3 at low-to-intermediate thresholds. Exploratory radiogenomics showed nominal NHS-associated coexpression modules and enrichment of WNT/beta-catenin, E2F, G2M-checkpoint, and immune-related programs. Discussion NHS discriminated IASLC Grade 1 from Grade 2/3 tumors, retained stable performance in two held-out cohorts from a second institution, and contributed most of the integrated model’s discrimination. The transcriptomic associations are hypothesis-generating, and recalibration and prospective multicenter evaluation are required before clinical application.