Bridging radiomics and histopathology: cross-modality consistency of radiomic features from CT to micro-CT in NSCLC

OBJECTIVE: Radiomics extracts quantitative features from medical images that may provide non-invasive biomarkers of tumor biology and heterogeneity. However, few studies have explored radiomics on micro-computed tomography (micro-CT) or its transferability to clinical CT. This study investigates the reproducibility and the potential biological correlation of radiomic features across in vivo CT, ex vivo CT, and ex vivo micro-CT in non-small-cell lung cancer (NSCLC). MATERIALS AND METHODS: A retrospective cohort of 60 NSCLC patients with preoperative CT scans and surgical specimens was analyzed. Ex vivo CT and micro-CT images were acquired and compared with in vivo CT using standardized preprocessing, including normalization, resampling, and registration. Tumor regions of interest (ROIs) were semi-automatically segmented, and 93 radiomic features were extracted with Pyradiomics. Cross-modality reproducibility and associations with histotype were evaluated using Spearman correlation, intraclass correlation coefficient, Bland-Altman analysis, and Mann-Whitney U test. RESULTS: Normalization and volume matching improved feature repeatability, with the highest agreement observed in normalized datasets using subsampled ROIs. Four texture-based features consistently showed high reproducibility and potential biological correlation, likely reflecting intratumoral heterogeneity and variation in cell density: DependenceNonUniformity, GrayLevelNonUniformity (GLDM and GLRLM), and Coarseness (NGTDM). These features reliably distinguished adenocarcinoma from squamous cell carcinoma across modalities, confirming their stability and potential as candidate features for transferable biomarkers. CONCLUSION: Harmonization and volume standardization are essential for cross-modality radiomic analyses. Stable texture features provide a potential transferable signature bridging micro-CT and clinical CT imaging in NSCLC, supporting their role as candidate features for further investigation in biologically oriented studies. KEY POINTS: Question Micro-CT serves as an intermediate imaging scale enabling radiomic feature extraction from ex vivo NSCLC tumors, allowing direct comparison with in vivo and ex vivo CT. Findings Intensity normalization and volume-matched subsampling between in vivo CT, ex vivo CT, and micro-CT reduced cross-modality feature variability, improving feature reproducibility. Relevance statement Normalization, volume matching, and cross-modality analysis support the identification of candidate texture features with consistent cross-scale behavior and exploratory associations with NSCLC histotype.