Mapping thrombus habitat: Non-contrast MRI radiomics and pixel-tile histomics approach to track venous thrombosis...

Determining the age and composition of deep vein thrombosis (DVT) is essential for optimizing thrombus removal strategies, yet clinical decision-making remains restrained by the subjectivity of symptom-based assessment. We applied non-contrast T1/T2 weighted MRI radiomics with habitat clustering to quantify thrombus evolution, validating MRI habitats against histopathology with translational clinical potential.

Venous thrombosis was induced in BALB/c mice using a refined inferior vena cava ligation model to ensure consistent thrombus development. Longitudinal and cross-sectional cohorts were imaged at 7 T MRI with T1- and T2-weighted sequences on post-ligation days 2, 7, and 14. Thrombus regions were delineated using a hybrid approach and voxel-level radiomic features were extracted. Unsupervised K-Means clustering defined MRI-based habitats. Imaging signatures were correlated with an artificial neural network pixel classifier and tile-based histomics clustering to quantify red blood cells (RBC), fibrin, and collagen.

Radiomic analysis showed a decline in Energy and TotalEnergy and a similar trend in GrayLevelNonUniformity, reflecting a transition from acute to more uniform chronic thrombi. A two habitats strategy could differentiate acute RBC-rich regions from fibrotic components. Histology confirmed RBC-rich areas fell from 88.22% to 6.52% over 14 days, while collagen-rich areas rose from 0.16% to 79.67%. MRI habitat proportions correlated strongly with histological tile clusters (Spearman r = 0.74, p = 0.0005).

Multiparametric MRI radiomics combined with habitat analysis captures thrombus composition and temporal evolution, with unsupervised histomics providing biological validation. These findings support the translational potential of MRI habitat analysis as a non-invasive biomarker of thrombus heterogeneity.