MRI-based perfusion-diffusion habitat analysis for characterizing intratumoral heterogeneity in rectal adenocarcinoma.

BACKGROUND

This study aimed to evaluate whether MRI-based perfusion-diffusion habitat imaging derived from dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) can characterize intratumoral heterogeneity and evaluate associations with pathologic stage, synchronous distant metastasis, and exploratory survival outcomes in rectal adenocarcinoma.

METHODS

This retrospective study included 73 patients with pathologically confirmed rectal adenocarcinoma who underwent preoperative DCE-MRI and DWI scans. The volume transfer constant (Ktrans) and apparent diffusion coefficient (ADC) maps were generated from DCE and DWI data, respectively. After manual tumor segmentation and image co-registration, voxel-wise Ktrans and ADC values were clustered using a k-means algorithm to identify distinct spatial habitats. Quantitative metrics extracted from each habitat were compared across pathologic subgroups and entered into multivariable logistic regression models for T staging and association with synchronous distant metastasis.

RESULTS

Three reproducible habitats were identified: Habitat 1, hyper-vasopermeability; Habitat 2, hypo-vasopermeability with hypo-cellularity; and Habitat 3, hypo-vasopermeability with hyper-cellularity. Compared with T1-2 tumors, T3-4 lesions showed significantly higher mean Ktrans and the extracellular-extravascular volume fraction (Ve) in Habitats 1 and 2 and lower mean ADC in Habitats 2 and 3. Multiple perfusion metrics from Habitat 1 significantly correlated with distant metastasis. The optimized logistic regression models achieved AUCs of 0.81 for T staging and 0.78 for distant metastasis prediction.

CONCLUSION

Combined DCE-MRI and DWI habitat imaging enables voxel-level assessment of intratumoral heterogeneity in rectal cancer and may provide a noninvasive imaging biomarker for preoperative T staging and assessment of tumor heterogeneity and systemic disease-associated imaging features.