A habitat radiomics model based on contrast-enhanced MRI for predicting early treatment response to hepatic arterial infusion chemotherapy in patients with unresectable hepatocellular carcinoma.

PURPOSE: To develop a contrast-enhanced Magnetic Resonance Imaging (CEMRI)-based habitat radiomics model for predicting early treatment response to hepatic artery infusion chemotherapy with fluorouracil, leucovorin, and oxaliplatin (HAIC-FOLFOX) in patients with unresectable hepatocellular carcinoma (HCC) and elucidate the underlying biological mechanisms.

METHODS

Among 120 HCC patients who underwent HAIC treatment, habitat features were extracted by applying clustering algorithms to preoperative CEMRI to delineate intratumoral subregions with distinct enhancement characteristics. Least absolute shrinkage and selection operator (LASSO) and logistic regression were employed for feature selection to construct habitat, conventional radiomics, clinical, and combined models. Internal validation was performed using 1000 bootstrap resamples. In a separate cohort of 107 surgically resected HCC patients, the habitat model was applied for risk stratification, and correlations between habitat features and pathomorphological characteristics, as well as immunohistochemical (IHC) markers, were investigated.

RESULTS

MRI images were categorized into three distinct habitats, and a predictive model was built from their proportional distribution. The habitat radiomics model achieved an area under the curve (AUC) of 0.868 (95% confidence interval (CI): 0.748–0.976), outperforming both conventional radiomics (AUC 0.849, 95% CI: 0.719–0.954) and clinical models (AUC 0.653, 95% CI: 0.497–0.802). The combined clinical-habitat model reached the highest AUC of 0.901 (95% CI: 0.795–0.989, P < 0.05). In the surgical cohort, low-risk habitat patients exhibited increased tumor necrosis/stromal components (elevated IntensityMin) and better differentiation (reduced CurvMean) (P < 0.05). Immunohistochemistry revealed higher microvessel density (CD34) and lower cancer stem cell marker expression (CK19, Glypican-3) in the low-risk group (P < 0.05).

CONCLUSION

The CEMRI habitat radiomics model accurately predicts early HAIC treatment response, with risk stratification significantly correlated with pathomorphological and molecular characteristics.