Multimodal MRI habitat atlas for personalised re-haemorrhage risk prediction in brainstem cavernous malformations

Objective To develop an MRI habitat atlas that is robust across different haemorrhage stages for haemorrhagic brainstem cavernous malformations (BSCMs) and to integrate habitat-derived imaging biomarkers with clinical variables for precise prediction of symptomatic re-haemorrhage. Methods A retrospective cohort of 205 eligible patients from Huashan Main Campus (2015–2020) was randomly divided into a discovery set (n=147) for model development and an internal validation set (n=58). External validation was performed using a prospective temporal cohort from Huashan West Campus (2021–2023, n=94). Each lesion was segmented into six biologically distinct habitats via unsupervised clustering of multiparametric MRI. Habitat-derived radiomic features were combined with clinical variables into a multimodal logistic regression model, which was rigorously validated both internally and temporally. Results The 2-year cumulative re-haemorrhage rate was 81% in high-risk lesions versus 26% in low-risk lesions. The combined habitat–clinical model achieved an area under the curve (AUC) of 0.833 (95% CI 0.777 to 0.889) in the training set and 0.851 in the external validation set, significantly outperforming both imaging-only (∆AUC+0.07, p=0.008) and clinical-only models (∆AUC+0.17, p<0.001). The model demonstrated excellent calibration and provided net clinical benefit across decision thresholds of 5%–75%. Conclusion The multimodal MRI habitat atlas provides a robust and reproducible tool for individualised re-haemorrhage risk stratification in BSCMs, facilitating clinical decision-making for surveillance or intervention while reducing the likelihood of overtreatment.