Spatiotemporal video of blood-brain barrier disruption in neuroinflammatory disorders

Evaluation on benchmark and clinical datasets reveals superior detection of neurovascular disruptions and alignment with expert annotations compared to existing methods. By offering temporally resolved and personalized assessments, our framework supports goals in dynamic neuroimaging, including early intervention and mechanistic disease understanding. This work contributes a scalable, interpretable tool for precision neuromonitoring in neuroinflammatory conditions. Unlike previous approaches that primarily depend on static neuroimaging features, handcrafted thresholds, or disease_specific heuristics, our method introduces a principled end-to-end framework that integrates dynamic video-based biomarkers with interpretable deep modeling. By disentangling transient motion patterns and physiological rhythms within a unified latent space, and aligning biomarker trajectories through patient-specific contextual priors, our method uniquely captures personalized temporal dynamics of BBB disruption. This represents a marked advancement over conventional methods in both adaptability and clinical interpretability, offering a new paradigm for precision neuromonitoring in neuroinflammatory settings.