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This review explores multi-mechanistic models and advanced imaging for improved hydrocephalus diagnosis and treatment, highlighting future directions.
Research paradigms in hydrocephalus are undergoing a profound shift—from a singular emphasis on CSF flow disturbance to a multi-mechanistic, network-interaction model. This review systematically integrates cutting-edge advances from fundamental biology to clinical diagnosis and therapy. Mechanistically, we delineate an interconnected pathological network encompassing neuroinflammation (e.g., the TLR4/NF-κB axis), glymphatic system dysfunction, cilia–ependymal dysregulation, and genetic susceptibility. This broad perspective underscores hydrocephalus as a systemic disorder rather than a purely hydrodynamic abnormality. Technologically, we highlight innovations driven by artificial intelligence (AI) and multimodal neuroimaging—including 4D flow MRI, DTI, and radiomics. These tools enable automated ventricular segmentation, quantitative fluid-dynamic profiling, and robust predictions of surgical outcomes. Consequently, they establish the technical foundation for a "data-driven" paradigm in diagnostics and therapeutics. Therapeutically, we discuss the expanding repertoire of interventions, extending beyond conventional shunt surgery to refined microsurgical techniques, targeted pharmacotherapies, and stem cell–based strategies. Finally, we argue that future progress will depend on integrating multicentre datasets with multi-omics technologies. Establishing this coordinated “mechanism–technology–clinic” framework will accelerate hydrocephalus management toward truly personalized precision medicine.
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Li et al. (2026) studied this question.
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