Differential diagnosis of non-hydrocephalus ventricular dilation and hydrocephalus

Ventriculomegaly is a common structural neuroimaging finding, yet its differentiation from hydrocephalus remains a substantial clinical challenge. Misclassification of non-hydrocephalic ventriculomegaly as hydrocephalus, or of hydrocephalus as simple ventriculomegaly, may result in inappropriate management, including unnecessary shunt surgery or delayed treatment. Accurate discrimination between these entities is therefore critical for optimal clinical decision-making. Based on a review of the major biomedical databases, we summarized current approaches to differentiating non-hydrocephalic ventriculomegaly from hydrocephalus using neuroimaging, cerebrospinal fluid (CSF) dynamics, biomarkers, and clinical symptoms, with the goal of establishing an integrated diagnostic framework. Neuroimaging markers, including the Evans Index (EI), callosal angle (CA), and disproportionately enlarged subarachnoid-space hydrocephalus (DESH), are useful for characterizing the pattern of ventricular enlargement, while advanced modalities such as phase-contrast MRI and diffusion tensor imaging (DTI) further enhance diagnostic performance. Assessment of CSF dynamics through intracranial pressure (ICP) monitoring, lumbar infusion testing, and resistance to CSF outflow (Rout) provides important insights into CSF circulatory dysfunction. In addition, CSF biomarkers such as tau and amyloid-β may assist in distinguishing hydrocephalus from neurodegenerative disease and age-related ventriculomegaly. Although gait disturbance, cognitive impairment, and urinary incontinence represent the classic clinical triad of hydrocephalus, symptom overlap across disorders limits their diagnostic specificity. Clinical assessment should therefore incorporate symptom patterns, temporal evolution, and treatment responsiveness. Overall, accurate differentiation between non-hydrocephalic ventriculomegaly and hydrocephalus requires a multidimensional strategy integrating neuroimaging, CSF dynamics, biomarkers, and clinical symptoms. This comprehensive framework may improve diagnostic accuracy and guide clinical management.