Reframing moyamoya vasculopathy within steno-occlusive disease of the circle of Willis

Moyamoya disease (MMD) is classically defined by progressive steno-occlusion of the terminal internal carotid artery (ICA) with associated basal collateral networks. Historically, however, this condition was conceptualized in Japan as part of a broader anatomical category-steno-occlusive disease of the circle of Willis (SOCW)-which preceded disease-specific nomenclature. Increasing genetic, developmental, and clinical evidence now challenges the strict separation between MMD and moyamoya syndrome (MMS). In this narrative review, we re-examine moyamoya-related conditions within a unified, location-defined framework and propose three advances: (1) an operational definition of SOCW with explicit anatomical boundaries; (2) a spectrum-based classification distinguishing phenotype from etiologic context; and (3) a refined, location-based multi-hit model integrating developmental vulnerability, genetic susceptibility, and acquired triggers. Historical analysis indicates that SOCW was originally defined as an anatomical category, within which moyamoya vasculopathy (MMV) represents the predominant but non-exclusive angiographic phenotype. Genetic studies identify RNF213 as a major susceptibility modifier influencing phenotypic expression and population prevalence, although substantial ethnic heterogeneity and incomplete penetrance indicate that RNF213 is neither necessary nor sufficient for disease development. Additional genetic and environmental factors may further influence disease expression. Developmental factors may contribute to the characteristic localization of disease, although current evidence remains indirect. This SOCW-based framework provides a structured approach to intracranial steno-occlusive disorders, facilitates interpretation of early or atypical presentations, and supports multimodal and longitudinal assessment rather than rigid categorical labeling. By integrating anatomical, genetic, and clinical dimensions, this model offers a pragmatic and biologically grounded basis for future research and refinement of disease classification.