Global Epidemiology and Risk Stratification of the Inferior Alveolar Nerve Anterior Loop: A CBCT-Based Systematic Review with AI-Assisted Clustering

The anterior loop (AL) of the inferior alveolar nerve is an important anatomical consideration during implant placement and surgical procedures in the interforaminal region. This systematic review evaluated global variability in AL prevalence and morphometry and explored population-level anatomical patterns using AI-assisted analysis. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-guided systematic review of cone-beam computed tomography (CBCT) studies was conducted across PubMed, Scopus, Web of Science, Embase, and Google Scholar. Eligible studies reporting AL prevalence, length, or related morphometric characteristics were included. Conventional descriptive evidence synthesis was supplemented by AI-assisted screening, text-based evidence processing, and K-means clustering of aggregated study-level variables to explore anatomical patterns. Risk-of-bias assessment was performed using appropriate quality-assessment tools. Ninety-two studies met the eligibility criteria. AL prevalence demonstrated substantial geographical variability, ranging from approximately 10% to >70%, whereas reported mean AL length generally ranged from 1.2 to 3.8 mm. Higher prevalence and longer AL measurements were reported in several Asian, Middle Eastern, and South American study populations, whereas lower values were observed in several European populations. AI-assisted clustering identified distinct groupings of published study populations based on combined prevalence and morphometric characteristics. These clusters represent exploratory population-level anatomical patterns and should not be interpreted as clinically validated predictors of individual surgical complications. Considerable methodological heterogeneity was observed across studies, including differences in populations, CBCT protocols, anatomical definitions, and measurement techniques. The AL demonstrates substantial global anatomical variability. CBCT provides valuable 3-dimensional assessment when clinically indicated. AI-assisted clustering may complement conventional evidence synthesis by identifying population-level anatomical patterns, although patient-level and external clinical validation is required.