Exploratory topological modeling of reported frequencies of aortic arch branching variations

Anatomical variations in the branching patterns of the aortic arch affect endovascular access, surgical planning, and cerebral perfusion strategies. However, the quantitative relationship between branching topology and the frequency distribution of these variations remains unclear. The study aimed to explore whether topological differences among final aortic arch branching configurations are associated with their reported frequencies. Seven pooled type-level frequency estimates from a published meta-analysis were analyzed. Node-Shift and Edge-Loss-Change Scores were defined from the final branching topology relative to Type 1 (separate brachiocephalic, left common carotid, and left subclavian origins from a left-sided arch). A three-parameter log-linear model was fitted by ordinary least squares to natural-log-transformed frequencies. Leave-one-out cross-validation and sensitivity analyses by study modality, study size, and exclusion of Type 1 or Type 4 (common brachiocephalic-left common carotid origin with a left vertebral artery arising directly from the arch) were performed. The fitted log-linear model had an intercept of 4.491 and coefficients of -2.751 for the Node-Shift Score and - 5.474 for the Edge-Loss-Change Score. The coefficient of determination was 0.932 on the log-frequency scale and 0.974 after back-transformation to the original frequency scale. Leave-one-out Q² values were 0.821 and 0.778 on the log and original scales, respectively. Coefficients remained negative in imaging-only, cadaveric-only, studies with at least 100 specimens, Type 1-excluded, and Type 4-excluded analyses. Within this seven-type aggregated dataset, configurations with larger topological scores had lower reported frequencies. The proposed scores provide a compact exploratory description of branching variation, but the model does not establish a developmental mechanism, predict individual anatomy, or support direct clinical decision-making without external validation.