Virtual Population to Re-assess AAA Risk Using Neck Geometry and Shape Compactness Alongside Maximum Diameter

Abstract

We present an automated, constraint-aware framework to generate demographically stratified virtual populations of AAAs and quantifies, at cohort scale, how neck geometry, shape compactness, and maximum diameter jointly modulate AAA haemodynamics. Using 258 CTA-derived cases, we generated 182 validated AAA geometries and ran 364 simulations, extracting 10 geometric descriptors and correlated with six haemodynamic biomarkers. The automated framework blends statistically grounded sampling, anatomical plausibility and regional morphing to provide a scalable route for reproducible computational fluid dynamics (CFD) to uncover geometry-biomarker relations at cohort scale. Proximal neck diameter and sphericity were the dominant determinants of wall shear magnitude. Neck diameter increased mean wall shear stress (WSS) (r {approx} 0.49) while reducing peak WSS0.95 (r {approx} -0.31) and low-time-averaged wall shear stress (TAWSS) area (r {approx} -0.27), whereas sphericity, a largely under-explored AAA shape descriptor, was the strongest inverse correlate of mean WSS (r {approx} -0.57). Maximum diameter minimally affected peak shear (r {approx} +0.06) but was associated with reduced mean WSS (r {approx} -0.41). Convexity, another such descriptor, was the dominant correlate of oscillatory shear, increasing OSI (r {approx} +0.46) while modestly lowering mean WSS (r {approx} -0.28). The framework reveals neck calibre and shape compactness, not maximum diameter alone, as dominant modulators of AAA haemodynamics.