Nonlinear and Episodic Growth in the Natural History of Ascending Aortic Dilation

ABSTRACT Background Predicting ascending aortic (AsAo) growth is challenging. Linear, continuous assumptions may oversimplify biology. We evaluated: (1) whether baseline body size–indexed diameter has a non-linear association with subsequent growth; and (2) whether patient-level trajectories are continuous or episodic. Methods Single-center, retrospective study (2012–2024). The Primary Cohort (n=3,315; ≥2 CT/MR scans) modeled the association between baseline indexed size (Z-score) and annualized growth using multivariable linear regression and generalized additive models (GAMs), adjusting for clinical covariates. A Sub-Cohort (n=1,055; ≥4 scans) was classified into longitudinal phenotypes: Stable (Total Growth <2.0 mm), Stable-with-Noise (Total Growth <2.0 mm with alternating small changes), Continuous Growth (Total Growth ≥2.0 mm without an episodic event), and Discontinuous/Episodic Growth (Total Growth ≥2.0 mm with ≥1 growth episode, defined as a diameter increase ≥2.0 mm within one interval or across two adjacent intervals). Results In the Primary Cohort, baseline Z-score showed a significant non-linear (U-shaped) association with subsequent growth in GAMs (p<0.001), with higher growth for small (Z<0) and severely dilated (Z>5) aortas. The size-growth relationship was significantly moderated by age, sex, blood pressure. In the Sub-Cohort, phenotype distribution was: Stable 50.4% (532/1,055), Stable-with-Noise 21.6% (228/1,055), Continuous 5.4% (57/1,055), and Discontinuous/Episodic 22.6% (238/1,055). Among patients with Total Growth ≥2.0 mm (n=295), 81% (238/295) were episodic and 58.3% (172/295) had a non-dilated baseline aorta (Z<2). Conclusion The cohort-level size–growth relationship is non-linear, and episodic growth behavior dominates among those that enlarge. These findings support reassessing surveillance intervals, risk communication, and threshold-based decision pathways in thoracic aortic disease.