Three-Dimensional Quantified Morphological Predictors of Intracranial Aneurysm Instability: A Longitudinal Study.

Background and purpose: The performance of current prediction models for intracranial aneurysm growth and rupture is suboptimal, and new markers are needed to improve prediction. There is a strong need for longitudinal studies that use standardized morphological parameters. In this longitudinal study, we aimed to identify standardized three-dimensional (3D) quantified morphological parameters as predictors of aneurysm growth or rupture during long-term follow-up.

Materials and methods: We used a database of consecutive patients with saccular unruptured intracranial aneurysms diagnosed between 2008-2018. Employing a retrospective case-cohort design, we included a computer-generated random sample of aneurysms from the full cohort and aneurysms with growth or rupture during follow-up outside the random sample. The case-cohort design is efficient for low-incidence outcomes while maintaining the temporal association between exposure and outcome. Aneurysms were annotated on baseline CTA or MRA images, and 3D morphological parameters were quantified. Univariable and multivariable Cox proportional hazards models were used to identify 3D morphological predictors of either aneurysm growth or aneurysm rupture. An inverse sampling probability weight was applied to obtain unbiased estimates of the hazard ratios.

Results: We included 278 patients (median age, 59 years [IQR50-66]; 209 women) with 327 aneurysms, of which 239 aneurysms were stable during follow-up (73%), 68 grew without subsequent rupture (21%), 7 grew with subsequent rupture (2%), and 13 ruptured without preceding growth (4%). In the multivariable model for growth prediction (median follow-up 4.1 years [IQR1.9-7.1]), 2 parameters were retained: major axis (HR 1.16, 95%CI: 0.84-1.61) and shape index (HR 1.53, 95%CI: 0.76-3.08), with a c-statistic of 0.56 (95%CI: 0.49-0.63). The same parameters were retained in the multivariable model for prediction of rupture (median follow-up 4.5 years [IQR2.1-7.3]): major axis (HR 2.27, 95%CI: 1.36-3.80) and shape index (HR 3.33, 95%CI: 0.95-11.62), with a c-statistic of 0.85 (95%CI: 0.77-0.94).

Conclusions: We identified major axis and shape index as candidate 3D quantified morphological predictors of both aneurysm growth and rupture, but only for rupture these had good discriminative power in our cohort. These parameters will need external validation and should be integrated with existing clinical prediction models.

Abbreviations: ELAPSS = Earlier subarachnoid hemorrhage, Location of the aneurysm, Age, Population, Size of the aneurysm, and Shape of the aneurysm; IBSI = imaging biomarker standardization initiative; PHASES = Population, Hypertension, Age, Size of aneurysm, Earlier SAH from another aneurysm, and Site of aneurysm; UIA = unruptured intracranial aneurysm.