Unruptured intracranial aneurysms: Prediction of growth and rupture

This thesis advances the understanding of unruptured intracranial aneurysms
(UIAs), focusing particularly on risk prediction, aneurysm growth, and aneurysm
wall enhancement (AWE). Despite the relatively low annual rupture rate of UIAs,
their unpredictable behaviour and devastating consequences necessitate precise risk
stratification and individualized management strategies.
A major component of this work measured the absolute risk of rupture after
aneurysm growth. In a multicentre cohort of 312 patients with growing aneurysms,
the 1-year rupture risk was 4.3%. Based on this dataset, the triple-S model,
integrating three independent predictors, aneurysm size, site, and shape, was
developed to estimate the rupture risk following growth, ranging from 2.1% to 10.6%
within the first year. This model provides clinicians with a practical tool to guide
decisions about preventive treatment.
This thesis investigated AWE using gadoliniumenhanced
magnetic resonance aneurysm wall imaging (MR-AWI). Although AWE
had been linked to aneurysm instability in cross-sectional studies, its longitudinal
predictive value remained uncertain. In this work, AWE predicted aneurysm growth
or rupture during short-term follow-up, but this association diminished after
adjustment for aneurysm size, except in aneurysms smaller than 7 mm, where AWE
may retain predictive potential.
Extending the observation period to 7.5 years, aneurysms with AWE demonstrated
a significantly higher probability of long-term instability than those without
enhancement, independent of aneurysm size and patient age. These findings
support AWE as a marker of chronic wall pathology and highlight the value of
incorporating wall imaging sequences into conventional MRA protocols for
individualized risk assessment.
Longitudinal imaging of 387 aneurysms showed that AWE was stable
over time, with enhancement appearing or disappearing in only 5.2% of aneurysms
during a median follow-up of 12 months. This stability suggests that the underlying
inflammatory and hemodynamic processes are long-lasting rather than transient.
A complementary 3D morphometric study revealed that AWE at baseline was
associated with increasing aneurysm wall curvedness over long-term follow-up
(median 5.8 years). The proportion of aneurysms with increased curvedness was
substantially higher among those with AWE (30%) compared with those without
(4%), independent of size (OR 6.1, 95%CI 1.01–50.3). These results indicate that
AWE marks biological mechanisms that promote structural remodelling and shape
irregularity, morphological features known to precede rupture.
In conclusion, this thesis highlights the value of combining clinical, morphological,
and imaging-based risk assessment to improve decision-making in patients with
UIAs. The demonstrated stability and prognostic significance of AWE, alongside
refined models such as triple-S, lay the groundwork for more precise and patientcentred
care.

Keypoints
● Risk stratification of UIAs remains challenging due to the limitations of existing
rupture risk models, particularly for small aneurysms.
● This thesis introduces the triple-S model for individualized absolute rupture risks
after aneurysm growht. Also, it demonstrates that AWE is a stable imaging marker
that independently predicts aneurysm instability.
● The triple-S model can support clinical decision-making and treatment
prioritization after aneurysm growth, whereas AWE shows promise as a marker of
chronic wall pathology and should be incorporated into future prospective cohorts
to refine individualized risk prediction in the general UIA population.