  Cerebral aneurysm rupture, leading to subarachnoid hemorrhage with a high
mortality rate, disproportionately affects younger populations, resulting in a
significant loss of productive life years. A significant proportion of these
deaths is due to aneurysmal re-bleeding within the first three days following
the initial bleed, prior to treatment. While early aneurysm treatment is
recommended, there is no consensus on the ideal timing, and emergency treatment
offers only an incremental benefit at a significant cost. Although various
multivariable prediction models have been proposed to provide personalized risk
assessments, no validated patient-specific predictor is available to
rationalize emergency treatment. Furthermore, no model has yet incorporated
emerging computational biomechanics-based biomarkers such as wall tension. In
this paper, we proposed and validated an efficient semi-automatic pipeline to
compute patient-specific cerebral aneurysm wall tension as a potential
biomarker for the likelihood of re-bleeding. Our pipeline uses the patient's
computed tomography angiography (CTA) image obtained at the time of
subarachnoid hemorrhage diagnosis to create a patient-specific biomechanical
model of the cerebral aneurysm using the finite element method. A distinctive
feature of our approach is the straightforward model creation and wall tension
computation using shell finite elements, without requiring patient-specific
material properties or aneurysm wall thickness. Our non-invasive,
patient-specific method for cerebral aneurysm wall tension can potentially
provide individualized risk prediction and enhance clinical decision-making.
