An In vivo Pilot Study to Estimate the Swelling of the Aneurysm Wall Rabbit Model Generated with Pulsed Fluid Against the Aneurysm Wall.

Purpose: This study addresses the critical issue of evaluating the risk of rupture of unruptured intracranial aneurysms (UIAs) through the assessment of the mechanical properties of the aneurysm wall. To achieve this, an original approach based on the development of an in vivo deformation device prototype (DDP) of the vascular wall is proposed. The DDP operates by pulsing a physiological fluid onto the vascular wall and measuring the resulting deformation using spectral photon counting computed tomography (SPCCT) imaging.

Development of a mechanical characterisation device for intracranial aneurysms: Calibration on polymeric phantom arteries.

Intracranial aneurysm is a major health issue related to biomechanical arterial wall degradation. Currently, no method allows predicting rupture risk based on in vivo quantitative mechanical data. This work is part of a large-scale project aimed at providing clinicians with a non-invasive patient-specific decision support tool, based on the in vivo mechanical characterisation of the aneurysm wall.

mechanical characterization of arterial wall using an inverse analysis procedure: application on an animal model of intracranial aneurysm.

Intracranial aneurysm is a pathology related to the deterioration of the arterial wall. This work is an essential part of a large-scale project aimed at providing clinicians with a non-invasive patient-specific decision support tool to facilitate the rupture risk assessment. It will lean on the link between the aneurysm shape clinically observed and a database derived from the mechanical characterization of aneurysms.

Towards the mechanical characterisation of unruptured intracranial aneurysms: Numerical modelling of interactions between a deformation device and the aneurysm wall.

Intracranial aneurysm is a critical pathology related to the arterial wall deterioration. This work is an essential aspect of a large scale project aimed at providing clinicians with a non-invasive patient-specific decision support tool regarding the rupture risk assessment. A machine learning algorithm links the aneurysm shape observed and a database of UIA clinical images associated with in vivo wall mechanical properties and rupture characterisation.