Machine learning and statistical shape modelling for real-time prediction of stent deployment in realistic anatomies.

The rise in minimally invasive procedures has created a demand for efficient and reliable planning software to predict intra- and post-operative outcomes. Surrogate modelling has shown promise, but challenges remain, particularly in cardiovascular applications, due to the complexity of parametrising anatomical structures and the need for large training datasets. This study aims to apply statistical shape modelling and machine learning for predicting stent deployment in real time using patient-specific models.

Correction: Bisighini et al. Fabrication of Compliant and Transparent Hollow Cerebral Vascular Phantoms for In Vitro Studies Using 3D Printing and Spin-Dip Coating. 2023, , 166.

In the original publication [...

Machine learning and reduced order modelling for the simulation of braided stent deployment.

Endoluminal reconstruction using flow diverters represents a novel paradigm for the minimally invasive treatment of intracranial aneurysms. The configuration assumed by these very dense braided stents once deployed within the parent vessel is not easily predictable and medical volumetric images alone may be insufficient to plan the treatment satisfactorily. Therefore, here we propose a fast and accurate machine learning and reduced order modelling framework, based on finite element simulations, to assist practitioners in the planning and interventional stages.

Fabrication of Compliant and Transparent Hollow Cerebral Vascular Phantoms for In Vitro Studies Using 3D Printing and Spin-Dip Coating.

Endovascular surgery through flow diverters and coils is increasingly used for the minimally invasive treatment of intracranial aneurysms. To study the effectiveness of these devices, in vitro tests are performed in which synthetic vascular phantoms are typically used to reproduce in vivo conditions. In this paper, we propose a manufacturing process to obtain compliant and transparent hollow vessel replicas to assess the mechanical behaviour of endovascular devices and perform flow measurements.