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.

Physics-Informed Graph Neural Networks to solve 1-D equations of blood flow.

Background And Objective: Computational models of hemodynamics can contribute to optimizing surgical plans, and improve our understanding of cardiovascular diseases. Recently, machine learning methods have become essential to reduce the computational cost of these models. In this study, we propose a method that integrates 1-D blood flow equations with Physics-Informed Graph Neural Networks (PIGNNs) to estimate the propagation of blood flow velocity and lumen area pulse waves along arteries.

A data-driven computational methodology towards a pre-hospital Acute Ischaemic Stroke screening tool using haemodynamics waveforms.

Background And Objective: Acute Ischaemic Stroke (AIS), a significant global health concern, results from occlusions in cerebral arteries, causing irreversible brain damage. Different type of treatments exist depending on the size and location of the occlusion. Challenges persist in achieving faster diagnosis and treatment, which needs to happen in the first hours after the onset of symptoms to maximize the chances of patient recovery.

Effect of foot stato-dynamic disorders on hemodynamics of the lower limb using strain-gauge plethysmography.

Background: The plantar venous pump (PVP), composed of deep plantar veins, is the most distal contributor to venous return from the lower limbs. A pressing need still exists to assess how plantar muscle contraction and gait affect PVP function, how foot stato-dynamic disorders (FSDs) can contribute to venous insufficiency, and how venous return can be optimally stimulated. Our first objective is to compare the venous blood hemodynamics in lower limbs between healthy subjects with a FSD and healthy subjects without a FSD to understand the influence of foot morphology in the performance of the PVP.

Effect of dysmorphic plantar arch on venous hemodynamics of the lower limb.

Background: The role of the plantar venous pump (PVP) on venous return is evident but the effects of the foot morphology have never been characterized properly.

Method: 52 healthy volunteers-26 with normal plantar arch (control) and 26 with dysmorphic plantar arch (in two subgroups: 13 flat feet, 13 hollow feet)-were included. Using Doppler ultrasound, we measured the diameter and the peak systolic velocity in the large veins of the lower limb after PVP stimulation by manual compression and bodyweight transfer.

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.

A nonlinear rotation-free shell formulation with prestressing for vascular biomechanics.

We implement a nonlinear rotation-free shell formulation capable of handling large deformations for applications in vascular biomechanics. The formulation employs a previously reported shell element that calculates both the membrane and bending behavior via displacement degrees of freedom for a triangular element. The thickness stretch is statically condensed to enforce vessel wall incompressibility via a plane stress condition.