Modelling and stabilization of coil deposition in intracranial aneurysm treatment
Improving the safety of neurovascular interventions
J.P.T. van der Staaij (TU Delft - Mechanical Engineering)
Matin Jafarian – Mentor (TU Delft - Team Matin Jafarian)
Aimee Sakes – Mentor (TU Delft - Medical Instruments & Bio-Inspired Technology)
Ton Van Den Boom – Coach (TU Delft - Team Ton van den Boom)
Jenny Della Santina – Coach (TU Delft - Learning & Autonomous Control)
J. C.F. Winter – Coach (TU Delft - Human-Robot Interaction)
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Abstract
An intracranial aneurysm is a bulge in the cerebral vasculature. The rupture of an aneurysm results in a brain bleed. As a consequence, most patients become severely handicapped or may even die. Preventive treatment with endovascular coiling is controversial due to the high risk of complications. These complications are partly caused by the current uncontrolled delivery of coils to the aneurysm. While recent developments in microcatheter design allow for improved positioning, no method has been devised to model and control the tension applied by the coil on the aneurysm wall throughout a coiling procedure. This thesis aims to come up with a method to improve the safety of aneurysm treatment.
This thesis presents a new way to dynamically model an endovascular coil and its interaction with a microcatheter and the aneurysm wall throughout a coil deployment procedure. The main advantage of this model is its low computational complexity allowing real-time control computation. A control architecture is presented that enables regulation of the contact force between the coil and the aneurysm wall while obeying the constraints imposed by the equipment and the environment. The presented architecture comprises an augmented energy-shaping controller working in parallel with a constraint preservation controller.
This thesis shows that this control architecture asymptotically stabilizes the aneurysm wall tension at the desired value throughout the coil deployment procedure.
This work provides a basis for modelling and control in future experimental validations. Therefore, this work is a promising first step in the modelling and control of robotic systems for neurovascular interventions and a step forward in the preventive treatment of intracranial aneurysms.