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Clinical Trial Summary

This project is aiming at the integration of a biomechanical computer program with a guidance code to simulate the endovascular repair (EVAR) procedure of abdominal aortic aneurysm (AAA). The computational time associated with finite element simulation generally renders its usage impractical for real-time application. Based on data collected during clinical interventions and a priori knowledge of AAA and endovascular device mechanical modeling, the investigators are proposing a deformable registration between preoperative CT-scans and per-operative fluoroscopy that will take into account prior simulations of participant specific EVAR procedures. To avoid the computational cost of a full finite element simulation, the investigators propose a simplified and real-time compliant repetitive mechanical behaviour based on participant specific parameters. The results of this research will provide the Canadian industry with the first realistic deformable vascular geometry tool for live endovascular intervention guidance. The proposed biomechanical modeling can be translated to other vascular intervention procedure by adjusting the biomechanical parameters.


Clinical Trial Description

Endovascular surgery requires of special surgical tools inserted and navigated through the vascular system to reach the site of a disease remotely. This navigation and treatment are perform under video X-Ray imager called fluoroscopy. This low-power X-Ray reveals only the bones, even though the surgery is performed on the vessels. Chemical agent dye can paint momentarily the vessel, but this agent is toxic when used in high dosage. In order to help the surgeon navigate its way, the investigators are developing with Siemens Healthineers an enhance visualization software that displays on the fluoroscopic image the vascular structures of the patient and adapts its shape by the deformation force of the endovascular tools. This can reduce the use of contrast agent, reduce the intervention time (thus reducing radiation exposure) and generally improve the surgical outcomes. To deform the vascular structure without its visualization, the investigators will use a mathematical function to compute the vessel shape when subjected to endovascular tools influence. This function will be based on biomechanical computer simulations performed on a large database of interventional images. Tissues of the entire abdominal region will be simplified and modeled to achieve the most realistic behaviour. Biomechanical simulations have been used in numerous medical applications as a validation tool. The investigators want to innovate and bring this complex simulation result to a live and reactive application. This technological innovation will improve substantially the performances and reliability of image fusion assisting software and set a new standard in medical care practices.The main objectives of this collaborative research project are: 1. Build a simulation model dataset based on existing patient data. 2. Compare simulation on per-operative data and improve the results accuracy over the large dataset by integrating the needed biomechanical properties and constitutive models. 3. Propose a workflow compatible with the Siemens architecture that implements the simulation output overlay 4. Based on the investigators existing biomechanical model, identify geometric, biomechanical and patient specific parameters such as tortuosity, calcification degree and distribution, presence and morphology of thrombus, material elastic properties of the incorporated structures and contact mechanics with surrounding structures. 5. Develop a mathematical tool to deform a vascular model to recreate the numerical mechanical behaviour. 6. Extend the simulation transfer method to a generic solution that can be adapted for interventions for other anatomic territories (ie neurovascular intervention: vessel deformation from coils and flow diverters) ;


Study Design


Related Conditions & MeSH terms


NCT number NCT03481075
Study type Interventional
Source Centre hospitalier de l'Université de Montréal (CHUM)
Contact Jennifer Satterthwaite, MSc
Phone 514-890-8000
Email jennifer.satterthwaite.chum@ssss.gouv.qc.ca
Status Recruiting
Phase N/A
Start date October 1, 2020
Completion date May 29, 2025

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