CE19 - Technologies pour la santé

Devices for augmEnted Endovascular navigation in complex Pathways – DEEP

DEEP: Devices for augmented endovascular navigation in complex pathways

New medical devices ensuring a safe, fast and efficient catheterization in all anatomical configurations.

Augmented catheterization and interventional decision support

Among minimally invasive surgical techniques, endovascular therapies have in recent years experienced a very important development for the treatment of neurovascular and cardiovascular diseases. During access to the treatment site, catheterization involves a technical gesture that can be very difficult in complex anatomical configurations. The aim of the DEEP project is to develop hardware and software devices to offer interventional practitioners innovative solutions for augmented endovascular navigation. These must allow the crossing of complex pathways as well as secured and controlled access to target sites that are difficult or impossible to reach at present. <br /><br />The progress envisaged in the DEEP project is expressed according to innovation axes with strong interactions:<br /> <br />- Increasing the performance of instrumental devices by means of active multi-curve catheters (multi-dof). This issue is addressed by the development of multi-curve devices and tools to assist in design and parameterization, based on digital simulation for complex patient cases.<br />- Perception enhancement for standard and active catheter navigation. This question is addressed by the design and development of decision support software devices for planning (trajectory, parameterization, pre-configuration) and navigation (realization of the gesture). It involves the analysis of patient data (specific or population) and simulation with a real- virtual confrontation.<br />- Augmented perception, decision and action. The objective here is to adopt an integrative approach from the design stage and to consider a computer-assisted active catheterization solution integrating the innovative hardware and software components proposed in DEEP.

The proposed approach jointly exploits the analysis of imaging data and numerical simulation. It is based on the on the following main steps:

- Clinical and functional specification, testing and validation: analysis of interventional scenarios, functional specification of demonstrators, data collection and evaluation.
- Analysis, processing and restitution of information: segmentation and description of representative patient data (complex pathological cases), segmentation of pathological regions by machine learning methods (vessels in low contrast areas, stenoses), population analysis and statistical shape modeling. Pre- /per-operative registration - fusion (visualization).
- Numerical simulation to analyze and predict the behavior of devices: exploitation of patient data, mechanical characterization and modeling of passive and active devices (guidewires, catheters), simulation by simplified approach, bio- and thermo-mechanical numerical simulation, model reduction methods to increase their efficiency, parameterization and validation with respect to intra-operative imaging observations (in-vitro, in-vivo).
- Development, implementation and integration: range of multi-dl active catheters that can be parameterized, (i) optimized in their structure and size, and (ii) indexed according to the needs related to the major classes of vascular anatomy; clinical decision support systems for (i) the choice and parameterization of devices (active, passive), through trajectory anticipation and selection of optimal activation sequence (active catheters) and (ii) the navigation guidance through visual restitution of deviations between planned trajectory and actual trajectory.

The project is in progress. The expected results are innovative medical devices (software and hardware) associated with care.
Different methods of segmentation of imaging data (MRI, CT) have been tested and validated (region growing, active contours, mathematical morphology, deep learning).
A statistical shape model to characterize and compare possible trajectories within vascular structures, at the level of the aortic arch and SAT, was developed.
Devices with shape memory alloy (SMA) active elements were developed for experimental purposes. A numerical model of the active guidewire was developed, integrating the different elements in an explicit way. For the SMA guidewire in particular, a behavior law has been implemented to reproduce the thermomechanical behavior of the particular alloys.

The aim of the project is to design decision support software tools and a new range of multi-curve catheters embedding active elements to augment the performance of catheterization.

A. Badrou, A. Bel-Brunon, N. Hamila, N. Tardif, et A. Gravouil, « Reduced order modeling of an active multi-curve guidewire for endovascular surgery », Computer Methods in Biomechanics and Biomedical Engineering, vol. 23, no sup1, p. S23-S24, oct. 2020, doi: 10.1080/10255842.2020.1811497.

Among minimally invasive surgical techniques, endovascular therapies have in recent years experienced a very important development for the treatment of neurovascular and cardiovascular diseases. During access to the treatment site, catheterization involves a technical gesture that can be very difficult in complex anatomical configurations. The aim of the DEEP project is to develop hardware and software devices to offer interventional practitioners innovative solutions for augmented endovascular navigation. These must allow the crossing of complex pathways as well as secured and controlled access to target sites that are difficult or impossible to reach at present. The research jointly exploits the analysis of imaging data and numerical simulation to design a new range of multi-curve catheters embedding active elements, and of decision support software tools to augment the performance of catheterization. Beyond the tasks related to scientific and technological developments (specifications and evaluations, information analysis and rendering, numerical simulation, hardware and software integration), a task specifically dedicated to the industrial exploitation of results is planned.

DEEP project brings together a very complementary consortium. Academic partners have expertise in medical imaging and image-guided cardiovascular interventions (LTSI), contact and structural mechanics for biomedical applications (LaMCoS). Industrial partners have proven expertise in developing software solutions for interventional decision support (Therenva SAS), active catheter design and development (BCV) and multi-domain finite element software (ANSYS France). Clinical expertise is also integrated into the consortium (A. de Rothschild Ophthalmological Foundation, LTSI clinicians).

Expected results are innovative medical devices (software and hardware) associated with care. They are spread over three levels: scientific, clinical and economic. The scientific production will result in original publications in the fields of information processing and predictive simulation for computer-aided medical interventions (CAMI).

From a clinical point of view, DEEP aims to meet the demand of practitioners that is very strong for new medical devices ensuring a safe, fast and efficient catheterization in all configurations (tortuous anatomies or complex anatomical variations). The expected benefits are therefore primarily a clinical benefit by improving the endovascular treatment of patients.

The DEEP project should contribute to strengthening France's competitiveness in the health technology sector. Proposed major innovations relate to the access phase during endovascular procedures. This "access" market is very important with an annual growth rate of 5% to 10%. BCV's active catheters are, to our knowledge, the only endovascular instruments with embedded activation currently in the industrialization phase. This integration of the actuation at the distal part of the catheters is an opening to the design of revolutionary tools capable of performing complex endovascular gestures, still impossible today. In addition to the development by Therenva of software solutions dedicated to active catheters, the development of decision support systems for the patient-specific choice of ancillaries currently available (passive catheters and guidewires) and augmented reality guidance of these tools, would represent a major and unprecedented advance. In a partnership strategy, ANSYS France aims to integrate its simulation and real-time calculation components into the Therenva and BCV solutions.

Project coordination

Pascal Haigron (LABORATOIRE TRAITEMENT DU SIGNAL ET DE L'IMAGE)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

FOR FONDATION A DE ROTHSCHILD
LaMCoS LABORATOIRE DE MECANIQUE DES CONTACTS ET DES STRUCTURES
BCV BASECAMP VASCULAR
LTSI LABORATOIRE TRAITEMENT DU SIGNAL ET DE L'IMAGE
ANSYS ANSYS FRANCE
Therenva THERENVA

Help of the ANR 642,041 euros
Beginning and duration of the scientific project: January 2019 - 48 Months

Useful links

Explorez notre base de projets financés

 

 

ANR makes available its datasets on funded projects, click here to find more.

Sign up for the latest news:
Subscribe to our newsletter