Towards Interactive Planning of Coil Embolization in Brain Aneurysms

The original publication is available at www.springerlink.comInternational audienceMany vascular pathologies can now be treated in a minimally invasive way thanks to interventional radiology. Instead of open surgery, it allows to reach the lesion of the arteries with therapeutic devices through a catheter. As a particular case, intracranial aneurysms are treated by filling the localized widening of the artery with a set of coils to prevent a rupture due to the weakened arterial wall. Considering the location of the lesion, close to the brain, and its very small size, the procedure requires a combination of careful planning and excellent technical skills. An interactive and reliable simulation, adapted to the patient anatomy, would be an interesting tool for helping the interventional neuroradiologist plan and rehearse a coil embolization procedure. This paper describes an original method to perform interactive simulations of coil embolization and proposes a clinical metric to quantitatively measure how the first coil fills the aneurysm. The simulation relies on an accurate reconstruction of the aneurysm anatomy and a real-time model of the coil for which sliding and friction contacts are taken into account. Simulation results are compared to real embolization procedure and exhibit good adequacy

Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels

International audienceIntra-operative brain shift is a well-known phenomenon that describes non-rigid deformation of brain tissues due to gravity and loss of cerebrospinal fluid among other phenomena. This has a negative influence on surgical outcome that is often based on pre-operative planning where the brain shift is not considered. We present a novel brain-shift aware Augmented Reality method to align pre-operative 3D data onto the deformed brain surface viewed through a surgical microscope. We formulate our non-rigid registration as a Shape-from-Template problem. A pre-operative 3D wire-like deformable model is registered onto a single 2D image of the cortical vessels, which is automatically segmented. This 3D/2D registration drives the underlying brain structures, such as tumors, and compensates for the brain shift in sub-cortical regions. We evaluated our approach on simulated and real data composed of 6 patients. It achieved good quantitative and qualitative results making it suitable for neurosurgical guidance

Time-Action Analysis of Catheter Manipulation During Navigation Tasks in Bifurcations

Endovascular intervention is a form of minimally invasive intervention that allows catheters to be placed in practically any location of the vascular tree. However, to provide access to all these remote locations, an extensive array of catheters is needed. A specific catheter is choose based on experience, without any objective indication of its suitability during the actual procedure (Bakker, N. H., Tanase, D., Reekers, J. A., and Grimbergen, C. A., 2002, "Evaluation of Vascular and Interventional Procedures with Time-Action Analysis: A Pilot Study," J. Vasc. Intervent. Radiol., 13(5), pp. 483-488). The aim of this study is to evaluate several catheters using time-action analysis during a navigation task in bifurcations of various geometries. The relation between the geometry of bifurcations, the catheters, and the time taken to perform specific actions is investigated. Nine novices manipulated five widely used selective catheters with a 0.035" guidewire in a model. In the model, four bifurcations of various diameters and angles were selected. Each bifurcation was cannulated six times with two different yet suitable catheters. The participants had no direct vision of the model but navigated the instruments using the images that were captured by a camera and displayed on a screen. All images presented to the participant were recorded and used for detailed time-action analysis of the various actions to cannulate a branch (e.g., catheter or guidewire retracted, rotated, and advanced). On average, the participants needed 28.3 s to cannulate a branch. When the ratio between the diameter of the main and side branch was high, the average time per task increased significantly, as did the number of attempts to navigate into a branch. However, neither the choice between the two suitable catheters for each bifurcation, nor the angles of the bifurcation made a significant difference in navigation time. Time-action analysis enabled objective measurement of the time spent on various actions to cannulate a branch. The results revealed that most time was spent on retracting and rotating the catheter. This was comparable for all catheters and branches, showing that all the instruments were manipulated in a similar way and presented the same difficulties

Image-guided Simulation of Heterogeneous Tissue Deformation For Augmented Reality during Hepatic Surgery

International audienceThis paper presents a method for real-time augmentation of vas- cular network and tumors during minimally invasive liver surgery. Internal structures computed from pre-operative CT scans can be overlaid onto the laparoscopic view for surgery guidance. Com- pared to state-of-the-art methods, our method uses a real-time biomechanical model to compute a volumetric displacement field from partial three-dimensional liver surface motion. This permits to properly handle the motion of internal structures even in the case of anisotropic or heterogeneous tissues, as it is the case for the liver and many anatomical structures. Real-time augmentation results are presented on in vivo and ex vivo data and illustrate the benefits of such an approach for minimally invasive surgery

Constrained Stochastic State Estimation for 3D Shape Reconstruction of Catheters and Guidewires in Fluoroscopic Images

Minimally invasive fluoroscopy-based procedures are the gold standard for diagnosis and treatment of various pathologies of the cardiovascular system. This kind of procedures imply for the clinicians to infer the 3D shape of the device from 2D images, which is known to be an ill-posed problem. In this paper we present a method to reconstruct the 3D shape of the interventional device, with the aim of improving the navigation. The method combines a physics-based simulation with non-linear Bayesian filter. Whereas the physics-based model provides a prediction of the shape of the device navigating within the blood vessels (taking into account non-linear interactions between the catheter and the surrounding anatomy), an Unscented Kalman Filter is used to correct the navigation model using 2D image features as external observations. The proposed framework has been evaluated on both synthetic and real data, under different model parameterization, filter parameters tuning and external observations data-sets. Comparing the reconstructed 3D shape with a known ground truth, for the synthetic data-set, we obtained an average 3D Hausdorff distance of 0.07 ± 0.37 mm; the 3D distance at the tip equal to 0.021 ± 0.009 mm and the 3D mean distance at the distal segment of the catheter equal to 0.02 ± 0.008 mm. For the real data-set, the obtained average 3D Hausdorff Distance was of 0.95 ± 0.35 mm, the average 3D distance at the tip is equal to 0.7 ± 0.45 mm with an average 3D mean distance at the distal segment of 0.7 ± 0.46 mm. These results show the ability of our method to retrieve the 3D shape of the device, under a variety of filter parameterizations and challenging conditions: errors on the friction coefficient, ambiguous views and non-linear complex phenomena such as stick and slip motions

Motion Control of Cable-Driven Continuum Catheter Robot through Contacts

International audienceCatheter-based intervention plays an important role in minimally invasive surgery. For the closed-loop control of catheter robot through contacts, the loss of contact sensing along the entire catheter might result in task failure. To deal with this problem, we propose a decoupled motion control strategy which allows to control insertion and bending independently. We model the catheter robot and the contacts using the Finite Element Method. Then, we combine the simulated system and the real system for the closed-loop motion control. The control inputs are computed by solving a quadratic programming (QP) problem with a linear complementarity problem (LCP). A simplified method is proposed to solve this optimization problem by converting it into a standard QP problem. Using the proposed strategy, not only the control inputs but also the contact forces along the entire catheter can be computed without using force sensors. Finally, we validate the proposed methods using both simulation and experiments on a cable-driven continuum catheter robot for the real-time motion control through contacts

Constrained Stochastic State Estimation of Deformable 1D Objects: Application to Single-view 3D Reconstruction of Catheters with Radio-opaque Markers

International audienceMinimally invasive fluoroscopy-based procedures are the gold standard for diagnosis and treatment of various pathologies of the cardiovascular system. This kind of procedures imply for the clinicians to infer the 3D shape of the device from 2D images, which is known to be an ill-posed 10 problem. In this paper we present a method to reconstruct the 3D shape of the interventional device, with the aim of improving the navigation. The method combines a physics-based simulation with non-linear Bayesian filter. Whereas the physics-based model provides a prediction of the shape of the device navigating within the blood vessels (taking into account non-linear interactions be-15 tween the catheter and the surrounding anatomy), an Unscented Kalman Filter is used to correct the navigation model using 2D image features as external observations. The proposed framework has been evaluated on both synthetic and real data, under different model parameterizations, filter parameters tuning and external observations data-sets. Comparing the reconstructed 3D shape with a known ground truth, for the synthetic data-set, we obtained average values for 3D Hausdorff Distance of $0.81 ± 0.53 mm$, for the 3D mean distance at the segment of $0.37 ± 0.17$ mm and an average 3D tip error of $0.24 ± 0.13 mm$. For the real data-set,we obtained an average 3D Hausdorff distance of $1.74 ± 0.77 mm$, a average 3D mean distance at the distal segment of 0.91 ± 0.14 mm, an average 3D error on the tip of $0.53 ± 0.09 mm$. These results show the ability of our method to retrieve the 3D shape of the device, under a variety of filter parameterizations and challenging conditions: uncertainties on model parameterization, ambiguous views and non-linear complex phenomena such as stick and slip motions

Software toolkit for modeling, simulation and control of soft robots

International audienceThe technological differences between traditional robotics and soft robotics have an impact on all of the modeling tools generally in use, including direct kinematics and inverse models, Jacobians, and dynamics. Due to the lack of precise modeling and control methods for soft robots, the promising concepts of using such design for complex applications (medicine, assistance, domestic robotics...) cannot be practically implemented. This paper presents a first unified software framework dedicated to modeling, simulation and control of soft robots. The framework relies on continuum mechanics for modeling the robotic parts and boundary conditions like actuators or contacts using a unified representation based on Lagrange multipliers. It enables the digital robot to be simulated in its environment using a direct model. The model can also be inverted online using an optimization-based method which allows to control the physical robots in the task space. To demonstrate the effectiveness of the approach, we present various soft robots scenarios including ones where the robot is interacting with its environment. The software has been built on top of SOFA, an open-source framework for deformable online simulation and is available at https://project.inria.fr/softrobot

Interactive Training System for Interventional Electrocardiology Procedures

International audienceRecent progress in cardiac catheterization and devices has allowed the development of new therapies for severe cardiac diseases like arrhythmias and heart failure. The skills required for such interventions are very challenging to learn, and are typically acquired over several years. Virtual reality simulators may reduce this burden by allowing trainees to practice such procedures without risk to patients. In this paper, we propose the first training system dedicated to cardiac electrophysiology, including pacing and ablation procedures. Our framework involves the simulation of a catheter navigation that reproduces issues intrinsic to intra-cardiac catheterization, and a graphics processing unit (GPU)-based electrophysiological model. A multi-threading approach is proposed to compute both physical simulations (navigation and electrophysiology) asynchronously. With this method, we reach computational performances that account for user interactions in real-time. Based on a scenario of cardiac arrhythmia, we demonstrate the ability of the user-guided simulator to navigate inside vessels and cardiac cavities with a catheter and to reproduce an ablation procedure involving: extra-cellular potential measurements, endocardial surface reconstruction, electrophysiol-ogy mapping, radio-frequency (RF) ablation, as well as electrical stimulation. A clinical evaluation assessing the different aspects of the simulation is presented. This works is a step towards computerized medical learning curriculum