Automatic Computation of Electrodes Trajectory for Deep Brain Stimulation

International audienceIn this paper, we propose an approach to find the optimal position of an electrode, for assisting surgeons in planning Deep Brain Stimulation. We first show how we formalized the rules governing this surgical procedure into geometric constraints. Then we explain our method, using a formal geometric solver, and a template built from 15 MRIs, used to propose a space of possible solutions and the optimal one. We show our results for the retrospective study on 8 implantations from 4 patients, and compare them with the trajectory of the electrode that was actually implanted. The results show a slight difference with the reference trajectories, with a better evaluation for our proposition

Brain-shift aware risk map for Deep Brain Stimulation Planning

International audienceIn Deep Brain Stimulation surgery, the efficiency of the procedure heavily relies on the accuracy of the placement of the stimulating electrode. Meanwhile, the effectiveness of the placement is difficult due to brain shifts occurring during and after the procedure. We propose an approach to overcome the limitations of current planning software that ignores brain shift. In particular, we consider the motion of vascular structures in order to reduce risks of dissecting a vessel during the procedure. Facing the difficulty to produce an exact brain shift prediction, we propose to build a brain shift aware risk map which embeds the vascular motion risk. This risk map is extrapolated using simulation from clinical studies that provide statistics on the displacement of anatomical landmarks during the procedure. Risk maps can be directly integrated into automatic path planning algorithms to better predict optimal electrode trajectories. The method relies on a physics-based simulation that takes into account brain deformation, electrode placement, cerebrospinal fluid, and vascular motion. The goal is to reproduce the spread of brain shift situations that are noted in clinical studies. Preliminary results show that it is possible to compute safe electrode trajectories even in case of brain shift and yet optimal regarding the placement within the targeted area

GPU-based 3D iceball modeling for fast cryoablation simulation and planning

Purpose The elimination of abdominal tumors by percutaneous cryoablation has been shown to be an effective and less invasive alternative to open surgery. Cryoablation destroys malignant cells by freezing them with one or more cryoprobes inserted into the tumor through the skin. Alternating cycles of freezing and thawing produce an enveloping iceball that causes the tumor necrosis. Planning such a procedure is difficult and time-consuming, as it is necessary to plan the number and cryoprobe locations and predict the iceball shape which is also influenced by the presence of heating sources, e.g., major blood vessels and warm saline solution, injected to protect surrounding structures from the cold. Methods This paper describes a method for fast GPU-based iceball modeling based on the simulation of thermal propagation in the tissue. Our algorithm solves the heat equation within a cube around the cryoprobes tips and accounts for the presence of heating sources around the iceball. Results Experimental results of two studies have been obtained: an ex vivo warm gel setup and simulation on five retrospective patient cases of kidney tumors cryoablation with various levels of complexity of the vascular structure and warm saline solution around the tumor tissue. The experiments have been conducted in various conditions of cube size and algorithm implementations. Results show that it is possible to obtain an accurate result within seconds. Conclusion The promising results indicate that our method yields accurate iceball shape predictions in a short time and is suitable for surgical planning

Preoperative trajectory planning for percutaneous procedures in deformable environments

International audienceIn image-guided percutaneous interventions, a precise planning of the needle path is a key factor to a successful intervention. In this paper we propose a novel method for computing a patient-specific optimal path for such interventions, accounting for both the deformation of the needle and soft tissues due to the insertion of the needle in the body. To achieve this objective, we propose an optimization method for estimating preoperatively a curved trajectory allowing to reach a target even in the case of tissue motion and needle bending. Needle insertions are simulated and regarded as evaluations of the objective function by the iterative planning process. In order to test the planning algorithm, it is coupled with a fast needle insertion simulation involving a flexible needle model and soft tissue finite element modeling, and experimented on the use-case of thermal ablation of liver tumors. Our algorithm has been successfully tested on twelve datasets of patient-specific geometries. Fast convergence to the actual optimal solution has been shown. This method is designed to be adapted to a wide range of percutaneous interventions

Helping the Designer in Solution Selection: Applications in CAD

Abstract. In CAD, symbolic geometric solvers allow to solve constraint systems, given under the form of a sketch and a set of constraints, by computing a symbolic construction plan describing how to build the required figure. But a construction plan does not usually define a unique figure, and the selection of the expected figure remains an important topic. This paper expose three methods, automatic or interactive, to help the designer in the exploration of the solution space. These methods guide him towards the expected solution, by basing the construction on the observation of the sketch. A set of examples from a large range of application domains illustrate the different methods.

Comparison of interactive and automatic segmentation of stereoelectroencephalography electrodes on computed tomography post-operative images: preliminary results

Stereoelectroencephalography is a surgical procedure used in the treatment of pharmacoresistant epilepsy. Multiple electrodes are inserted in the patient's brain in order to record the electrical activity and detect the epileptogenic zone at the source of the seizures. An accurate localisation of their contacts on post-operative images is a crucial step to interpret the recorded signals and achieve a successful resection afterwards. In this Letter, the authors propose interactive and automatic methods to help the surgeon with the segmentation of the electrodes and their contacts. Then, they present a preliminary comparison of the methods in terms of accuracy and processing time through experimental measurements performed by two users, and discuss these first results. The final purpose of this work is to assist the neurosurgeons and neurologists in the contacts localisation procedure, make it faster, more precise and less tedious

Dynamic path planning for percutaneous procedures in the abdomen during free breathing

International audiencePercutaneous procedures are increasingly used for the treatment of tumors in abdominal structures. Most of the time, these procedures are planned based on static preoperative images, and do not take into account any motions, while breathing control is not always applicable. In this paper, we present a method to automatically adjust the planned path in real time according to the breathing. First, an estimation of the organs motions during breathing is performed during an observation phase. Then we propose an approach named Real Time Intelligent Trajectory (RTIT) that consists in finding the most appropriate moments to push the needle along the initially planned path, based on the motions and the distance to surrounding organs. We also propose a second approach called Real Time Straight Trajectory (RTST) that examines sixteen scenarios of needle insertion at constant speed, starting at eight different moments of the breathing cycle with two different speeds. We evaluated our methods on six 3D models of abdominal structures built using image datasets and a real-time simulation of breathing movements. We measured the deviation from the initial path, the target positioning error, and the distance of the actual path to risky structures. The path proposed by RTIT approach is compared to the best path proposed by RTST. We show that the RTIT approach is relevant and adapted to breathing movements. The modification of the path remains minimal while collisions with obstacles are avoided. This study on simulations constitutes a first step towards intelligent robotic insertion under real-time image guidance