Expert-validated CSF segmentation of MNI atlas enhances accuracy of virtual glioma growth patterns.

Biomathematical modeling of glioma growth has been developed to optimize treatments delivery and to evaluate their efficacy. Simulations currently make use of anatomical knowledge from standard MRI atlases. For example, cerebrospinal fluid (CSF) spaces are obtained by automatic thresholding of the MNI atlas, leading to an approximate representation of real anatomy. To correct such inaccuracies, an expert-revised CSF segmentation map of the MNI atlas was built. Several virtual glioma growth patterns of different locations were generated, with and without using the expert-revised version of the MNI atlas. The adequacy between virtual and radiologically observed growth patterns was clearly higher when simulations were based on the expert-revised atlas. This work emphasizes the need for close collaboration between clinicians and researchers in the field of brain tumor modeling.

A topologically faithful, tissue-guided, spatially varying meshing strategy for computing patient-specific head models for endoscopic pituitary surgery simulation.

This paper presents a method for tessellating tissue boundaries and their interiors, given as input a map consisting of relevant tissue classes of the head, in order to produce anatomical models for finite-element-based simulation of endoscopic pituitary surgery. Our surface meshing method is based on the simplex model, which is initialized by duality from the topologically accurate results of the Marching Cubes algorithm, and which affords explicit control over mesh scale, while using tissue information to adhere to relevant boundaries. Our mesh scale strategy is spatially varying, based on the distance to a central point or linearized surgical path. The tetrahedralization stage also features a spatially varying mesh scale, consistent with that of the surface mesh.

SOFA--an open source framework for medical simulation.

SOFA is a new open source framework primarily targeted at medical simulation research. Based on an advanced software architecture, it allows to (1) create complex and evolving simulations by combining new algorithms with algorithms already included in SOFA; (2) modify most parameters of the simulation--deformable behavior, surface representation, solver, constraints, collision algorithm, etc.--by simply editing an XML file; (3) build complex models from simpler ones using a scene-graph description; (4) efficiently simulate the dynamics of interacting objects using abstract equation solvers; and (5) reuse and easily compare a variety of available methods. In this paper we highlight the key concepts of the SOFA architecture and illustrate its potential through a series of examples.

An electromechanical model of the heart for image analysis and simulation.

This paper presents a new three-dimensional electromechanical model of the two cardiac ventricles designed both for the simulation of their electrical and mechanical activity, and for the segmentation of time series of medical images. First, we present the volumetric biomechanical models built. Then the transmembrane potential propagation is simulated, based on FitzHugh-Nagumo reaction-diffusion equations. The myocardium contraction is modeled through a constitutive law including an electromechanical coupling. Simulation of a cardiac cycle, with boundary conditions representing blood pressure and volume constraints, leads to the correct estimation of global and local parameters of the cardiac function. This model enables the introduction of pathologies and the simulation of electrophysiology interventions. Moreover, it can be used for cardiac image analysis. A new proactive deformable model of the heart is introduced to segment the two ventricles in time series of cardiac images. Preliminary results indicate that this proactive model, which integrates a priori knowledge on the cardiac anatomy and on its dynamical behavior, can improve the accuracy and robustness of the extraction of functional parameters from cardiac images even in the presence of noisy or sparse data. Such a model also allows the simulation of cardiovascular pathologies in order to test therapy strategies and to plan interventions.

A topologically faithful, tissue-guided, spatially varying meshing strategy for the computation of patient-specific head models for endoscopic pituitary surgery simulation.

This paper presents a method for tessellating tissue boundaries and their interiors, given as input a tissue map consisting of relevant classes of the head, in order to produce anatomical models for finite element-based simulation of endoscopic pituitary surgery. Our surface meshing method is based on the simplex model, which is initialized by duality from the topologically accurate results of the Marching Cubes algorithm, and which features explicit control over mesh scale, while using tissue information to adhere to relevant boundaries. Our mesh scale strategy is spatially varying, based on the distance to a central point or linearized surgical path. The tetrahedralization stage also features a spatially varying mesh scale, consistent with that of the surface mesh.

Optimal electrode diameter in relation to volume of the cochlea.

The volume of the cochlea is a key parameter for electrode-array design. Indeed, it constrains the diameter of the electrode-array for low-traumatic positioning in the scala timpani. The present report shows a model of scala timpani volume extraction from temporal bones images in order to estimate a maximum diameter of an electrode-array. Nine temporal bones were used, and passed to high-resolution computed tomography scan. Using image-processing techniques, scala timpani were extracted from images, and cross-section areas were estimated along cochlear turns. Cochlear implant electrode-array was fitted in these cross-sections. Results show that the electrode-array diameter is small enough to fit in the scala timpani, however the diameter is restricted at the apical part.

Removing tetrahedra from manifold tetrahedralisation: application to real-time surgical simulation.

This paper proposes an efficient method for removing tetrahedra from a tetrahedral mesh while keeping its manifold property. We first define precisely the notion of manifold tetrahedral mesh and stress its relevance in the context of real-time surgery simulation. We then provide a method for removing a tetrahedron that complies with the manifold definition. This removal may require in some cases the removal of neighboring tetrahedra. After providing an exhaustive description of the tetrahedron removal algorithm, its efficiency is evaluated for different mesh configurations. This algorithm is currently used in the context of real-time surgery simulation where the action of an ultrasonic lancet can be simulated by the removal of small set of tetrahedra from a tetrahedralisation.

Simulation of cardiac pathologies using an electromechanical biventricular model and XMR interventional imaging.

Simulating cardiac electromechanical activity is of great interest for a better understanding of pathologies and for therapy planning. Design and validation of such models is difficult due to the lack of clinical data. XMR systems are a new type of interventional facility in which patients can be rapidly transferred between X-ray and MR systems. Our goal is to design and validate an electromechanical model of the myocardium using XMR imaging. The proposed model is computationally fast and uses clinically observable parameters. We present the integration of anatomy, electrophysiology, and motion from patient data. Pathologies are introduced in the model and simulations are compared to measured data. Initial qualitative comparison on the two clinical cases presented is encouraging. Once fully validated, these models will make it possible to simulate different interventional strategies.

A Pipeline for the Generation of Realistic 3D Synthetic Echocardiographic Sequences: Methodology and Open-Access Database.

Quantification of cardiac deformation and strain with 3D ultrasound takes considerable research efforts. Nevertheless, a widespread use of these techniques in clinical practice is still held back due to the lack of a solid verification process to quantify and compare performance. In this context, the use of fully synthetic sequences has become an established tool for initial in silico evaluation. Nevertheless, the realism of existing simulation techniques is still too limited to represent reliable benchmarking data. Moreover, the fact that different centers typically make use of in-house developed simulation pipelines makes a fair comparison difficult. In this context, this paper introduces a novel pipeline for the generation of synthetic 3D cardiac ultrasound image sequences. State-of-the art solutions in the fields of electromechanical modeling and ultrasound simulation are combined within an original framework that exploits a real ultrasound recording to learn and simulate realistic speckle textures. The simulated images show typical artifacts that make motion tracking in ultrasound challenging. The ground-truth displacement field is available voxelwise and is fully controlled by the electromechanical model. By progressively modifying mechanical and ultrasound parameters, the sensitivity of 3D strain algorithms to pathology and image properties can be evaluated. The proposed pipeline is used to generate an initial library of 8 sequences including healthy and pathological cases, which is made freely accessible to the research community via our project web-page.

Deformable biomechanical models: application to 4D cardiac image analysis.

This article describes a methodology for creating a generic volumetric biomechanical model from different image modalities and segmenting time series of medical images using this model. The construction of such a generic model consists of three stages: geometric meshing, non-rigid deformation of the mesh in images of various modalities, and image-to-mesh information mapping through rasterization. The non-rigid deformation stage, which relies on a combination of global and local deformations, can then be used to segment time series of images, e.g. cine MRI or gated SPECT cardiac images. We believe that this type of deformable biomechanical model can play an important role in the extraction of useful quantitative local parameters of cardiac function. The biomechanical model of the heart will be coupled with an electrical model of another collaborative project in order to simulate and analyze a larger class of pathologies.

A fully three-dimensional method for facial reconstruction based on deformable models.

Two facial models corresponding to two deceased subjects have been manually created and the two corresponding skulls have been dissected and skeletonized. These pairs of skull/ facial data have been scanned with a CT scanner, and the computed geometric three-dimensional models of both skulls and facial tissue have been built. One set of skull/facial data will be used as a reference set whereas the second set is used as ground truth for validating our method. After a semi-automatic face-skull registration, we apply an original computing global parametric transformation T that turns the reference skull into the skull to be reconstructed. This algorithm is based upon salient lines of the skull called crest lines: more precisely the crest lines of the first skull are matched to the crest lines of the second skull by an iterative closest point algorithm. Then we apply this algorithm to the reference face to obtain the "unknown" face to be reconstructed. The reliability and difficulties of this original technique are then discussed.

Fully automatic anatomical, pathological, and functional segmentation from CT scans for hepatic surgery.

OBJECTIVE: To improve the planning of hepatic surgery, we have developed a fully automatic anatomical, pathological, and functional segmentation of the liver derived from a spiral CT scan. MATERIALS AND METHODS: From a 2 mm-thick enhanced spiral CT scan, the first stage automatically delineates skin, bones, lungs, kidneys, and spleen by combining the use of thresholding, mathematical morphology, and distance maps. Next, a reference 3D model is immersed in the image and automatically deformed to the liver contours. Then an automatic Gaussian fitting on the imaging histogram estimates the intensities of parenchyma, vessels, and lesions. This first result is next improved through an original topological and geometrical analysis, providing an automatic delineation of lesions and veins. Finally, a topological and geometrical analysis based on medical knowledge provides hepatic functional information that is invisible in medical imaging: portal vein labeling and hepatic anatomical segmentation according to the Couinaud classification. RESULTS: Clinical validation performed on more than 30 patients shows that delineation of anatomical structures by this method is often more sensitive and more specific than manual delineation by a radiologist. CONCLUSION: This study describes the methodology used to create the automatic segmentation of the liver with delineation of important anatomical, pathological, and functional structures from a routine CT scan. Using the methods proposed in this study, we have confirmed the accuracy and utility of the creation of a 3D liver model compared with the conventional reading of the CT scan by a radiologist. This work may allow improved preoperative planning of hepatic surgery by more precisely delineating liver pathology and its relationship to normal hepatic structures. In the future, this data may be integrated with computer-assisted surgery and thus represents a first step towards the development of an augmented-reality surgical system.

Efficient linear elastic models of soft tissues for real-time surgery simulation.

In this paper, we describe the basic components of a surgery simulator prototype developed at INRIA. We present two physical models which are well suited for surgery simulation. These models are based on linear elasticity theory and finite elements modeling. The former model can deforme large tetrahedral meshes in real-time but does not allow any topological changes. On the contrary, the latter biomechanical model can simulate the cutting and tearing of soft tissue but must have a limited number of vertices to run in real-time. We propose a method for combining these two approaches into a hybrid model which may allow real time deformations and cuttings of large enough anatomical structures.

Geometric and physical representations for a simulator of hepatic surgery.

Despite the large interest in simulators of minimally invasive surgery, it is still unclear to what extent simulators can achieve the task of training medical students in surgical procedures. The answer to that question is certainly linked to the realism of displays and force-feedback systems and to the level of interaction provided by the computer system. In this paper, we describe the virtual environment for anatomical and surgical training on the liver, currently under construction at INRIA. We specifically address the problems of geometric representation and physical modeling and their impact on the two aforementioned problems: realism and real-time interaction.

An automatic virtual patient reconstruction from CT-scans for hepatic surgical planning.

UNLABELLED: PROBLEM/BACKGROUND: In order to help hepatic surgical planning we perfected automatic 3D reconstruction of patients from conventional CT-scan, and interactive visualization and virtual resection tools. TOOLS AND METHODS: From a conventional abdominal CT-scan, we have developed several methods allowing the automatic 3D reconstruction of skin, bones, kidneys, lung, liver, hepatic lesions, and vessels. These methods are based on deformable modeling or thresholding algorithms followed by the application of mathematical morphological operators. From these anatomical and pathological models, we have developed a new framework for translating anatomical knowledge into geometrical and topological constraints. More precisely, our approach allows to automatically delineate the hepatic and portal veins but also to label the portal vein and finally to build an anatomical segmentation of the liver based on Couinaud definition which is currently used by surgeons all over the world. Finally, we have developed a user friendly interface for the 3D visualization of anatomical and pathological structures, the accurate evaluation of volumes and distances and for the virtual hepatic resection along a user-defined cutting plane. RESULTS: A validation study on a 30 patients database gives 2 mm of precision for liver delineation and less than 1 mm for all other anatomical and pathological structures delineation. An in vivo validation performed during surgery also showed that anatomical segmentation is more precise than the delineation performed by a surgeon based on external landmarks. This surgery planning system has been routinely used by our medical partner, and this has resulted in an improvement of the planning and performance of hepatic surgery procedures. CONCLUSION: We have developed new tools for hepatic surgical planning allowing a better surgery through an automatic delineation and visualization of anatomical and pathological structures. These tools represent a first step towards the development of an augmented reality system combined with computer assisted tele-robotical surgery.

Improved myocardial motion estimation combining tissue Doppler and B-mode echocardiographic images.

We propose a technique for myocardial motion estimation based on image registration using both B-mode echocardiographic images and tissue Doppler sequences acquired interleaved. The velocity field is modeled continuously using B-splines and the spatiotemporal transform is constrained to be diffeomorphic. Images before scan conversion are used to improve the accuracy of the estimation. The similarity measure includes a model of the speckle pattern distribution of B-mode images. It also penalizes the disagreement between tissue Doppler velocities and the estimated velocity field. Registration accuracy is evaluated and compared to other alternatives using a realistic synthetic dataset, obtaining mean displacement errors of about 1 mm. Finally, the method is demonstrated on data acquired from six volunteers, both at rest and during exercise. Robustness is tested against low image quality and fast heart rates during exercise. Results show that our method provides a robust motion estimate in these situations.

Preliminary specificity study of the Bestel-Clément-Sorine electromechanical model of the heart using parameter calibration from medical images.

Patient-specific cardiac modelling can help in understanding pathophysiology and predict therapy effects. This requires the personalization of the geometry, kinematics, electrophysiology and mechanics. We use the Bestel-Clément-Sorine (BCS) electromechanical model of the heart, which provides reasonable accuracy with a reduced parameter number compared to the available clinical data at the organ level. We propose a preliminary specificity study to determine the relevant global parameters able to differentiate the pathological cases from the healthy controls. To this end, a calibration algorithm on global measurements is developed. This calibration method was tested successfully on 6 volunteers and 2 heart failure cases and enabled to tune up to 7 out of the 14 necessary parameters of the BCS model, from the volume and pressure curves. This specificity study confirmed domain-knowledge that the relaxation rate is impaired in post-myocardial infarction heart failure and the myocardial stiffness is increased in dilated cardiomyopathy heart failures.

3D strain assessment in ultrasound (Straus): a synthetic comparison of five tracking methodologies.

This paper evaluates five 3D ultrasound tracking algorithms regarding their ability to quantify abnormal deformation in timing or amplitude. A synthetic database of B-mode image sequences modeling healthy, ischemic and dyssynchrony cases was generated for that purpose. This database is made publicly available to the community. It combines recent advances in electromechanical and ultrasound modeling. For modeling heart mechanics, the Bestel-Clement-Sorine electromechanical model was applied to a realistic geometry. For ultrasound modeling, we applied a fast simulation technique to produce realistic images on a set of scatterers moving according to the electromechanical simulation result. Tracking and strain accuracies were computed and compared for all evaluated algorithms. For tracking, all methods were estimating myocardial displacements with an error below 1 mm on the ischemic sequences. The introduction of a dilated geometry was found to have a significant impact on accuracy. Regarding strain, all methods were able to recover timing differences between segments, as well as low strain values. On all cases, radial strain was found to have a low accuracy in comparison to longitudinal and circumferential components.

Understanding the mechanisms amenable to CRT response: from pre-operative multimodal image data to patient-specific computational models.

This manuscript describes our recent developments towards better understanding of the mechanisms amenable to cardiac resynchronization therapy response. We report the results from a full multimodal dataset corresponding to eight patients from the euHeart project. The datasets include echocardiography, MRI and electrophysiological studies. We investigate two aspects. The first one focuses on pre-operative multimodal image data. From 2D echocardiography and 3D tagged MRI images, we compute atlas based dyssynchrony indices. We complement these indices with presence and extent of scar tissue and correlate them with CRT response. The second one focuses on computational models. We use pre-operative imaging to generate a patient-specific computational model. We show results of a fully automatic personalized electromechanical simulation. By case-per-case discussion of the results, we highlight the potential and key issues of this multimodal pipeline for the understanding of the mechanisms of CRT response and a better patient selection.

Personalization of a cardiac electromechanical model using reduced order unscented Kalman filtering from regional volumes.

Patient-specific cardiac modeling can help in understanding pathophysiology and therapy planning. However it requires to combine functional and anatomical data in order to build accurate models and to personalize the model geometry, kinematics, electrophysiology and mechanics. Personalizing the electromechanical coupling from medical images is a challenging task. We use the Bestel-Clément-Sorine (BCS) electromechanical model of the heart, which provides reasonable accuracy with a reasonable number of parameters (14 for each ventricle) compared to the available clinical data at the organ level. We propose a personalization strategy from cine MRI data in two steps. We first estimate global parameters with an automatic calibration algorithm based on the Unscented Transform which allows to initialize the parameters while matching the volume and pressure curves. In a second step we locally personalize the contractilities of all AHA (American Heart Association) zones of the left ventricle using the reduced order unscented Kalman filtering on Regional Volumes. This personalization strategy was validated synthetically and tested successfully on eight healthy and three pathological cases.