Biomedical subjects

Vincent Luboz

Publications and source records attributed to Vincent Luboz.

8 recordsLinked to original sources

PubMed2006

Smooth vasculature reconstruction with circular and elliptic cross sections.

This paper presents a method to segment and reconstruct vascular structure from patient volumetric scan. First, a semi-automatic segmentation phase leads to the vessels centerlines and the estimated circular or elliptic cross section description. Then, the skeleton data are used by the reconstruction phase to generate the three dimensional vascular surface. This structured surface is able to handle interactive visualization, real-time and robust physics-based modeling. The accuracy and consistency of our technique are evaluated on a vascular phantom as well as two clinical data sets. Experiments show that the proposed technique reaches a good balance in terms of mesh smoothness, compactness, and accuracy, where elliptic cross section estimation induces lower error.

Blood Vessels↗

PubMed2005

A segmentation and reconstruction technique for 3D vascular structures.

In the context of stroke therapy simulation, a method for the segmentation and reconstruction of human vasculature is presented and evaluated. Based on CTA scans, semi-automatic tools have been developed to reduce dataset noise, to segment using active contours, to extract the skeleton, to estimate the vessel radii and to reconstruct the associated surface. The robustness and accuracy of our technique are evaluated on a vascular phantom scanned in different orientations. The reconstructed surface is compared to a surface generated by marching cubes followed by decimation and smoothing. Experiments show that the proposed technique reaches a good balance in terms of smoothness, number of triangles, and distance error. The reconstructed surface is suitable for real-time simulation, interactive navigation and visualization.

Algorithms↗

PubMed2005

Computer assisted planning and orbital surgery: patient-related prediction of osteotomy size in proptosis reduction.

BACKGROUND: Proptosis is characterized by a protrusion of the eyeball due to an increase of the orbital tissue volume. To recover a normal eyeball positioning, the most frequent surgical technique consists in the osteotomy of orbital walls combined with the manual loading on the eyeball. Only a rough clinical rule is currently available for the surgeons but it is useless for this technique. The first biomechanical model dealing with proptosis reduction, validated in one patient, has been previously proposed by the authors. METHODS: This paper proposes a rule improving the pre-operative planning of the osteotomy size in proptosis reduction. Patient-related poroelastic finite element models combined with sensitivity studies were used to propose two clinical rules to improve the pre-operative planning of proptosis reduction. This poroelastic model was run on 12 patients. Sensitivity studies permitted to establish relationships between the osteotomy size, the patient-related orbital volume, the decompressed tissue volume and the eyeball backward displacement. FINDINGS: The eyeball displacement and the osteotomy size were non-linearly related: an exponential rule has been proposed. The patient-related orbital volume showed a significant influence: a bi-quadratic analytical equation liking the osteotomy size, the orbital volume and the targeted eyeball protrusion has been established. INTERPRETATION: Two process rules derived from patient-related biomechanical FE models have been proposed for the proptosis reduction planning. The implementation of the process rules into a clinical setting is easy since only a sagittal radiography is required. The osteotomy size can be monitored using optical guided instruments.

Adult↗

PubMed2005

Orbital and maxillofacial computer aided surgery: patient-specific finite element models to predict surgical outcomes.

This paper addresses an important issue raised for the clinical relevance of Computer-Assisted Surgical applications, namely the methodology used to automatically build patient-specific finite element (FE) models of anatomical structures. From this perspective, a method is proposed, based on a technique called the mesh-matching method, followed by a process that corrects mesh irregularities. The mesh-matching algorithm generates patient-specific volume meshes from an existing generic model. The mesh regularization process is based on the Jacobian matrix transform related to the FE reference element and the current element. This method for generating patient-specific FE models is first applied to computer-assisted maxillofacial surgery, and more precisely, to the FE elastic modelling of patient facial soft tissues. For each patient, the planned bone osteotomies (mandible, maxilla, chin) are used as boundary conditions to deform the FE face model, in order to predict the aesthetic outcome of the surgery. Seven FE patient-specific models were successfully generated by our method. For one patient, the prediction of the FE model is qualitatively compared with the patient's post-operative appearance, measured from a computer tomography scan. Then, our methodology is applied to computer-assisted orbital surgery. It is, therefore, evaluated for the generation of 11 patient-specific FE poroelastic models of the orbital soft tissues. These models are used to predict the consequences of the surgical decompression of the orbit. More precisely, an average law is extrapolated from the simulations carried out for each patient model. This law links the size of the osteotomy (i.e. the surgical gesture) and the backward displacement of the eyeball (the consequence of the surgical gesture).

Algorithms↗

PubMed2005

New approaches to computer-based interventional neuroradiology training.

For over 20 years, interventional methods have substantially improved the outcomes of patients with cardiovascular disease. However, these procedures require an intricate combination of visual and tactile feedback and extensive training periods. In this paper, a prototype of endovascular therapy training system is presented. A set of core simulation components applicable to most vascular procedures has been designed and integrated into a real-time high-fidelity interventional neuroradiology training system for the prompt treatment of ischemic stroke. We believe it will improve the quality of training and the speed of learning without putting patients at risk.

Computer Simulation↗

PubMed2004

Prediction of tissue decompression in orbital surgery.

OBJECTIVE: A method to predict the relationships between decompressed volume of orbital soft tissues, backward displacement of globe after osteotomy, and force exerted by the surgeon, was proposed to improve surgery planning in exophthalmia reduction. DESIGN: A geometric model and a poroelastic finite element model were developed, based on computed tomography scan data. BACKGROUND: The exophthalmia is characterized by a protrusion of the eyeball. Surgery consists in an osteotomy of the orbit walls to decompress the orbital content. A few clinical observations ruling on an almost linear relationship between globe backward displacement and tissue-decompressed volume are described in the literature. METHODS: Fast prediction of decompressed volume is derived from the geometric model: a sphere in interaction with a cone. Besides, a poroelastic finite element model involving morphology, material properties of orbital components and surgical gesture was implemented. RESULTS: The geometric model provided a better decompression volume estimation than the finite element model. Besides, the finite element model permitted to quantify the backward displacement, the surgical gesture and the stiffness of the orbital content. CONCLUSIONS: The preliminary results obtained for one patient, in accordance with the clinical literature, were relatively satisfying. An efficient aid for location and size of osteotomies was derived and seemed to be able to help in the surgery planning.

Decompression, Surgical↗

PubMed2003

Patient specific finite element model of the face soft tissues for computer-assisted maxillofacial surgery.

This paper addresses the prediction of face soft tissue deformations resulting from bone repositioning in maxillofacial surgery. A generic 3D Finite Element model of the face soft tissues was developed. Face muscles are defined in the mesh as embedded structures, with different mechanical properties (transverse isotropy, stiffness depending on muscle contraction). Simulations of face deformations under muscle actions can thus be performed. In the context of maxillofacial surgery, this generic soft-tissue model is automatically conformed to patient morphology by elastic registration, using skin and skull surfaces segmented from a CT scan. Some elements of the patient mesh could be geometrically distorted during the registration, which disables Finite Element analysis. Irregular elements are thus detected and automatically regularized. This semi-automatic patient model generation is robust, fast and easy to use. Therefore it seems compatible with clinical use. Six patient models were successfully built, and simulations of soft tissue deformations resulting from bone displacements performed on two patient models. Both the adequation of the models to the patient morphologies and the simulations of post-operative aspects were qualitatively validated by five surgeons. Their conclusions are that the models fit the morphologies of the patients, and that the predicted soft tissue modifications are coherent with what they would expect.

Biomechanical Phenomena↗

PubMed2002

Biomechanical models to simulate consequences of maxillofacial surgery.

This paper presents the biomechanical finite element models that have been developed in the framework of the computer-assisted maxillofacial surgery. After a brief overview of the continuous elastic modelling method, two models are introduced and their use for computer-assisted applications discussed. The first model deals with orthognathic surgery and aims at predicting the facial consequences of maxillary and mandibular osteotomies. For this, a generic three-dimensional model of the face is automatically adapted to the morphology of the patient by the mean of elastic registration. Qualitative simulations of the consequences of an osteotomy of the mandible can thus be provided. The second model addresses the Sleep Apnoea Syndrome. Its aim is to develop a complete modelling of the interaction between airflow and upper airways walls during breathing. Dynamical simulations of the interaction during a respiratory cycle are computed and compared with observed phenomena.

Biomechanical Phenomena↗