Personalized modeling for real-time pressure ulcer prevention in sitting posture.

Ischial pressure ulcer is an important risk for every paraplegic person and a major public health issue. Pressure ulcers appear following excessive compression of buttock's soft tissues by bony structures, and particularly in ischial and sacral bones. Current prevention techniques are mainly based on daily skin inspection to spot red patches or injuries. Nevertheless, most pressure ulcers occur internally and are difficult to detect early. Estimating internal strains within soft tissues could help to evaluate the risk of pressure ulcer. A subject-specific biomechanical model could be used to assess internal strains from measured skin surface pressures. However, a realistic 3D non-linear Finite Element buttock model, with different layers of tissue materials for skin, fat and muscles, requires somewhere between minutes and hours to compute, therefore forbidding its use in a real-time daily prevention context. In this article, we propose to optimize these computations by using a reduced order modeling technique (ROM) based on proper orthogonal decompositions of the pressure and strain fields coupled with a machine learning method. ROM allows strains to be evaluated inside the model interactively (i.e. in less than a second) for any pressure field measured below the buttocks. In our case, with only 19 modes of variation of pressure patterns, an error divergence of one percent is observed compared to the full scale simulation for evaluating the strain field. This reduced model could therefore be the first step towards interactive pressure ulcer prevention in a daily set-up.

Biomechanical modeling to prevent ischial pressure ulcers.

With 300,000 paraplegic persons only in France, ischial pressure ulcers represent a major public health issue. They result from the buttocks׳ soft tissues compression by the bony prominences. Unfortunately, the current clinical techniques, with - in the best case - embedded pressure sensor mats, are insufficient to prevent them because most are due to high internal strains which can occur even with low pressures at the skin surface. Therefore, improving prevention requires using a biomechanical model to estimate internal strains from skin surface pressures. However, the buttocks׳ soft tissues׳ stiffness is still unknown. This paper provides a stiffness sensitivity analysis using a finite element model. Different layers with distinct Neo Hookean materials simulate the skin, fat and muscles. With Young moduli in the range [100-500 kPa], [25-35 kPa], and [80-140 kPa] for the skin, fat, and muscles, respectively, maximum internal strains reach realistic 50 to 60% values. The fat and muscle stiffnesses have an important influence on the strain variations, while skin stiffness is less influent. Simulating different sitting postures and changing the muscle thickness also result in a variation in the internal strains.

Using CamiTK for rapid prototyping of interactive computer assisted medical intervention applications.

Computer Assisted Medical Intervention (CAMI hereafter) is a complex multi-disciplinary field. CAMI research requires the collaboration of experts in several fields as diverse as medicine, computer science, mathematics, instrumentation, signal processing, mechanics, modeling, automatics, optics, etc. CamiTK is a modular framework that helps researchers and clinicians to collaborate together in order to prototype CAMI applications by regrouping the knowledge and expertise from each discipline. It is an open-source, cross-platform generic and modular tool written in C++ which can handle medical images, surgical navigation, biomedicals simulations and robot control. This paper presents the Computer Assisted Medical Intervention ToolKit (CamiTK) and how it is used in various applications in our research team.

Simulation of endovascular guidewire behaviour and experimental validation.

Guidewire manipulation is a core skill in endovascular interventional radiology procedures. Simulation-based training offers a valuable alternative for mastering these skills, but requires a faithful replication of complex guidewire behaviour inside the vasculature. This paper presents the integration of real flexural modulus (FM) measurements into our guidewire model that mimics the flexibility of standard guidewires. The variation of FM along the length of each wire was determined for seven commonly used guidewires using a three-point bending test for the main body and a two-point bending test for the flexible end. Guidewire FM values were then attributed to seven different models, each formed by a series of particles connected by links of variable FM and replicating the flexible end shape. The FM integration was done through a trial and error process matching real FM to virtual bending coefficient. This mass-spring representation captures the required range of behaviour and enables accurate deformation within virtual vasculature.

Guidewire and catheter behavioural simulation.

Guidewire and catheter manipulation is a core skill in endovascular interventional radiology. It is usually acquired in an apprenticeship on patients, but this training is expensive and risky. Simulation offers an efficient alternative for core skills training, though the instrument complex behaviour requires accurate replication. This paper reviews the mass-spring model used to simulate seven guidewires and three catheters, and the matching with their real world counterparts by tuning our model's bending coefficient, which allows replication of the instrument flexibility. This coefficient was matched through computed tomography imaging of a vascular phantom in which each instrument was inserted and manipulated. With an average distance of 2.27 mm (standard deviation: 1.54) between real and virtual instruments, our representation showed realistic behaviour.

Segmentation of 3D vasculatures for interventional radiology simulation.

Training in interventional radiology is slowly shifting towards simulation which allows the repetition of many interventions without putting the patient at risk. Accurate segmentation of anatomical structures is a prerequisite of realistic surgical simulation. Therefore, our aim is to develop a generic approach to provide fast and precise segmentation of various virtual anatomies covering a wide range of pathology, directly from patient CT/MRA images. This paper presents a segmentation framework including two segmentation methods: region model based level set segmentation and hierarchical segmentation. We compare them to an open source application ITK-SNAP which provides similar approaches. The subjective human influence such as inconsistent inter-observer errors and aliasing artifacts etc. are analysed. The proposed segmentation techniques have been successfully applied to create a database of various anatomies with different pathologies, which is used in computer-based simulation for interventional radiology training.

Segmentation and reconstruction of vascular structures for 3D real-time simulation.

We propose a technique to obtain accurate and smooth surfaces of patient specific vascular structures, using two steps: segmentation and reconstruction. The first step provides accurate and smooth centerlines of the vessels, together with cross section orientations and cross section fitting. The initial centerlines are obtained from a homotopic thinning of the vessels segmented using a level set method. In addition to circle fitting, an iterative scheme fitting ellipses to the cross sections and correcting the centerline positions is proposed, leading to a strong improvement of the cross section orientations and of the location of the centerlines. The second step consists of reconstructing the surface based on this data, by generating a set of topologically preserved quadrilateral patches of branching tubular structures. It improves Felkel's meshing method (Felkel et al., 2004) by: allowing a vessel to have multiple parents and children, reducing undersampling artifacts, and adapting the cross section distribution. Experiments, on phantom and real datasets, show that the proposed technique reaches a good balance in terms of smoothness, number of triangles, and distance error. This technique can be applied in interventional radiology simulations, virtual endoscopy and in reconstruction of smooth and accurate three-dimensional models for use in simulation.

Real-time Seldinger technique simulation in complex vascular models.

PURPOSE: Commercial interventional radiology vascular simulators emulate instrument navigation and device deployment, though none supports the Seldinger technique, which provides initial access to the vascular tree. This paper presents a novel virtual environment for teaching this core skill. METHODS: Our simulator combines two haptic devices: vessel puncture with a virtual needle and catheter and guidewire manipulation. The simulation software displays the instrument interactions with the vessels. Instruments are modelled using a mass-spring approximation, while efficient collision detection and collision response allow real time interactions. RESULTS: Experienced interventional radiologists evaluated the haptic components of our simulator as realistic and accurate. The vessel puncture haptic device proposes a first prototype to simulate the Seldinger technique. Our simulator presents realistic instrument behaviour when compared to real instruments in a vascular phantom. CONCLUSION: This paper presents the first simulator to train the Seldinger technique. The preliminary results confirm its utility for interventional radiology training.

CT scan merging to enhance navigation in interventional radiology simulation.

We present a method to merge two distinct CT scans acquired from different patients such that the second scan can supplement the first when it is missing necessary supporting anatomy. The aim is to provide vascular intervention simulations with full body anatomy. Often, patient CT scans are confined to a localised region so that the patient is not exposed to more radiation than necessary and to increase scanner throughput. Unfortunately, this localised scanning region may be limiting for some applications where surrounding anatomy may be required and where approximate supporting anatomy is acceptable. The resulting merged scan can enhance body navigation simulations with X-ray rendering by providing a complete anatomical reference which may be useful in training and rehearsal. An example of the use of our CT scan merging technique in the field of interventional radiology is described.

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.

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).

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.

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.

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.

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.

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 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.