53 research outputs found

    Variational methods for modeling and simulation of tool-tissue interaction

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    Ph.DDOCTOR OF PHILOSOPH

    Real-time simulation of surgery by Proper Generalized Decomposition techniques

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    La simulación quirúrgica por ordenador en tiempo real se ha convertido en una alternativa muy atractiva a los simuladores quirúrgicos tradicionales. Entre otras ventajas, los simuladores por ordenador consiguen ahorros importantes de tiempo y de costes de mantenimiento, y permiten que los estudiantes practiquen sus habilidades quirúrgicas en un entorno seguro tantas veces como sea necesario. Sin embargo, a pesar de las capacidades de los ordenadores actuales, la cirugía computacional sigue siendo un campo de investigación exigente. Uno de sus mayores retos es la alta velocidad a la que se tienen que resolver complejos problemas de mecánica de medios continuos para que los interfaces hápticos puedan proporcionar un sentido del tacto realista (en general, se necesitan velocidades de respuesta de 500-1000 Hz).Esta tesis presenta algunos métodos numéricos novedosos para la simulación interactiva de dos procedimientos quirúrgicos habituales: el corte y el rasgado (o desgarro) de tejidos blandos. El marco común de los métodos presentados es el uso de la Descomposición Propia Generalizada (PGD en inglés) para la generación de vademécums computacionales, esto es, metasoluciones generales de problemas paramétricos de altas dimensiones que se pueden evaluar a velocidades de respuesta compatibles con entornos hápticos.En el caso del corte, los vademécums computacionales se utilizan de forma conjunta con técnicas basadas en XFEM, mientras que la carga de cálculo se distribuye entre una etapa off-line (previa a la ejecución interactiva) y otra on-line (en tiempo de ejecución). Durante la fase off-line, para el órgano en cuestión se precalculan tanto un vademécum computacional para cualquier posición de una carga, como los desplazamientos producidos por un conjunto de cortes. Así, durante la etapa on-line, los resultados precalculados se combinan de la forma más adecuada para obtener en tiempo real la respuesta a las acciones dirigidas por el usuario. En cuanto al rasgado, a partir de una ecuación paramétrica basada en mecánica del daño continuo, se obtiene un vademécum computacional. La complejidad del modelo se reduce mediante técnicas de Descomposición Ortogonal Propia (POD en inglés), y el vademécum se incorpora a una formulación incremental explícita que se puede interpretar como una especie de integrador temporal.A modo de ejemplo, el método para el corte se aplica a la simulación de un procedimiento quirúrgico refractivo de la córnea conocido como queratotomía radial, mientras que el método para el rasgado se centra en la simulación de la colecistectomía laparoscópica (la extirpación de la vesícula biliar mediante laparoscopia). En ambos casos, los métodos implementados ofrecen excelentes resultados en términos de velocidades de respuesta y producen simulaciones muy realistas desde los puntos de vista visual y háptico.The real-time computer-based simulation of surgery has proven to be an appealing alternative to traditional surgical simulators. Amongst other advantages, computer-based simulators provide considerable savings on time and maintenance costs, and allow trainees to practice their surgical skills in a safe environment as often as necessary. However, in spite of the current computer capabilities, computational surgery continues to be a challenging field of research. One of its major issues is the high speed at which complex problems in continuum mechanics have to be solved so that haptic interfaces can render a realistic sense of touch (generally, feedback rates of 500–1 000 Hz are required). This thesis introduces some novel numerical methods for the interactive simulation of two usual surgical procedures: cutting and tearing of soft tissues. The common framework of the presented methods is the use of the Proper Generalised Decomposition (PGD) for the generation of computational vademecums, i. e. general meta-solutions of parametric high-dimensional problems that can be evaluated at feedback rates compatible with haptic environments. In the case of cutting, computational vademecums are used jointly with XFEM-based techniques, and the computing workload is distributed into an off-line and an on-line stage. During the off-line stage, both a computational vademecum for any position of a load and the displacements produced by a set of cuts are pre-computed for the organ under consideration. Thus, during the on-line stage, the pre-computed results are properly combined together to obtain in real-time the response to the actions driven by the user. Concerning tearing, a computational vademecum is obtained from a parametric equation based on continuum damage mechanics. The complexity of the model is reduced by Proper Orthogonal Decomposition (POD) techniques, and the vademecum is incorporated into an explicit incremental formulation that can be viewed as a sort of time integrator. By way of example, the cutting method is applied to the simulation of a corneal refractive surgical procedure known as radial keratotomy, whereas the tearing method focuses on the simulation of laparoscopic cholecystectomy (i. e. the removal of the gallbladder). In both cases, the implemented methods offer excellent performances in terms of feedback rates, and produce.<br /

    Haptic simulation of tissue tearing during surgery

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    We present a method for the real-time, interactive simulation of tissue tearing during laparoscopic surgery. The method is designed to work at haptic feedback rates (i.e., around 1kHz). Tissue tearing is simulated under the general framework of continuum damage mechanics. The problem is stated as a general, multidimensional parametric problem, which is solved by means of Proper Generalized Decomposition (PGD) methods. One of the main novelties is the reduction of history-dependent problems, such as damage mechanics, by resorting to an approach in which a reduced-order field of initial damage values is considered as a parameter of the formulation. We focus on the laparoscopic cholecystectomy procedure as a general example of the performance of the method

    Semiautomated 3D liver segmentation using computed tomography and magnetic resonance imaging

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    Le foie est un organe vital ayant une capacité de régénération exceptionnelle et un rôle crucial dans le fonctionnement de l’organisme. L’évaluation du volume du foie est un outil important pouvant être utilisé comme marqueur biologique de sévérité de maladies hépatiques. La volumétrie du foie est indiquée avant les hépatectomies majeures, l’embolisation de la veine porte et la transplantation. La méthode la plus répandue sur la base d'examens de tomodensitométrie (TDM) et d'imagerie par résonance magnétique (IRM) consiste à délimiter le contour du foie sur plusieurs coupes consécutives, un processus appelé la «segmentation». Nous présentons la conception et la stratégie de validation pour une méthode de segmentation semi-automatisée développée à notre institution. Notre méthode représente une approche basée sur un modèle utilisant l’interpolation variationnelle de forme ainsi que l’optimisation de maillages de Laplace. La méthode a été conçue afin d’être compatible avec la TDM ainsi que l' IRM. Nous avons évalué la répétabilité, la fiabilité ainsi que l’efficacité de notre méthode semi-automatisée de segmentation avec deux études transversales conçues rétrospectivement. Les résultats de nos études de validation suggèrent que la méthode de segmentation confère une fiabilité et répétabilité comparables à la segmentation manuelle. De plus, cette méthode diminue de façon significative le temps d’interaction, la rendant ainsi adaptée à la pratique clinique courante. D’autres études pourraient incorporer la volumétrie afin de déterminer des marqueurs biologiques de maladie hépatique basés sur le volume tels que la présence de stéatose, de fer, ou encore la mesure de fibrose par unité de volume.The liver is a vital abdominal organ known for its remarkable regenerative capacity and fundamental role in organism viability. Assessment of liver volume is an important tool which physicians use as a biomarker of disease severity. Liver volumetry is clinically indicated prior to major hepatectomy, portal vein embolization and transplantation. The most popular method to determine liver volume from computed tomography (CT) and magnetic resonance imaging (MRI) examinations involves contouring the liver on consecutive imaging slices, a process called “segmentation”. Segmentation can be performed either manually or in an automated fashion. We present the design concept and validation strategy for an innovative semiautomated liver segmentation method developed at our institution. Our method represents a model-based approach using variational shape interpolation and Laplacian mesh optimization techniques. It is independent of training data, requires limited user interactions and is robust to a variety of pathological cases. Further, it was designed for compatibility with both CT and MRI examinations. We evaluated the repeatability, agreement and efficiency of our semiautomated method in two retrospective cross-sectional studies. The results of our validation studies suggest that semiautomated liver segmentation can provide strong agreement and repeatability when compared to manual segmentation. Further, segmentation automation significantly shortens interaction time, thus making it suitable for daily clinical practice. Future studies may incorporate liver volumetry to determine volume-averaged biomarkers of liver disease, such as such as fat, iron or fibrosis measurements per unit volume. Segmental volumetry could also be assessed based on subsegmentation of vascular anatomy

    Automatic registration of 3D models to laparoscopic video images for guidance during liver surgery

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    Laparoscopic liver interventions offer significant advantages over open surgery, such as less pain and trauma, and shorter recovery time for the patient. However, they also bring challenges for the surgeons such as the lack of tactile feedback, limited field of view and occluded anatomy. Augmented reality (AR) can potentially help during laparoscopic liver interventions by displaying sub-surface structures (such as tumours or vasculature). The initial registration between the 3D model extracted from the CT scan and the laparoscopic video feed is essential for an AR system which should be efficient, robust, intuitive to use and with minimal disruption to the surgical procedure. Several challenges of registration methods in laparoscopic interventions include the deformation of the liver due to gas insufflation in the abdomen, partial visibility of the organ and lack of prominent geometrical or texture-wise landmarks. These challenges are discussed in detail and an overview of the state of the art is provided. This research project aims to provide the tools to move towards a completely automatic registration. Firstly, the importance of pre-operative planning is discussed along with the characteristics of the liver that can be used in order to constrain a registration method. Secondly, maximising the amount of information obtained before the surgery, a semi-automatic surface based method is proposed to recover the initial rigid registration irrespective of the position of the shapes. Finally, a fully automatic 3D-2D rigid global registration is proposed which estimates a global alignment of the pre-operative 3D model using a single intra-operative image. Moving towards incorporating the different liver contours can help constrain the registration, especially for partial surfaces. Having a robust, efficient AR system which requires no manual interaction from the surgeon will aid in the translation of such approaches to the clinics

    A Computational Image-Based Guidance System for Precision Laparoscopy

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    This dissertation presents our progress toward the goal of building a computational image-based guidance system for precision laparoscopy; in particular, laparoscopic liver resection. As we aim to keep our working goal as simple as possible, we have focused on the most important questions of laparoscopy - predicting the new location of tumors and resection plane after a liver maneuver during surgery. Our approach was to build a mechanical model of the organ based on pre-operative images and register it to intra-operative data. We proposed several practical and cost-effective methods to obtain the intra-operative data in the real procedure. We integrated all of them into a framework on which we could develop new techniques without redoing everything. To test the system, we did an experiment with a porcine liver in a controlled setup: a wooden lever was used to elevate a part of the liver to access the posterior of the liver. We were able to confirm that our model has decent accuracy for tumor location (approximately 2 mm error) and resection plane (1% difference in remaining liver volume after resection). However, the overall shape of the liver and the fiducial markers still left a lot to be desired. For further corrections to the model, we also developed an algorithm to reconstruct the 3D surface of the liver utilizing Smart Trocars, a new surgical instrument recognition system. The algorithm had been verified by an experiment on a plastic model using the laparoscopic camera as a mean to obtain surface images. This method had millimetric accuracy provided the angle between two endoscope views is not too small. In an effort to transit our research from porcine livers to human livers, in-vivo experiments had been conducted on cadavers. From those studies, we found a new method that used a high-frequency ventilator to eliminate respiratory motion. The framework showed the potential to work on real organs in clinical settings. Hence, the studies on cadavers needed to be continued to improve those techniques and complete the guidance system.Computer Science, Department o

    Computational Anatomy for Multi-Organ Analysis in Medical Imaging: A Review

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    The medical image analysis field has traditionally been focused on the development of organ-, and disease-specific methods. Recently, the interest in the development of more 20 comprehensive computational anatomical models has grown, leading to the creation of multi-organ models. Multi-organ approaches, unlike traditional organ-specific strategies, incorporate inter-organ relations into the model, thus leading to a more accurate representation of the complex human anatomy. Inter-organ relations are not only spatial, but also functional and physiological. Over the years, the strategies 25 proposed to efficiently model multi-organ structures have evolved from the simple global modeling, to more sophisticated approaches such as sequential, hierarchical, or machine learning-based models. In this paper, we present a review of the state of the art on multi-organ analysis and associated computation anatomy methodology. The manuscript follows a methodology-based classification of the different techniques 30 available for the analysis of multi-organs and multi-anatomical structures, from techniques using point distribution models to the most recent deep learning-based approaches. With more than 300 papers included in this review, we reflect on the trends and challenges of the field of computational anatomy, the particularities of each anatomical region, and the potential of multi-organ analysis to increase the impact of 35 medical imaging applications on the future of healthcare.Comment: Paper under revie

    Development of an online progressive mathematical model of needle deflection for application to robotic-assisted percutaneous interventions

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    A highly flexible multipart needle is under development in the Mechatronics in Medicine Laboratory at Imperial College, with the aim to achieve multi-curvature trajectories inside biological soft tissue, such as to avoid obstacles during surgery. Currently, there is no dedicated software or analytical methodology for the analysis of the needle’s behaviour during the insertion process, which is instead described empirically on the basis of experimental trials on synthetic tissue phantoms. This analysis is crucial for needle and insertion trajectory design purposes. It is proposed that a real-time, progressive, mathematical model of the needle deflection during insertion be developed. This model can serve three purposes, namely, offline needle and trajectory design in a forward solution of the model, when the loads acting on needle from the substrate are known; online, real-time identification of the loads that act on the needle in a reverse solution, when the deflections at discrete points along the needle length are known; and the development of a sensitivity matrix, which enables the calculation of the corrective loads that are required to drive the needle back on track, if any deviations occur away from a predefined trajectory. Previously developed mathematical models of needle deflection inside soft tissue are limited to small deflection and linear strain. In some cases, identical tip path and body shape after full insertion of the needle are assumed. Also, the axial load acting on the needle is either ignored or is calculated from empirical formulae, while its inclusion would render the model nonlinear even for small deflection cases. These nonlinearities are a result of the effects of the axial and transverse forces at the tip being co-dependent, restricting the calculation of the independent effects of each on the needle’s deflection. As such, a model with small deflection assumptions incorporating tip axial forces can be called “quasi-nonlinear” and a methodology is proposed here to tackle the identification of such axial force in the linear range. During large deflection of the needle, discrepancies between the shape of the needle after the insertion and its tip path, computed during the insertion, also significantly increase, causing errors in a model based on the assumption that they are the same. Some of the models developed to date have also been dependent on existing or experimentally derived material models of soft tissue developed offline, which is inefficient for surgical applications, where the biological soft tissue can change radically and experimentation on the patient is limited. Conversely, a model is proposed in this thesis which, when solved inversely, provides an estimate for the contact stiffness of the substrate in a real-time manner. The study and the proposed model and techniques involved are limited to two dimensional projections of the needle movements, but can be easily extended to the 3-dimensional case. Results which demonstrate the accuracy and validity of the models developed are provided on the basis of simulations and via experimental trials of a multi-part 2D steering needle in gelatine.Open Acces
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