Accurate needle placement is critical to the success of needle-based interventions. Needle deflection due to tissue non-homogeneity and dynamic forces results in targeting error, potentially requiring repeated insertions. Real-time imaging enables closed-loop control of the needle during insertion, improving insertion accuracy. The needle localization algorithm proposed in this thesis models the needle as a parametric polynomial equation optimized to minimize beam bending energy relative to a set of observed needle coordinates. Simulated insertions using an MRI dataset show that the minimum bending energy model allows planning of subsequent imaging planes to capture the moving needle while estimating the shape of the needle with low error.

Surgical operations and processing of natural product require accurate presentation of the target area in order to achieve precise incisions. An excellent example is the deboning automation for chicken breast meat, for which the pose of the wing can greatly affect the cutting efficiency, ability to fix the structure, and product yield. In contrast to engineering objects, biological products present difficulties such as variation in size, shape, and material properties. Unlike past research, which generally found ways to emulate the manual cutting motion, this thesis investigates the effects of wing manipulation on incision tasks. The objective of this thesis is to develop an analytical model for characterizing the manipulation for pose presentation of a musculoskeletal structure for a specified incision. The manipulation model consists of joint kinematics, the mechanics of bio-materials, and a grasping mechanism to determine the joint pose and forces for a given manipulation trajectory. The model provides a basis for monitoring the cutting of bio-material via non-visual information, as well as for design of a compliant mechanism that can be used in an industrial automation application. To gain a better understanding, a wing manipulation test-bed consisting of a force/torque sensor at the point of wing manipulation has been developed. Two specific examples are investigated. The first is needle insertion into bio-materials, and the other is the shoulder cutting operation associated with chicken breast meat deboning. The effects of manipulation on needle insertion forces are used to quantify improvements in insertion point accuracy and required insertion force. Force signatures are also developed for insertion into the biomaterials located within the shoulder joint. The information gathered from both the manipulation model and needle insertion experiments provide a basis for successful implementation of the automation of the shoulder cut. While the experimentation presented in this thesis is developed in the context of poultry processing, which has immediate contributions as a tool that would facilitate the design of the automated cutting mechanisms in poultry industry, we expect that the development of the models will find a broad range of applications ranging from general meat processing, to surgical simulation, and physical therapy.

L’objectif de cette thèse est l’étude et le développement d’un outil de planification de trajectoires adaptatives guidée par robot afin d’assister l’insertion des aiguilles biseautées semi-rigides en procédures percutanées sous imagerie scanner ou IRM. L’approche est basée sur un nouveau modèle de la déflexion de l’aiguille qui permet une prédiction hors ligne des déformations de l’aiguille et une amélioration des performances d’insertion en ligne. Cette amélioration permet de compenser les incertitudes sur les connaissances de l’environnement et les approximations lors de la modélisation de l’aiguille. Les résultats des tests in vitro pour différentes plateformes robotiques ont confirmé la viabilité de la méthode proposée. / The goal of this thesis is the study and development of a tool for robot-driven adaptive needle insertion planning in order to assist percutaneous insertions of beveled semi-rigid needles guided by CT or MR images. The approach is based on a novel needle deflection prediction model that provides offline predictions and improve online the needle insertion performance. This improvement allows to compensate for environment uncertainties and approximations of needle-tissue interactions modeling. Results obtained from in vitro tests, using different robot platforms confirmed the viability of our method.

Ces travaux de thèse apportent plusieurs contributions à la conception de dispositifs d'assistance robotisés pour la réalisation de procédures d'insertion d'aiguille sous imageur à rayons X. Partant de la tâche de positionnement et d'orientation d'une aiguille, plusieurs architectures mécaniques inédites à quatre degrés de liberté ont été proposées. Un algorithme de synthèse dimensionnelle a été conçu pour calculer les paramètres structuraux de ces mécanismes en étudiant leurs singularités, tout en tenant compte des contraintes antagonistes de compacité du système, de capacité d'actionnement et de taille d'espace de travail. Une décomposition modulaire du dispositif d'assistance a permis de proposer des solutions pour un outil dédié à l'insertion d'aiguille avec retour d'effort. Cet outil comporte un dispositif d'insertion, un système de préhension d'aiguille et un capteur d'effort spécifique pour le retour d'effort. / This thesis focuses on finding solutions for the design and the technological bottlenecks involving development of a slave robotic assistant for needle insertion procedures. The needed functionalities for the slave device were sought to be achieved by adopting a modular approach. This required the design and the development of different devices which satisfy targeted functionalities. A study of needle positioning devices was carried out which led to the synthesis of novel mechanisms for the task of needle axis translation and the needle axis orientation. A novel dimensional synthesis algorithm was developed to calculate the structural parameters of these mechanism while studying their singularities and considering the antagonistic constraints of system compactness, actuation torques and workspace size. The modular decomposition also allowed to offer solutions for an insertion tool dedicated to needle insertion with force feedback. This insertion tool consists of a device for inserting the needle, a device for grasping the needle and a force sensor for force feedback.

Les techniques d'insertion d'aiguille font partie des interventions chirurgicales les plus courantes. L'efficacité de ces interventions dépend fortement de la précision du positionnement des aiguilles dans un emplacement cible à l'intérieur du corps du patient. L'objectif principal dans cette thèse est de développer un système robotique autonome, capable d'insérer une aiguille flexible dans une structure déformable le long d'une trajectoire prédéfinie. L’originalité de ce travail se trouve dans l’utilisation de simulations inverses par éléments finis (EF) dans la boucle de contrôle du robot pour prédire la déformation des structures. La particularité de ce travail est que pendant l’insertion, les modèles EF sont continuellement recalés (étape corrective) grâce à l’information extraite d’un système d’imagerie peropératoire. Cette étape permet de contrôler l’erreur des modèles par rapport aux structures réelles et ainsi éviter qu'ils divergent. Une seconde étape (étape de prédiction) permet, à partir de la position corrigée, d’anticiper le comportement de structures déformables, en se reposant uniquement sur les prédictions des modèles biomécaniques. Ceci permet ainsi d’anticiper la commande du robot pour compenser les déplacements des tissus avant même le déplacement de l’aiguille. Expérimentalement, nous avions utilisé notre approche pour contrôler un robot réel afin d'insérer une aiguille flexible dans une mousse déformable le long d'une trajectoire (virtuelle) prédéfinie. Nous avons proposé une formulation basée sur des contraintes permettant le calcul d'étapes prédictives dans l'espace de contraintes offrant ainsi un temps d'insertion total compatible avec les applications cliniques. Nous avons également proposé un système de réalité augmentée pour la chirurgie du foie ouverte. La méthode est basée sur un recalage initial semi-automatique et un algorithme de suivi peropératoire basé sur des marqueurs (3D) optiques. Nous avons démontré l'applicabilité de cette approche en salle d'opération lors d'une chirurgie de résection hépatique. Les résultats obtenus au cours de ce travail de thèse ont conduit à trois publications (deux IROS et un ICRA) dans les conférences internationales puis à un journal (Transactions on Robotics) en cours de révision. / Needle-based interventions are among the least invasive surgical approaches to access deep internal structures into organs' volumes without damaging surrounding tissues. Unlike traditional open surgery, needle-based approaches only affect a localized area around the needle, reducing this way the occurrence of traumas and risks of complications \cite{Cowan2011}. Many surgical procedures rely on needles in nowadays clinical routines (biopsies, local anesthesia, blood sampling, prostate brachytherapy, vertebroplasty ...). Radiofrequency ablation (RFA) is an example of percutaneous procedure that uses heat at the tip of a needle to destroy cancer cells. Such alternative treatments may open new solutions for unrespectable tumors or metastasis (concerns about the age of the patient, the extent or localization of the disease). However, contrary to what one may think, needle-based approaches can be an exceedingly complex intervention. Indeed, the effectiveness of the treatment is highly dependent on the accuracy of the needle positioning (about a few millimeters) which can be particularly challenging when needles are manipulated from outside the patient with intra-operative images (X-ray, fluoroscopy or ultrasound ...) offering poor visibility of internal structures. Human factors, organs' deformations, needle deflection and intraoperative imaging modalities limitations can be causes of needle misplacement and rise significantly the technical level necessary to master these surgical acts. The use of surgical robots has revolutionized the way surgeons approach minimally invasive surgery. Robots have the potential to overcome several limitations coming from the human factor: for instance by filtering operator tremors, scaling the motion of the user or adding new degrees of freedom at the tip of instruments. A rapidly growing number of surgical robots has been developed and applied to a large panel of surgical applications \cite{Troccaz2012}. Yet, an important difficulty for needle-based procedures lies in the fact that both soft tissues and needles tend to deform as the insertion proceeds in a way that cannot be described with geometrical approaches. Standard solutions address the problem of the deformation extracting a set of features from per-operative images (also called \textit{visual servoing)} and locally adjust the pose/motion of the robot to compensate for deformations \cite{Hutchinson1996}. [...]To overcome these limitations, we introduce a numerical method allowing performing inverse Finite Element simulations in real-time. We show that it can be used to control an articulated robot while considering deformations of structures during needle insertion. Our approach relies on a forward FE simulation of a needle insertion (involving complex non-linear phenomena such as friction, puncture and needle constraints).[...]

<p>Subcutaneous injection through devices such as autoinjectors is a preferred delivery method for wide array of pharmaceuticals such as monoclonal antibodies. Needle insertion during drug delivery involves large deformation, damage, and fracture of the skin tissue and affects drug transport and uptake. Yet, our understanding of needle insertion biomechanics is limited, but is crucially important to create autoinjectors that lead to the least amount of pain, penetrate the skin to a desired depth, produce small lesions that minimize back flow of drug, and operate robustly even given the variability in the skin mechanics among individuals. Computational models of needle insertion lends itself as an excellent avenue for studying the biomechanics of injector- skin interactions and for proposing better device designs. This work is focused on introducing a comprehensive computational modeling framework for optimizing needle insertion by autoinjector devices, while addressing limitations in experimental data and constitutive modeling of damage and fracture mechanisms in skin</p>