• Introduction to Surgical Robotics by P. Poignet
  • Abstract: In order to give an overview of the domains covered by Medical robotics, I will first present some R&D projects in assistive technologies and rehabilitation robotics, before focusing on surgical robotics. Then, I will analyze some classical surgical functions ("machining", constrained manipulation, constrained targeting, surface tracking, microsurgery), from the viewpoint of the engineer, in order to illustrate the limitations of the manual procedures. This analysis will serve to justify the introduction of robotics in surgery. The added-values and limitations of computer & robot aided surgery will be discussed. A state of the art will present the main prototypes and commercial systems. Finally, I will list some future directions of R&D and technical challenges.
• In Technical I with M. Tavakoli: Collaborative Image-guided Closed-loop Control of Steerable Needles
  • Abstract: This lecture will demonstrate the potentials of robotics technologies for improving healthcare by enhancing needle-based surgeries and therapies. In permanent implant brachytherapy, needles loaded with radioactive seeds are used to reach planned locations in the prostate, where the seeds are deployed. Accurate seed placement is a key factor that influences the effectiveness of the procedure. However, current manual techniques can place seeds with an accuracy of only about 5 mm, which is a substantial error given the average prostate size. We will discuss mechatronic technologies for precisely steering a needle towards its intended location using feedback control. Closed-loop control of needle in tissue is challenging due to measurement errors, unmodelled dynamics created by tissue heterogeneity and motion of targets within the tissue, only to name a few. We will review recent progress made in this area including modelling needle-tissue interaction, sensing needle deflection, and controlling the needle trajectory.
• In Modelling & Simulation I with C. Duriez: Mechanical modeling of soft solids for robotics
  • Abstract: In this class, we will study the mechanical modeling of soft solids, in particular soft tissues for surgical simulation and deformable matter for soft robotics. In both case, some state of the art methods allow to obtain a good tradeoff between precision and computation time. The ultimate objective being to be able to use the deformable models for the education of surgeons and for planning and the control of surgical robots. The presentation will also include the open challenges of the field. The class will be followed by a practice session, during which the students will be asked to model, simulate and control a soft robotic manipulator.
• In Technical VI with C. Bergeles: Modelling, design, and control of flexible robots
  • Abstract: Continuum robots can navigate anatomical pathways to reach deep seated pathology locations. Their flexible structure makes them ideal intraluminal navigation and operation in confined spaces. Critically, however, their flexibility comes at the expense of manipulability, force capability, workspace, intuitiveness and operational safety. This talk will focus on a specific class of continuum robots, the concentric tube robot. I will discuss modelling of those robots, also visiting the fields of machine learning for kinematics and inverse kinematics derivation. Patient- and surgery- specific design processes for optimal operational capability of the robots will be presented. The talk will conclude with new control algorithms that consider the inherent non-holonomic constraints of these elongated slender continuum robots, showing how mechanical instabilities and control “local minima” can be avoided.
• In Future trends in surgical robotics II with P. Fiorini: Autonomy in Robotic Surgery: motivations, risks and technologies.
  • Abstract: It is rather unlikely that, in our lifetime, we will see a fully autonomous robot performing an unassisted surgery. However, it is very possible that some form of autonomous assistance to the surgical process will be introduced to robotic surgery in the near future. Thus, we need to analyze the ethical, legal and practical implications of autonomous surgical robots, discuss what parts of autonomy are feasible with realistic technologies, and what could be their real benefits to patients and surgeons. In this talk I will present our current research in cognitive architectures for autonomous task execution and show the results of learning and executing simple training task, environment modelling and developing novel sensorized instruments.
• In Technical V with G. Hattab: Introduction to surgical AR.
  • Abstract: The use of Augmented Reality (AR) for the visualization of 3D biomedical image data is possible thanks to a growing number of hardware and software solutions. As technical challenges and barriers to development diminish, it is increasingly important to take into account the specific capacities and constraints of the surgeon's perceptual and cognitive systems. This introduction allows the formulation of task-specific questions while presenting four aspects for surgical AR. First, the basic concepts and definitions of augmented reality. Second, a commonly used paradigm that addresses legitimate problems in a surgical context (e.g. accuracy of registration). Third, a set of visualization guidelines to improve the quality of the surgeon's perception. Fourth and last, a practical framework that evaluates the importance of visual encodings and renderings for surgical AR.
• In Medical II with J. Hubert: Surgeon, bed-side surgeon and team training in robotic surgery. The Example of Urology.
  • Abstract: Unlike the name of the world's leading robotics company ("Intuitive") suggests, the efficient and secure use of a robot requires an incompressible learning time as for any new sophisticated tool. This learning involves two steps for the surgeon: - Technical mastery of the instrument, essential whatever the level of the surgeon who wishes to start robotics. This initial technical training requires several days to automatically master all the robot's controls. - Knowledge of the different steps of each surgical procedure. This procedural training is faster in experienced surgeons who are familiar with the surgeries they have already performed in open or laparoscopic approaches. As is shown in the robotic literature, the learning curve has been done on the patient during years; few centers had the same approach as Nancy in 2000, when pioneer surgeons had worked for 1 year on inanimate model, then on pig model before starting on human beings. These on the patient learning practices are no longer eligible. This was the subject of clear recommendations from the French HAS (High Authority for Health): "never the first time on a patient". Development of surgical simulators in 2008 (an already standard training technique in aeronautics and other fields) has transformed robotic pedagogy, as several companies (Mimic, Simbionix ...) are developing these instruments. These simulators have become essential in the initial technical training programs, and allow to accelerate the mastery of the machine. Procedural training, which is more surgery oriented, still needs to be structured and to take benefit from more appropriate simulation techniques. With experience it became apparent that the surgeon's assistant has a much more important role in robotics than in any other type of surgeries and that a specific team training was mandatory. Here again an answer is brought by simulation with the development of specific simulators such as the Mimic XTT. If surgical robots have achieved a degree of maturity, the surgeons’ training still requires to be better structured. Simulators have important progress to make in order to offer exercises whose quality is equivalent to what exists for video games.
• In Technical II with P. Jannin: Surgical Skill Analysis and Modeling.
  • Abstract: The There is an important trend in Surgical robotics in strong collaboration between surgeon and robots. The surgical quality and success strongly depend on surgeon’s skills. It is well admitted that skills are not technical ones only. Non-technical skills or socio-cognitive processes are also of importance. Whatever the degree of collaboration and the level of autonomy, surgical robotics needs analysis and models of these skills. In this presentation, I will present different studies and methodologies developed for such purposes, with a special focus on procedural skills. I will illustrate by examples covering different aspects of surgical skills from technical to non-technical ones, such as the quantitative evaluation of surgical technical and procedural skills, the development of a surgical simulation system for training procedural skills based on an interactive and collaborative virtual reality environment and the study of neurosurgical non-technical skills.
• In Future trends in surgical robotics I with A. Menciassi: Minimally invasive surgery enabled by wireless solutions.
  • Abstract: Minimally invasive surgery requires miniature driving and actuation solutions in order to reduce the trauma when incisions to the patient skin are produced. In the continuous trend to look for actuation and therapy solutions which can be really minimally invasive, magnetic field and ultrasounds play a major role. In this lecture, the speaker will illustrate how magnetic fields can be used for driving, anchoring and triggering some devices or phenomena in remote areas of the human body. Thus the speaker will describe how ultrasounds, once focused with an acoustic lens, can be also used for therapy and how ultrasound forces and effects can be used for several minimally invasive therapy applications.
• In Technical IV with L. Soler: Augmented Surgery: From AR to AI.
  • Abstract: TA new surgery area is rising: the Augmented Surgery. It aims to augment surgeon vision, surgeon gesture and surgeon decision, introducing the Augmented Surgery concept. Augmented surgical vision is based on 3D/4D patient-specific modelling. The first step consists in the Visible Patient online 3D modelling of organs and pathologies from a patient’s medical image (CT or MRI). Preoperatively, the resulting virtual clone can be used to plan and simulate the surgical procedure thanks to user-friendly mobile software. Intraoperative assistance will then consist in Augmented Reality that provides a kind of virtual transparency of the patient. Main limits of this technique are linked to organ movement and deformation between the preoperative image and the intraoperative position and shape. To overcome this limit, the introduction of 3D-medical imaging systems in the Operating Room is then mandatory. The intraoperative medical image is registered with the preoperative image in order to correct organ deformations. By adding the laparoscopic image analysis, it is then possible to compute in real-time the precise location and shape of organs and pathology. This information can be combined with a robotic system to develop the next generation of automated robots linked to Artificial Intelligence. A.I. will so not only assist surgeons in therapy definition, but also control and assist them intraoperatively just like a pilot during a flight.
• In Registration I with J. Troccaz: Image and Robot registration in Computer-Assisted Medical Interventions.
  • Abstract: The general problem of registration consists in determining the geometrical relationship between different reference frames where some information is represented. In the context of computer-assisted surgery, this term is most often used when fusing imaging data coming from multi-modality sensors and acquired in different places or at different times. When a robot is introduced, this device also needs to be registered to the data. Indeed, in order to enable the robot to execute a pre-defined plan, or to assist the surgeon in this execution, the relationship between patient data where the planning is defined and the robot reference frame has to be determined. In this talk we will first present this general context and introduce basics of image registration. In a second part, we will focus on the specific robot registration issue and we will describe how it has been solved for different categories of systems. Several examples are detailed and discussed