CE33 - Interaction, Robotique – Intelligence artificielle



SuPErvised Robotic surgeRY <br />- application to radiofrequency ablation of liver tumors -

Robotization and automation of radiofrequency ablation procedures for liver tumors

Liver cancer is the sixth most common cancer. With more than 40,000 new cases each year, it is the third leading cause of cancer death in the world. The standard treatment for primary liver tumors and metastases is open surgery with significant associated risk factors. Alternative treatments exist for unresectable liver metastases. Radiofrequency ablation (RFA) is a percutaneous procedure that uses heat dissipated at the tip of the needle to destroy cancer cells. RFA was developed to access internal organs and deep structures while reducing the risk of infections, bleeding and postoperative pain. However, contrary to what one might think, the RFA approach can be an extremely complex intervention. Indeed, the effectiveness of the treatment strongly depends on the positioning of the needle, which can be particularly difficult with these long needles, manipulated from the outside using intraoperative images (fluoroscopy or ultrasound) offering limited visibility of internal structures. <br /> <br />In this project, we want to develop new solutions for the control of medical robots interacting with soft tissues. Our goal is to develop a robotic, autonomous, but supervised system capable of interacting with deformable structures. This work is motivated by recent advances in the field of medical simulation which has reached a level of realism sufficient for teaching and surgical training, even for visual aids and augmented reality during surgery. We believe these models can provide essential information for anticipating and predicting deformations in order to automatize the robotic control of the needle insertion.

The problem of automatic needle insertion consists in finding the movements of the robot manipulating the needle in order to position its tip, while taking into account the deformation of the trajectory and the tumor identified initially. These deformities are caused by tissue/needle interactions and the physiological movements of the patient. Once the needle is inserted into the tissue, the robot can no longer be viewed independently of its environment, which must then be integrated into the robotic control. The originality of our approach lies in the use of inverse finite element (FE) simulations in the robot control loop to predict the deformation of structures.

During the insertion, FE models are continuously registered (corrective step) using information extracted from an intraoperative imaging system. This step makes it possible to control the error of the models compared to the real structures. A second step (prediction step) makes it possible to anticipate the behavior of deformable structures, relying only on the predictions of biomechanical models. This allows the robot control to be adjusted to compensate for tissue movement even before the needle moves. Finally, for obvious safety reasons, it is important for the surgeon to be able to take control of the automatic system at any time. We propose to integrate a remote handling system in the control loop, allowing sharing the robot control in difficult areas.

For the success of this project, we have identified three axes of research that lie at the intersection of several scientific fields:
(1) Task 1: Predictive biomechanical models and image error control.
(2) Task 2: Control model by inverse simulation and remote manipulation.
(3) Task 3: Design, prototyping and validation of the system in realistic applications.

The results of this project will provide solutions to a current problem, still unresolved by the scientific community. This work will be implemented on a dedicated hardware platform. This consists of a collaborative robot equipped with a previously designed needle handling tool. A strong motivation is to bring our research results to an experimental prototype allowing the qualitative and quantitative evaluation of our approach.

In accordance with our dissemination strategy, we are considering presentations in the most prestigious international conferences of the medical simulation community (Miccai, Ipcai), robotics conferences (Iros, Icra) and also publication in one or several journals at factor significant impact (IEEE transaction on robotics, Media, etc.).

A development effort will also be made to make available the methods developed in the open source simulation software SOFA. This approach will increase the visibility of work on a very dynamic subject. The combination of scientific publications and open source software will greatly facilitate exchanges between scientists and the effective dissemination of results. Our approach will ensure the exchange and interoperability of software without sacrificing the possibility of marketing our results.

Medical robotics is now a well-established field with many clinical, research and commercial applications. The issues of controlling robotic interaction are still widely open today when it comes to soft environments. The technical and industrial results of this project are particularly relevant for companies in digital information and technologies for computer-assisted surgery as well as for manufacturers of medical imaging. The vision is that the next generations of medical robots will provide access to advanced algorithms and the automation of complex tasks, thus reducing operating time, risks for patients, and therefore the additional cost associated with robots.

Our tool could interest the entire French and international hepatobiliary surgical community and change treatment standards for percutaneous strategies that are much less burdensome and traumatic for patients. By proposing innovative tools for the fields of surgical simulation and hepatology, this project contributes to bringing scientific developments centered on a social and economic problem of primary importance. The expected medical objectives are multiple:
1. Decrease trauma and complication rates for patients such as infections, bleeding and postoperative pain.
2. Decrease in postoperative morbidity through better preservation of the pedicles necessary for the functionality of the remaining parenchyma.
3. Training of young surgeons using a deformable liver model to simulate realistic clinical situations (immersive virtual reality).

Our project is part of the logical evolution of surgery to improve safety, recovery time and provide less aggressive treatments for patients.

1. Hadrien Courtecuisse, Zhifan Jiang, Olivier Mayeur, Jean-Francois Witz, Pauline Lecomte-Grosbras, et al.. Three-dimensional physics-based registration of pelvic system using 2D dynamic magnetic resonance imaging slices. Strain, Wiley-Blackwell, 2020, 56 (3)

2. Paul Baksic, Hadrien Courtecuisse, Christian Duriez, Bernard Bayle. Robotic needle insertion in moving soft tissues using constraint-based inverse Finite Element simulation. ICRA 2020 - IEEE International Conference on Robotics and Automation, May 2020, Paris, France.

3. Paul Baksic, Hadrien Courtecuisse, Matthieu Chabanas, Bernard Bayle. FEM-based confidence assessment of non-rigid registration. Surgetica 2019, 2019, Rennes, France.

Percutaneous medical procedures, using surgical needles, are among the least invasive approaches to accessing deep internal structures of organs without damaging surrounding tissues. Today, many surgical procedures rely on the use of needles allowing for complex interventions such as curie-therapies or thermoablations of tumors (cryoablation, radio frequencies). Unlike traditional open surgery, these approaches only affect a localized area around the needle reducing this way trauma and risks of complications. These treatments also offer new solutions for tumors or for metastases for which traditional methods may be contraindicated due to the age of the patient and the extent or location of the disease.
Although they provide very good results, these interventions significantly increase the level of expertise required for practitioners. Thermoablation can be extremely complex to achieve since the effectiveness of the treatment will mainly depend on the accuracy of needle’s positioning, limited by the fact that needles are manipulated from outside of the patient using intraoperative images offering poor visibility of internal structures. Medical robotics has the potential to assist surgical gesture, overcome limitations due to human factors and increase the accuracy of tools positioning. Many research projects and commercial products aim to develop surgical robots for needle insertion assistance. However, the deformation of the organs remains, an open problem limiting the development of these robots for wide use in the operating room.
In this project, we want to develop new solutions for the control of medical robots interacting with soft tissues. This work is motivated by recent advances in the field of medical simulation achieving a sufficient level of realism to help surgeons during the operation. These simulations are now used for training of surgeons, and even for visual assistance during the operation thanks to augmented reality. The maturity of these techniques now suggests the ability to use a simulation intraoperatively to control the motion of a robotic system for needle insertion. This is really a challenge, because in general, very few information can be extracted in real time from images during an intervention. We believe that even minimal knowledge of the mechanical behavior of structures, associated with the use of images can make it possible and allow a robot to reach a pre-identified target during a planning stage, without human intervention.
The originality of our approach lies in the fact that we will address the problem of deformation using inverse real-time finite element simulations in the control loop of the robot. This represents important scientific obstacles that will be addressed in this project. In particular, we will need to achieve an optimal compromise between the accuracy and speed of models to predict the interaction of soft tissues and needles. These works will be implemented on a dedicated hardware platform. This consists of a collaborative robot equipped with a previously designed needle manipulation tool, which will allow the validation of the method in realistic applications. A strong motivation is to bring our research results to an experimental prototype allowing for qualitative and quantitative evaluation of our method.

Project coordinator

Monsieur Hadrien Courtecuisse (Laboratoire des sciences de l'Ingénieur, de l'Informatique et de l'Imagerie (UMR 7357))

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.


ICube Laboratoire des sciences de l'Ingénieur, de l'Informatique et de l'Imagerie (UMR 7357)

Help of the ANR 302,215 euros
Beginning and duration of the scientific project: December 2018 - 36 Months

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