Early beginnings in surgical robotics

Jocelyne Troccaz, an emeritus research director at CNRS and member of the Academy of Sciences, first encountered surgical robotics in 1990 at the TIMC laboratory, where a robot had already been developed in collaboration with an industrial partner and a neurosurgeon from the CHU of Grenoble for neurosurgery procedures.

Technological needs in modern surgery

The evolution of surgery since the 1980s has created new technological needs, particularly with the development of video surgery and minimally invasive surgery, which introduced instruments through small openings and required progress in imaging, image processing, robotics, and interfaces. Surgical robotics is part of a broader framework of computer-assisted medical and surgical assistance, where patient data such as MRI, scans, ultrasound, and video are linked and used to plan procedures and guide surgeons during operations.

Collaboration with the medical community

The TIMC laboratory has worked closely with the medical world, with important collaborations with hospital practitioners and some members of the laboratory or doctoral students being doctors or interns at the CHU of Grenoble. Projects in this field often take several years to develop, evaluate, and possibly disseminate. The CNRS has played an essential role in supporting long-term research in direct contact with medical teams and facilitating the transfer of results to industry when sufficiently mature.

Real-world applications of surgical robotics

Concrete examples of the use of these technologies include work on radiotherapy and image fusion in the context of prostate cancer, which led to patents transferred to industry players. In the 2000s, urologists from Grenoble and Paris approached the laboratory for prostate biopsies, leading to the development of image processing methods that allow MRI information to be used during ultrasound-guided biopsies. These solutions have been industrialized and today concern more than a million patients in about fifty countries.

Role and limits of surgical robots

Surgical robots do not replace surgeons but aim to assist them by improving the precision of gestures, facilitating access to certain areas, and synchronizing with mobile organs. However, the medical decision-making, assessment of situations, and responsibility toward the patient remain human. Ethical and technical limits of this collaboration with robots include ensuring the technology is not harmful, provides a benefit, and is safe and reliable. The question of the relationship between risks and benefits is central, as well as ensuring equitable access to these innovations.

Challenges in the operating room

Concrete constraints in the operating room include the need for specific interfaces that allow users to operate while wearing gloves and respecting aseptic rules. The operating environment imposes strict norms, such as electromagnetic compatibility and cleaning of devices in contact with the patient. Time is also limited during procedures, which must be considered in the development of solutions.

Future of surgical robotics

Prospects for technological development include the integration of artificial intelligence, which can provide assistance in the automatic analysis of surgical video and alerting operators to unusual situations. However, the challenge is not necessarily to make surgical robots autonomous, as surgery is complex and each patient is different. Certain endocorporeal deformable devices will need to adapt in real time to a deformable environment and will require a certain autonomy and embedded intelligence.

Importance of diversity in the field

In terms of diversity in the field, Troccaz emphasizes the importance of gender and other forms of diversity in all areas, including research, computer science, engineering, robotics, and medicine. She hopes that young girls will understand that they can pursue careers in these fields and that they have varied models to project themselves into. Diversity is also crucial for the quality of technologies developed, as systems based on data and artificial intelligence depend on what they have learned and what their designers have chosen to take into account.