HUS Technical sequencing at IHU Strasbourg: a world first in neoplastic diseases

HUS Technical sequencing at IHU Strasbourg: a world first in neoplastic diseases

At the IHU Strasbourg, Prof. Anne Olland and Prof. Pierre-Emmanuel Falcoz, of the Thoracic Surgery and Lung Transplant Department at the University Hospitals in Strasbourg, performed a ground-breaking technical sequencing on Thursday 26 October, benefiting from the institute’s specialty in image-guided minimally invasive robot-assisted surgery.

For the first time, the technical sequencing took place entirely on site, around the patient, who did not need to be transported from one examination to the next. This sequence enabled precise minimally invasive (robot-assisted surgery) and parenchymal sparing (controlled segmentectomy). This surgery offers greater precision and reliability in the early stages of neoplastic disease. The world-first sequencing also expands the IHU Strasbourg’s specialty domains, historically linked to digestive surgery.

This work was the fruit of close multidisciplinary collaboration with IBODEs, radio manipulators, intensive care anaesthetists, as well as interventional radiologists, management teams and industry representatives.


The offer of precise, reliable surgery on early-stage neoplastic disease: imaging as close as possible to the surgical procedure enables accurate 3-dimensional reconstruction on a CT scan performed on a patient who is already asleep and in the operating position at the time of surgery, with no positional shift and no lag in the evolution of the disease with a CT scan performed on the same day (compared with a CT scan usually performed lying down, with a lag of one to several days or even weeks in relation to the surgical procedure). The technical sequence takes place around the patient, who does not need to be transported from one examination to the next, enabling precise, minimally invasive, parenchymal-sparing surgery. This technical development remains linked to the HUS’s cross-disciplinary lung cancer research programs.

Artificial Intelligence enters the operating room: A world first at the IHU Strasbourg

Artificial Intelligence enters the operating room: A world first at the IHU Strasbourg

The scientific and medical teams at the IHU have just taken a major step in the international race towards the surgery of the future. They have successfully deployed an image analysis system driven in real time by computer software using Artificial Intelligence, to automatically control the progress of a minimally invasive operation on a patient.


During the operation performed by Prof. Didier Mutter on 25th November, a minimally invasive gallbladder removal, the video acquired by the endoscopic camera was analyzed in real time by Artificial Intelligence algorithms designed Prof. Nicolas Padoy and his team at IHU/University of Strasbourg. The software can follow all stages of the operation and movement of the instruments, recognize the anatomy, and automatically perform controls of the surgical scene at key steps. All the information can be communicated to the surgical team in the form of notifications or augmented reality images that are completely synchronous with the video of the operating field. The operation was broadcast live from one of the Strasbourg IHU operating rooms on the screens of the Digestive Surgery Congress in Rome and the World Congress of Endoscopic Surgery in Barcelona.

Predictive and personalized medicine of pancreatic cancer I AAP générique ANR 2021 I PRCI Projects

Predictive and personalized medicine of pancreatic cancer I AAP générique ANR 2021 I PRCI Projects

Project CancerProfile
IHU Strasbourg + Luxembourg Institute of Health.

With a 5-year survival rate remaining in the single digits, pancreatic ductal adenocarcinoma cancer (PDAC) has the poorest prognosis of all digestive cancers due to the lack of early diagnosis and limited response to treatments. It is the deadliest worldwide, with a mortality which is predicted to increase in western countries as population age and levels of obesity rise. It often develops without apparent symptoms, and the diagnosis is typically established late in the progression of the disease, at which point only 15 to 20% of patients are eligible for surgical resection, which remains the only curative treatment. Thus, palliative chemotherapy remains a mainstay in the management of this disease. However, the strong resistance to currently used chemotherapeutic agents represents a major treatment bottleneck, and the development of effective therapeutic approaches to fight PDAC is still an urgent medical need.


CancerProfile is a multidisciplinary translational research project aimed at improveing early diagnosis and prediction of PDAC tumor response to treatments, combining cutting edge Artificial Intelligence-augmented histological imaging and innovative functional profiling of patient tumor-derived organoids, to foster precision medicine of PDAC. The project will lay the foundation for a large clinical study to evaluate the implementation of personalized treatment for PDAC patients. It will lead to the establishment of a unique biobanking and database organization, that can serve as a platform for other basic and translational European research projects.

Artificial Intelligence for Safer Surgery

Artificial Intelligence for Safer Surgery

Clinicians and computer scientists at CAMMA, a joint research group between IHU Strasbourg and ICube/University of Strasbourg, have teamed up to improve safety in laparoscopic cholecystectomy using artificial intelligence (AI).

The Strasbourg-based team first proposed the 5-second rule, a simple yet effective cognitive aid to promote the implementation of guidelines for safe cholecystectomy. In an article published in the Journal of the American College of Surgeons, they demonstrate that a 5-second-long intraoperative time out to recall best practices induces a three-fold increase in the achievement of the Critical View of Safety, an essential step to prevent bile duct injuries.


In a commentary entitled “Time to Stop and Pause”, the lead author of the worldwide guidelines on safe cholecystectomy Dr L Michael Brunt writes:

“Of all the quality improvement measures implemented in surgery and medicine over the last many years, the simple act of a momentary pause to stop, look, and reflect before proceeding with an irreversible step in an operation, may arguably have one of the highest benefit-to-risk ratios, especially given the minimal time to do it and the considerable potential upside for enhancing patient safety” 

Concurrently, the same team has developed and published on the Annals of Surgery DeepCVS, the first AI model capable of recognizing important anatomical structures and automatically assessing the achievement of the aforementioned safety view to provide surgeons with intraoperative decision support.

To try DeepCVS, please visit:

Finally, in a second article in the Annals of Surgery, the team presents EndoDigest, a computer vision platform providing short videos selectively documenting critical steps of procedures to promote transparency, research, and education in surgery.

The multidisciplinary team led by Prof. Nicolas Padoy is now starting collaborations with other surgical centers and industrial partners like NVIDIA to validate and optimize these prototypes, essential steps to translate these and other AI algorithms to operating rooms and finally generate value for patients, surgeons, and healthcare systems.


To learn more or contact the team, please visit: