What we do
The objective of IO Surgical Research is the creation of three-dimensional models in augmented reality and their use in real-time in Robotic and Laparoscopic Urological Oncological Surgery and experimenting their application in the surgical therapy of prostate and kidney cancer.
The project has as final interlocutors the medical specialists operating in the oncological field and not only; it has therefore a wide application in health care and surgical training, being an essential element in the surgical procedures in order to raise safety standards, reproducibility and therapeutic outcomes. The fact that the experimental project finds its application in the Genoese territory will be a further element of attraction for multinationals in the Healthcare sector, in particular related to endoscopy and surgical robotics.
The detailed acquisition of the patient's anatomy is the key to tailor-made surgical management of tumours. In the last decade, prostate and renal cancer surgery for example has been revolutionised by the rapid implementation of robotic technology.
The Urological Clinic of the San Martino Hospital in Genoa, in collaboration with Digital Tree Innovation Habitat, has developed the idea of creating a prototype of coherent real-time interaction between holograms of anatomical structures and live organs, such as kidney and prostate, during assisted robotic laparoscopic surgical procedures.
The initial implementation phase required the close synergy of medical-surgical and bio-engineering skills.
Within the University of Genoa, the two departments collaborating in this project are DISC and DIBRIS.
IO Surgical Research s.r.l. consists of a dedicated multidisciplinary research group composed as follows:
- CT&MO: Prof. Carlo Terrone and Prof. Paolo Traverso
- CTO Robotics, AI & Automation: Prof. Fulvio Mastrogiovanni
- Director: Marco Bressani
In the next 12 months of research, at least two researcherswill join the organisation, with specific machine learning skills to consolidate the research project and develop a specific algorithm capable of predicting and digitally transforming the deformation of tissues subjected to stress during the surgical procedure.