Robot-assisted urology

Within this research line, the 'Urology Research Group' focuses on both clinical and translational scientific research concerning robot-assisted surgery within urology.

Research projects

Cytokine-guided Robotic Surgery (CY-ROS)

The primary outcome of this study is to determine the diagnostic accuracy of serum cytokine values in predicting postoperative paralytic ileus after robot-assisted urological surgery (cystectomy or kidney transplantation) in relation to intraoperative pneumoperitoneal pressures.


Robot-assisted kidney (auto)transplantation (RAKT & RAKAT)

This research concerns prospective clinical research on robot-assisted kidney transplantation after living donation and auto-transplantation of the kidney in adults and children.


Computer-assisted support for Robot-assisted urological Surgery (CASRAS)

Peri-operative computer-assisted support with robot-assisted partial nephrectomies: pre-operative planning, intra- and post-operative evaluation. Artificial intelligence ("deep learning") is used to automate the production of 3D kidney (perfusion) models and to develop autonomous robot-assistance.


Prospective follow-up of uro-oncological surgery (URO-ONCO PROSPECTIVE)

This concerns prospective clinical research in which we investigate the diagnostics and treatments of patients undergoing surgery for urological tumours of the bladder, kidney, urinary tract, prostate and testis.


  • Collaboration with various services of the University Hospital Ghent: Radiotherapy, Medical Oncology, Nuclear medicine, Pathological anatomy, Thoracic and vascular surgery, Nephrology, Anesthesia, Radiology and Medical Imaging
  • Collaboration with the Faculty of Engineering and Architecture (Ghent University) and IBiTech
  • National collaboration with ORSI Academy in Melle
  • International collaborations: Hertfordshire and Bedfordshire Urological Cancer Centre (UK), Lister Hospital (UK) for the CY-ROS trial and the EAU Robotic Urology Section RAKT working group for a common online prospective database



  • Sofie Everaert, study nurse

+32 9 332 59 73

  • Charles Van Praet, researcher

+32 9 332 19 55

  • Karel Decaestecker, research coordinator

+32 9 332 01 39