Canada Spends Logo

Explore our Budget 2026 analysis

Grant: Engage Grants Program

University of Ontario Institute of Technology

$25,000.00

From virtual reality simulation to collaborative surgery: Enabling data-driven teleoperated percutaneous nephrolithotomy****

FY 2018-19

Summary
Percutaneous nephrolithotomy (PCNL) was quickly established as the leading procedure used for management of urinary calculi for large urinary stones. Despite over 40 years of development, PCNL remains a challenging procedure to learn. Particularly in less experienced hands, PCNL can lead to higher complication rates compared to other endoscopic procedures. Developing adequate expertise to achieve surgical competence is not trivial as it involves training in gaining access to the kidney, but also in stone fragmentation, tool navigation, and stone scavenging. Due to the procedure steep learning curve and inherent complexity, PCNL residents will inevitably perform a certain number of sub-optimal interventions during the training process. *Marion Surgical has identified the need to improve PCNL training and maintain it as a safe and effective treatment for patients. The company has developed a virtual reality simulator that affords residents the opportunity to train in a systematic environment that does not compromise patient safety. The system reproduces what an operating room would look like, and offers real-time fluoroscopic images of the kidney to the operator, who manipulates a surgical tool using a force-feedback device. The latter emulates the sensation of touch with the human tissue and as in a real-world intervention. *The purpose of this collaboration is to create a data-driven telerobotic system that co-manipulates the surgical tools in tandem with the surgeon in order to improve clinical outcomes of residents. The project will train two Master students in emerging areas of robot-aided surgey and the outcomes of this project will lead to better clinical outcomes during PCNL. It will allow Marion Surgical to develop some of the first-ever applications of machine learning to the growing area of virtual surgery and make a strong entry into the emerging surgical robotics market. *
Program
Engage Grants Program
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
536211-2018
Name nom
Rossa, Carlos
Department département
Engineering and Applied Science, Faculty of
Organization id
19222
Institution établissement
University of Ontario Institute of Technology
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
25000
Program id
EGP
Program name en
Engage Grants Program
Program name fr
Programme de subventions d'engagement partenariat
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1553
Committee name en
Ontario Internal Decision Committee
Committee name fr
Comité de décision interne pour l'Ontario
Area of application code
1102
Area of application group en
Health, education and social services
Area of application group fr
Santé publique, éducation et services sociaux
Area of application en
Biomedical engineering
Area of application fr
Génie biomédical
Research subject code
2600
Research subject group en
Robotics
Research subject group fr
Robotique
Research subject en
Robotics
Research subject fr
Robotique
Partie
1
Nb partie
1
Application title
From virtual reality simulation to collaborative surgery: Enabling data-driven teleoperated percutaneous nephrolithotomy****
Keyword
NSERC
Application summary
Percutaneous nephrolithotomy (PCNL) was quickly established as the leading procedure used for management of urinary calculi for large urinary stones. Despite over 40 years of development, PCNL remains a challenging procedure to learn. Particularly in less experienced hands, PCNL can lead to higher complication rates compared to other endoscopic procedures. Developing adequate expertise to achieve surgical competence is not trivial as it involves training in gaining access to the kidney, but also in stone fragmentation, tool navigation, and stone scavenging. Due to the procedure steep learning curve and inherent complexity, PCNL residents will inevitably perform a certain number of sub-optimal interventions during the training process. *Marion Surgical has identified the need to improve PCNL training and maintain it as a safe and effective treatment for patients. The company has developed a virtual reality simulator that affords residents the opportunity to train in a systematic environment that does not compromise patient safety. The system reproduces what an operating room would look like, and offers real-time fluoroscopic images of the kidney to the operator, who manipulates a surgical tool using a force-feedback device. The latter emulates the sensation of touch with the human tissue and as in a real-world intervention. *The purpose of this collaboration is to create a data-driven telerobotic system that co-manipulates the surgical tools in tandem with the surgeon in order to improve clinical outcomes of residents. The project will train two Master students in emerging areas of robot-aided surgey and the outcomes of this project will lead to better clinical outcomes during PCNL. It will allow Marion Surgical to develop some of the first-ever applications of machine learning to the growing area of virtual surgery and make a strong entry into the emerging surgical robotics market. *