Development and validation of a Virtual Colorectal Surgical Trainer (VCoST)

Introduction: 

Development and validation of a Virtual Colorectal Surgical Trainer (VCoST) Abstract For the first time in the history of surgery, a hands-on surgical technical skills examination ? the Colorectal Objective Structured Assessment of Technical Skills (COSATS), developed by the American Society of Colon and Rectal Surgeons (ASCRS) ? has been introduced in the American Board of Colon and Rectal Surgeons (ABCRS) examination, starting in 2014. The COSATS requires an elaborate setup with eight different stations through which residents must circulate to perform five open surgical tasks (rectal prolapse, pelvic bleeding, ileal pouch anal anastomosis, coloanal anastomosis, handsewn anastomosis), two laparoscopic and a colonoscopic task. It is anticipated that a computer generated virtual reality (VR)-based simulator with both visual and haptic (touch) feedback could provide an integrated training and evaluation environment for colorectal residents to climb their learning curves without risk to actual patients, standardize the process of skill training and credentialing and allow objective quantification of performance, without the need for human proctors. While VR simulation technology is being developed for colonoscopy and laparoscopic surgical procedures, three major technical hurdles have thwarted the development of VR-based simulation of open surgical procedures, such as the ones in COSATS: (1) fully immersive 3D visualization to allow surgeons to interact with the patient?s anatomy directly using their hands as well as manipulate untethered surgical tools; (2) high fidelity stable computations for contact detection, response and physical simulations; and (3) full-hand bi-manual haptic interactions with the virtual anatomy and untethered surgical tools.
 

Focus Area: 
Haptics and Virtual Reality
Machine Learning and Data Science
Real-time Computational Algorithms
Researchers: 

Our aim, in this present proposal, is to overcome these challenges and design, develop, and evaluate, for the first time, a Virtual Colorectal Surgical Trainer (VCoST) for the five open surgical tasks in the COSATS. To achieve our goal, a multidisciplinary research team has been assembled to achieve the following specific aims: (SA1) Develop a VCoST platform. Specifically, we will develop: (1) highly realistic simulation of the five open COSATS tasks within an immersive 3D high definition (HD) head mounted display (HMD) system; (2) physics-based simulations based on in vivo experimental studies; (3) novel haptic interface devices (with both tactile and force feedback) that allow realistic full-hand interactions with the virtual anatomy and untethered surgical tools; and (4) real time assessment and feedback. (SA2) Establish the validity of the VCoST as a training tool. We will conduct experiments on voluntarily enrolled subjects to establish face and construct validity of the VCoST. We hypothesize that the VCoST tasks, like the COSATS tasks, will be capable of distinguishing the skill levels of graduating general surgery and colorectal surgery residents.(SA3) Evaluate the usefulness of the VCoST as a training tool. We will perform learning, retention, and transfer-of-learning studies on the VCoST. We hypothesize that residents who trained with VCoST will demonstrate learning and transfer in the clinical environment, and will perform better than a control group.

The goal of this research is to develop advanced computer-based technology that will allow colorectal surgeons to practice their surgical skills on computer-generated models that will help them reduce errors in the operating room. This technology will also allow them to be certified. Surgical procedures, learnt and perfected in this risk-free manner before application to patients, will translate to reduced patient morbidity and improved patient outcomes resulting in faster healing, shorter hospital stay, reduced complications and treatment costs and, overall, an improved healthcare system.

Project Sponsor: 
https://www.nih.gov/
Grant Name: 
R01EB025241