Development and Validation of a Virtual Basic Laparoscopic Skill Trainer (VBLaST) For the first time in the history of surgical education, a comprehensive program to teach and evaluate the cognitive and psychomotor aspects unique to laparoscopic surgery - the Fundamentals of Laparoscopic Surgery (FLS) developed originally by the Society of American Gastrointestinal Endoscopic Surgery (SAGES) and subsequently by a joint committee which includes the American College of Surgeons (ACS) - is being embraced nationally for training and credentialing laparoscopic surgeons. As an example of its growing acceptance by the medical community, starting in 2009, the American Board of Surgeons has mandated that passing the FLS certifying examination will be required for taking the board examination in surgery. While the cognitive assessment in FLS is based on 75 multiple-choice questions, a proctored examination is used for the manual skills assessment which includes five tasks to be performed in a portable pelvic trainer box with built-in video camera: bimanual peg transfer, precise pattern cutting, use of ligating loops and suturing with intracorporeal and extracorporeal knot tying. In spite of the growing popularity of the FLS, there are several major problems with this box trainer paradigm: (1) the assessment is subjective, (2) there is no feedback during learning except when an experienced trainer is present, (3) a large number of qualified proctors must be engaged during test taking, (4) the training material must be constantly replaced, and (5) the test-takers must travel to one of the 27 Regional Test Centers or the Annual SAGES meeting or the ACS Clinical Congress. To overcome these problems and to enable greater dissemination, we propose to develop and validate a Virtual Basic Laparoscopic Skill Trainer (VBLaST) whereby tasks available in the FLS may be performed on PCs and laptops with inexpensive haptic (touch) interface devices, such as the Phantom(R) OmniTM. To develop the VBLaST a novel set of technologies must be developed including rapid, but highly realistic physics-based virtual interaction paradigms and statistical machine learning techniques to develop a """"""""virtual mentor"""""""" which will provide real time automated feedback to the trainees. A comprehensive set of studies involving students, residents, fellows and practicing surgeons at Boston area hospitals (e.g., BIDMC, Tufts Medical Center, Cambridge Health Alliance, Harvard, MGH, Brigham &Women's, Lahey Clinic) will be undertaken to test the validity of the VBLaST as a training tool and establish its usefulness in transferring the acquired skills to the operating room. Once validated, the VBLaST will have exponential impact in reducing training costs and training time while improving patient safety and outcomes, A multidisciplinary team with collective expertise in physics-based interactive medical simulation, laparoscopic surgery and surgical education, and human factors engineering has been assembled to achieve the following Specific Aims: SA1) To develop a realistic virtual basic laparoscopic skill trainer (VBLaST) platform to perform all the tasks available in the FLS training tool box. SA2) To establish the validity of the VBLaST as a training tool. SA3) To evaluate the usefulness of the VBLaST as a training tool. SA4) To develop a web-based interface for the VBLaST.
The goal of this research is to develop a comprehensive computer-based technology that will allow surgical trainees to practice their surgical skills and to take standardized tests on computer-based models. Surgical procedures and techniques, learnt and perfected in this risk-free manner before application to patients, will translate to fewer operating room errors, reduced patient morbidity and improved patient outcomes resulting in faster healing, shorter hospital stay and reduced post surgical complications and treatment costs.
| Linsk, Ali M; Monden, Kimberley R; Sankaranarayanan, Ganesh et al. (2018) Validation of the VBLaST pattern cutting task: a learning curve study. Surg Endosc 32:1990-2002 |
| Karaki, Wafaa; Rahul; Lopez, Carlos A et al. (2018) A Two-Scale Model of Radio-Frequency Electrosurgical Tissue Ablation. Comput Mech 62:803-814 |
| Cetinsaya, Berk; Gromski, Mark A; Lee, Sangrock et al. (2018) A task and performance analysis of endoscopic submucosal dissection (ESD) surgery. Surg Endosc : |
| Han, Zhongqing; Rahul, Suvranu De (2018) A Multiphysics Model for Radiofrequency Activation of Soft Hydrated Tissues. Comput Methods Appl Mech Eng 337:527-548 |
| Dorozhkin, Denis; Olasky, Jaisa; Jones, Daniel B et al. (2017) OR fire virtual training simulator: design and face validity. Surg Endosc 31:3527-3533 |
| Demirel, Doga; Yu, Alexander; Baer-Cooper, Seth et al. (2017) Generative Anatomy Modeling Language (GAML). Int J Med Robot 13: |
| Dargar, Saurabh; Akyildiz, Ali C; De, Suvranu (2017) In Situ Mechanical Characterization of Multilayer Soft Tissue Using Ultrasound Imaging. IEEE Trans Biomed Eng 64:2595-2606 |
| Qi, Di; Panneerselvam, Karthikeyan; Ahn, Woojin et al. (2017) Virtual interactive suturing for the Fundamentals of Laparoscopic Surgery (FLS). J Biomed Inform 75:48-62 |
| Suvranu De, Rahul (2017) A multi-physics model for ultrasonically activated soft tissue. Comput Methods Appl Mech Eng 314:71-84 |
| Demirel, Doga; Yu, Alexander; Halic, Tansel et al. (2016) Virtual Airway Skills Trainer (VAST) Simulator. Stud Health Technol Inform 220:91-7 |
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