Computation and Measurement of Force and Tissue Damage for the Grasper-tissue Interface in Robot-assisted Minimal Invasive Surgery

Cheng, Lei (2015) Computation and Measurement of Force and Tissue Damage for the Grasper-tissue Interface in Robot-assisted Minimal Invasive Surgery. Doctoral thesis, University of Washington.

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Robot-assisted minimally invasive surgery (RMIS) has many benefits for patients. However, loss of haptic feedback in the technique is a major limitation to surgeons since extensive applied force due to the lack of haptic feedback may cause unrecognized tissue damage. Also a surgical simulator without touch sensation is less adequate to train medical students to handle tissue safely. Various previous studies have reported the quantified tissue damage resulting from mechanical compression such as due to a surgical instrument grasping tissue; however, most of them require in-vitro bench work analysis, which limits their application in clinical conditions. This work provides a nonlinear finite element (FE) analysis of the grasper-tissue interaction to predict the reaction force on grasper jaws and degree of damage inside tissue. It also investigates the effects of the boundary conditions and material properties of the FE model on the simulated von Mises stress value and tissue damage. Four FE models were analyzed: two-dimensional (2D) plane strain model, 2D plane stress model, full three-dimensional (3D) model, and 3D thin membrane model. Our study shows that for integrated von Mises stress and tissue damage computations, the 3D thin membrane model yielded results closest to the full 3D analysis and required only 0.2% of the compute time. Then the 3D thin membrane model was used further to extract the three descriptors (length, width and depth) of tissue deformation. Correlations between applied force from in vitro experiments and tissue models validate the ability to predict force from deformation. Finally, a wide range of grasper-tissue interfaces were evaluated regarding tissue damage magnitude and grasp quality. By comparing the results with previously published studies, we confirmed that the computational methodology is useful for researchers to develop and test various designs of graspers, reducing the need for time-consuming and expensive in vivo experiments. The results presented in this study can guide engineers to design surgical instruments to improve patient safety. Additionally it is useful for improving the surgical simulator performance by reflecting more realistic tissue material property and displaying tissue damage severity.

Item Type: Thesis (Doctoral)
Subjects: C Surgical Robots > CC Preventing Tissue Damage
Divisions: Department of Mechanical Engineering
Depositing User: Blake Hannaford
Date Deposited: 07 Jul 2017 23:21
Last Modified: 07 Jul 2017 23:21

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