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Assessment of Tissue Damage due to Mechanical StressesBioRobotics Laboratory, Department of Bioengineering University of Washington Box 352500, Seattle, WA 98195-2500, USA {sd6, rosen}@u.washington.edu, ldagan{at}gmail.com, blake{at}ee.washington.edu
BioRobotics Laboratory, Department of Bioengineering University of Washington Box 352500, Seattle, WA 98195-2500, USA {sd6, rosen}@u.washington.edu, ldagan{at}gmail.com, blake{at}ee.washington.edu
BioRobotics Laboratory, Department of Bioengineering University of Washington Box 352500, Seattle, WA 98195-2500, USA {sd6, rosen}@u.washington.edu, ldagan{at}gmail.com, blake{at}ee.washington.edu
BioRobotics Laboratory, Department of Bioengineering University of Washington Box 352500, Seattle, WA 98195-2500, USA {sd6, rosen}@u.washington.edu, ldagan{at}gmail.com, blake{at}ee.washington.edu
Department of Anatomic Pathology University of Washington Box 352500, Seattle, WA 98195-2500, USA ps3{at}u.washington.edu
Department of Surgery, University of Washington Box 352500, Seattle, WA 98195-2500, USA mssurg{at}u.washington.edu While there are many benefits to minimally invasive surgery (MIS), force feedback or touch sensation is limited in the currently available MIS tools, such as surgical robots, creating the potential for excessive force application during surgery and unintended tissue injury. The goal of this work was to develop a methodology with which to identify stress magnitudes and durations that can be safely applied with a MIS grasper to di ferent tissues, potentially improving MIS device design and reducing potentially adverse clinically relevant consequences. Using the porcine model, stresses typically applied in MIS were applied to liver, ureter and small bowel using a motorized endoscopic grasper. Acute indicators of tissue damage including cellular death and infiltration of inflammatory cells were measured using histological and image analysis techniques. Finite element analysis was used to identify approximate stress distributions experienced by the tissues. Parameters used in these finite element models specifically reflected the properties of liver, which served as an initial proxy for all tissues, as stress distributions rather than absolute values were desired. Local regions predicted to have uniform stress by the computational models were mapped to and analyzed in the tissue samples for acute damage. Analysis of variance (ANOVA) and post-hoc analyses were used to detect stress magnitudes and durations that caused significantly increased tissue damage with the goal to ultimately identify safe stress `thresholds' during grasping of the studied tissues. Preliminary data suggests a graded non-linear response between applied stress magnitude and apoptosis in liver and small bowel as well as neutrophil infiltration in the small bowel. The ureter appeared to be more resistant to injury at the tested stress levels. By identifying stress magnitudes and durations within the range of grasping loads applied in MIS, it may be possible for researchers to create a `smart' surgical robot that can guide a surgeon to manipulate tissues with minimal resulting damage. In addition, surgical simulator design can be improved to reflect more realistic tissue responses and evaluate trainees' tissue handling skills.
Key Words: grasping • tissue damage • histological quantification • minimally invasive surgery • finite element analysis • surgical grasper
The International Journal of Robotics Research, Vol. 26, No. 11-12,
1159-1171 (2007) This article has been cited by other articles:
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