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UBC Theses and Dissertations

Image and haptic guidance for robot-assisted laparoscopic surgery Mohareri, Omid

Abstract

Surgical removal of the prostate gland using the da Vinci surgical robot is the state of the art treatment option for organ confined prostate cancer. The da Vinci system provides excellent 3D visualization of the surgical site and improved dexterity, but it lacks haptic force feedback and subsurface tissue visualization. The overall objective of the work done in this thesis is to augment the existing visualization tools of the da Vinci with ones that can identify the prostate boundary, critical structures, and cancerous tissue so that prostate resection can be carried out with minimal damage to the adjacent critical structures, and therefore, with minimal complications. Towards this objective we designed and implemented a real-time image guidance system based on a robotic transrectal ultrasound (R-TRUS) platform that works in tandem with the da Vinci surgical system and tracks its surgical instruments. In addition to ultrasound as an intrinsic imaging modality, the system was first used to bring pre-operative magnetic resonance imaging (MRI) to the operating room by registering the pre-operative MRI to the intraoperative ultrasound and displaying the MRI image at the correct physical location based on the real-time ultrasound image. Second, a method of using the R-TRUS system for tissue palpation is proposed by expanding it to be used in conjunction with a real-time strain imaging technique. Third, another system based on the R-TRUS is described for detecting dominant prostate tumors, based on a combination of features extracted from a novel multi-parametric quantitative ultrasound elastography technique. We tested our systems in an animal study followed by human patient studies involving n = 49 patients undergoing da Vinci prostatectomy. The clinical studies were conducted to evaluate the feasibility of using these systems in real human procedures, and also to improve and optimize our imaging systems using patient data. Finally, a novel force feedback control framework is presented as a solution to the lack of haptic feedback in the current clinically used surgical robots. The framework has been implemented on the da Vinci surgical system using the da Vinci Research Kit controllers and its performance has been evaluated by conducting user studies.

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Attribution-NonCommercial-NoDerivs 2.5 Canada

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