Analyzing Liver Surface Indentation for In Vivo Refinement of Tumor Location in Minimally Invasive Surgery
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Annals of Biomedical Engineering (Ó 2020) https://doi.org/10.1007/s10439-020-02698-4
Original Article
Analyzing Liver Surface Indentation for In Vivo Refinement of Tumor Location in Minimally Invasive Surgery YINGQIAO YANG , KAI-LEUNG YUNG, TIN WAI ROBERT HUNG, and KAI-MING YU Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, R606, 1 Yuk Road, Hung Hom, Kowloon, Hong Kong (Received 16 August 2020; accepted 18 November 2020) Associate Editor Ender A. Finol oversaw the review of this article.
Abstract—Manual palpation to update the position of subsurface tumor(s) is a normal practice in open surgery, but is not possible through the small incisions of minimally invasive surgery (MIS). This paper proposes a method that has the potential to use a simple constant-force indenter and the existing laparoscopic camera for tumor location refinement in MIS. The indenter floats with organ movement to generate a static surface deformation on the soft tissue, resolving problems of previous studies that require complicated measurement of force and displacement during indentation. By analyzing the deformation profile, we can intraoperatively update the tumor’s location in real-time. Indentation experiments were conducted on healthy and ‘‘diseased’’ porcine liver specimens to obtain the deformation surrounding the indenter site. An inverse finite element (FE) algorithm was developed to determine the optimal material parameters of the healthy liver tissue. With these parameters, a computational model of tumorous tissue was constructed to quantitatively evaluate the effects of the tumor location on the induced deformation. By relating the experimental data from the ‘‘diseased’’ liver specimen to the computational results, we estimated the radial distance between the tumor and the indenter, as well as the angular position of the tumor relative to the indenter. Keywords—Soft tissue modeling, Inverse finite element analysis, Tumor locating, Surgical indentation, Robotic-assisted minimally invasive surgery.
Address correspondence to Yingqiao Yang, Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, R606, 1 Yuk Road, Hung Hom, Kowloon, Hong Kong. Electronic mail: [email protected]
INTRODUCTION Imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI) allow clinicians to detect tumor(s) and map their position inside the human body before surgery. However, the location of a tumor at the intraoperative stage may have moved from where it was located due to living organs moving with body orientation, respiration, and surgical manipulations.10,25 Updating the intraoperative tumor location is necessary for surgeons to make precise resections with minimum damage to the organ. Although there are different types of tumors and some of them are softer than the surrounding tissue, in this study, we mainly focus on the tumors typically stiffer than the healthy tissue, which are also the majority.14,28 Surgeons in open surgery exploit this
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