Dataset Information

Surgical Retraction of Non-Uniform Deformable Layers of Tissue: 2D Robot Grasping and Path Planning.

ABSTRACT: Robotic surgical assistants (RSAs) have the potential to facilitate surgeries and reduce human fatigue. In this paper we focus on surgical retraction, the common surgical primitive of grasping and lifting a thin layer of tissue to expose an underlying area. Given a 2D cross-sectional model of heterogeneous tissue with embedded structures (such as veins) and a desired underlying exposure region, we present an algorithm that computes a set of stable and secure grasp-and-retract trajectories, and runs a 3D finite element (FEM) simulation to certify the quality of each trajectory. To choose secure candidate grasp locations, we introduce the continuous spring method and combine it with the Deformation Space (D-Space) approach to grasping deformable objects with a linearized potential energy model based on the locations of embedded bodies. Experiments show that this method produces many of the same grasps as an exhaustive computation with an FEM mesh, but is orders of magnitude cheaper: our method runs in O(? log ?) time, when ? is the number of veins, while the FEM computation takes O(pn 3) time, where n is the number of nodes in the FEM mesh and p is the number of nodes on its perimeter. Furthermore, we present a constant tissue curvature (CTC) retraction trajectory that distributes strain uniformly around the medial axis of the tissue, by moving the gripper such that the tissue follows a constant-curvature, constant-length arc. 3D FEM simulations show that the CTC achieves retractions with lower tissue strain than circular and linear trajectories. Overall, our algorithm computes and certifies a high-quality retraction in about one minute on a PC.

SUBMITTER: Jansen R

PROVIDER: S-EPMC6324737 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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Surgical Retraction of Non-Uniform Deformable Layers of Tissue: 2D Robot Grasping and Path Planning.

Jansen Rik R Hauser Kris K Chentanez Nuttapong N van der Stappen Frank F Goldberg Ken K

Proceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems 20091001

Robotic surgical assistants (RSAs) have the potential to facilitate surgeries and reduce human fatigue. In this paper we focus on <i>surgical retraction</i>, the common surgical primitive of grasping and lifting a thin layer of tissue to expose an underlying area. Given a 2D cross-sectional model of heterogeneous tissue with embedded structures (such as veins) and a desired underlying exposure region, we present an algorithm that computes a set of stable and secure grasp-and-retract trajectories ...[more]

PMID: 30631637

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Project description:BackgroundThe minimum volume standard is 100 robot-assisted radical prostatectomy (RARP) procedures per hospital in the Netherlands, so patients have to be referred to high-volume surgical centers for RARP. During preoperative work-up, prostate biopsies taken elsewhere are reassessed, with upgrading or downgrading of the initial Gleason grade group a possible consequence.ObjectiveTo determine if prostate biopsy reassessment leads to adjustment of the surgical plan regarding a nerve-sparing approach and extended pelvic lymph node dissection (ePLND) during RARP.Design setting and participantsFor 125 men who were referred to the Prosper prostate center at Canisius Wilhelmina Hospital (CWH) in the Netherlands between 2013 and 2016, results for the initial assessment of prostate biopsy by a local uropathologist were compared to results for biopsy reassessment by dedicated uropathologists at CWH.Results and limitationsThe pathologists reached agreement in 80% of the cases. In cases for which there was disagreement (n = 25), biopsy revision involved upgrading of the initial grade group in 68% and downgrading in 32%. Biopsy reassessment led to a change in surgical plan in ten cases (8%). As a result of upgrading, ePLND was performed in three patients (2%). ePLND was omitted in one patient (1%) because of downgrading. For three patients (2%) a non-nerve-sparing procedure was planned after upgrading of the initial grade group. For four patients (3%), a unilateral nerve-sparing procedure was performed after downgrading.ConclusionsThis study shows that there is large interobserver agreement between uropathologists in the assessment of Gleason grade group in prostate biopsy specimens. Reassessment rarely leads to a change in surgical plan regarding the indication for a nerve-sparing approach and ePLND. Therefore, reassessment of prostate biopsy before radical prostatectomy can be omitted when the initial pathological assessment was performed by a dedicated uropathologist.Patient summaryReassessment of the initial prostate biopsy specimen for patients referred to a specialist center for robot-assisted removal of the prostate rarely influences surgical planning and can be omitted.

Project description:Percutaneous pelvic screw placement is challenging due to narrow bone corridors surrounded by vulnerable structures and difficult visual interpretation of complex anatomical shapes in 2D x-ray projection images. To address these challenges, a system for planning, guidance, and quality assurance (QA) is presented, providing functionality analogous to surgical navigation, but based on robust 3D-2D image registration techniques using fluoroscopy images already acquired in routine workflow. Two novel aspects of the system are investigated: automatic planning of pelvic screw trajectories and the ability to account for deformation of surgical devices (K-wire deflection). Atlas-based registration is used to calculate a patient-specific plan of screw trajectories in preoperative CT. 3D-2D registration aligns the patient to CT within the projective geometry of intraoperative fluoroscopy. Deformable known-component registration (dKC-Reg) localizes the surgical device, and the combination of plan and device location is used to provide guidance and QA. A leave-one-out analysis evaluated the accuracy of automatic planning, and a cadaver experiment compared the accuracy of dKC-Reg to rigid approaches (e.g. optical tracking). Surgical plans conformed within the bone cortex by 3-4?mm for the narrowest corridor (superior pubic ramus) and??>5?mm for the widest corridor (tear drop). The dKC-Reg algorithm localized the K-wire tip within 1.1?mm and 1.4° and was consistently more accurate than rigid-body tracking (errors up to 9?mm). The system was shown to automatically compute reliable screw trajectories and accurately localize deformed surgical devices (K-wires). Such capability could improve guidance and QA in orthopaedic surgery, where workflow is impeded by manual planning, conventional tool trackers add complexity and cost, rigid tool assumptions are often inaccurate, and qualitative interpretation of complex anatomy from 2D projections is prone to trial-and-error with extended fluoroscopy time.

Dataset Information

Surgical Retraction of Non-Uniform Deformable Layers of Tissue: 2D Robot Grasping and Path Planning.

Publications

Surgical Retraction of Non-Uniform Deformable Layers of Tissue: 2D Robot Grasping and Path Planning.

Similar Datasets

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