Literature DB >> 33040602

Accuracy of Touch-Based Registration During Robotic Image-Guided Partial Nephrectomy Before and After Tumor Resection in Validated Phantoms.

Nicholas L Kavoussi1, Bryn Pitt2, James M Ferguson2, Josephine Granna2, Andria Remirez2, Naren Nimmagadda1, Rachel Melnyk3, Ahmed Ghazi4, Eric J Barth2, Robert J Webster2, Stanley Duke Herrell1.   

Abstract

Aim: Image-guided surgery (IGS) allows for accurate, real-time localization of subsurface critical structures during surgery. No prior IGS systems have described a feasible method of intraoperative reregistration after manipulation of the kidney during robotic partial nephrectomy (PN). We present a method for seamless reregistration during IGS and evaluate accuracy before and after tumor resection in two validated kidney phantoms. Materials and
Methods: We performed robotic PN on two validated kidney phantoms-one with an endophytic tumor and one with an exophytic tumor-with our IGS system utilizing the da Vinci Xi robot. Intraoperatively, the kidney phantoms' surfaces were digitized with the da Vinci robotic manipulator via a touch-based method and registered to a three-dimensional segmented model created from cross-sectional CT imaging of the phantoms. Fiducial points were marked with a surgical marking pen and identified after the initial registration using the robotic manipulator. Segmented images were displayed via picture-in-picture in the surgeon console as tumor resection was performed. After resection, reregistration was performed by reidentifying the fiducial points. The accuracy of the initial registration and reregistration was compared.
Results: The root mean square (RMS) averages of target registration error (TRE) were 2.53 and 4.88 mm for the endophytic and exophytic phantoms, respectively. IGS enabled resection along preplanned contours. Specifically, the RMS averages of the normal TRE over the entire resection surface were 0.75 and 2.15 mm for the endophytic and exophytic phantoms, respectively. Both tumors were resected with grossly negative margins. Point-based reregistration enabled instantaneous reregistration with minimal impact on RMS TRE compared with the initial registration (from 1.34 to 1.70 mm preresection and from 1.60 to 2.10 mm postresection). Conclusions: We present a novel and accurate registration and reregistration framework for use during IGS for PN with the da Vinci Xi surgical system. The technology is easily integrated into the surgical workflow and does not require additional hardware.

Entities:  

Keywords:  image-guided surgery; kidney cancer; robotics

Mesh:

Year:  2020        PMID: 33040602      PMCID: PMC7987368          DOI: 10.1089/end.2020.0363

Source DB:  PubMed          Journal:  J Endourol        ISSN: 0892-7790            Impact factor:   2.619


  14 in total

1.  Kidney deformation and intraprocedural registration: a study of elements of image-guided kidney surgery.

Authors:  Hernan O Altamar; Rowena E Ong; Courtenay L Glisson; Davis P Viprakasit; Michael I Miga; Stanley Duke Herrell; Robert L Galloway
Journal:  J Endourol       Date:  2010-12-13       Impact factor: 2.942

2.  Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration.

Authors:  Jiaolong Yang; Hongdong Li; Dylan Campbell; Yunde Jia
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2015-12-30       Impact factor: 6.226

3.  Feasibility study for image-guided kidney surgery: assessment of required intraoperative surface for accurate physical to image space registrations.

Authors:  Anne B Benincasa; Logan W Clements; S Duke Herrell; Robert L Galloway
Journal:  Med Phys       Date:  2008-09       Impact factor: 4.071

4.  Surgical navigation using three-dimensional computed tomography images fused intraoperatively with live video.

Authors:  Kazuhiro Nakamura; Yukio Naya; Satoki Zenbutsu; Kazuhiro Araki; Shuko Cho; Sho Ohta; Naoki Nihei; Hiroyoshi Suzuki; Tomohiko Ichikawa; Tatsuo Igarashi
Journal:  J Endourol       Date:  2010-04       Impact factor: 2.942

5.  Augmented reality to the rescue of the minimally invasive surgeon. The usefulness of the interposition of stereoscopic images in the Da Vinci™ robotic console.

Authors:  Francesco Volonté; Nicolas C Buchs; François Pugin; Joël Spaltenstein; Boris Schiltz; Minoa Jung; Monika Hagen; Osman Ratib; Philippe Morel
Journal:  Int J Med Robot       Date:  2012-12-13       Impact factor: 2.547

6.  A novel method for texture-mapping conoscopic surfaces for minimally invasive image-guided kidney surgery.

Authors:  Rowena Ong; Courtenay L Glisson; Jessica Burgner-Kahrs; Amber Simpson; Andrei Danilchenko; Ray Lathrop; S Duke Herrell; Robert J Webster; Michael Miga; Robert L Galloway
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-01-13       Impact factor: 2.924

7.  An effective visualisation and registration system for image-guided robotic partial nephrectomy.

Authors:  Philip Pratt; Erik Mayer; Justin Vale; Daniel Cohen; Eddie Edwards; Ara Darzi; Guang-Zhong Yang
Journal:  J Robot Surg       Date:  2012-01-13

8.  Comparison study of intraoperative surface acquisition methods for surgical navigation.

Authors:  Amber L Simpson; Jessica Burgner; Courtenay L Glisson; S Duke Herrell; Burton Ma; Thomas S Pheiffer; Robert J Webster; Michael I Miga
Journal:  IEEE Trans Biomed Eng       Date:  2012-08-23       Impact factor: 4.538

9.  Augmented reality: a new tool to improve surgical accuracy during laparoscopic partial nephrectomy? Preliminary in vitro and in vivo results.

Authors:  Dogu Teber; Selcuk Guven; Tobias Simpfendörfer; Mathias Baumhauer; Esref Oguz Güven; Faruk Yencilek; Ali Serdar Gözen; Jens Rassweiler
Journal:  Eur Urol       Date:  2009-05-19       Impact factor: 20.096

10.  Mechanical and functional validation of a perfused, robot-assisted partial nephrectomy simulation platform using a combination of 3D printing and hydrogel casting.

Authors:  Rachel Melnyk; Bahie Ezzat; Elizabeth Belfast; Patrick Saba; Shamroz Farooq; Timothy Campbell; Stephen McAleavey; Mark Buckley; Ahmed Ghazi
Journal:  World J Urol       Date:  2019-11-02       Impact factor: 4.226

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  4 in total

1.  Robotic partial nephrectomy in 3D virtual reconstructions era: is the paradigm changed?

Authors:  Enrico Checcucci; Francesco Porpiglia; Daniele Amparore; Federico Piramide; Sabrina De Cillis; Paolo Verri; Alberto Piana; Angela Pecoraro; Mariano Burgio; Matteo Manfredi; Umberto Carbonara; Michele Marchioni; Riccardo Campi; Cristian Fiori
Journal:  World J Urol       Date:  2022-02-22       Impact factor: 4.226

Review 2.  New imaging technologies for robotic kidney cancer surgery.

Authors:  Stefano Puliatti; Ahmed Eissa; Enrico Checcucci; Pietro Piazza; Marco Amato; Stefania Ferretti; Simone Scarcella; Juan Gomez Rivas; Mark Taratkin; Josè Marenco; Ines Belenchon Rivero; Karl-Friedrich Kowalewski; Giovanni Cacciamani; Ahmed El-Sherbiny; Ahmed Zoeir; Abdelhamid M El-Bahnasy; Ruben De Groote; Alexandre Mottrie; Salvatore Micali
Journal:  Asian J Urol       Date:  2022-06-01

Review 3.  Patient-specific, touch-based registration during robotic, image-guided partial nephrectomy.

Authors:  Naren Nimmagadda; James M Ferguson; Nicholas L Kavoussi; Bryn Pitt; Eric J Barth; Josephine Granna; Robert J Webster; S Duke Herrell
Journal:  World J Urol       Date:  2021-06-16       Impact factor: 4.226

Review 4.  Machine learning applications to enhance patient specific care for urologic surgery.

Authors:  Patrick W Doyle; Nicholas L Kavoussi
Journal:  World J Urol       Date:  2021-05-28       Impact factor: 4.226

  4 in total

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