Literature DB >> 12768493

Computer-assisted orthopedic surgery.

Nobuhiko Sugano1.   

Abstract

Computer-assisted surgery (CAS) utilizing robotic or image-guided technologies has been introduced into various orthopedic fields. Navigation and robotic systems are the most advanced parts of CAS, and their range of functions and applications is increasing. Surgical navigation is a visualization system that gives positional information about surgical tools or implants relative to a target organ (bone) on a computer display. There are three types of surgical planning that involve navigation systems. One makes use of volumetric images, such as computed tomography, magnetic resonance imaging, or ultrasound echograms. Another makes use of intraoperative fluoroscopic images. The last type makes use of kinetic information about joints or morphometric information about the target bones obtained intraoperatively. Systems that involve these planning methods are called volumetric image-based navigation, fluoroscopic navigation, and imageless navigation, respectively. To overcome the inaccuracy of hand-controlled positioning of surgical tools, three robotic systems have been developed. One type directs a cutting guide block or a drilling guide sleeve, with surgeons sliding a bone saw or a drill bit through the guide instrument to execute a surgical action. Another type constrains the range of movement of a surgical tool held by a robot arm such as ACROBOT. The last type is an active system, such as ROBODOC or CASPAR, which directs a milling device automatically according to preoperative planning. These CAS systems, their potential, and their limitations are reviewed here. Future technologies and future directions of CAS that will help provide improved patient outcomes in a cost-effective manner are also discussed.

Entities:  

Mesh:

Year:  2003        PMID: 12768493     DOI: 10.1007/s10776-002-0623-6

Source DB:  PubMed          Journal:  J Orthop Sci        ISSN: 0949-2658            Impact factor:   1.601


  19 in total

Review 1.  Pedicle screw insertion accuracy with different assisted methods: a systematic review and meta-analysis of comparative studies.

Authors:  Nai-Feng Tian; Qi-Shan Huang; Ping Zhou; Yang Zhou; Rui-Kai Wu; Yi Lou; Hua-Zi Xu
Journal:  Eur Spine J       Date:  2010-09-23       Impact factor: 3.134

2.  [Navigated drilling for femoral head necrosis. Experimental and clinical results].

Authors:  J Beckmann; M Tingart; L Perlick; C Lüring; J Grifka; S Anders
Journal:  Orthopade       Date:  2007-05       Impact factor: 1.087

3.  Evaluation of accuracy of an electromagnetic computer-assisted navigation system in total knee arthroplasty.

Authors:  A J Graydon; S Malak; I A Anderson; R P Pitto
Journal:  Int Orthop       Date:  2008-05-28       Impact factor: 3.075

4.  FCN-based approach for the automatic segmentation of bone surfaces in ultrasound images.

Authors:  M Villa; G Dardenne; M Nasan; H Letissier; C Hamitouche; E Stindel
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-09-07       Impact factor: 2.924

5.  Co-localized augmented human and X-ray observers in collaborative surgical ecosystem.

Authors:  Javad Fotouhi; Mathias Unberath; Tianyu Song; Jonas Hajek; Sing Chun Lee; Bastian Bier; Andreas Maier; Greg Osgood; Mehran Armand; Nassir Navab
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-07-26       Impact factor: 2.924

Review 6.  Computer-assisted Orthopaedic Surgery.

Authors:  David Hernandez; Roja Garimella; Adam E M Eltorai; Alan H Daniels
Journal:  Orthop Surg       Date:  2017-06-07       Impact factor: 2.071

7.  Computer-assisted hip and knee arthroplasty. Navigation and active robotic systems: an evidence-based analysis.

Authors: 
Journal:  Ont Health Technol Assess Ser       Date:  2004-02-01

8.  CT-based automated planning of acetabular cup for total hip arthroplasty (THA) based on hybrid use of two statistical atlases.

Authors:  Yoshiyuki Kagiyama; Itaru Otomaru; Masaki Takao; Nobuhiko Sugano; Masahiko Nakamoto; Futoshi Yokota; Noriyuki Tomiyama; Yukio Tada; Yoshinobu Sato
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-06-25       Impact factor: 2.924

9.  Anatomical evaluation of CT-MRI combined femoral model.

Authors:  Yeon S Lee; Jong K Seon; Vladimir I Shin; Gyu-Ha Kim; Moongu Jeon
Journal:  Biomed Eng Online       Date:  2008-01-30       Impact factor: 2.819

10.  Is the transverse acetabular ligament a reliable cup orientation guide?

Authors:  Hirohito Abe; Takashi Sakai; Toshimitsu Hamasaki; Masaki Takao; Takashi Nishii; Nobuo Nakamura; Nobuhiko Sugano
Journal:  Acta Orthop       Date:  2012-09-14       Impact factor: 3.717

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