Literature DB >> 17564173

Application accuracy in frameless image-guided neurosurgery: a comparison study of three patient-to-image registration methods.

Peter A Woerdeman1, Peter W A Willems, Herke J Noordmans, Cornelis A F Tulleken, Jan Willem Berkelbach van der Sprenkel.   

Abstract

OBJECT: The aim of this study was to compare three patient-to-image registration methods in frameless stereotaxy in terms of their application accuracy (the accuracy with which the position of a target can be determined intraoperatively). In frameless stereotaxy, imaging information is transposed to the surgical field to show the spatial position of a localizer or surgical instrument. The mathematical relationship between the image volume and the surgical working space is calculated using a rigid body transformation algorithm, based on point-pair matching or surface matching.
METHODS: Fifty patients who were scheduled to undergo a frameless image-guided neurosurgical procedure were included in the study. Prior to surgery, the patients underwent either computerized tomography (CT) scanning or magnetic resonance (MR) imaging with widely distributed adhesive fiducial markers on the scalp. An extra fiducial marker was placed on the head as a target, as near as possible to the intracranial lesion. Prior to each surgical procedure, an optical tracking system was used to perform three separate patient-to-image registration procedures, using anatomical landmarks, adhesive markers, or surface matching. Subsequent to each registration, the target registration error (TRE), defined as the Euclidean distance between the image space coordinates and world space coordinates of the target marker, was determined. Independent of target location or imaging modality, mean application accuracy (+/- standard deviation) was 2.49 +/- 1.07 mm when using adhesive markers. Using the other two registration strategies, mean TREs were significantly larger (surface matching, 5.03 +/- 2.30 mm; anatomical landmarks, 4.97 +/- 2.29 mm; p < 0.001 for both).
CONCLUSIONS: The results of this study show that skin adhesive fiducial marker registration is the most accurate noninvasive registration method. When images from an earlier study are to be used and accuracy may be slightly compromised, anatomical landmarks and surface matching are equally accurate alternatives.

Entities:  

Mesh:

Year:  2007        PMID: 17564173     DOI: 10.3171/jns.2007.106.6.1012

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  18 in total

1.  General approach to first-order error prediction in rigid point registration.

Authors:  Andrei Danilchenko; J Michael Fitzpatrick
Journal:  IEEE Trans Med Imaging       Date:  2010-11-11       Impact factor: 10.048

2.  Comparative study of application accuracy of two frameless neuronavigation systems: experimental error assessment quantifying registration methods and clinically influencing factors.

Authors:  Dimitrios Paraskevopoulos; Andreas Unterberg; Roland Metzner; Jens Dreyhaupt; Georg Eggers; Christian Rainer Wirtz
Journal:  Neurosurg Rev       Date:  2011-01-19       Impact factor: 3.042

3.  The role of registration in accurate surgical guidance.

Authors:  J M Fitzpatrick
Journal:  Proc Inst Mech Eng H       Date:  2010       Impact factor: 1.617

4.  Regional-surface-based registration for image-guided neurosurgery: effects of scan modes on registration accuracy.

Authors:  Yuan Dong; Chenxi Zhang; Dafeng Ji; Manning Wang; Zhijian Song
Journal:  Int J Comput Assist Radiol Surg       Date:  2019-05-04       Impact factor: 2.924

Review 5.  Image-guided, stereotactic perforator flap surgery: a prospective comparison of current techniques and review of the literature.

Authors:  W M Rozen; A Buckland; M W Ashton; D L Stella; T J Phillips; G I Taylor
Journal:  Surg Radiol Anat       Date:  2009-01-22       Impact factor: 1.246

6.  Customized, rapid-production microstereotactic table for surgical targeting: description of concept and in vitro validation.

Authors:  Robert F Labadie; Jason Mitchell; Ramya Balachandran; J Michael Fitzpatrick
Journal:  Int J Comput Assist Radiol Surg       Date:  2009-02-28       Impact factor: 2.924

7.  Strategies for Improving and Evaluating Robot Registration Performance.

Authors:  Karl Van Wyk; Jeremy A Marvel
Journal:  IEEE Trans Autom Sci Eng       Date:  2018       Impact factor: 5.083

8.  Calibrating 3D Scanner in the Coordinate System of Optical Tracker for Image-To-Patient Registration.

Authors:  Wenjie Li; Jingfan Fan; Shaowen Li; Zhaorui Tian; Zhao Zheng; Danni Ai; Hong Song; Jian Yang
Journal:  Front Neurorobot       Date:  2021-05-14       Impact factor: 2.650

9.  Quantitative error analysis for computer assisted navigation: a feasibility study.

Authors:  Ö Güler; M Perwög; F Kral; F Schwarm; Z R Bárdosi; G Göbel; W Freysinger
Journal:  Med Phys       Date:  2013-02       Impact factor: 4.071

10.  3D preoperative planning in the ER with OsiriX®: when there is no time for neuronavigation.

Authors:  Mauricio Mandel; Robson Amorim; Wellingson Paiva; Marcelo Prudente; Manoel Jacobsen Teixeira; Almir Ferreira de Andrade
Journal:  Sensors (Basel)       Date:  2013-05-16       Impact factor: 3.576

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.