Literature DB >> 17644002

Brain mapping in stereotactic surgery: a brief overview from the probabilistic targeting to the patient-based anatomic mapping.

Jean-Jacques Lemaire1, Jérôme Coste, Lemlih Ouchchane, François Caire, Christophe Nuti, Philippe Derost, Vittorio Cristini, Jean Gabrillargues, Simone Hemm, Franck Durif, Jean Chazal.   

Abstract

In this article, we briefly review the concept of brain mapping in stereotactic surgery taking into account recent advances in stereotactic imaging. The gold standard continues to rely on probabilistic and indirect targeting, relative to a stereotactic reference, i.e., mostly the anterior (AC) and the posterior (PC) commissures. The theoretical position of a target defined on an atlas is transposed into the stereotactic space of a patient's brain; final positioning depends on electrophysiological analysis. The method is also used to analyze final electrode or lesion position for a patient or group of patients, by projection on an atlas. Limitations are precision of definition of the AC-PC line, probabilistic location and reliability of the electrophysiological guidance. Advances in MR imaging, as from 1.5-T machines, make stereotactic references no longer mandatory and allow an anatomic mapping based on an individual patient's brain. Direct targeting is enabled by high-quality images, an advanced anatomic knowledge and dedicated surgical software. Labeling associated with manual segmentation can help for the position analysis along non-conventional, interpolated planes. Analysis of final electrode or lesion position, for a patient or group of patients, could benefit from the concept of membership, the attribution of a weighted membership degree to a contact or a structure according to its level of involvement. In the future, more powerful MRI machines, diffusion tensor imaging, tractography and computational modeling will further the understanding of anatomy and deep brain stimulation effects.

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Year:  2007        PMID: 17644002     DOI: 10.1016/j.neuroimage.2007.05.055

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  18 in total

1.  Influence of heterogeneous and anisotropic tissue conductivity on electric field distribution in deep brain stimulation.

Authors:  Mattias Aström; Jean-Jacques Lemaire; Karin Wårdell
Journal:  Med Biol Eng Comput       Date:  2011-11-19       Impact factor: 2.602

2.  Generation of individualized thalamus target maps by using statistical shape models and thalamocortical tractography.

Authors:  A Jakab; R Blanc; E L Berényi; G Székely
Journal:  AJNR Am J Neuroradiol       Date:  2012-06-14       Impact factor: 3.825

3.  Probabilistic analysis of activation volumes generated during deep brain stimulation.

Authors:  Christopher R Butson; Scott E Cooper; Jaimie M Henderson; Barbara Wolgamuth; Cameron C McIntyre
Journal:  Neuroimage       Date:  2010-10-23       Impact factor: 6.556

4.  Visualization of intra-thalamic nuclei with optimized white-matter-nulled MPRAGE at 7T.

Authors:  Thomas Tourdias; Manojkumar Saranathan; Ives R Levesque; Jason Su; Brian K Rutt
Journal:  Neuroimage       Date:  2013-09-07       Impact factor: 6.556

Review 5.  Automated neurosurgical stereotactic planning for intraoperative use: a comprehensive review of the literature and perspectives.

Authors:  Marc Zanello; Romain Carron; Sophie Peeters; Pietro Gori; Alexandre Roux; Isabelle Bloch; Catherine Oppenheim; Johan Pallud
Journal:  Neurosurg Rev       Date:  2020-05-20       Impact factor: 3.042

6.  Fully automated targeting using nonrigid image registration matches accuracy and exceeds precision of best manual approaches to subthalamic deep brain stimulation targeting in Parkinson disease.

Authors:  Srivatsan Pallavaram; Pierre-François DʼHaese; Wendell Lake; Peter E Konrad; Benoit M Dawant; Joseph S Neimat
Journal:  Neurosurgery       Date:  2015-06       Impact factor: 4.654

Review 7.  A Comprehensive Review of Brain Connectomics and Imaging to Improve Deep Brain Stimulation Outcomes.

Authors:  Joshua K Wong; Erik H Middlebrooks; Sanjeet S Grewal; Leonardo Almeida; Christopher W Hess; Michael S Okun
Journal:  Mov Disord       Date:  2020-04-12       Impact factor: 10.338

8.  Deep brain stimulation in Parkinson's disease: motor effects relative to the MRI-defined STN.

Authors:  Juergen Ralf Schlaier; Christine Hanson; Annette Janzen; Claudia Fellner; Andreas Hochreiter; Martin Proescholdt; Alexander Brawanski; Max Lange
Journal:  Neurosurg Rev       Date:  2014-02-28       Impact factor: 3.042

9.  Use of efficacy probability maps for the post-operative programming of deep brain stimulation in essential tremor.

Authors:  Fenna T Phibbs; Srivatsan Pallavaram; Christopher Tolleson; Pierre-François D'Haese; Benoit M Dawant
Journal:  Parkinsonism Relat Disord       Date:  2014-09-16       Impact factor: 4.891

10.  Automated 3-dimensional brain atlas fitting to microelectrode recordings from deep brain stimulation surgeries.

Authors:  J Luis Luján; Angela M Noecker; Christopher R Butson; Scott E Cooper; Benjamin L Walter; Jerrold L Vitek; Cameron C McIntyre
Journal:  Stereotact Funct Neurosurg       Date:  2009-06-26       Impact factor: 1.875

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