Literature DB >> 24799270

PyDBS: an automated image processing workflow for deep brain stimulation surgery.

Tiziano D'Albis1, Claire Haegelen, Caroline Essert, Sara Fernández-Vidal, Florent Lalys, Pierre Jannin.   

Abstract

PURPOSE: Deep brain stimulation (DBS) is a surgical procedure for treating motor-related neurological disorders. DBS clinical efficacy hinges on precise surgical planning and accurate electrode placement, which in turn call upon several image processing and visualization tasks, such as image registration, image segmentation, image fusion, and 3D visualization. These tasks are often performed by a heterogeneous set of software tools, which adopt differing formats and geometrical conventions and require patient-specific parameterization or interactive tuning. To overcome these issues, we introduce in this article PyDBS, a fully integrated and automated image processing workflow for DBS surgery.
METHODS: PyDBS consists of three image processing pipelines and three visualization modules assisting clinicians through the entire DBS surgical workflow, from the preoperative planning of electrode trajectories to the postoperative assessment of electrode placement. The system's robustness, speed, and accuracy were assessed by means of a retrospective validation, based on 92 clinical cases.
RESULTS: The complete PyDBS workflow achieved satisfactory results in 92 % of tested cases, with a median processing time of 28 min per patient.
CONCLUSION: The results obtained are compatible with the adoption of PyDBS in clinical practice.

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Year:  2014        PMID: 24799270     DOI: 10.1007/s11548-014-1007-y

Source DB:  PubMed          Journal:  Int J Comput Assist Radiol Surg        ISSN: 1861-6410            Impact factor:   2.924


  18 in total

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3.  CranialVault and its CRAVE tools: a clinical computer assistance system for deep brain stimulation (DBS) therapy.

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Journal:  Med Image Anal       Date:  2010-08-01       Impact factor: 8.545

4.  Visualization and navigation system development and application for stereotactic deep-brain neurosurgeries.

Authors:  Ting Guo; Kirk W Finnis; Andrew G Parrent; Terry M Peters
Journal:  Comput Aided Surg       Date:  2006-09

5.  Avoiding the ventricle: a simple step to improve accuracy of anatomical targeting during deep brain stimulation.

Authors:  Ludvic Zrinzo; Arjen L J van Hulzen; Alessandra A Gorgulho; Patricia Limousin; Michiel J Staal; Antonio A F De Salles; Marwan I Hariz
Journal:  J Neurosurg       Date:  2009-06       Impact factor: 5.115

6.  Least-squares fitting of two 3-d point sets.

Authors:  K S Arun; T S Huang; S D Blostein
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7.  Automatic computation of electrode trajectories for Deep Brain Stimulation: a hybrid symbolic and numerical approach.

Authors:  Caroline Essert; Claire Haegelen; Florent Lalys; Alexandre Abadie; Pierre Jannin
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-08-25       Impact factor: 2.924

8.  Anatomo-clinical atlases correlate clinical data and electrode contact coordinates: application to subthalamic deep brain stimulation.

Authors:  Florent Lalys; Claire Haegelen; Maroua Mehri; Sophie Drapier; Marc Vérin; Pierre Jannin
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9.  Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration.

Authors:  Arno Klein; Jesper Andersson; Babak A Ardekani; John Ashburner; Brian Avants; Ming-Chang Chiang; Gary E Christensen; D Louis Collins; James Gee; Pierre Hellier; Joo Hyun Song; Mark Jenkinson; Claude Lepage; Daniel Rueckert; Paul Thompson; Tom Vercauteren; Roger P Woods; J John Mann; Ramin V Parsey
Journal:  Neuroimage       Date:  2009-01-13       Impact factor: 6.556

Review 10.  Neuroimaging and deep brain stimulation.

Authors:  D Dormont; D Seidenwurm; D Galanaud; P Cornu; J Yelnik; E Bardinet
Journal:  AJNR Am J Neuroradiol       Date:  2009-09-12       Impact factor: 4.966

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  22 in total

1.  Statistical study of parameters for deep brain stimulation automatic preoperative planning of electrodes trajectories.

Authors:  Caroline Essert; Sara Fernandez-Vidal; Antonio Capobianco; Claire Haegelen; Carine Karachi; Eric Bardinet; Maud Marchal; Pierre Jannin
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-07-26       Impact factor: 2.924

2.  Connections of the dorsolateral prefrontal cortex with the thalamus: a probabilistic tractography study.

Authors:  Pierre-Jean Le Reste; C Haegelen; B Gibaud; T Moreau; X Morandi
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3.  Image-guided preoperative prediction of pyramidal tract side effect in deep brain stimulation: proof of concept and application to the pyramidal tract side effect induced by pallidal stimulation.

Authors:  Clement Baumgarten; Yulong Zhao; Paul Sauleau; Cecile Malrain; Pierre Jannin; Claire Haegelen
Journal:  J Med Imaging (Bellingham)       Date:  2016-06-30

4.  Multi-modal imaging with specialized sequences improves accuracy of the automated subcortical grey matter segmentation.

Authors:  Andrew J Plassard; Shunxing Bao; Pierre F D'Haese; Srivatsan Pallavaram; Daniel O Claassen; Benoit M Dawant; Bennett A Landman
Journal:  Magn Reson Imaging       Date:  2019-05-21       Impact factor: 2.546

5.  Self-guided training for deep brain stimulation planning using objective assessment.

Authors:  Matthew S Holden; Yulong Zhao; Claire Haegelen; Caroline Essert; Sara Fernandez-Vidal; Eric Bardinet; Tamas Ungi; Gabor Fichtinger; Pierre Jannin
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-04-04       Impact factor: 2.924

6.  Automatic preoperative planning of DBS electrode placement using anatomo-clinical atlases and volume of tissue activated.

Authors:  Olga Dergachyova; Yulong Zhao; Claire Haegelen; Pierre Jannin; Caroline Essert
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-03-20       Impact factor: 2.924

7.  Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging.

Authors:  Andreas Horn; Ningfei Li; Till A Dembek; Ari Kappel; Chadwick Boulay; Siobhan Ewert; Anna Tietze; Andreas Husch; Thushara Perera; Wolf-Julian Neumann; Marco Reisert; Hang Si; Robert Oostenveld; Christopher Rorden; Fang-Cheng Yeh; Qianqian Fang; Todd M Herrington; Johannes Vorwerk; Andrea A Kühn
Journal:  Neuroimage       Date:  2018-09-01       Impact factor: 6.556

8.  Improving recorded volume in mesial temporal lobe by optimizing stereotactic intracranial electrode implantation planning.

Authors:  R Zelmann; S Beriault; M M Marinho; K Mok; J A Hall; N Guizard; C Haegelen; A Olivier; G B Pike; D L Collins
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-03-26       Impact factor: 2.924

9.  DBStar: An Open-Source Tool Kit for Imaging Analysis with Patient-Customized Deep Brain Stimulation Platforms.

Authors:  Peter M Lauro; Shane Lee; Minkyu Ahn; Andrei Barborica; Wael F Asaad
Journal:  Stereotact Funct Neurosurg       Date:  2018-02-07       Impact factor: 1.875

10.  Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation.

Authors:  Jinyoung Kim; Yuval Duchin; Reuben R Shamir; Remi Patriat; Jerrold Vitek; Noam Harel; Guillermo Sapiro
Journal:  Hum Brain Mapp       Date:  2018-10-31       Impact factor: 5.038

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