Literature DB >> 22559661

Reduced risk trajectory planning in image-guided keyhole neurosurgery.

Reuben R Shamir1, Leo Joskowicz, Idit Tamir, Elad Dabool, Lihi Pertman, Adam Ben-Ami, Yigal Shoshan.   

Abstract

PURPOSE: The authors present and evaluate a new preoperative planning method and computer software designed to reduce the risk of candidate trajectories for straight rigid tool insertion in image-guided keyhole neurosurgery.
METHODS: Trajectories are computed based on the surgeon-defined target and a candidate entry point area on the outer head surface on preoperative CT/MRI scans. A multiparameter risk card provides an estimate of the risk of each trajectory according to its proximity to critical brain structures. Candidate entry points in the outer head surface areas are then color-coded and displayed in 3D to facilitate selection of the most adequate point. The surgeon then defines and/or revised the insertion trajectory using an interactive 3D visualization of surrounding structures. A safety zone around the selected trajectory is also computed to visualize the expected worst-case deviation from the planned insertion trajectory based on tool placement errors in previous surgeries.
RESULTS: A retrospective comparative study for ten selected targets on MRI head scans for eight patients showed a significant reduction in insertion trajectory risk. Using the authors' method, trajectories longer than 30 mm were an average of 2.6 mm further from blood vessels compared to the conventional manual method. Average planning times were 8.4 and 5.9 min for the conventional technique and the authors' method, respectively. Neurosurgeons reported improved understanding of possible risks and spatial relations for the trajectory and patient anatomy.
CONCLUSIONS: The suggested method may result in safer trajectories, shorter preoperative planning time, and improved understanding of risks and possible complications in keyhole neurosurgery.

Entities:  

Mesh:

Year:  2012        PMID: 22559661     DOI: 10.1118/1.4704643

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  12 in total

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2.  Cerebrovascular segmentation and planning of depth electrode insertion for epilepsy surgery.

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3.  Multi-trajectories automatic planner for StereoElectroEncephaloGraphy (SEEG).

Authors:  E De Momi; C Caborni; F Cardinale; G Casaceli; L Castana; M Cossu; R Mai; F Gozzo; S Francione; L Tassi; G Lo Russo; L Antiga; G Ferrigno
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4.  The role of automatic computer-aided surgical trajectory planning in improving the expected safety of stereotactic neurosurgery.

Authors:  M Trope; R R Shamir; L Joskowicz; Z Medress; G Rosenthal; A Mayer; N Levin; A Bick; Y Shoshan
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-11-20       Impact factor: 2.924

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
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6.  Stability, structure and scale: improvements in multi-modal vessel extraction for SEEG trajectory planning.

Authors:  Maria A Zuluaga; Roman Rodionov; Mark Nowell; Sufyan Achhala; Gergely Zombori; Alex F Mendelson; M Jorge Cardoso; Anna Miserocchi; Andrew W McEvoy; John S Duncan; Sébastien Ourselin
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7.  Multisurgeon, multisite validation of a trajectory planning algorithm for deep brain stimulation procedures.

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9.  Multimodal connectivity based eloquence score computation and visualisation for computer-aided neurosurgical path planning.

Authors:  Saeed M Bakhshmand; Roy Eagleson; Sandrine de Ribaupierre
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10.  Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment.

Authors:  Rachel Sparks; Gergely Zombori; Roman Rodionov; Mark Nowell; Sjoerd B Vos; Maria A Zuluaga; Beate Diehl; Tim Wehner; Anna Miserocchi; Andrew W McEvoy; John S Duncan; Sebastien Ourselin
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-07-01       Impact factor: 2.924

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