ArticleInternational journal of computer assisted radiology and surgery2017
Automated multiple trajectory planning algorithm for the placement of stereo-electroencephalography (SEEG) electrodes in epilepsy treatment.
Article in International journal of computer assisted radiology and surgery, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.
- Automatic Path-Planning Techniques for Minimally Invasive Stereotactic Neurosurgical Procedures-A Systematic Review.Sensors (Basel, Switzerland) · 2024Pooled it
- Computer-assisted stereoelectroencephalography planning: center-specific priors enhance planning.Frontiers in neurology · 2025Article
- Implantation accuracy of novel polyimide stereotactic electroencephalographic depth electrodes-a human cadaveric study.Frontiers in medical technology · 2024Article
- Optimization of patient-specific stereo-EEG recording sensitivity.Brain communications · 2023Article
- Validation of a novel path planner for stereotactic neurosurgical interventions-A retrospective clinical study.The international journal of medical robotics + computer assisted surgery : MRCAS · 2022Article
- Previous, current, and future stereotactic EEG techniques for localising epileptic foci.Expert review of medical devices · 2022Review
- FreeSurfer and 3D Slicer-Assisted SEEG Implantation for Drug-Resistant Epilepsy.Frontiers in neurorobotics · 2022Article
- Software tool for visualization of a probabilistic map of the epileptogenic zone from seizure semiologies.Frontiers in neuroinformatics · 2022Article
- Automated computation and analysis of accuracy metrics in stereoencephalography.Journal of neuroscience methods · 2020Article
- Automation Advances in Stereoelectroencephalography Planning.Neurosurgery clinics of North America · 2020Review
- Refining Planning for Stereoelectroencephalography: A Prospective Validation of Spatial Priors for Computer-Assisted Planning With Application of Dynamic Learning.Frontiers in neurology · 2020Article
- CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer Assisted Interventions.Proceedings of the IEEE. Institute of Electrical and Electronics Engineers · 2020Article
- The Effect of Vascular Segmentation Methods on Stereotactic Trajectory Planning for Drug-Resistant Focal Epilepsy: A Retrospective Cohort Study.World neurosurgery: X · 2019Article
- Stereoelectroencephalography electrode placement: Detection of blood vessel conflicts.Epilepsia · 2019Article
- Improving patient safety during introduction of novel medical devices through cumulative summation analysis.Journal of neurosurgery · 2019Article
- Stereoelectroencephalography in epilepsy, cognitive neurophysiology, and psychiatric disease: safety, efficacy, and place in therapy.Neuropsychiatric disease and treatment · 2019Review
- Optimizing Trajectories for Cranial Laser Interstitial Thermal Therapy Using Computer-Assisted Planning: A Machine Learning Approach.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2019Article
- Comparison of interactive and automatic segmentation of stereoelectroencephalography electrodes on computed tomography post-operative images: preliminary results.Healthcare technology letters · 2018Article
- Automatic segmentation of stereoelectroencephalography (SEEG) electrodes post-implantation considering bending.International journal of computer assisted radiology and surgery · 2018Article
- Getting the best outcomes from epilepsy surgery.Annals of neurology · 2018Review
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeAbout one-third of individuals with focal epilepsy continue to have seizures despite optimal medical management. These patients are potentially curable with neurosurgery if the epileptogenic zone (EZ) can be identified and resected. Stereo-electroencephalography (SEEG) to record epileptic activity with intracranial depth electrodes may be required to identify the EZ. Each SEEG electrode trajectory, the path between the entry on the skull and the cerebral target, must be planned carefully to avoid trauma to blood vessels and conflicts between electrodes. In current clinical practice trajectories are determined manually, typically taking 2-3 h per patient (15 min per electrode). Manual planning (MP) aims to achieve an implantation plan with good coverage of the putative EZ, an optimal spatial resolution, and 3D distribution of electrodes. Computer-assisted planning tools can reduce planning time by quantifying trajectory suitability.
methodsWe present an automated multiple trajectory planning (MTP) algorithm to compute implantation plans. MTP uses dynamic programming to determine a set of plans. From this set a depth-first search algorithm finds a suitable plan. We compared our MTP algorithm to (a) MP and (b) an automated single trajectory planning (STP) algorithm on 18 patient plans containing 165 electrodes.
resultsMTP changed all 165 trajectories compared to MP. Changes resulted in lower risk (122), increased grey matter sampling (99), shorter length (92), and surgically preferred entry angles (113). MTP changed 42 % (69/165) trajectories compared to STP. Every plan had between 1 to 8 (median 3.5) trajectories changed to resolve electrode conflicts, resulting in surgically preferred plans.
conclusionMTP is computationally efficient, determining implantation plans containing 7-12 electrodes within 1 min, compared to 2-3 h for MP.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.