Precise Electrode Co-Alignment in Deep Brain Stimulation Fusing Neuroimaging and Electrophysiology
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378050%3A_____%2F25%3A00643720" target="_blank" >RIV/68378050:_____/25:00643720 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21230/25:00388062 RIV/00023752:_____/25:43921645 RIV/00216208:11110/25:10506533 RIV/00064165:_____/25:10506533
Result on the web
<a href="https://doi.org/10.1111/ejn.70309" target="_blank" >https://doi.org/10.1111/ejn.70309</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1111/ejn.70309" target="_blank" >10.1111/ejn.70309</a>
Alternative languages
Result language
angličtina
Original language name
Precise Electrode Co-Alignment in Deep Brain Stimulation Fusing Neuroimaging and Electrophysiology
Original language description
We present a multimodal framework to improve the precision of electrode placement in deep brain stimulation (DBS) by fusing preoperative neuroimaging with intraoperative electrophysiology for accurate electrode co-alignment. The workflow integrates automated subthalamic nucleus (STN) segmentation from preoperative MRI using a two-step convolutional neural network (CNN), classification of microelectrode recordings (MER) with a transformer encoder and spatial co-alignment via a discrete optimisation procedure. Implemented as a 3D Slicer plugin, the pipeline enables real-time visualisation and interactive use during surgery. In validation on retrospective data of 17 trajectories from 12 Parkinson's disease patients, co-alignment reduced the mean lateral localisation error by 0.3 mm relative to an intraoperative reference, indicating improved agreement between electrophysiological and anatomical targets. Automated STN segmentation achieved a Dice similarity of 0.62 +/- 0.10, providing a robust starting point for manual refinement. This approach improves the understanding of electrode position within STN during surgery, incorporating preoperative and intraoperative data, offers clinicians a practical, real-time tool to enhance targeting accuracy. By directly integrating imaging and MER evidence, the framework addresses persistent challenges in DBS and represents a step toward more personalised and precise neurosurgical interventions.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10608 - Biochemistry and molecular biology
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
European Journal of Neuroscience
ISSN
0953-816X
e-ISSN
1460-9568
Volume of the periodical
62
Issue of the periodical within the volume
10
Country of publishing house
GB - UNITED KINGDOM
Number of pages
12
Pages from-to
e70309
UT code for WoS article
001628117400017
EID of the result in the Scopus database
2-s2.0-105022314651