Ihor Varha presents Precise Electrode Co-Alignment in Deep Brain Stimulation Fusing Neuroimaging and Electrophysiology
On 2026-01-29 - 2026-01-29 11:00:00 at G205, Karlovo náměstí 13, Praha 2
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 [1, 20 mins lecture + 10 mins discussion].
[1] Varga I, Novak D, Urgosik D, Kybic J, Ruzicka F, Filip P, Jech R, Horn A,
Bakstein E. Precise Electrode Co-Alignment in Deep Brain Stimulation Fusing
Neuroimaging and Electrophysiology. Eur J Neurosci. 2025
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 [1, 20 mins lecture + 10 mins discussion].
[1] Varga I, Novak D, Urgosik D, Kybic J, Ruzicka F, Filip P, Jech R, Horn A,
Bakstein E. Precise Electrode Co-Alignment in Deep Brain Stimulation Fusing
Neuroimaging and Electrophysiology. Eur J Neurosci. 2025