Lead-DBS Demonstrates Sensory-Motor Nucleus Stimulation: A Real-Life Simulation of a Computerized Tool in Parkinson’s Disease
WSSFN 2025 Interim Meeting. Abstract 0084.
DOI:
https://doi.org/10.47924/neurotarget2025532Resumen
Introduction: Medical literature consistently identifies the sensorimotor region within the subthalamic nucleus (STN) and internal globus pallidus (GPi) as the optimal targets for Deep Brain Stimulation (DBS) in Parkinson’s disease. Accurate electrode placement and adequate stimulation of these regions are directly associated with better clinical outcomes. To assess surgical precision and stimulation effects, neuroimaging-based software tools such as Lead-DBS can localize electrode positions and estimate the volume of tissue activated (VTA). In this study, we applied Lead-DBS to a real-life Parkinson’s disease population to analyze electrode localization, simulate VTAs, and visually confirm stimulation overlap with the sensorimotor subregions.
Method: We conducted a cross-sectional analysis of patients with Parkinson’s disease who underwent DBS surgery at a Brazilian neurosurgical center between 2022 and 2025. Preoperative high-resolution MRI and postoperative CT scans were processed using Lead-DBS software (version 3.2), following a standardized workflow including image coregistration, spatial normalization, and semiautomatic electrode reconstruction. ‘Sweetspot’ mapping was then conducted, taking into account the latest individual stimulation parameters. To improve anatomical interpretation, VTA data were exported to the 3D Slicer software (Version 5.8), overlaid on a T1-weighted atlas, and rendered using color-graded filters representing activation intensity.
Results: Nineteen patients (38 electrodes) were included in the study, with 12 cases targeting the STN and seven targeting the GPi. Group electrode reconstruction demonstrated close anatomical proximity to the intended sensorimotor targets. Sweetspot simulation revealed predominant stimulation of the dorsolateral portion of both the STN and GPi, corresponding to the sensorimotor subregions.
Discussion: Lead-DBS has proven to be a practical and accessible tool for postoperative electrode localization and stimulation field visualization in a real-life clinical population. The observed stimulation patterns were aligned with the established sensorimotor target zones reported in the literature. Nevertheless, further studies are warranted to validate its clinical predictive value.
Conclusions: Lead-DBS effectively demonstrated stimulation of the sensorimotor subnuclei in a real-life Parkinson’s disease population, reinforcing its utility for anatomical and functional visualization in DBS surgery.
Métricas
Citas
Horn A, Li N, Dembek TA, Kappel A, Boulay C, Ewert S, et al. Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging. NeuroImage. 2019;184.
Neudorfer C, Butenko K, Oxenford S, Rajamani N, Achtzehn J, Goede L, et al. Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks. NeuroImage. 2023;268.
Kovačević J, Meijering E. 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings: Welcome. 2006.
Maks CB, Butson CR, Walter BL, Vitek JL, McIntyre CC. Deep brain stimulation activation volumes and their association with neurophysiological mapping and therapeutic outcomes. Journal of Neurology, Neurosurgery and Psychiatry. 2009;80(6).
Follett KA, Weaver FM, Stern M, Hur K, Harris CL, Luo P, et al. Pallidal versus Subthalamic Deep-Brain Stimulation for Parkinson’s Disease. New England Journal of Medicine. 2010;362(22).
Descargas
Publicado
Cómo citar
Número
Sección
Licencia
Derechos de autor 2025 Renato Renato Barradas Rodrigues, Leonardo De Favi Bocca, Ana Victoria Calado Godoy Carlos De Lima, Thiago Garcia Varga, Rubens Mendes Martins Da Silva, Thiago Pereira Rodrigues, Carolina Candeias Da Silva, Ricardo Silva Centeno

Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
Este artículo se distribuye bajo la licencia Creative Commons Attribution 4.0 License. A menos que se indique lo contrario, el material publicado asociado se distribuye bajo la misma licencia.
