How accurately are subthalamic nucleus electrodes implanted relative to the ideal stimulation location for Parkinson's disease?

Anatomical targeting for electrode localization in subthalamic nucleus deep brain stimulation: A comparative study

BACKGROUND AND PURPOSE

In deep brain stimulation (DBS), accurate electrode placement is essential for optimizing patient outcomes. Localizing electrodes enables insight into therapeutic outcomes and development of metrics for use in clinical trials. Methods of defining anatomical targets have been described with varying accuracy and objectivity. To assess variability in anatomical targeting, we compare four methods of defining an appropriate target for DBS of the subthalamic nucleus for Parkinson's disease.

METHODS

The methods compared are direct visualization, red nucleus-based indirect targeting, mid-commissural point-based indirect targeting, and automated template-based targeting. This study assessed 226 hemispheres in 113 DBS recipients (39 females, 73 males, 62.2 ± 7.7 years). We utilized the electrode placement error (the Euclidean distance between the defined target and closest DBS electrode) as a metric for comparative analysis. Pairwise differences in electrode placement error across the four methods were compared using the Kruskal-Wallis H-test and Wilcoxon signed-rank tests.

RESULTS

Interquartile ranges of the differences in electrode placement error spanned 1.18-1.56 mm. A Kruskal-Wallis H-test reported a statistically significant difference in the median of at least two groups (H(5) = 41.052, p < .001). Wilcoxon signed-rank tests reported statistically significant difference in two comparisons: direct visualization versus red nucleus-based indirect, and direct visualization versus automated template-based methods (T < 9215, p < .001).

CONCLUSIONS

All methods were similarly discordant in their relative accuracy, despite having significant technical differences in their application. The differing protocols and technical aspects of each method, however, have the implication that one may be more practical depending on the clinical or research application at hand.

Evaluation of the PaCER Algorithm for Postoperative Subthalamic Nucleus Deep Brain Stimulation Electrode Localization. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023;2023:1-4. [PMID: 38083396 DOI: 10.1109/embc40787.2023.10340555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Deep Brain Stimulation (DBS) is an established therapy for many movement disorders. DBS entails electrical stimulation of precise brain structures using permanently implanted electrodes. Following implantation, locating the electrodes relative to the target brain structure assists patient outcome optimization. Here we evaluated an open-source automatic algorithm (PaCER) to localize individual electrodes on Computed Tomography imaging (co-registered to Magnetic Resonance Imaging). In a dataset of 111 participants, we found a modified version of the algorithm matched manual-markups with median error less than 0.191 mm (interquartile range 0.698 mm). Given the error is less than the voxel resolution (1 mm3) of the images, we conclude that the automatic algorithm is suitable for DBS electrode localizations.Clinical Relevance- Automated DBS electrode localization identifies the closest electrode to the target brain structure; allowing the neurologist to direct electrical stimulation to maximize patient outcomes. Further, if none of the electrodes are deemed suitable, localization will guide re-implantation.