Objective: To evaluate the utility of pseudo-monopolar local field potential (LFP) recordings using Electrode Identifier (EI; automated contact-ranking algorithm) for contact selection in STN-DBS, compared to reconstructed monopolar signals derived from Electrode Survey (ES; conventional bipolar survey) recordings.

Background: Monopolar review for contact selection in STN-DBS for Parkinson’s disease is time intensive and expert dependent. LFP activity in the beta range (13-30 Hz) correlates with bradykinesia and rigidity and is modulated by dopaminergic therapy and DBS, supporting its role as a programming biomarker. The EI-feature from the Medtronic Percept^TM neurostimulator may facilitate rapid beta-guided contact selection. However, its clinical utility in routine programming remains unclear.

Method: Data were collected at Charité Universitätsmedizin Berlin and Amsterdam UMC. Optimal contacts were selected and parameters were optimized with routine clinical care. Motor outcomes were assessed with MDS-UPDRS III. LFPs were recorded in medication OFF/stimulation OFF conditions during rest. EI rankings were generated by its algorithm. ES bipolar recordings underwent offline distance-weighted reconstruction to generate monopolar rankings. Predictive accuracy (top-1 and ≥80%-thresholded top-2 contacts) was evaluated per hemisphere, and associations with motor improvement were analyzed using mixed-effects models.

Results: LFPs were recorded from 138 hemispheres. Multiple EI recordings were excluded due to unavailable rankings, insufficient signal separation, alpha peak selection, or visual spectral discordances, leaving 44 hemispheres with final level-contacts. EI demonstrated predictive performance above permutation-derived chance levels (top-1: 45%, p=0.007; top-2: 57%, p=0.146), while ES did not (top-1: 36%, p=0.003; top-2: 52%, p=0.063). Paired accuracy differences were not significant (top-1: p=0.572; top-2 p=0.856). Concordance with the clinically selected stimulation contact was not associated with responder status or motor improvement.

Conclusion: EI shows potential for guiding contact selection when reliable outputs are available but currently lacks the robustness and transparency needed for routine clinical use. Improvements in signal processing and post-processing transparency may enable EI to support initial contact selection.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/evaluating-pseudo-monopolar-lfp-recordings-from-the-stn-for-optimized-dbs-contact-selection-in-parkinsons-disease/