Sweet spot

Sweet spot

The sweet spot is a place where a combination of factors results in a maximum response for a given amount of effort.

The results of a study of Zolal et al. suggested the possibility that atlas-based clustering, as well as diffusion tractography-based parcellation, can be useful in estimating the stimulation target (“sweet spot”) for Subthalamic deep brain stimulation for Parkinson’s disease. Atlas-based as well as diffusion-based clustering might become a useful tool in DBS trajectory planning 1).

Stimulation effects of 449 DBS settings in 21 PD patients were clinically and quantitatively assessed through standardized monopolar reviews and mapped into standard space. A sweet spot for best motor outcome was determined using voxelwise and nonparametric permutation statistics. Two independent cohorts were used to investigate whether stimulation overlap with the sweet spot could predict acute motor outcome (10 patients, 163 settings) and long-term overall Unified Parkinson’s Disease Rating Scale Part III (UPDRS-III) improvement (63 patients).

Results: Significant clusters for suppression of rigidity and akinesia, as well as for overall motor improvement, resided around the dorsolateral border of the STN. Overlap of the volume of tissue activated with the sweet spot for overall motor improvement explained R2 = 37% of the variance in acute motor improvement, more than triple what was explained by overlap with the STN (R2 = 9%) and its sensorimotor subpart (R2 = 10%). In the second independent cohort, sweet spot overlap explained R2 = 20% of the variance in long-term UPDRS-III improvement, which was equivalent to the variance explained by overlap with the STN (R2 = 21%) and sensorimotor STN (R2 = 19%).

Interpretation: This study is the first to predict clinical improvement of parkinsonian motor symptoms across cohorts based on local DBS effects only. The new approach revealed a distinct sweet spot for STN DBS in PD. Stimulation overlap with the sweet spot can predict short- and long-term motor outcome and may be used to guide DBS programming 2).

Based on local field potential data acquired from 54 patients undergoing STN-DBS, power values within alpha, beta, low beta, and high beta bands were calculated. Values were projected into common stereotactic space after DBS lead localization. Recorded beta power values were significantly higher at posterior and dorsal lead positions, as well as in active compared with inactive pairs. The peak of activity in the beta band was situated within the sensorimotor functional zone of the nucleus. In contrast, higher alpha activity was found in a more ventromedial region, potentially corresponding to associative or premotor functional zones of the STN. Beta- and alpha-power peaks were then used as seeds in a fiber tracking experiment. Here, the beta-site received more input from primary motor cortex whereas the alpha-site was more strongly connected to premotor and prefrontal areas. The results summarize predominant spatial locations of frequency signatures recorded in STN-DBS patients in a probabilistic fashion. The site of predominant beta-activity may serve as an electrophysiologically determined target for optimal outcome in STN-DBS for PD in the future 3).



Zolal A, Polanski WH, Klingelhoefer L, Kitzler HH, Linn J, Podlesek D, Sitoci-Ficici KH, Reichmann H, Leonhardt GK, Schackert G, Sobottka SB. Parcellation of the Subthalamic Nucleus in Parkinson’s Disease: A Retrospective Analysis of Atlas- and Diffusion-Based Methods. Stereotact Funct Neurosurg. 2020 Sep 23:1-8. doi: 10.1159/000509780. Epub ahead of print. PMID: 32966999.

Dembek TA, Roediger J, Horn A, Reker P, Oehrn C, Dafsari HS, Li N, Kühn AA, Fink GR, Visser-Vandewalle V, Barbe MT, Timmermann L. Probabilistic sweet spots predict motor outcome for deep brain stimulation in Parkinson disease. Ann Neurol. 2019 Oct;86(4):527-538. doi: 10.1002/ana.25567. PMID: 31376171.

Horn A, Neumann WJ, Degen K, Schneider GH, Kühn AA. Toward an electrophysiological “sweet spot” for deep brain stimulation in the subthalamic nucleus. Hum Brain Mapp. 2017 Jul;38(7):3377-3390. doi: 10.1002/hbm.23594. Epub 2017 Apr 8. PMID: 28390148; PMCID: PMC6867148.

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