Probabilistic maps for deep brain stimulation - Impact of methodological differences

Modeling the volume of tissue activated in deep brain stimulation and its clinical influence: a review

Deep brain stimulation (DBS) is a neuromodulatory therapy that has been FDA approved for the treatment of various disorders, including but not limited to, movement disorders (e.g., Parkinson's disease and essential tremor), epilepsy, and obsessive-compulsive disorder. Computational methods for estimating the volume of tissue activated (VTA), coupled with brain imaging techniques, form the basis of models that are being generated from retrospective clinical studies for predicting DBS patient outcomes. For instance, VTA models are used to generate target-and network-based probabilistic stimulation maps that play a crucial role in predicting DBS treatment outcomes. This review defines the methods for calculation of tissue activation (or modulation) including ones that use heuristic and clinically derived estimates and more computationally involved ones that rely on finite-element methods and biophysical axon models. We define model parameters and provide a comparison of commercial, open-source, and academic simulation platforms available for integrated neuroimaging and neural activation prediction. In addition, we review clinical studies that use these modeling methods as a function of disease. By describing the tissue-activation modeling methods and highlighting their application in clinical studies, we provide the neural engineering and clinical neuromodulation communities with perspectives that may influence the adoption of modeling methods for future DBS studies.

The role of the motor thalamus in deep brain stimulation for essential tremor

The advent of next-generation technology has significantly advanced the implementation and delivery of Deep Brain Stimulation (DBS) for Essential Tremor (ET), yet controversies persist regarding optimal targets and networks responsible for tremor genesis and suppression. This review consolidates key insights from anatomy, neurology, electrophysiology, and radiology to summarize the current state-of-the-art in DBS for ET. We explore the role of the thalamus in motor function and describe how differences in parcellations and nomenclature have shaped our understanding of the neuroanatomical substrates associated with optimal outcomes. Subsequently, we discuss how seminal studies have propagated the ventral intermediate nucleus (Vim)-centric view of DBS effects and shaped the ongoing debate over thalamic DBS versus stimulation in the posterior subthalamic area (PSA) in ET. We then describe probabilistic- and network-mapping studies instrumental in identifying the local and network substrates subserving tremor control, which suggest that the PSA is the optimal DBS target for tremor suppression in ET. Taken together, DBS offers promising outcomes for ET, with the PSA emerging as a better target for suppression of tremor symptoms. While advanced imaging techniques have substantially improved the identification of anatomical targets within this region, uncertainties persist regarding the distinct anatomical substrates involved in optimal tremor control. Inconsistent subdivisions and nomenclature of motor areas and other subdivisions in the thalamus further obfuscate the interpretation of stimulation results. While loss of benefit and habituation to DBS remain challenging in some patients, refined DBS techniques and closed-loop paradigms may eventually overcome these limitations.

Long-Term Follow-Up of Unilateral Deep Brain Stimulation Targeting the Caudal Zona Incerta in 13 Patients with Parkinsonian Tremor

INTRODUCTION

Deep brain stimulation (DBS) is an established treatment for Parkinson's disease (PD) and other movement disorders. The ventral intermediate nucleus of the thalamus is considered as the target of choice for tremor disorders, including tremor-dominant PD not suitable for DBS in the subthalamic nucleus (STN). In the last decade, several studies have shown promising results on tremor from DBS in the posterior subthalamic area (PSA), including the caudal zona incerta (cZi) located posteromedial to the STN. The aim of this study was to evaluate the long-term effect of unilateral cZi/PSA-DBS in patients with tremor-dominant PD.

METHODS

Thirteen patients with PD with medically refractory tremor were included. The patients were evaluated using the motor part of the Unified Parkinson Disease Rating Scale (UPDRS) off/on medication before surgery and off/on medication and stimulation 1-2 years (short-term) after surgery and at a minimum of 3 years after surgery (long-term).

RESULTS

At short-term follow-up, DBS improved contralateral tremor by 88% in the off-medication state. This improvement persisted after a mean of 62 months. Contralateral bradykinesia was improved by 40% at short-term and 20% at long-term follow-up, and the total UPDRS-III by 33% at short-term and by 22% at long-term follow-up with stimulation alone.

CONCLUSIONS

Unilateral cZi/PSA-DBS seems to remain an effective treatment for patients with severe Parkinsonian tremor several years after surgery. There was also a modest improvement on bradykinesia.

How Sample Size Impacts Probabilistic Stimulation Maps in Deep Brain Stimulation

Probabilistic stimulation maps of deep brain stimulation (DBS) effect based on voxel-wise statistics (p-maps) have increased in literature over the last decade. These p-maps require correction for Type-1 errors due to multiple testing based on the same data. Some analyses do not reach overall significance, and this study aims to evaluate the impact of sample size on p-map computation. A dataset of 61 essential tremor patients treated with DBS was used for the investigation. Each patient contributed with four stimulation settings, one for each contact. From the dataset, 5 to 61 patients were randomly sampled with replacement for computation of p-maps and extraction of high- and low-improvement volumes. For each sample size, the process was iterated 20 times with new samples generating in total 1140 maps. The overall p-value corrected for multiple comparisons, significance volumes, and dice coefficients (DC) of the volumes within each sample size were evaluated. With less than 30 patients (120 simulations) in the sample, the variation in overall significance was larger and the median significance volumes increased with sample size. Above 120 simulations, the trends stabilize but present some variations in cluster location, with a highest median DC of 0.73 for n = 57. The variation in location was mainly related to the region between the high- and low-improvement clusters. In conclusion, p-maps created with small sample sizes should be evaluated with caution, and above 120 simulations in single-center studies are probably required for stable results.