Tissue Activation Calculation in Dual-lead Deep Brain Stimulation

TL;DR

This work tackles the problem that dual-lead DBS near each other induces interacting electric fields that invalidate the common assumption of independent single-lead VTAs. It develops patient-specific global dual-lead finite element models and compares them to approximations derived from independent single-lead solutions using two activation metrics, EF-norm and AF-Max. The key findings show that simple VTA superposition underestimates activation, while summing the underlying electric fields or Hessians before thresholding overestimates activation, with consistent target-coverage biases observed across two patient cohorts. The study demonstrates that accurate dual-lead DBS programming likely requires global dual-lead models to predict activation and optimize contact configurations, especially when leads are in close proximity or target medial structures, highlighting important implications for model-based DBS optimization and clinical planning.

Abstract

Deep Brain Stimulation (DBS) is a well-established neurosurgical treatment aiming at symptom alleviation in a range of neurological and psychiatric diseases. Computational models of DBS are widely used to investigate the effects of stimulation on neural tissue, to explore stimulation targets and sweetspots, and ultimately, to aid clinicians in the DBS programming by calculating the stimulation parameters. Commonly, DBS is performed bilaterally, i.e. with one lead in each brain hemisphere, where computational models are solved independently for one lead at a time. This paper treats scenarios where multiple DBS leads are implanted in close proximity to one another, resulting in interacting electrical fields and, therefore, potentially overlapping stimulation spreads. In particular, a global dual-lead model is compared to approximations derived from single-lead approaches in a cohort of twelve multiple sclerosis (MS) tremor patients. It is concluded that simple superposition of volumes of tissue activated (VTAs) underestimates activation, while superposition of electric fields or activating functions leads to overestimation. It is concluded that given close proximity of DBS leads, the VTA cannot be computed individually as stimulation fields exhibit significant and complex interaction. The approach is extended to modeling two obsessive compulsive disorder patients with medially placed leads, where similar VTA discrepancies as in the MS patient cohort are observed.

Figures (7)

• Figure 1: Grid of neurons surrounding the leads. For illustration, only a single plane of the full $20 \times 20 \times 20$ mm uniform grid (node spacing: 0.4mm) is shown. Each axon (light grey) has a length of 1mm.
• Figure 2: Lead placement for (a) one patient from cohort I relative to the VIM (red) and the VO (orange) Ewert2018 and (b) one patient from cohort II relative to the MD (green) and the anterior (blue) nuclei of the thalamusIlinsky2018. The figures were rendered in Lead-DBS Neudorfer2023.
• Figure 3: VTA computed from \ref{['eq:Enorm']} for the two DBS leads in patient 16. VTAs were computed under clinical settings with a) only the ViM lead, b) only the VO lead, and c) both leads active. A clear effect of the floating contacts on the non-active lead can be observed.
• Figure 4: Number of activated nodes in Cohort I for the EF-norm (left) and AF Max (right), respectively. The dual solution is approximated by the two approaches presented in \ref{['sec:approximations']}.
• Figure 5: Distribution plots of total activations, exclusive activations, and missed activations for cohort I. The number of activations were normalized with respect to the total number of activations in the respective dual model.