Neuroimaging Technological Advancements for Targeting in Functional Neurosurgery

Abstract

Purpose of review Ablations and particularly deep brain stimulation (DBS) of a variety of CNS targets are established therapeutic tool for movement disorders. Accurate targeting of the intended structure is crucial for optimal clinical outcomes. However, most targets used in functional neurosurgery are poorly visualized on routine MRI and indirect targeting methods are commonly used. This article reviews recent neuroimaging advancements for targeting in movement disorders. Recent findings Dedicated MRI sequences can often visualise anatomical structures commonly targeted during DBS surgery, including at 1.5T field strengths. Due to recent technological advancements, MR images using ultra-high magnetic field strengths and new acquisition parameters allow for markedly improved visualization of common movement disorder targets. In addition, novel neuroimaging techniques have enabled group-level analysis of DBS patients and delineation of areas associated with clinical benefits. These areas might diverge from the conventionally targeted nuclei and may instead correspond to white matter tracts or hubs of functional networks. Summary Neuroimaging advancements have enabled direct visualization-based targeting as well as optimization and adjustment of conventionally targeted structures.

Probabilistic Mapping of Deep Brain Stimulation: Insights from 15 Years of Therapy

“…These studies have provided evidence of differential tract engagement between therapeutic and nontherapeutic DBS for depression and OCD 88,90,97,98 . In addition, several studies have applied large‐scale, publicly available normative resting state fMRI and dMRI datasets to DBS cohorts, permitting connectomic analysis of patients lacking native fMRI/dMRI scans 14 . Again, these analyses have demonstrated that the pattern of structural and functional networks engaged by DBS is predictive of clinical outcome in varied diseases including PD, dystonia, tremor, and OCD 19,50,51,99 .…”

“…To examine potential connectomic differences between these hotspots and routinely described contact coordinates, functional and structural network maps were computed using high‐quality normative connectomes in a manner similar to previous studies 19,64–68 . Although these data may not reflect the idiosyncrasies of patient‐ or pathology‐specific connectivity, they typically offer superior data quality to native imaging due to the specialized hardware and optimized acquisition parameters used by normative data initiatives 69–71 and the technical (eg, spatial resolution, signal‐to‐noise ratio, artifactual) concessions and hardware/technique inconsistencies that are associated with clinical scans 14 . First, VTAs associated with above‐mean clinical improvement (see Table 2) were employed as seeds for connectomic mapping within 2 large‐scale normative datasets: a 1,000‐subject resting state functional MRI (fMRI) dataset (Brain Genomics Superstruct Project; http://neuroinformatics.harvard.edu/gsp/) 70 and a 985‐subject multishell diffusion‐weighted MRI (dMRI) dataset (Human Connectome Project; http://www.humanconnectomeproject.org/) 72 assembled into a ∼12 million‐streamline, whole‐brain tractogram using generalized q‐sampling imaging (http://dsi-studio.labsolver.org) and Lead‐Connectome (http://www.lead-connectome.org).…”

“…Group‐level, magnetic resonance imaging (MRI)‐based probabilistic stimulation mapping is one powerful tool with which to redress this issue, permitting targeting, programming, and clinical outcome data from past DBS interventions to be pooled and scrutinized for emergent trends 14 . Probabilistic mapping techniques have become particularly powerful given recent neuroimaging advancements in (1) normalization of individual patient brain scans into a shared “standard space” for purposes of group‐level analysis, 15 (2) DBS lead localization based on postoperative imaging, 16 and (3) estimation of the activation volume (or volume of tissue activated [VTA])—the spatial extent of the perielectrode electric field wherein modulation of neuronal activity is assumed to occur—according to patient‐specific stimulation settings 17–19 .…”

Evaluation of Automatic Segmentation of Thalamic Nuclei through Clinical Effects Using Directional Deep Brain Stimulation Leads: A Technical Note

“…For targeting, there are two basic approaches: indirect targeting using coordinates derived from autopsy-based atlases, or direct visualization of target structures on magnetic resonance imaging (MRI). However, in contrast to the STN and GPi, in vivo segmentation of thalamic nuclei such as the VIM remains challenging, despite significant advances in neuroimaging technology [ 3 , 4 ]. Although some groups have reported VIM visualization on 3T proton density [ 5 ], fast gray matter T1 inversion recovery sequences [ 6 ], or ultra-high field MRI [ 4 ], it is not readily visible on conventional stereotactic MR imaging sequences.…”

“…However, in contrast to the STN and GPi, in vivo segmentation of thalamic nuclei such as the VIM remains challenging, despite significant advances in neuroimaging technology [ 3 , 4 ]. Although some groups have reported VIM visualization on 3T proton density [ 5 ], fast gray matter T1 inversion recovery sequences [ 6 ], or ultra-high field MRI [ 4 ], it is not readily visible on conventional stereotactic MR imaging sequences. Other recent advances include connectivity-based segmentation of the VIM using probabilistic tractography [ 2 ].…”