Feasibility of Using Ultra-High Field (7 T) MRI for Clinical Surgical Targeting

The advantages of ultra-high magnetic field (7 Tesla) MRI for basic science research and neuroscience applications have proven invaluable. Structural and functional MR images of the human brain acquired at 7 T exhibit rich information content with potential utility for clinical applications. However, (1) substantial increases in susceptibility artifacts, and (2) geometrical distortions at 7 T would be detrimental for stereotactic surgeries such as deep brain stimulation (DBS), which typically use 1.5 T images for surgical planning. Here, we explore whether these issues can be addressed, making feasible the use of 7 T MRI to guide surgical planning. Twelve patients with Parkinson's disease, candidates for DBS, were scanned on a standard clinical 1.5 T MRI and a 7 T MRI scanner. Qualitative and quantitative assessments of global and regional distortion were evaluated based on anatomical landmarks and transformation matrix values. Our analyses show that distances between identical landmarks on 1.5 T vs. 7 T, in the mid-brain region, were less than one voxel, indicating a successful co-registration between the 1.5 T and 7 T images under these specific imaging parameter sets. On regional analysis, the central part of the brain showed minimal distortion, while inferior and frontal areas exhibited larger distortion due to proximity to air-filled cavities. We conclude that 7 T MR images of the central brain regions have comparable distortions to that observed on a 1.5 T MRI, and that clinical applications targeting structures such as the STN, are feasible with information-rich 7 T imaging

Comprehensive in vivo Mapping of the Human Basal Ganglia and Thalamic Connectome in Individuals Using 7T MRI

Basal ganglia circuits are affected in neurological disorders such as Parkinson's disease (PD), essential tremor, dystonia and Tourette syndrome. Understanding the structural and functional connectivity of these circuits is critical for elucidating the mechanisms of the movement and neuropsychiatric disorders, and is vital for developing new therapeutic strategies such as deep brain stimulation (DBS). Knowledge about the connectivity of the human basal ganglia and thalamus has rapidly evolved over recent years through non-invasive imaging techniques, but has remained incomplete because of insufficient resolution and sensitivity of these techniques. Here, we present an imaging and computational protocol designed to generate a comprehensive in vivo and subject-specific, three-dimensional model of the structure and connections of the human basal ganglia. High-resolution structural and functional magnetic resonance images were acquired with a 7-Tesla magnet. Capitalizing on the enhanced signal-to-noise ratio (SNR) and enriched contrast obtained at high-field MRI, detailed structural and connectivity representations of the human basal ganglia and thalamus were achieved. This unique combination of multiple imaging modalities enabled the in-vivo visualization of the individual human basal ganglia and thalamic nuclei, the reconstruction of seven white-matter pathways and their connectivity probability that, to date, have only been reported in animal studies, histologically, or group-averaged MRI population studies. Also described are subject-specific parcellations of the basal ganglia and thalamus into sub-territories based on their distinct connectivity patterns. These anatomical connectivity findings are supported by functional connectivity data derived from resting-state functional MRI (R-fMRI). This work demonstrates new capabilities for studying basal ganglia circuitry, and opens new avenues of investigation into the movement and neuropsychiatric disorders, in individual human subjects

Method for localizing intraoperative recordings from deep brain stimulation surgery using post-operative structural MRI

Background: Implantation of deep brain stimulation (DBS) electrodes for the treatment of involuntary movement disorders, such as Parkinson's disease, routinely relies on the use of intraoperative electrophysiological confirmation to identify the optimal therapeutic target in the brain. However, only a few options exist to visualize the relative anatomic localization of intraoperative electrophysiological recordings with respect to post-operative imaging. We have developed a novel processing pipeline to visualize intraoperative electrophysiological signals registered to post-operative neuroanatomical imaging. New method: We developed a processing pipeline built on the use of ITK-SNAP and custom MATLAB scripts to visualize the anatomical localization of intraoperative electrophysiological recordings mapped onto the post-operative MRI following implantation of DBS electrodes. This method combines the user-defined relevant electrophysiological parameters measured during the surgery with a manual segmentation of the DBS electrode from post-operative MRI; mapping the microelectrode recording (MER) depths along the DBS lead track. Results: We demonstrate the use of our processing pipeline on data from Parkinson's disease patients undergoing DBS implantation targeted to the subthalamic nucleus (STN). The primary processing components of the pipeline are: extrapolation of the lead wire and alignment of intraoperative electrophysiology. Conclusion: We describe the use of a processing pipeline to aid clinicians and researchers engaged in deep brain stimulation work to correlate and visualize the intraoperative recording data with the post-operative DBS trajectory

MRI-Related Heating near Deep Brain Stimulation Electrodes: More Data Are Needed

Magnetic resonance imaging (MRI) of patients with implanted deep brain stimulation (DBS) devices poses a challenge for healthcare providers. As a consequence of safety concerns about magnetic field interactions with the device, induced electrical currents and thermal damage due to radiofrequency heating, a number of stringent guidelines have been proposed by the device manufacturer. Very few detailed investigations of these safety issues have been published to date, and the stringent manufacturer guidelines have gone unchallenged, leading some hospitals and imaging centers around the world to ban or restrict the use of MRI in DBS patients. The purpose of this review is to stimulate research towards defining appropriate guidelines for the use of MRI in patients with DBS. Additionally, this review is intended to help healthcare providers and researchers make sound clinical judgments about the use of MRI in the setting of implanted DBS devices

Towards automated sleep-stage classification for adaptive deep brain stimulation targeting sleep in patients with Parkinson’s disease

Abstract Sleep dysfunction affects over 90% of Parkinson’s disease patients. Recently, subthalamic nucleus deep brain stimulation has shown promise for alleviating sleep dysfunction. We previously showed that a single-layer neural network could classify sleep stages from local field potential recordings in Parkinson’s disease patients. However, it was unable to categorise non-rapid eye movement into its different sub-stages. Here we employ a larger hidden layer network architecture to distinguish the substages of non-rapid eye movement with reasonable accuracy, up to 88% for the lightest substage and 92% for deeper substages. Using Shapley attribution analysis on local field potential frequency bands, we show that low gamma and high beta are more important to model decisions than other frequency bands. These results suggest that the proposed neural network-based classifier can be employed for deep brain stimulation treatment in commercially available devices with lower local field potential sampling frequencies

Quantitative and statistical summary of anatomical based registration.

<p>Box plots of the statistics of the co-registered landmarks' distances, obtained from individual patients, for T₁W (top row – a and b) and T₂W (low row – c and d) images. Further comparison is done between images acquired by 7T/PS (left column – a and c) and 7T/AS (right column – b and d). The red lines represent the average, top and bottom of the box represent the first and third quintile, respectively, the whiskers show the maximum and minimum values, and the asterix represent the outliers. The statistics is of distances between the anatomical landmarks assigned on 1.5 T images and the corresponding anatomical landmarks assigned on the 7 T images, after a global landmarks-free coordinates transformation to the 1.5 T image space. As can be seen, the distances are on the order of one voxel, indicating a high degree of correspondence between the two co-registered images.</p