Variability Between Direct and Indirect Targeting of the Anterior Nucleus of the Thalamus

Advancing thalamic neuromodulation in epilepsy: Bridging adult data to pediatric care

Thalamic neuromodulation has emerged as a treatment option for drug-resistant epilepsy (DRE) with widespread and/or undefined epileptogenic networks. While deep brain stimulation (DBS) and responsive neurostimulation (RNS) depth electrodes offer means for electrical stimulation of the thalamus in adult patients with DRE, the application of thalamic neuromodulation in pediatric epilepsy remains limited. To address this gap, the Neuromodulation Expert Collaborative was established within the Pediatric Epilepsy Research Consortium (PERC) Epilepsy Surgery Special Interest Group. In this expert review, existing evidence and recommendations for thalamic neuromodulation modalities using DBS and RNS are summarized, with a focus on the anterior (ANT), centromedian(CMN), and pulvinar nuclei of the thalamus. To-date, only DBS of the ANT is FDA approved for treatment of DRE in adult patients based on the results of the pivotal SANTE (Stimulation of the Anterior Nucleus of Thalamus for Epilepsy) study. Evidence for other thalamic neurmodulation indications and targets is less abundant. Despite the lack of evidence, positive responses to thalamic stimulation in adults with DRE have led to its off-label use in pediatric patients. Although caution is warranted due to differences between pediatric and adult epilepsy, the efficacy and safety of pediatric neuromodulation appear comparable to that in adults. Indeed, CMN stimulation is increasingly accepted for generalized and diffuse onset epilepsies, with recent completion of one randomized trial. There is also growing interest in using pulvinar stimulation for temporal plus and posterior quadrant epilepsies with one ongoing clinical trial in Europe. The future of thalamic neuromodulation holds promise for revolutionizing the treatment landscape of childhood epilepsy. Ongoing research, technological advancements, and collaborative efforts are poised to refine and improve thalamic neuromodulation strategies, ultimately enhancing the quality of life for children with DRE.

CM-Pf deep brain stimulation in polyneuromodulation for epilepsy

OBJECTIVE

Neuromodulation is a viable option for patients with drug-resistant epilepsies. We reviewed the management of patients with two deep brain neurostimulators. In addition, patients implanted with a device targeting the centromedian-parafascicular (CM-Pf) nuclear complex supplements this report to provide an illustrative case to implantation and programming a patient with three active devices.

METHODS

A narrative review using PubMed and Embase identified patients with drug-resistant epilepsy implanted with more than one neurostimulator was performed. Combinations of vagus nerve stimulation (VNS), deep brain stimulation (DBS), and responsive neurostimulation (RNS) were identified. We provide a background of a newly reported case of an adult with a triple implant eventually responding to CM-Pf DBS as the third implant following suboptimal benefit from VNS and RNS.

RESULTS

In review of the literature, dual-device therapy is increasing in reports of use with combinations of VNS, RNS, and DBS to treat patients with drug-resistant epilepsy. We review dual-device implants with thalamic DBS device combinations, functional neural networks, and programming patients with dual devices. CM-Pf is a new target for DBS and has shown a variable response in focal epilepsy. We report the unique case of 28-year-old male with drug-resistant focal epilepsy who experienced a 75% seizure reduction with CM-Pf DBS as his third device after suboptimal responses to VNS and RNS. After 9 months, he also experienced seizure freedom from recurrent focal to bilateral tonic-clonic seizures. No medical or surgical complications or safety issues were encountered.

CONCLUSION

We demonstrate safety and feasibility in an adult combining active VNS, RNS, and CM-Pf DBS. Patients with dual-device therapy who experience a suboptimal response to initial device use at optimized settings should not be considered a neuromodulation "failure." Strategies to combine devices require a working knowledge of brain networks.

Structural and functional abnormalities and cognitive profiles in older adults with early-onset and late-onset focal epilepsy

This study aimed to determine the patterns of changes in structure, function, and cognitive ability in early-onset and late-onset older adults with focal epilepsy (OFE). This study first utilized the deformation-based morphometry analysis to identify structural abnormalities, which were used as the seed region to investigate the functional connectivity with the whole brain. Next, a correlation analysis was performed between the altered imaging findings and neuropsychiatry assessments. Finally, the potential role of structural-functional abnormalities in the diagnosis of epilepsy was further explored by using mediation analysis. Compared with healthy controls (n = 28), the area of reduced structural volume was concentrated in the bilateral cerebellum, right thalamus, and right middle cingulate cortex, with frontal, temporal, and occipital lobes also affected in early-onset focal epilepsy (n = 26), while late-onset patients (n = 31) displayed cerebellar, thalamic, and cingulate atrophy. Furthermore, correlation analyses suggest an association between structural abnormalities and cognitive assessments. Dysfunctional connectivity in the cerebellum, cingulate cortex, and frontal gyrus partially mediates the relationship between structural abnormalities and the diagnosis of early-onset focal epilepsy. This study identified structural and functional abnormalities in early-onset and late-onset focal epilepsy and explored characters in cognitive performance. Structural-functional coupling may play a potential role in the diagnosis of epilepsy.

Real-Time Optimal Synthetic Inversion Recovery Image Selection (RT-OSIRIS) for Deep Brain Stimulation Targeting

Deep brain stimulation (DBS) is a method of electrical neuromodulation used to treat a variety of neuropsychiatric conditions including essential tremor, Parkinson's disease, epilepsy, and obsessive-compulsive disorder. The procedure requires precise placement of electrodes such that the electrical contacts lie within or in close proximity to specific target nuclei and tracts located deep within the brain. DBS electrode trajectory planning has become increasingly dependent on direct targeting with the need for precise visualization of targets. MRI is the primary tool for direct visualization, and this has led to the development of numerous sequences to aid in visualization of different targets. Synthetic inversion recovery images, specified by an inversion time parameter, can be generated from T1 relaxation maps, and this represents a promising method for modifying the contrast of deep brain structures to accentuate target areas using a single acquisition. However, there is currently no accessible method for dynamically adjusting the inversion time parameter and observing the effects in real-time in order to choose the optimal value. In this work, we examine three different approaches to implementing an application for real-time optimal synthetic inversion recovery image selection and evaluate them based on their ability to display continually-updated synthetic inversion recovery images as the user modifies the inversion time parameter. These methods include continuously computing the inversion recovery equation at each voxel in the image volume, limiting the computation only to the voxels of the orthogonal slices currently displayed on screen, or using a series of lookup tables with precomputed solutions to the inversion recovery equation. We find the latter implementation provides for the quickest display updates both when modifying the inversion time and when scrolling through the image. We introduce a publicly available cross-platform application built around this conclusion. We also briefly discuss other details of the implementations and considerations for extensions to other use cases.

Synthetic Inversion Image Generation using MP2RAGE T1 Mapping for Surgical Targeting in Deep Brain Stimulation and Lesioning

BACKGROUND

Advances in MRI technology have increased interest in direct targeting for deep brain stimulation (DBS). Various imaging sequences have been shown to provide increased contrast of numerous common DBS targets, such as T1-weighted, Fast Gray Matter Acquisition T1 Inversion Recovery (FGATIR), gray matter nulled, and Edge-Enhancing Gradient Echo (EDGE); however, the continual increase in the number of necessary sequences has led to an increase in imaging time, which is undesirable. Additionally, carefully timed inversion pulses can often lead to less-than-ideal contrast in some subjects, particularly in ultra-high field MRI, where B1+ field inhomogeneity can lead to substantial contrast variation.

OBJECTIVES

This study proposes using 3D MP2RAGE-based T1 maps to retrospectively synthesize images of any desired inversion time, including T1-weighted, FGATIR, and EDGE contrasts, to visualize specific DBS targets at both 3T and 7T.

METHOD

First, a systematic sequence optimization framework was applied to optimize MP2RAGE T1 mapping sequence parameters for the purpose of DBS planning. Next, we show that synthetic inversion-time images can be generated through a mathematical transformation of the T1 maps. The sequence was then applied to patients undergoing preoperative planning for DBS at 3T and 7T to generate synthetic contrasts used in surgical planning.

RESULTS

We show that synthetic image contrasts can be generated across a full range of inversion times at 3T and 7T, including commonly used sequences for DBS targeting, such as T1-weighted, FGATIR, and EDGE. Acquisition through a single sequence shortens scan time compared to acquiring the sequences independently without affecting image quality or contrast.

CONCLUSIONS

The generation of synthetic images for DBS targeting allows faster acquisition of many key sequences, as well as the ability to optimize contrast properties post-acquisition to account for the variable B1+ effects present in ultra-high field MRI. The proposed approach has the potential to reduce imaging time and improve the accuracy of DBS targeting at 1.5T, 3T, and 7T.

Deep brain stimulation of thalamus for epilepsy

Neuromodulation (neurostimulation) is a relatively new and rapidly growing treatment for refractory epilepsy. Three varieties are approved in the US: vagus nerve stimulation (VNS), deep brain stimulation (DBS) and responsive neurostimulation (RNS). This article reviews thalamic DBS for epilepsy. Among many thalamic sub-nuclei, DBS for epilepsy has been targeted to the anterior nucleus (ANT), centromedian nucleus (CM), dorsomedial nucleus (DM) and pulvinar (PULV). Only ANT is FDA-approved, based upon a controlled clinical trial. Bilateral stimulation of ANT reduced seizures by 40.5% at three months in the controlled phase (p = .038) and 75% by 5 years in the uncontrolled phase. Side effects related to paresthesias, acute hemorrhage, infection, occasional increased seizures, and usually transient effects on mood and memory. Efficacy was best documented for focal onset seizures in temporal or frontal lobe. CM stimulation may be useful for generalized or multifocal seizures and PULV for posterior limbic seizures. Mechanisms of DBS for epilepsy are largely unknown, but animal work points to changes in receptors, channels, neurotransmitters, synapses, network connectivity and neurogenesis. Personalization of therapies, in terms of connectivity of the seizure onset zone to the thalamic sub- nucleus and individual characteristics of the seizures, might lead to improved efficacy. Many questions remain about DBS, including the best candidates for different types of neuromodulation, the best targets, the best stimulation parameters, how to minimize side effects and how to deliver current noninvasively. Despite the questions, neuromodulation provides useful new opportunities to treat people with refractory seizures not responding to medicines and not amenable to resective surgery.

Clinical outcome of imaging-based programming for anterior thalamic nucleus deep brain stimulation

OBJECTIVE

The authors hypothesized that the proximity of deep brain stimulator contacts to the anterior thalamic nucleus-mammillothalamic tract (ANT-MMT) junction determines responsiveness to treatment with ANT deep brain stimulation (DBS) in drug-resistant epilepsy and conducted this study to test that hypothesis.

METHODS

This retrospective study evaluated patients who had undergone ANT DBS electrode implantation and whose devices were programmed to stimulate nearest the ANT-MMT junction based on direct MRI visualization. The proximity of the active electrode to the ANT and the ANT-MMT junction was compared between responders (≥ 50% reduction in seizure frequency) and nonresponders. Linear regression was performed to assess the percentage of seizure reduction and distance to both the ANT and the ANT-MMT junction.

RESULTS

Four (57.1%) of 7 patients had ≥ 50% reduction in seizures. All 4 responders had at least one contact within 1 mm of the ANT-MMT junction, whereas the 3 patients with < 50% seizure improvement did not have a contact within 1 mm of the ANT-MMT junction. Additionally, the 4 responders demonstrated contact positioning closer to the ANT-MMT junction than the 3 nonresponders (mean distance from MMT: 0.7 mm on the left and 0.6 mm on the right in responders vs 3.0 mm on the left and 2.3 mm on the right in nonresponders). However, proximity of the electrode contact to any point in the ANT nucleus did not correlate with seizure reduction. Greater seizure improvement was correlated with a contact position closer to the ANT-MMT junction (R2 = 0.62, p = 0.04). Seizure improvement was not significantly correlated with proximity of the contact to any ANT border (R2 = 0.24, p = 0.26).

CONCLUSIONS

Obtained using a combination of direct visualization and targeted programming of the ANT-MMT junction, data in this study support the hypothesis that proximity to the ANT alone does not correlate with seizure reduction in ANT DBS, whereas proximity to the ANT-MMT junction does. These findings support the importance of direct targeting in ANT DBS, as well as imaging-informed programming. Additionally, the authors provide supportive evidence for future prospective trials using ANT-MMT junction for direct surgical targeting.

Neuroimaging and thalamic connectomics in epilepsy neuromodulation

Neuromodulation is an increasingly utilized therapy for the treatment of people with drug-resistant epilepsy. To date, the most common and effective target has been the thalamus, which is known to play a key role in multiple forms of epilepsy. Neuroimaging has facilitated rapid developments in the understanding of functional targets, surgical and programming techniques, and the effects of thalamic stimulation. In this review, the role of neuroimaging in neuromodulation is explored. First, the structural and functional changes of the thalamus in common epilepsy syndromes are discussed as the rationale for neuromodulation of the thalamus. Next, methods for imaging different thalamic nuclei are presented, as well as rationale for the need of direct surgical targeting rather than reliance on traditional stereotactic coordinates. Lastly, we discuss the potential role of neuroimaging in assessing the effects of thalamic stimulation and as a potential biomarker for neuromodulation outcomes.

Brain structural differences in temporal lobe and frontal lobe epilepsy patients: A voxel-based morphometry and vertex-based surface analysis

PURPOSE

Exploration of the effect of chronic recurrent seizures in focal epilepsy on brain volumes has produced many conflicting reports. To determine differences in brain structure in temporal lobe epilepsy (TLE) and extratemporal epilepsy (using frontal lobe epilepsy (FLE) a surrogate) further, we performed a retrospective analysis of a large cohort of patients with seizure-onset zone proven by intracranial monitoring.

METHODS

A total of 120 TLE patients, 86 FLE patients, and 54 healthy controls were enrolled in this study. An analysis of variance of voxel-based morphometry (VBM) was used to seek morphometric brain differences among TLE patients, FLE patients, and healthy controls. Additionally, a vertex-based surface analysis was utilized to analyze the hippocampus and thalamus. Significant side-specific differences in hippocampal gray matter volume were present between the left TLE (LTLE), right TLE RTLE (RTLE), and control groups (p<0.05, family-wise error (FWE) corrected).

RESULTS

Vertex analyses revealed significant volume reduction in inferior parts of the left hippocampus in the LTLE group and lateral parts of the right hippocampus in the RTLE group compared to controls (p<0.05, FWE corrected). Significant differences were also detected between the LTLE and control group in the bilateral medial and inferior thalamus (p<0.05, FWE corrected). FLE patients did not exhibit focal atrophy of gray matter across the brain.

CONCLUSION

Our results highlight the variation in morphometric lateralized changes in the brain between different epilepsy onset zones, providing critical insight into the natural history of people with drug-resistant focal epilepsies.

DeepNavNet: Automated Landmark Localization for Neuronavigation

Functional neurosurgery requires neuroimaging technologies that enable precise navigation to targeted structures. Insufficient image resolution of deep brain structures necessitates alignment to a brain atlas to indirectly locate targets within preoperative magnetic resonance imaging (MRI) scans. Indirect targeting through atlas-image registration is innately imprecise, increases preoperative planning time, and requires manual identification of anterior and posterior commissure (AC and PC) reference landmarks which is subject to human error. As such, we created a deep learning-based pipeline that consistently and automatically locates, with submillimeter accuracy, the AC and PC anatomical landmarks within MRI volumes without the need for an atlas. Our novel deep learning pipeline (DeepNavNet) regresses from MRI scans to heatmap volumes centered on AC and PC anatomical landmarks to extract their three-dimensional coordinates with submillimeter accuracy. We collated and manually labeled the location of AC and PC points in 1128 publicly available MRI volumes used for training, validation, and inference experiments. Instantiations of our DeepNavNet architecture, as well as a baseline model for reference, were evaluated based on the average 3D localization errors for the AC and PC points across 311 MRI volumes. Our DeepNavNet model significantly outperformed a baseline and achieved a mean 3D localization error of 0.79 ± 0.33 mm and 0.78 ± 0.33 mm between the ground truth and the detected AC and PC points, respectively. In conclusion, the DeepNavNet model pipeline provides submillimeter accuracy for localizing AC and PC anatomical landmarks in MRI volumes, enabling improved surgical efficiency and accuracy.

Edge-enhancing gradient echo with multi-image co-registration and averaging (EDGE-MICRA) for targeting thalamic centromedian and parafascicular nuclei

BACKGROUND AND PURPOSE

Deep brain stimulation of the thalamus is an effective treatment for multiple neurological disorders. The centromedian and parafascicular nuclei are recently emerging targets for multiple conditions, such as epilepsy and Tourette syndrome; however, their limited visibility on conventional magnetic resonance imaging sequences has been a major obstacle. The goal of this study was to demonstrate the feasibility of a high-resolution and high-contrast targeting sequence for centromedian-parafascicular deep brain stimulation using a recently described magnetic resonance imaging sequence, three-dimensional edge-enhancing gradient echo.

METHODS

The three-dimensional edge-enhancing gradient echo sequence was performed on a normal volunteer for a total of six acquisitions. Multi-image co-registration and averaging was performed by first co-registering each of the six scans and then averaging to produce an edge-enhancing gradient echo-multi-image co-registration and averaging scan. The averaging was also performed for two, three, four and five scans to assess the change in the signal-to-noise ratio and identify the ideal balance of image quality and scan time.

RESULTS

The edge-enhancing gradient echo-multi-image co-registration and averaging scan allowed clear boundary delineation of the centromedian and parafascicular nuclei. The signal-to-noise ratio increased as a function of increasing scan number, but the added gain was small beyond four scans for the imaging parameters used in this study.

CONCLUSIONS

The recently described three-dimensional edge-enhancing gradient echo sequence provides an easily implementable approach, using widely available magnetic resonance imaging technology without complex post-processing techniques, to delineate centromedian and parafascicular nuclei for deep brain stimulation targeting.

Neuroimaging Advances in Deep Brain Stimulation: Review of Indications, Anatomy, and Brain Connectomics

Deep brain stimulation is an established therapy for multiple brain disorders, with rapidly expanding potential indications. Neuroimaging has advanced the field of deep brain stimulation through improvements in delineation of anatomy, and, more recently, application of brain connectomics. Older lesion-derived, localizationist theories of these conditions have evolved to newer, network-based "circuitopathies," aided by the ability to directly assess these brain circuits in vivo through the use of advanced neuroimaging techniques, such as diffusion tractography and fMRI. In this review, we use a combination of ultra-high-field MR imaging and diffusion tractography to highlight relevant anatomy for the currently approved indications for deep brain stimulation in the United States: essential tremor, Parkinson disease, drug-resistant epilepsy, dystonia, and obsessive-compulsive disorder. We also review the literature regarding the use of fMRI and diffusion tractography in understanding the role of deep brain stimulation in these disorders, as well as their potential use in both surgical targeting and device programming.