ABSTRACT
Oculogyric crises are acute episodes of sustained, typically upward, conjugate deviation of the eyes. Oculogyric crises usually occur as the result of acute D2-dopamine receptor blockade, but the brain areas causally involved in generating this symptom remain elusive. Here, we used data from 14 previously reported cases of lesion-induced oculogyric crises and employed lesion network mapping to identify their shared connections throughout the brain. This analysis yielded a common network that included basal ganglia, thalamic and brainstem nuclei, as well as the cerebellum. Comparison of this network with gene expression profiles associated with the dopamine system revealed spatial overlap specifically with the gene coding for dopamine receptor type 2 (DRD2), as defined by a large-scale transcriptomic database of the human brain. Furthermore, spatial overlap with DRD2 and DRD3 gene expression was specific to brain lesions associated with oculogyric crises when contrasted to lesions that led to other movement disorders. Our findings identify a common neural network causally involved in the occurrence of oculogyric crises and provide a pathophysiological link between lesion locations causing this syndrome and its most common pharmacological cause, namely DRD2 blockade.
Subject(s)
Brain , Ocular Motility Disorders , Receptors, Dopamine D2 , Transcriptome , Humans , Receptors, Dopamine D2/genetics , Receptors, Dopamine D2/metabolism , Ocular Motility Disorders/genetics , Brain/metabolism , Male , Female , Middle Aged , Adult , Nerve Net/metabolism , Aged , Dopamine/metabolism , Receptors, Dopamine D3/genetics , Receptors, Dopamine D3/metabolismABSTRACT
Comprehensive understanding of the neural circuits involving the ventral tegmental area is essential for elucidating the anatomo-functional mechanisms governing human behaviour as well as the therapeutic and adverse effects of deep brain stimulation for neuropsychiatric diseases. While the ventral tegmental area has been successfully targeted with deep brain stimulation for different neuropsychiatric diseases, the axonal connectivity of the region has not been fully understood. Here using fiber micro-dissections in human cadaveric hemispheres, population-based high-definition fiber tractography, and previously reported deep brain stimulation hotspots, we find that the ventral tegmental area participates in an intricate network involving the serotonergic pontine nuclei, basal ganglia, limbic system, basal forebrain, and prefrontal cortex, which is implicated in the treatment of obsessive-compulsive disorder, major depressive disorder, Alzheimer's disease, cluster headaches, and aggressive behaviors.
ABSTRACT
Dystonia is a debilitating disease with few treatment options. One effective option is deep brain stimulation (DBS) to the internal pallidum. While cervical and generalized forms of isolated dystonia have been targeted with a common approach to the posterior third of the nucleus, large-scale investigations regarding optimal stimulation sites and potential network effects have not been carried out. Here, we retrospectively studied clinical results following DBS for cervical and generalized dystonia in a multicenter cohort of 80 patients. We model DBS electrode placement based on pre- and postoperative imaging and introduce an approach to map optimal stimulation sites to anatomical space. Second, we investigate which tracts account for optimal clinical improvements, when modulated. Third, we investigate distributed stimulation effects on a whole-brain functional connectome level. Our results show marked differences of optimal stimulation sites that map to the somatotopic structure of the internal pallidum. While modulation of the striatopallidofugal axis of the basal ganglia accounted for optimal treatment of cervical dystonia, modulation of pallidothalamic bundles did so in generalized dystonia. Finally, we show a common multisynaptic network substrate for both phenotypes in the form of connectivity to the cerebellum and somatomotor cortex. Our results suggest a brief divergence of optimal stimulation networks for cervical vs. generalized dystonia within the pallidothalamic loop that merge again on a thalamo-cortical level and share a common whole-brain network.
Subject(s)
Deep Brain Stimulation , Dystonic Disorders , Torticollis , Deep Brain Stimulation/methods , Dystonic Disorders/therapy , Globus Pallidus , Humans , Thalamus , Torticollis/therapy , Treatment OutcomeABSTRACT
OBJECTIVE: This study was undertaken to describe relationships between electrode localization and motor outcomes from the subthalamic nucleus (STN) deep brain stimulation (DBS) in early stage Parkinson disease (PD) pilot clinical trial. METHODS: To determine anatomical and network correlates associated with motor outcomes for subjects randomized to early DBS (n = 14), voxelwise sweet spot mapping and structural connectivity analyses were carried out using outcomes of motor progression (Unified Parkinson Disease Rating Scale Part III [UPDRS-III] 7-day OFF scores [∆baselineâ24 months, MedOFF/StimOFF]) and symptomatic motor improvement (UPDRS-III ON scores [%∆baselineâ24 months, MedON/StimON]). RESULTS: Sweet spot mapping revealed a location associated with slower motor progression in the dorsolateral STN (anterior/posterior commissure coordinates: 11.07 ± 0.82mm lateral, 1.83 ± 0.61mm posterior, 3.53 ± 0.38mm inferior to the midcommissural point; Montreal Neurological Institute coordinates: +11.25, -13.56, -7.44mm). Modulating fiber tracts from supplementary motor area (SMA) and primary motor cortex (M1) to the STN correlated with slower motor progression across STN DBS subjects, whereas fiber tracts originating from pre-SMA and cerebellum were negatively associated with motor progression. Robustness of the fiber tract model was demonstrated in leave-one-patient-out (R = 0.56, p = 0.02), 5-fold (R = 0.50, p = 0.03), and 10-fold (R = 0.53, p = 0.03) cross-validation paradigms. The sweet spot and fiber tracts associated with motor progression revealed strong similarities to symptomatic motor improvement sweet spot and connectivity in this early stage PD cohort. INTERPRETATION: These results suggest that stimulating the dorsolateral region of the STN receiving input from M1 and SMA (but not pre-SMA) is associated with slower motor progression across subjects receiving STN DBS in early stage PD. This finding is hypothesis-generating and must be prospectively tested in a larger study. ANN NEUROL 2023;94:271-284.
Subject(s)
Deep Brain Stimulation , Parkinson Disease , Subthalamic Nucleus , White Matter , Humans , Subthalamic Nucleus/physiology , Parkinson Disease/diagnostic imaging , Parkinson Disease/therapy , Deep Brain Stimulation/methods , Treatment OutcomeABSTRACT
BACKGROUND: Recent imaging studies identified a brain network associated with clinical improvement following deep brain stimulation (DBS) in Parkinson's disease (PD), the PD response network. OBJECTIVES: This study aimed to assess the impact of neuromodulation on PD motor symptoms by targeting this network noninvasively using multifocal transcranial direct current stimulation (tDCS). METHODS: In a prospective, randomized, double-blinded, crossover trial, 21 PD patients (mean age 59.7 years, mean Hoehn & Yahr [H&Y] 2.4) received multifocal tDCS targeting the a-priori network. Twenty-minute sessions of tDCS and sham were administered on 2 days in randomized order. Movement Disorder Society-Unified Parkinson's Disease Rating Scale-Part III (MDS-UPDRS-III) scores were assessed. RESULTS: Before intervention, MDS-UPDRS-III scores were comparable in both conditions (stimulation days: 37.38 (standard deviation [SD] = 12.50, confidence interval [CI] = 32.04, 42.73) vs. sham days: 36.95 (SD = 13.94, CI = 30.99, 42.91), P = 0.63). Active stimulation resulted in a reduction by 3.6 points (9.7%) to 33.76 (SD = 11.19, CI = 28.98, 38.55) points, whereas no relevant change was observed after sham stimulation (36.43 [SD = 14.15, CI = 30.38, 42.48], average improvement: 0.5 [1.4%]). Repeated-measures analysis of variance (ANOVA) confirmed significance (main effect of time: F(1,20)=4.35, P < 0.05). Tukey's post hoc tests indicated MDS-UPDRS-III improvement after active stimulation (t [20] = 2.9, P = 0.03) but not after sham (t [20] = 0.42, P > 0.05). In a subset of patients that underwent DBS surgery later, their DBS response correlated with tDCS effects (R = 0.55, P(1) = 0.04). CONCLUSION: Noninvasive, multifocal tDCS targeting a DBS-derived network significantly improved PD motor symptoms. Despite a small effect size, this study provides proof of principle for the successful noninvasive neuromodulation of an invasively identified network. Future studies should investigate repeated tDCS sessions and their utility for screening before DBS surgery. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
ABSTRACT
Historically, pathological brain lesions provided the foundation for localization of symptoms and therapeutic lesions were used as a treatment for brain diseases. New medications, functional neuroimaging and deep brain stimulation have led to a decline in lesions in the past few decades. However, recent advances have improved our ability to localize lesion-induced symptoms, including localization to brain circuits rather than individual brain regions. Improved localization can lead to more precise treatment targets, which may mitigate traditional advantages of deep brain stimulation over lesions such as reversibility and tunability. New tools for creating therapeutic brain lesions such as high intensity focused ultrasound allow for lesions to be placed without a skin incision and are already in clinical use for tremor. Although there are limitations, and caution is warranted, improvements in lesion-based localization are refining our therapeutic targets and improved technology is providing new ways to create therapeutic lesions, which together may facilitate the return of the lesion.
Subject(s)
Brain Diseases , Nervous System Diseases , Humans , Brain Mapping , Brain/pathology , TremorABSTRACT
OBJECTIVES: Endoscopic trans-anal colonic decompression (ECD) may be requested in the case of massive colon distension, but evidence regarding success and safety issues remains scarce. The aim of this analysis is to examine the technical success, complications and clinical outcome in a large series of patients undergoing an ECD in various clinical scenarios. A standardized evaluation system was used to identify the pre-interventional risk parameters that might be helpful to guide clinical decision making. METHODS: In this single-centre retrospective study, the modified Clavien-Dindo classification (CDC) was applied to assess technical success, complications and clinical outcome of 125 consecutive patients who underwent ECD between 2007 and 2020. PRIMARY ENDPOINT: post interventional 90-day mortality. Secondary endpoints: periprocedural complications (CDC event IV-V) and technical success rate. All Martin criteria for standardized reporting of complications were met. Uni- and multivariable analyses for prediction of complications were carried out. RESULTS: The overall technical success rate was 90%. The periprocedural complication rate was low with 3%. Overall 90-day mortality was 31%. Univariable analyses showed a significant correlation between 90-day mortality and ASA≥4 (p<0.001, odds ratio [OR] 15.33), general anaesthesia (p=0.05, OR 21.42) and elevated serological infection parameters (p 0.028, OR 1.004). The pre-interventional multivariable model identified ASA ≥4 (p <0.001; OR 10.94) as the only independent risk factor. CONCLUSIONS: ECD is a safe, easily available, technical feasible, inexpensive and successful tool for colonic decompression in various colonic obstruction scenarios, even in critically ill patients. ASA Score ≥IV can be helpful to identify patients at risk for complications/mortality after ECD.
Subject(s)
Endoscopy , Intestinal Obstruction , Humans , Retrospective Studies , Colon , Decompression/adverse effectsABSTRACT
Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.
Subject(s)
Deep Brain Stimulation , Parkinson Disease , Subthalamic Nucleus , Humans , Deep Brain Stimulation/methods , Parkinson Disease/therapy , Retrospective Studies , Brain/diagnostic imaging , Magnetic Resonance Imaging/methodsABSTRACT
Segmenting deep brain structures from magnetic resonance images is important for patient diagnosis, surgical planning, and research. Most current state-of-the-art solutions follow a segmentation-by-registration approach, where subject magnetic resonance imaging (MRIs) are mapped to a template with well-defined segmentations. However, registration-based pipelines are time-consuming, thus, limiting their clinical use. This paper uses deep learning to provide a one-step, robust, and efficient deep brain segmentation solution directly in the native space. The method consists of a preprocessing step to conform all MRI images to the same orientation, followed by a convolutional neural network using the nnU-Net framework. We use a total of 14 datasets from both research and clinical collections. Of these, seven were used for training and validation and seven were retained for testing. We trained the network to segment 30 deep brain structures, as well as a brain mask, using labels generated from a registration-based approach. We evaluated the generalizability of the network by performing a leave-one-dataset-out cross-validation, and independent testing on unseen datasets. Furthermore, we assessed cross-domain transportability by evaluating the results separately on different domains. We achieved an average dice score similarity of 0.89 ± 0.04 on the test datasets when compared to the registration-based gold standard. On our test system, the computation time decreased from 43 min for a reference registration-based pipeline to 1.3 min. Our proposed method is fast, robust, and generalizes with high reliability. It can be extended to the segmentation of other brain structures. It is publicly available on GitHub, and as a pip package for convenient usage.
Subject(s)
Brain , Image Processing, Computer-Assisted , Humans , Image Processing, Computer-Assisted/methods , Reproducibility of Results , Brain/diagnostic imaging , Neural Networks, Computer , Magnetic Resonance Imaging/methodsABSTRACT
OBJECTIVE: With a growing appreciation for interindividual anatomical variability and patient-specific brain connectivity, advanced imaging sequences offer the opportunity to directly visualize anatomical targets for deep brain stimulation (DBS). The lack of quantitative evidence demonstrating their clinical utility, however, has hindered their broad implementation in clinical practice. METHODS: Using fast gray matter acquisition T1 inversion recovery (FGATIR) sequences, the present study identified a thalamic hypointensity that holds promise as a visual marker in DBS. To validate the clinical utility of the identified hypointensity, we retrospectively analyzed 65 patients (26 female, mean age = 69.1 ± 12.7 years) who underwent DBS in the treatment of essential tremor. We characterized its neuroanatomical substrates and evaluated the hypointensity's ability to predict clinical outcome using stimulation volume modeling and voxelwise mapping. Finally, we determined whether the hypointensity marker could predict symptom improvement on a patient-specific level. RESULTS: Anatomical characterization suggested that the identified hypointensity constituted the terminal part of the dentatorubrothalamic tract. Overlap between DBS stimulation volumes and the hypointensity in standard space significantly correlated with tremor improvement (R2 = 0.16, p = 0.017) and distance to hotspots previously reported in the literature (R2 = 0.49, p = 7.9e-4). In contrast, the amount of variance explained by other anatomical atlas structures was reduced. When accounting for interindividual neuroanatomical variability, the predictive power of the hypointensity increased further (R2 = 0.37, p = 0.002). INTERPRETATION: Our findings introduce and validate a novel imaging-based marker attainable from FGATIR sequences that has the potential to personalize and inform targeting and programming in DBS for essential tremor. ANN NEUROL 2022;91:613-628.
Subject(s)
Deep Brain Stimulation , Essential Tremor , Aged , Aged, 80 and over , Deep Brain Stimulation/methods , Diffusion Tensor Imaging/methods , Essential Tremor/diagnostic imaging , Essential Tremor/therapy , Female , Humans , Male , Middle Aged , Retrospective Studies , Thalamus/diagnostic imagingABSTRACT
OBJECTIVE: The objective of this study was to obtain individual clinical and neuroimaging data of patients undergoing deep brain stimulation (DBS) for essential tremor (ET) from 5 different European centers to identify predictors of outcome and to identify an optimal stimulation site. METHODS: We analyzed retrospectively baseline covariates, pre- and postoperative clinical tremor scores (for 12 months) as well as individual imaging data from 119 patients to obtain individual electrode positions and stimulation volumes. Individual imaging and clinical data were used to calculate a probabilistic stimulation map in normalized space using voxel-wise statistical analysis. Finally, we used this map to train a classifier to predict tremor improvement. RESULTS: Probabilistic mapping of stimulation effects yielded a statistically significant cluster that was associated with a tremor improvement >50%. This cluster of optimal stimulation extended from the posterior subthalamic area to the ventralis intermedius nucleus and coincided with a normative structural connectivity-based cerebellothalamic tract (CTT). The combined features "distance between the stimulation volume and the significant cluster" and "CTT activation" were used as a predictor of tremor improvement. This correctly classified a >50% tremor improvement with a sensitivity of 89% and a specificity of 57%. INTERPRETATION: Our multicenter ET probabilistic stimulation map identified an area of optimal stimulation along the course of the CTT. The results of this study are mainly descriptive until confirmed in independent datasets, ideally through prospective testing. This target will be made openly available and may be used to guide surgical planning and for computer-assisted programming of DBS in the future. ANN NEUROL 2022;91:602-612.
Subject(s)
Deep Brain Stimulation , Essential Tremor , Deep Brain Stimulation/methods , Essential Tremor/therapy , Humans , Prospective Studies , Retrospective Studies , Treatment Outcome , Tremor/therapyABSTRACT
BACKGROUND: Subthalamic nucleus (STN) beta (13 - 35 Hz) activity is a biomarker reflecting motor state in Parkinson's disease (PD). Adaptive deep brain stimulation (DBS) aims to use beta activity for therapeutic adjustments, but many aspects of beta activity in real-life situations are unknown. OBJECTIVE: The aim was to investigate Christmas-related influences on beta activity in PD. METHODS: Differences in Christmas Day to nonfestive daily averages in chronic biomarker recordings in 4 PD patients with a sensing-enabled STN DBS implant were retrospectively analyzed. Sweet-spot and whole-brain network connectomic analyses were performed. RESULTS: Beta activity was significantly reduced on Christmas Eve in all patients (4.00-9.00 p.m.: -12.30 ± 10.78%, P = 0.015). A sweet spot in the dorsolateral STN connected recording sites to motor, premotor, and supplementary motor cortices. CONCLUSIONS: We demonstrate that festive events can reduce beta biomarker activity. We conclude that circadian and holiday-related changes should be considered when tailoring adaptive DBS algorithms to patient demands. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
Subject(s)
Deep Brain Stimulation , Motor Cortex , Parkinson Disease , Subthalamic Nucleus , Humans , Parkinson Disease/therapy , Retrospective Studies , Subthalamic Nucleus/physiologyABSTRACT
BACKGROUND: The house dust mite (HDM) sublingual immunotherapy (SLIT)-tablet is a treatment option for allergic rhinitis with/without conjunctivitis (AR/C) approved in adults worldwide and in adolescents in some countries. OBJECTIVE: To supplement existing adolescent HDM SLIT-tablet safety data by conducting the MT-18 trial in adolescents. METHODS: MT-18 (EudraCT:2020-000446-34) was a phase 3, open-label, single-arm, 28-day safety trial of daily HDM SLIT-tablet (12 SQ-HDM dose) in European adolescents (12-17 years) with HDM AR/C, with or without asthma. The primary end point was at least 1 treatment-emergent adverse event (TEAE). MT-18 results were compared with 12 SQ-HDM adolescent subpopulation data from previously described 1-year phase 3 trials conducted in North America (P001; clinicaltrials.gov:NCT01700192) or Japan (TO-203-3-2; JapicCTI:121848). RESULTS: No treatment-related anaphylaxis, epinephrine administrations, severe local swellings, severe mouth or throat edema, or eosinophilic esophagitis occurred in the trials. For MT-18 (N = 253), P001 (N adolescents = 189), and TO-203-3-2 (N adolescents = 206), the percentage of adolescents treated with 12 SQ-HDM reporting any TEAE was 88%, 95%, and 93%, respectively, and the percentage reporting any treatment-related AE (TRAE) was 86%, 93%, and 66%, respectively. The most common TRAEs were local application site reactions. Most TRAEs were mild in intensity and were typically experienced the first 1 to 2 days of treatment. There were no asthma-related TEAEs with the HDM SLIT-tablet. The safety profile appears similar between adolescents with or without asthma at baseline. CONCLUSION: The HDM SLIT-tablet was well tolerated in European, North American, and Japanese adolescents with HDM AR/C, indicating safety of the HDM SLIT-tablet is insensitive to age or geographic region. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: (P001: NCT01700192); EudraCT: (MT-18; 2020-000446-34); JapicCTI: (TO-203-3-2; 121848).
Subject(s)
Asthma , Conjunctivitis, Allergic , Conjunctivitis , Rhinitis, Allergic, Perennial , Rhinitis, Allergic , Sublingual Immunotherapy , Adolescent , Adult , Animals , Humans , Antigens, Dermatophagoides , Asthma/drug therapy , Conjunctivitis/chemically induced , Dermatophagoides pteronyssinus , Double-Blind Method , Pyroglyphidae , Rhinitis, Allergic, Perennial/drug therapy , Sublingual Immunotherapy/adverse effects , Sublingual Immunotherapy/methods , Tablets/therapeutic use , Treatment OutcomeABSTRACT
The subthalamic nucleus and internal pallidum are main target sites for deep brain stimulation in Parkinson's disease. Multiple trials that investigated subthalamic versus pallidal stimulation were unable to settle on a definitive optimal target between the two. One reason could be that the effect is mediated via a common functional network. To test this hypothesis, we calculated connectivity profiles seeding from deep brain stimulation electrodes in 94 patients that underwent subthalamic and 28 patients with pallidal treatment based on a normative connectome atlas calculated from 1000 healthy subjects. In each cohort, we calculated connectivity profiles that were associated with optimal clinical improvements. The two maps showed striking similarity and were able to cross-predict outcomes in the respective other cohort (R = 0.37 at P < 0.001; R = 0.34 at P = 0.032). Next, we calculated an agreement map, which retained regions common to both target sites. Crucially, this map was able to explain an additional amount of variance in clinical improvements of either cohort when compared to the maps calculated on each cohort alone. Finally, we tested profiles and predictive utility of connectivity maps calculated from different motor symptom subscores with a specific focus on bradykinesia and rigidity. While our study is based on retrospective data and indirect connectivity metrics, it may deliver empirical data to support the hypothesis of a largely overlapping network associated with effective deep brain stimulation in Parkinson's disease irrespective of the specific target.
Subject(s)
Deep Brain Stimulation , Parkinson Disease , Subthalamic Nucleus , Globus Pallidus , Humans , Parkinson Disease/therapy , Retrospective StudiesABSTRACT
Brain lesions are a rare cause of tic disorders. However, they can provide uniquely causal insights into tic pathophysiology and can also inform on possible neuromodulatory therapeutic targets. Based on a systematic literature review, we identified 22 cases of tics causally attributed to brain lesions and employed 'lesion network mapping' to interrogate whether tic-inducing lesions would be associated with a common network in the average human brain. We probed this using a normative functional connectome acquired in 1000 healthy participants. We then examined the specificity of the identified network by contrasting tic-lesion connectivity maps to those seeding from 717 lesions associated with a wide array of neurological and/or psychiatric symptoms within the Harvard Lesion Repository. Finally, we determined the predictive utility of the tic-inducing lesion network as a therapeutic target for neuromodulation. Specifically, we collected retrospective data of 30 individuals with Tourette disorder, who underwent either thalamic (n = 15; centromedian/ventrooralis internus) or pallidal (n = 15; anterior segment of globus pallidus internus) deep brain stimulation and calculated whether connectivity between deep brain stimulation sites and the lesion network map could predict clinical improvements. Despite spatial heterogeneity, tic-inducing lesions mapped to a common network map, which comprised the insular cortices, cingulate gyrus, striatum, globus pallidus internus, thalami and cerebellum. Connectivity to a region within the anterior striatum (putamen) was specific to tic-inducing lesions when compared with control lesions. Connectivity between deep brain stimulation electrodes and the lesion network map was predictive of tic improvement, regardless of the deep brain stimulation target. Taken together, our results reveal a common brain network involved in tic generation, which shows potential as a therapeutic target for neuromodulation.
Subject(s)
Deep Brain Stimulation , Tics , Tourette Syndrome , Humans , Deep Brain Stimulation/methods , Retrospective Studies , Treatment Outcome , Brain/pathology , Neural Networks, ComputerABSTRACT
The subthalamic nucleus (STN) is a primary target for deep brain stimulation in Parkinson's disease (PD). Although small in size, the STN is commonly partitioned into sensorimotor, cognitive/associative, and limbic subregions based on its structural connectivity profile to cortical areas. We investigated whether such a regional specialization is also supported by functional connectivity between local field potential recordings and simultaneous magnetoencephalography. Using a novel data set of 21 PD patients, we replicated previously reported cortico-STN coherence networks in the theta/alpha and beta frequency ranges, and looked for the spatial distribution of these networks within the STN region. Although theta/alpha and beta coherence peaks were both observed in on-medication recordings from electrode contacts at several locations within and around the STN, sites with theta/alpha coherence peaks were situated at significantly more inferior MNI coordinates than beta coherence peaks. Sites with only theta/alpha coherence peaks, i.e. without distinct beta coherence, were mostly located near the border of sensorimotor and cognitive/associative subregions as defined by a tractography-based atlas of the STN. Peak coherence values were largely unaltered by the medication state of the subject, however, theta/alpha peaks were more often identified in recordings obtained after administration of dopaminergic medication. Our findings suggest the existence of a frequency-specific topography of cortico-STN coherence within the STN, albeit with considerable spatial overlap between functional networks. Consequently, optimization of deep brain stimulation targeting might remain a trade-off between alleviating motor symptoms and avoiding adverse neuropsychiatric side effects.
Subject(s)
Deep Brain Stimulation , Parkinson Disease , Subthalamic Nucleus , Dopamine Agents , Humans , MagnetoencephalographyABSTRACT
Lead-DBS is an open-source, semi-automatized and widely applied software tool facilitating precise localization of deep brain stimulation electrodes both in native as well as in standardized stereotactic space. While automatized preprocessing steps within the toolbox have been tested and validated in previous studies, the interrater reliability in manual refinements of electrode localizations using the tool has not been objectified so far. Here, we investigate the variance introduced in this processing step by different raters when localizing electrodes based on postoperative CT or MRI. Furthermore, we compare the performance of novel trainees that received a structured training and more experienced raters with an expert user. We show that all users yield similar results with an average difference in localizations ranging between 0.52-0.75 mm with 0.07-0.12 mm increases in variability when using postoperative MRI and following normalization to standard space. Our findings may pave the way toward formal training for using Lead-DBS and demonstrate its reliability and ease-of-use for imaging research in the field of deep brain stimulation.
Subject(s)
Deep Brain Stimulation , Parkinson Disease , Subthalamic Nucleus , Deep Brain Stimulation/methods , Electrodes, Implanted , Humans , Magnetic Resonance Imaging/methods , Parkinson Disease/therapy , Reproducibility of Results , Subthalamic Nucleus/physiologyABSTRACT
OBJECTIVE: The subthalamic nucleus (STN) and internal globus pallidus (GPi) are the most effective targets in deep brain stimulation (DBS) for Parkinson's disease (PD). However, the common and specific effects on brain connectivity of stimulating the 2 nuclei remain unclear. METHODS: Patients with PD receiving STN-DBS (n = 27, 6 women, mean age 64.8 years) or GPi-DBS (n = 28, 13 women, mean age 64.6 years) were recruited for resting-state functional magnetic resonance imaging to assess the effects of STN-DBS and GPi-DBS on brain functional dynamics. RESULTS: The functional connectivity both between the somatosensory-motor cortices and thalamus, and between the somatosensory-motor cortices and cerebellum decreased in the DBS-on state compared with the off state (p < 0.05). The changes in thalamocortical connectivity correlated with DBS-induced motor improvement (p < 0.05) and were negatively correlated with the normalized intersection volume of tissues activated at both DBS targets (p < 0.05). STN-DBS modulated functional connectivity among a wider range of brain areas than GPi-DBS (p = 0.009). Notably, only STN-DBS affected connectivity between the postcentral gyrus and cerebellar vermis (p < 0.001) and between the somatomotor and visual networks (p < 0.001). INTERPRETATION: Our findings highlight common alterations in the motor pathway and its relationship with the motor improvement induced by both STN- and GPi-DBS. The effects on cortico-cerebellar and somatomotor-visual functional connectivity differed between groups, suggesting differentiated neural modulation of the 2 target sites. Our results provide mechanistic insight and yield the potential to refine target selection strategies for focal brain stimulation in PD. ANN NEUROL 2021;90:670-682.
Subject(s)
Deep Brain Stimulation , Globus Pallidus/physiopathology , Parkinson Disease/physiopathology , Parkinson Disease/therapy , Subthalamic Nucleus/physiopathology , Aged , Cerebellum/physiopathology , Deep Brain Stimulation/methods , Female , Globus Pallidus/surgery , Humans , Magnetic Resonance Imaging/methods , Male , Middle Aged , Subthalamic Nucleus/surgery , Thalamus/physiopathologyABSTRACT
Deep brain stimulation (DBS) depends on precise delivery of electrical current to target tissues. However, the specific brain structures responsible for best outcome are still debated. We applied probabilistic stimulation mapping to a retrospective, multidisorder DBS dataset assembled over 15 years at our institution (ntotal = 482 patients; nParkinson disease = 303; ndystonia = 64; ntremor = 39; ntreatment-resistant depression/anorexia nervosa = 76) to identify the neuroanatomical substrates of optimal clinical response. Using high-resolution structural magnetic resonance imaging and activation volume modeling, probabilistic stimulation maps (PSMs) that delineated areas of above-mean and below-mean response for each patient cohort were generated and defined in terms of their relationships with surrounding anatomical structures. Our results show that overlap between PSMs and individual patients' activation volumes can serve as a guide to predict clinical outcomes, but that this is not the sole determinant of response. In the future, individualized models that incorporate advancements in mapping techniques with patient-specific clinical variables will likely contribute to the optimization of DBS target selection and improved outcomes for patients. ANN NEUROL 2021;89:426-443.
Subject(s)
Anorexia Nervosa/therapy , Deep Brain Stimulation/methods , Depressive Disorder, Treatment-Resistant/therapy , Dystonia/therapy , Parkinson Disease/therapy , Tremor/therapy , Adult , Aged , Brain Mapping , Connectome , Female , Globus Pallidus/diagnostic imaging , Gyrus Cinguli/diagnostic imaging , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Patient-Specific Modeling , Probability , Retrospective Studies , Subthalamic Nucleus/diagnostic imaging , Treatment Outcome , Ventral Thalamic Nuclei/diagnostic imagingABSTRACT
BACKGROUND: Finding the optimal deep brain stimulation (DBS) parameters from a multitude of possible combinations by trial and error is time consuming and requires highly trained medical personnel. OBJECTIVE: We developed an automated algorithm to identify optimal stimulation settings in Parkinson's disease (PD) patients treated with subthalamic nucleus (STN) DBS based on imaging-derived metrics. METHODS: Electrode locations and monopolar review data of 612 stimulation settings acquired from 31 PD patients were used to train a predictive model for therapeutic and adverse stimulation effects. Model performance was then evaluated within the training cohort using cross-validation and on an independent cohort of 19 patients. We inverted the model by applying a brute-force approach to determine the optimal stimulation sites in the target region. Finally, an optimization algorithm was established to identify optimal stimulation parameters. Suggested stimulation parameters were compared to the ones applied in clinical practice. RESULTS: Predicted motor outcome correlated with observed outcome (R = 0.57, P < 10-10 ) across patients within the training cohort. In the test cohort, the model explained 28% of the variance in motor outcome differences between settings. The stimulation site for maximum motor improvement was located at the dorsolateral border of the STN. When compared to two empirical settings, model-based suggestions more closely matched the setting with superior motor improvement. CONCLUSION: We developed and validated a data-driven model that can suggest stimulation parameters leading to optimal motor improvement while minimizing the risk of stimulation-induced side effects. This approach might provide guidance for DBS programming in the future. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.