Background: Deep brain stimulation (DBS) is an effective evidence-based therapy for
dystonia. However, no unequivocal predictors of therapy responses exist. We investigate
whether patients optimally responding to DBS present distinct brain network organization and
structural patterns. Methods: Eighty-two dystonia patients with segmental and generalized
dystonia were classified based on the clinical response 36 months after DBS, as responders
or non-responders (above or below 70% improvement, respectively) from which fifty-one met
these requirements (mean age 51.3 ± 13.2 years; 25 female) and were included into further
analysis. From preoperative MRI we assessed cortical thickness and structural covariance,
which were then fed into network analysis using graph theory. We designed a support vector
machine to classify subjects for the clinical response based on group network properties and
individual grey matter fingerprints. Results: Non-responders showed cortical atrophy mainly
in the sensorimotor and visuomotor areas and disturbed network topology in these regions.
Classification analyses achieved 88% of accuracy using individual grey matter atrophy
patterns to predict responders. Conclusion: The analysis of cortical thinning and network
properties could be developed into independent predictors to identify dystonia patients who
benefit from DBS.
... as described previously. 20 Briefly, the procedures included nonbrain data removal, image intensity normalization, tessellation of the gray/white matter boundary, automated correction of topology, and surface deformation to identify tissue borders. In each vertex, cortical thickness was considered as the distance between the white and gray matter surfaces of the reconstructed cortical mantle. ...
... The support vector machine (SVM), a supervised machine learning algorithm, can accurately and effectively solve data classification and regression issues. 20 In the present study, the DBS efficacy prediction was applied with the library for SVM (Version 3.2, https:// www.csie.ntu.edu.tw/~cjlin/ libsv m/) and MATLAB (Version 2018b, Mathworks, Inc.). ...
... Firstly, the size of the cohort was not very large. Although other studies focusing on the DBS outcome only involved a small number of patients, 11,20 there is no doubt that the large cohort could enhance the reliable of model. ...
Aim:
Subthalamic nucleus deep brain stimulation (STN-DBS) has been reported to be effective in treating motor symptoms in Parkinson's disease (PD), which may be attributed to changes in the brain network. However, the association between brain morphology and initial STN-DBS efficacy, as well as the performance of prediction using neuroimaging, has not been well illustrated. Therefore, we aim to investigate these issues.
Methods:
In the present study, 94 PD patients underwent bilateral STN-DBS, and the initial stimulation efficacy was evaluated. Brain morphology was examined by magnetic resonance imaging (MRI). The volume of tissue activated in the motor STN was measured with MRI and computed tomography. The prediction of stimulation efficacy was achieved with a support vector machine, using brain morphology and other features, after feature selection and hyperparameter optimization.
Results:
A higher stimulation efficacy was correlated with a thicker right precentral cortex. No association with subcortical gray or white matter volumes was observed. These morphological features could estimate the individual stimulation response with an r value of 0.5678, an R2 of 0.3224, and an average error of 11.4%. The permutation test suggested these predictions were not based on chance.
Conclusion:
Our results indicate that changes in morphology are associated with the initial stimulation motor response and could be used to predict individual initial stimulation-related motor responses.
... New techniques for the application of DBS have emerged with the advent of imaging, which has resulted in a paradigm shift toward targeted modulation of a particular network (Gonzalez-Escamilla et al., 2019, 2020Horn et al., 2019). Another emerging and as yet unresolved area is how beta oscillatory activity in the basal ganglia is affected by DBS and how this is associated with symptom improvement (Lofredi et al., 2019;Petersson et al., 2020). ...
... In a recent review, we comprehensively describe the causal interrogations and modulations of network states using neuroimaging and electrophysiology . Using structural magnetic resonance imaging (sMRI), we were further able to show in the pre-operative MRI the cortical thickness (CT) in the frontal lobe predicted the clinical improvement after STN-DBS (Muthuraman et al., 2017) and cortical atrophy in sensorimotor areas in dystonia patients (Gonzalez-Escamilla et al., 2019). In the same direction, frontal lobe network proxies can predict postoperative clinical response to STN-DBS using diffusion tensor imaging (DTI; Koirala et al., 2018). ...
We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer’s disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.
... The T out for each patient was obtained at the best improvement score between three and five years post-DBS implantation to provide a long-term clinically stabilised score, (35)(36)(37) excluding two patients who due to the recency of date of implantation, best two-year post-operative scores were used. Unlike movement disorders such as ...
Background: Cervical dystonia is a movement disorder, characterised by involuntary head and neck muscle contractions. Although deep brain stimulation (DBS) of the globus pallidus internus (GPi) is an effective treatment option, motor outcomes can vary even when sufficient targeting accuracy is achieved. Increasing evidence supports a role of brainstem and cerebellum dysfunction in cervical dystonia pathogenesis.
Objective: To determine whether morphometry of brainstem and dentate nuclei, and DBS stimulatory overlap with cerebello-thalamic tracts modelled from normative connectivity, were related to DBS clinical motor outcomes.
Methods: 27 patients with idiopathic cervical dystonia underwent bilateral targeting of the GPi. and were separated into suboptimal and optimal motor outcome groups. Dentate nuclei and brainstem volumes were quantified in association with clinical outcomes. A brainstem shape analysis was conducted and used as a seed to assess connectivity from a normative structural connectome. Patient-specific electrodes were modelled to quantify stimulatory overlap with the GPi and proximity to cerebellothalamic tracts.
Results: GPi implantation accuracy did not significantly differ between groups. Significantly reduced dentate nuclei and brainstem volumes were observed in patients with poorer clinical outcomes. Regional surface shape change of the brainstem was also observed in patients with poorer responses. Fibre tracking from this area intersected cerebellar, pallidal and cortical motor regions. Electrode field intersection with the non-decussating dentatorubrothalamic tract in the right, and in both hemispheres were also positively associated with clinical outcome.
Conclusions: Variability in cerebellar and brainstem morphometry, and stimulation of non-decussating cerebello-thalamic pathways may contribute to the mediation of DBS motor outcomes.
... Through the cortical connectivity-based putaminal parcellations, they further discovered that the connectivity between the primary motor putamen and the posterior GPi limb could predict the GPi-DBS outcomes in cervical dystonia. Also, Gonzalez-Escamilla et al. (2019) proposed that the GM thickness of the regions where structural covariance network topology showed abnormality could significantly stratify the GPi-DBS therapeutic effects in generalized/cervical dystonic patients. However, these studies are almost all about GPi-DBS, and no neuroimaging biomarkers for STN-DBS outcomes exist. ...
Background
The physiopathologic mechanism of Meige syndrome (MS) has not been clarified, and neuroimaging studies centering on cerebellar changes in MS are scarce. Moreover, even though deep brain stimulation (DBS) of the subthalamic nucleus (STN) has been recognized as an effective surgical treatment for MS, there has been no reliable biomarker to predict its efficacy.
Objective
To characterize the volumetric alterations of gray matter (GM) in the cerebellum in MS and to identify GM measurements related to a good STN-DBS outcome.
Methods
We used voxel-based morphometry and lobule-based morphometry to compare the regional and lobular GM differences in the cerebellum between 47 MS patients and 52 normal human controls (HCs), as well as between 31 DBS responders and 10 DBS non-responders. Both volumetric analyses were achieved using the Spatially Unbiased Infratentorial Toolbox (SUIT). Further, we performed partial correlation analyses to probe the relationship between the cerebellar GM changes and clinical scores. Finally, we plotted the receiver operating characteristic (ROC) curve to select biomarkers for MS diagnosis and DBS outcomes prediction.
Results
Compared to HCs, MS patients had GM atrophy in lobule Crus I, lobule VI, lobule VIIb, lobule VIIIa, and lobule VIIIb. Compared to DBS responders, DBS non-responders had lower GM volume in the left lobule VIIIb. Moreover, partial correlation analyses revealed a positive relationship between the GM volume of the significant regions/lobules and the symptom improvement rate after DBS surgery. ROC analyses demonstrated that the GM volume of the significant cluster in the left lobule VIIIb could not only distinguish MS patients from HCs but also predict the outcomes of STN-DBS surgery with high accuracy.
Conclusion
MS patients display bilateral GM shrinkage in the cerebellum relative to HCs. Regional GM volume of the left lobule VIIIb can be a reliable biomarker for MS diagnosis and DBS outcomes prediction.
... The currently leading hypothesis on its neurophysiological basis, though still debated, is that of a network disorder encompassing cortico-basal ganglia-thalamo-cortical and cerebellar networks (2). Despite the absence of marked, readily visible structural alterations in conventional clinical MRI scans, which may even be considered a clinical hallmark of dystonia, data from more precise neuroimaging and anatomical studies support the previous notion, reporting differences in the volume of basal ganglia, cerebellum and cortical structures in patients with isolated dystonias (3)(4)(5). Furthermore, functional MRI studies have also repeatedly pointed to these key regions responsible for sensorimotor processing and integration (6). ...
Background
Deep brain stimulation of the internal globus pallidus (GPi DBS) is an invasive therapeutic modality intended to retune abnormal central nervous system patterns and relieve the patient of dystonic or other motor symptoms.
Objectives
The aim of the presented research was to determine the neuroanatomical signature of GPi DBS modulation and its association with the clinical outcome.
Methods
This open-label fixed-order study with cross-sectional validation against healthy controls analysed the resting-state functional MRI activity changes induced by GPi DBS in 18 dystonia patients of heterogeneous aetiology, focusing on both global (full brain) and local connectivity (local signal homogeneity).
Results
Compared to the switched-off state, the activation of GPi DBS led to the restoration of global subcortical connectivity patterns (in both putamina, diencephalon and brainstem) towards those of healthy controls, with positive direct correlation over large-scale cortico-basal ganglia-thalamo-cortical and cerebellar networks with the clinical improvement. Nonetheless, on average, GPi DBS also seemed to bring local connectivity both in the cortical and subcortical regions farther away from the state detected in healthy controls. Interestingly, its correlation with clinical outcome showed that in better DBS responders, local connectivity defied this effect and approached healthy controls.
Conclusions
All in all, the extent of restoration of both these main metrics of interest towards the levels found in healthy controls clearly correlated with the clinical improvement, indicating that the restoration of network state towards more physiological condition may be a precondition for successful GPi DBS outcome in dystonia.
... The severe structural impairments in those areas would lead to more difficulties in repressing dystonic symptoms. Also, previous studies have, respectively investigated the associations of the clinical outcomes with cortical integrity (56) and functional activities (57), of which results involved regions within sensorimotor related networks. Finally, multimodal imaging studies apart from VBM are also required to assist in describing comprehensive disease characteristics and their associations with clinical outcomes, which aims to screen patients likely to benefit from DBS or other invasive procedures. ...
The understanding of brain structural abnormalities across different clinical forms of dystonia and their contribution to clinical characteristics remains unclear. The objective of this study is to investigate shared and specific gray matter volume (GMV) abnormalities in various forms of isolated idiopathic dystonia. We collected imaging data from 73 isolated idiopathic dystonia patients and matched them with healthy controls to explore the GMV alterations in patients and their correlations with clinical characteristics using the voxel-based morphometry (VBM) technique. In addition, we conducted an activation likelihood estimation (ALE) meta-analysis of previous VBM studies. Our study demonstrated widespread morphometry alterations in patients with idiopathic dystonia. Multiple systems were affected, which mainly included basal ganglia, sensorimotor, executive control, and visual networks. As the result of the ALE meta-analysis, a convergent cluster with increased GMV was found in the left globus pallidus. In subgroup VBM analyses, decreased putamen GMV was observed in all clinic forms, while the increased GMV was observed in parahippocampal, lingual, and temporal gyrus. GD demonstrated the most extensive GMV abnormalities in cortical regions, and the aberrant GMV of the posterior cerebellar lobe was prominent in CD. Moreover, trends of increased GMV regions of the left precuneus and right superior frontal gyrus were demonstrated in the moderate-outcome group compared with the superior-outcome group. Results of our study indicated shared pathophysiology of the disease-centered on the dysfunction of the basal ganglia-thalamo-cortical circuit, impairing sensorimotor integration, high-level motor execution, and cognition of patients. Dysfunction of the cerebello-thalamo-cortical circuit could also be involved in CD especially. Finally, the frontal-parietal pathway may act as a potential marker for predicting treatment outcomes such as deep brain stimulation.
... Subthalamic nuclei deep brain stimulation (STN-DBS) is a well-established treatment for multiple movement disorders, especially Parkinson's disease (PD) [1,2]. STN-DBS has shown long-term efficacy [3] and has typically been used in advanced PD patients since many years [4]. ...
Subthalamic nuclei deep brain stimulation (STN-DBS) is a well-established treatment for Parkinson's disease (PD). Some studies have confirmed the long-term efficacy is associated with brain connectivity; however, whether the initial outcome is associated with brain connectivity and efficacy of prediction based on these factors has not been well investigated. In the present study, a total of 98 patients were divided into a training set (n = 78) and a test set (n = 20). The stimulation and medication responses were calculated based on the motor performance. The functional and structural connectomes were established based on a public database and used to measure the association between stimulation response and brain connectivity. The prediction of initial outcome was achieved via a machine learning algorithm-support vector machine based on the model established with the training set. It was found that the initial outcome of STN-DBS was associated with functional/structural connectivities between the volume of tissue activated and multiple brain regions, including the supplementary motor area, precentral and frontal areas, cingulum, temporal cortex, and striatum. These factors could be used to predict the initial outcome, with an r value of 0.4978 (P = 0.0255). Our study demonstrates a correlation between a specific connectivity pattern and initial outcome of STN-DBS, which could be used to predict the initial outcome of DBS.
... Deep Brain Stimulation (DBS) has matured into a staple of modern therapeutics for movement disorders and is considered a promising tool toward the treatment of psychiatric conditions (Vedam-Mai et al., 2021). More importantly, DBS has been the engine propelling the development of a diverse ecosystem of technological innovations, ranging from surgical navigation systems that incorporate connectome data (Li et al., 2020) to algorithms that predict the therapeutic outcomes of brain stimulation (Gonzalez-Escamilla et al., 2019;Reich et al., 2019), and implantable neurostimulators that integrate chronic monitoring and real-time modulation of neural activity (Stanslaski et al., 2018;Topalovic et al., 2020). ...
... This approach seems promising also in the search for potential biomarkers predicting future clinical effects of DBS. For example, classification using a support vector machine based on the distribution of cortical atrophy within the associative, SM, and visuomotor areas resulted in 88% accuracy in estimating the pallidal DBS outcome in patients with segmental and generalized dystonia (65). The future use of these methods therefore seems promising. ...
Improved care for people with dystonia presents a number of challenges. Major gaps in knowledge exist with regard to how to optimize the diagnostic process, how to leverage discoveries in pathophysiology into biomarkers, and how to develop an evidence base for current and novel treatments. These challenges are made greater by the realization of the wide spectrum of symptoms and difficulties faced by people with dystonia, which go well-beyond motor symptoms. A network of clinicians, scientists, and patients could provide resources to facilitate information exchange at different levels, share mutual experiences, and support each other's innovative projects. In the past, collaborative initiatives have been launched, including the American Dystonia Coalition, the European Cooperation in Science and Technology (COST—which however only existed for a limited time), and the Dutch DystonieNet project. The European Reference Network on Rare Neurological Diseases includes dystonia among other rare conditions affecting the central nervous system in a dedicated stream. Currently, we aim to broaden the scope of these initiatives to a comprehensive European level by further expanding the DystoniaNet network, in close collaboration with the ERN-RND. In line with the ERN-RND, the mission of DystoniaNet Europe is to improve care and quality of life for people with dystonia by, among other endeavors, facilitating access to specialized care, overcoming the disparity in education of medical professionals, and serving as a solid platform to foster international clinical and research collaborations. In this review, both professionals within the dystonia field and patients and caregivers representing Dystonia Europe highlight important unsolved issues and promising new strategies and the role that a European network can play in activating them.
Purpose of review:
Deep brain stimulation (DBS) is currently the most effective treatment for medically refractory dystonia with globus pallidus internus (GPi) usually the preferred target. Despite the overall success of DBS in dystonia, there remains variability in treatment outcome in both short and long-term follow-up, due to various factors. Factors contributing to variability in outcome comprise 'Dystonia Related' including dystonia classification, semiology, duration, body distribution, orthopaedic deformity, aetiology and genetic cause. The majority of these factors are identifiable from clinical assessment, brain MRI and genetic testing, and therefore merit careful preoperative consideration. 'DBS related' factors include brain target, accuracy of lead placement, stimulation parameters, time allowed for response, neurostimulation technology employed and DBS induced side-effects. In this review, factors contributing to variability in short and long-term dystonia DBS outcome are reviewed and discussed.
Recent findings:
The recognition of differential DBS benefit in monogenic dystonia, increasing experience with subthalamic nucleus (STN) DBS and in DBS for Meige syndrome, elucidation of DBS side effects and novel neurophysiological and imaging techniques to assist in predicting clinical outcome.
Summary:
Improved understanding of factors contributing to variability of DBS outcome in dystonia may assist in patient selection and predicting surgical outcomes.
Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI. In three cohorts (two human, one macaque), we find that the resulting morphometric similarity networks (MSNs) have a complex topological organization comprising modules and high-degree hubs. Human MSN modules recapitulate known cortical cytoarchitectonic divisions, and greater inter-regional morphometric similarity was associated with stronger inter-regional co-expression of genes enriched for neuronal terms. Comparing macaque MSNs with tract-tracing data confirmed that morphometric similarity was related to axonal connectivity. Finally, variation in the degree of human MSN nodes accounted for about 40% of between-subject variability in IQ. Morphometric similarity mapping provides a novel, robust, and biologically plausible approach to understanding how human cortical networks underpin individual differences in psychological functions.
Cortical surface area is an increasingly used brain morphology metric that is ontogenetically and phylogenetically distinct from cortical thickness and offers a separate index of neurodevelopment and disease. However, the various existing methods for assessment of cortical surface area from magnetic resonance images have never been systematically compared. We show that the surface area method implemented in FreeSurfer corresponds closely to the exact, but computationally more demanding, mass-conservative (pycnophylactic) method, provided that images are smoothed. Thus, the data produced by this method can be interpreted as estimates of cortical surface area, as opposed to areal expansion. In addition, focusing on the joint analysis of thickness and area, we compare an improved, analytic method for measuring cortical volume to a permutation-based nonparametric combination (NPC) method. We use the methods to analyze area, thickness and volume in young adults born preterm with very low birth weight, and show that NPC analysis is a more sensitive option for studying joint effects on area and thickness, giving equal weight to variation in both of these 2 morphological features.
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is nowadays an evidence-based state of the art therapy option for motor and non-motor symptoms in patients with Parkinson's disease (PD). However, the exact anatomical regions of the cerebral network that are targeted by STN-DBS have not been precisely described and no definitive pre-intervention predictors of the clinical response exist. In this study, we test the hypothesis that the clinical effectiveness of STN-DBS depends on the connectivity profile of the targeted brain networks. Therefore, we used diffusion-weighted imaging (DWI) and probabilistic tractography to reconstruct the anatomical networks and the graph theoretical framework to quantify the connectivity profile. DWI was obtained pre-operatively from 15 PD patients who underwent DBS (mean age = 67.87 ± 7.88, 11 males, H&Y score = 3.5 ± 0.8) using a 3T MRI scanner (Philips Achieva). The pre-operative connectivity properties of a network encompassing frontal, prefrontal cortex and cingulate gyrus were directly linked to the postoperative clinical outcome. Eccentricity as a topological-characteristic of the network defining how cerebral regions are embedded in relation to distant sites correlated inversely with the applied voltage at the active electrode for optimal clinical response. We found that network topology and pre-operative connectivity patterns have direct influence on the clinical response to DBS and may serve as important and independent predictors of the postoperative clinical outcome.
Introduction:
Pallidal deep brain stimulation (GPi-DBS) is an effective therapy for isolated dystonia, but 10-20% of patients show improvement below 25-30%. We here investigated causes of insufficient response to GPi-DBS in isolated dystonia in a cross-sectional study.
Methods:
Patients with isolated dystonia at time of surgery, and <30% improvement on the Burke-Fahn-Marsden dystonia-rating-scale (BFMDRS) after ≥6 months of continuous GPi-DBS were videotaped ON and OFF stimulation, and history, preoperative videos, brain MRI, medical records, stimulation settings, stimulation system integrity, lead location, and genetic information were obtained and reviewed by an expert panel.
Results:
22 patients from 11 centres were included (8 men, 14 women; 9 generalized, 9 segmental, 3 focal, 1 bibrachial dystonia; mean (range): age 48.7 (25-72) years, disease duration 22.0 (2-40) years, DBS duration 45.5 (6-131) months). Mean BFMDRS-score was 31.7 (4-93) preoperatively and 32.3 (5-101) postoperatively. Half of the patients (n = 11) had poor lead positioning alone or in combination with other problems (combined with: other disease n = 6, functional dystonia n = 1, other problems n = 2). Other problems were disease other than isolated inherited or idiopathic dystonia (n = 5), fixed deformities (n = 2), functional dystonia (n = 3), and other causes (n = 1). Excluding patients with poor lead location from further analysis, non-isolated dystonia accounted for 45.5%, functional dystonia for 27.3%, and fixed deformities for 18.2%. In patients with true isolated dystonia, lead location was the most frequent problem.
Conclusion:
After exclusion of lead placement and stimulation programming issues, non-isolated dystonia, functional dystonia and fixed deformities account for the majority of GPi-DBS failures in dystonia.
In recent years, researchers have increased attentions to the morphological brain network, which is generally constructed by measuring the mathematical correlation across regions using a certain morphometric feature, such as regional cortical thickness and voxel intensity. However, cerebral structure can be characterized by various factors, such as regional volume, surface area, and curvature. Moreover, most of the morphological brain networks are population-based, which has limitations in the investigations of individual difference and clinical applications. Hence, we have extended previous studies by proposing a novel method for realizing the construction of an individual-based morphological brain network through a combination of multiple morphometric features. In particular, interregional connections are estimated using our newly introduced feature vectors, namely, the Pearson correlation coefficient of the concatenation of seven morphometric features. Experiments were performed on a healthy cohort of 55 subjects (24 males aged from 20 to 29 and 31 females aged from 20 to 28) each scanned twice, and reproducibility was evaluated through test–retest reliability. The robustness of morphometric features was measured firstly to select the more reproducible features to form the connectomes. Then the topological properties were analyzed and compared with previous reports of different modalities. Small-worldness was observed in all the subjects at the range of the entire network sparsity (20–40%), and configurations were comparable with previous findings at the sparsity of 23%. The spatial distributions of the hub were found to be significantly influenced by the individual variances, and the hubs obtained by averaging across subjects and sparsities showed correspondence with previous reports. The intraclass coefficient of graphic properties (clustering coefficient = 0.83, characteristic path length = 0.81, betweenness centrality = 0.78) indicates the robustness of the present method. Results demonstrate that the multiple morphometric features can be applied to form a rational reproducible individual-based morphological brain network.
While deep brain stimulation of the subthalamic nucleus (STN-DBS) has evolved to an
evidence-based standard treatment for Parkinson’s disease (PD), the targeted cerebral
networks are poorly described and no objective predictors for the postoperative clinical
response exist.
To elucidate the systemic mechanisms of DBS, we analysed cerebral grey matter properties
using cortical thickness measurements and addressed the dependence of structural integrity on
clinical outcome. Thirty one patients with idiopathic PD without dementia (23 males, age:
63.4±9.3, Hoehn and Yahr: 3.5 ± 0.8) were selected for DBS treatment. The patients
underwent whole-brain preoperative T1 MR-Imaging at 3 T. Grey matter integrity was
assessed by cortical thickness measurements with FreeSurfer. The clinical motor outcome
markedly improved after STN-DBS in comparison to the preoperative condition. The cortical
thickness of the frontal lobe (paracentral area and superior frontal region) predicted the
clinical improvement after STN-DBS. Moreover, in patients with cortical atrophy of these
areas a higher stimulation voltage was needed for an optimal clinical response. Our data
suggest that the effects of STN-DBS in PD directly depend on frontal lobe grey matter
integrity. Cortical atrophy of this region might represent a distinct predictor of a poor motor
outcome after STN-DBS in PD patients.
Objective:
Benign Essential Blepharospasm (BEB) and hemifacial spasm (HFS) are the most common hyperkinetic movement disorders of facial muscles. Although similar in clinical presentation different pathophysiological mechanisms are assumed. Botulinum Neurotoxin (BoNT) is a standard evidence-based treatment for both conditions. In this study we aimed to assess grey matter microstructural differences between these two groups of patients and compared them with healthy controls. In patients we furthermore tracked the longitudinal morphometric changes associated with BoNT therapy. We hypothesized microstructural differences between the groups at the time point of maximum symptoms representation and distinct longitudinal grey matter dynamics with symptom improvement.
Methods:
Cross-sectional and longitudinal analyses of 3T 3D-T1 MRI images from BEB, HFS patients prior to and one month after BoNT therapy and from a group of age and sex matched healthy controls. Cortical thickness as extracted from Freesurfer was assessed as parameter of microstructural integrity.
Results:
BoNT therapy markedly improved motor symptoms in patients with BEB and HFS. Significant differences of grey matter integrity have been found between the two patients groups. The BEB group showed lower cortical thickness at baseline in the frontal-rostral, supramarginal and temporal regions compared to patients with HFS. In this group BoNT treatment was associated with a cortical thinning in the primary motor cortex and the pre-supplementary motor area (pre-SMA). Contrary patients with HFS showed no longitudinal CT changes. A decreased cortical thickness was attested bilaterally in the temporal poles and in the right superior frontal region in BEB patients in comparison to HC. Patients in the HFS group presented a decreased CT in the left lingual gyrus and temporal pole.
Conclusions:
Although patients with BEB and HFS present clinically with involuntary movements of facial muscles, they exhibited differences in cortical thickness. While BoNT therapy was equally effective in both groups, widespread changes of cortical morphology occurred only in BEB patients. We demonstrated specific disease- and therapy-dependent structural changes induced by BoNT in the studied hyperkinetic conditions.
Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping, based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI. In three cohorts (two human, one macaque), we find that the resulting morphometric similarity networks (MSNs) have a complex topological organisation comprising modules and high-degree hubs. Human MSN modules recapitulate known cortical cytoarchitectonic divisions, and greater inter-regional morphometric similarity was associated with stronger inter-regional co-expression of genes enriched for neuronal terms. Comparing macaque MSNs to tract-tracing data confirmed that morphometric similarity was related to axonal connectivity. Finally, variation in the degree of human MSN nodes accounted for about 40% of between-subject variability in IQ. Morphometric similarity mapping provides a novel, robust and biologically plausible approach to understanding how human cortical networks underpin individual differences in psychological functions.
Objective:
To investigate cortical activity using scalp EEG in patients with isolated dystonia treated with chronic deep brain stimulation (DBS), on and off stimulation.
Methods:
We analyzed 64-channel scalp EEG in 12 isolated dystonia patients treated with chronic DBS (7 generalized, 5 cervical/segmental; 7 globus pallidus (GP), 5 subthalamic nucleus (STN)), and 20 healthy age-matched controls. Recordings during rest and movement task, and clinical motor scores, were collected with DBS-on and during a 90-min DBS washout.
Results:
Resting state alpha power in the dominant (or contralateral to more dystonic side) motor cortex channel during DBS was comparable to healthy controls, but it increased when DBS was stopped. Resting state and movement-related alpha coherence between bilateral motor cortex channels was increased off DBS.
Conclusions:
Chronic DBS reduces exaggerated alpha oscillations and interhemispheric alpha coherence in the motor cortex of patients with isolated dystonia.
Significance:
These findings complement related studies in Parkinson's disease and support the view that network desynchronization is a prominent mechanism of DBS in movement disorders.
Background:
Deep brain stimulation (DBS) of the globus pallidus internus (GPi-DBS) is among the most effective treatment options for dystonias. Because the term "dystonia" is defined by a characteristic phenomenology of involuntary muscle contractions, which may present with a large clinical and pathogenetic heterogeneity, decision making for or against GPi-DBS can be difficult in individual patients.
Methods:
A search of the PubMed database for research and review articles, focused on "deep brain stimulation" and "dystonia" was used to identify clinical trials and to determine current concepts in the surgical management of dystonia. Patient selection in previous studies was recategorized by the authors using the new dystonia classification put forward by a consensus committee of experts in dystonia research. The evidence and knowledge gaps are summarized and commented by the authors taking into account expert opinion and personal clinical experience for providing practical guidance in patient selection for DBS in dystonia.
Results:
The literature review shows that pallidal deep brain stimulation is most effective in patients with isolated dystonia irrespective of the underlying etiology. In contrast, patients with combined dystonias are less likely to benefit from DBS, because the associated neurological symptoms (e.g., hypotonia or ataxia), with the exception of myoclonus, do not respond to pallidal neurostimulation.
Conclusions:
It is important to recognize the clinical features of dystonia, because the distinction between isolated and combined dystonia syndromes may predict the treatment response to pallidal deep brain stimulation. The aim of this review is to help guide clinicians with advising patients about deep brain stimulation therapy for dystonia and refering appropriate candidates to surgical centers.
![General workflow for identifying putative image predictor markers of GPi-DBS clinical outcomes. From left to right: the MRI data were processed in FreeSurfer to obtain a regional estimation of cortical thickness (CT) and to construct the group covariance matrices. In each of the 2 cohorts, group-wise analyses between patients showing moderate outcome (MOG) and superior outcome (SOG) 3 years after GPi-DBS were then conducted for CT, subcortical volumes, and network topology (metrics: gamma, lambda, and sigma). For predicting the GPi-DBS responsiveness, as the network analyses do not straightforwardly allow deriving individual measures, we took advantage of the group-specific metrics being created at different network densities (n = 20 for each group) and extracted the values for each density to create a group-level SVM to test the network parameters. To further bridge the connection between the individual structural markers and the network connectivity, the cortical thickness of the regions showing altered local connectivity and that in turn also showed decreased structure were used as individual "network-derived" features into the SVM. These 2 kinds of features (network metrics for all single densities and network-derived) were compared against a third model in which the volume of the subcortical structures showing group differences was used as features in the SVM. [Color figure can be viewed at wileyonlinelibrary.com]](https://www.researchgate.net/profile/Gabriel-Gonzalez-Escamilla/publication/334452163/figure/fig1/AS:794603519229953@1566459650719/General-workflow-for-identifying-putative-image-predictor-markers-of-GPi-DBS-clinical_Q320.jpg)
![Cortical thinning in the brain of the moderate-outcome group. (A) Overlap map depicting the regions where GPi-DBS moderate-outcome dystonia patients showed decreased cortical thickness compared with the superior-outcome group in both discovery and independent test cohorts. Top row, lateral hemisphere surfaces; bottom row, medial hemisphere surfaces. Fp, frontal pole; infF, inferior frontal; SupF, superior frontal; latOcc, lateral occipital; SoM, sensorimotor area (paracentral); PrC, precuneus; pCal, pericalcarine; vPM, ventral primary motor; midF, middle frontal. (B) Regression plots showing that patients with higher structural integrity require lower DBS stimulation amplitudes to achieve superior outcomes (red line). The same trend is observed for moderate-outcome (blue) groups. Nuisance variables: age and sex; P corrected for multiple comparisons using Monte Carlo Z simulations at P < 0.05. [Color figure can be viewed at wileyonlinelibrary.com]](https://www.researchgate.net/profile/Gabriel-Gonzalez-Escamilla/publication/334452163/figure/fig2/AS:794603519242243@1566459650796/Cortical-thinning-in-the-brain-of-the-moderate-outcome-group-A-Overlap-map-depicting_Q320.jpg)
