Dataset Information

Pallido-putaminal connectivity predicts outcomes of deep brain stimulation for cervical dystonia.

ABSTRACT: Cervical dystonia is a non-degenerative movement disorder characterized by dysfunction of both motor and sensory cortico-basal ganglia networks. Deep brain stimulation targeted to the internal pallidum is an established treatment, but its specific mechanisms remain elusive, and response to therapy is highly variable. Modulation of key dysfunctional networks via axonal connections is likely important. Fifteen patients underwent preoperative diffusion-MRI acquisitions and then progressed to bilateral deep brain stimulation targeting the posterior internal pallidum. Severity of disease was assessed preoperatively and later at follow-up. Scans were used to generate tractography-derived connectivity estimates between the bilateral regions of stimulation and relevant structures. Connectivity to the putamen correlated with clinical improvement, and a series of cortical connectivity-based putaminal parcellations identified the primary motor putamen as the key node (r = 0.70, P = 0.004). A regression model with this connectivity and electrode coordinates explained 68% of the variance in outcomes (r = 0.83, P = 0.001), with both as significant explanatory variables. We conclude that modulation of the primary motor putamen-posterior internal pallidum limb of the cortico-basal ganglia loop is characteristic of successful deep brain stimulation treatment of cervical dystonia. Preoperative diffusion imaging contains additional information that predicts outcomes, implying utility for patient selection and/or individualized targeting.

SUBMITTER: Raghu ALB

PROVIDER: S-EPMC8719844 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Pallido-putaminal connectivity predicts outcomes of deep brain stimulation for cervical dystonia.

Raghu Ashley L B ALB Eraifej John J Sarangmat Nagaraja N Stein John J FitzGerald James J JJ Payne Stephen S Aziz Tipu Z TZ Green Alexander L AL

Brain : a journal of neurology 20211201 12

Cervical dystonia is a non-degenerative movement disorder characterized by dysfunction of both motor and sensory cortico-basal ganglia networks. Deep brain stimulation targeted to the internal pallidum is an established treatment, but its specific mechanisms remain elusive, and response to therapy is highly variable. Modulation of key dysfunctional networks via axonal connections is likely important. Fifteen patients underwent preoperative diffusion-MRI acquisitions and then progressed to bilate ...[more]

PMID: 34293093

Similar Datasets

Project description:Deep brain stimulation may be an effective therapy for select cases of severe, treatment-refractory Tourette syndrome; however, patient responses are variable, and there are no reliable methods to predict clinical outcomes. The objectives of this retrospective study were to identify the stimulation-dependent structural networks associated with improvements in tics and comorbid obsessive-compulsive behaviour, compare the networks across surgical targets, and determine if connectivity could be used to predict clinical outcomes. Volumes of tissue activated for a large multisite cohort of patients (n = 66) implanted bilaterally in globus pallidus internus (n = 34) or centromedial thalamus (n = 32) were used to generate probabilistic tractography to form a normative structural connectome. The tractography maps were used to identify networks that were correlated with improvement in tics or comorbid obsessive-compulsive behaviour and to predict clinical outcomes across the cohort. The correlated networks were then used to generate 'reverse' tractography to parcellate the total volume of stimulation across all patients to identify local regions to target or avoid. The results showed that for globus pallidus internus, connectivity to limbic networks, associative networks, caudate, thalamus, and cerebellum was positively correlated with improvement in tics; the model predicted clinical improvement scores (P = 0.003) and was robust to cross-validation. Regions near the anteromedial pallidum exhibited higher connectivity to the positively correlated networks than posteroventral pallidum, and volume of tissue activated overlap with this map was significantly correlated with tic improvement (P < 0.017). For centromedial thalamus, connectivity to sensorimotor networks, parietal-temporal-occipital networks, putamen, and cerebellum was positively correlated with tic improvement; the model predicted clinical improvement scores (P = 0.012) and was robust to cross-validation. Regions in the anterior/lateral centromedial thalamus exhibited higher connectivity to the positively correlated networks, but volume of tissue activated overlap with this map did not predict improvement (P > 0.23). For obsessive-compulsive behaviour, both targets showed that connectivity to the prefrontal cortex, orbitofrontal cortex, and cingulate cortex was positively correlated with improvement; however, only the centromedial thalamus maps predicted clinical outcomes across the cohort (P = 0.034), but the model was not robust to cross-validation. Collectively, the results demonstrate that the structural connectivity of the site of stimulation are likely important for mediating symptom improvement, and the networks involved in tic improvement may differ across surgical targets. These networks provide important insight on potential mechanisms and could be used to guide lead placement and stimulation parameter selection, as well as refine targets for neuromodulation therapies for Tourette syndrome.

Project description:Background and purposeDeep brain stimulation is a well-established treatment for generalized dystonia, but outcomes remain variable. Establishment of an imaging marker to guide device targeting and programming could possibly impact the efficacy of deep brain stimulation in dystonia, particularly in the absence of acute clinical markers to indicate benefit. We hypothesize that the stimulation-based functional and structural connectivity using resting-state fMRI and DTI can predict therapeutic outcomes in patients with generalized dystonia and deep brain stimulation.Materials and methodsWe performed a retrospective analysis of 39 patients with inherited or idiopathic-isolated generalized dystonia who underwent bilateral globus pallidus internus deep brain stimulation. After electrode localization, the volumes of tissue activated were modeled and used as seed regions for functional and structural connectivity measures using a normative data base. Resulting connectivity maps were correlated with postoperative improvement in the Unified Dystonia Rating Scale score.ResultsStructural connectivity between the volumes of tissue activated and the primary sensorimotor cortex was correlated with Unified Dystonia Rating Scale improvement, while more anterior prefrontal connectivity was inversely correlated with Unified Dystonia Rating Scale improvement. Functional connectivity between the volumes of tissue activated and primary sensorimotor regions, motor thalamus, and cerebellum was most correlated with Unified Dystonia Rating Scale improvement; however, an inverse correlation with Unified Dystonia Rating Scale improvement was seen in the supplemental motor area and premotor cortex.ConclusionsFunctional and structural connectivity with multiple nodes of the motor network is associated with motor improvement in patients with generalized dystonia undergoing deep brain stimulation. Results from this study may serve as a basis for future development of clinical markers to guide deep brain stimulation targeting and programming in dystonia.

Dataset Information

Pallido-putaminal connectivity predicts outcomes of deep brain stimulation for cervical dystonia.

Publications

Pallido-putaminal connectivity predicts outcomes of deep brain stimulation for cervical dystonia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets