Connectomic Targets für die Tiefenhirnstimulation

Deep brain stimulation (DBS), a highly effective and well-established treatment option for movement disorders, is now also used to treat psychiatric disorders, such as obsessive-compulsive disorder (OCD) or major depression. A variety of surgical targets for DBS have been proposed not only for different diseases but also for the same disease. However, different targets may potentially lie within the same brain network or even alongside the same fiber bundle which is responsible for clinical improvement. Within the scope of this study, we hence investigated whether different stimulation sites would modulate one common tract target mediating beneficial OCD outcome. Specifically, four cohorts of OCD patients that underwent DBS to either the anterior limb of the internal capsule (ALIC) or the subthalamic nucleus (STN) were analyzed using a connectomic approach. Fiber tracts that were associated with clinical improvement – based on the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) – were isolated, assigned with predictive values and visualized. The same fronto-subcortical fiber tract that was positively discriminative of good clinical outcome emerged for both target-specific cohorts. Moreover, the tract derived from data of the ALIC-cohort was predictive of clinical improvement in the STN-cohort and vice versa. The results suggest that modulating a specific fronto-subthalamic fiber bundle may represent an important unifying substrate for improving global obsessive-compulsive behavior in OCD across different stimulation sites. In synergy, the study advances the concept of connectomic deep brain stimulation above and beyond OCD, showing for the first time that a connectivity-derived model could potentially facilitate defining the connectomic target for DBS.Die Tiefe Hirnstimulation (DBS), eine hochwirksame und etablierte Behandlungsoption bei Bewegungsstörungen, wird mittlerweile auch bei psychiatrischen Erkrankungen wie Zwangsstörungen (OCD) oder schweren Depressionen eingesetzt. Mehrere chirurgische Ziele für die DBS existieren nicht nur für verschiedene Krankheiten, sondern teilweise auch für dieselbe Krankheit. Möglicherweise liegen jedoch unterschiedliche Ziele innerhalb eines selben Gehirnnetzwerks oder sogar innerhalb desselben Faserbündels, welches für die klinische Verbesserung verantwortlich ist. Im Rahmen dieser Studie untersuchten wir daher, ob verschiedene Stimulationsorte einen gemeinsamen Trakt modulieren, welcher ein vorteilhaftes klinisches OCD-Ergebnis vermittelt. Konkret wurden vier Kohorten von Patienten mit einer Zwangsstörung, bei welchen die Implantation einer DBS entweder an dem vorderen Teil der Capsula interna (ALIC) oder am Nucleus subthalamicus (STN) durchgeführt wurde, unter Benutzung eines strukturellen Konnektoms analysiert. Fasertrakte, die mit einer klinischen Verbesserung assoziiert waren – basierend auf der Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) – wurden isoliert, mit prädiktiven Werten belegt und visualisiert. Für beide zielspezifische Kohorten trat der gleiche fronto-subkortikale Fasertrakt auf, der mit einem guten klinischen Ergebnis assoziiert war. Darüber hinaus war der aus den Daten der ALIC-Kohorte abgeleitete Trakt prädiktiv für eine klinische Verbesserung in der STN-Kohorte und umgekehrt. Die Ergebnisse legen nahe, dass die Modulation eines spezifischen fronto-subthalamischen Faserbündels ein wichtiges verbindendes Substrat zur Verbesserung des Zwangsverhaltens bei Zwangsstörungen über verschiedene Stimulationsorte hinweg darstellen kann. In Synergie entwickelt diese Studie das Konzept der konnektomischen Tiefenhirnstimulation über die Zwangsstörung hinaus und zeigt erstmalig, dass ein von der Konnektivität abgeleitetes Modell möglicherweise die Definition eines konnektomischen Ziels für die DBS erleichtern könnte

Mapping holmes tremor circuit using the human brain connectome

ObjectiveHolmes tremor is a debilitating movement disorder with limited treatment options. Lesions causing Holmes tremor can occur in multiple different brain locations, leaving the neuroanatomical substrate unclear. Here, we test whether lesion locations that cause Holmes tremor map to a connected brain circuit and whether this circuit might serve as a useful therapeutic target.MethodsCase reports of Holmes tremor caused by focal brain lesions were identified through a systematic literature search. Connectivity between each lesion location and the rest of the brain was computed using resting state functional connectivity magnetic resonance imaging data from 1,000 healthy volunteers. Commonalities across lesion locations were identified. This Holmes tremor circuit was then compared to neurosurgical treatment targets and clinical efficacy.ResultsWe identified 36 lesions causing Holmes tremor, which were scattered across multiple different brain regions. However, all lesion locations were connected to a common brain circuit with nodes in the red nucleus, thalamus, globus pallidus, and cerebellum. In cases with effective neurosurgical treatment, the treatment target was connected with the lesion location, indicating that a second hit to the same circuit might be beneficial. Commonly used deep brain stimulation targets such as the ventral intermediate nucleus and subthalamic nucleus fell outside our Holmes tremor circuit, whereas the globus pallidus target was close, consistent with published clinical response rates for these targets.InterpretationLesions causing Holmes tremor are part of a single connected brain circuit that may serve as an improved therapeutic target.</p

Lead-OR: A multimodal platform for deep brain stimulation surgery

Background: Deep brain stimulation (DBS) electrode implant trajectories are stereotactically defined using preoperative neuroimaging. To validate the correct trajectory, microelectrode recordings (MERs) or local field potential recordings can be used to extend neuroanatomical information (defined by MRI) with neurophysiological activity patterns recorded from micro- and macroelectrodes probing the surgical target site. Currently, these two sources of information (imaging vs. electrophysiology) are analyzed separately, while means to fuse both data streams have not been introduced. Methods: Here, we present a tool that integrates resources from stereotactic planning, neuroimaging, MER, and high-resolution atlas data to create a real-time visualization of the implant trajectory. We validate the tool based on a retrospective cohort of DBS patients (N = 52) offline and present single-use cases of the real-time platform. Results: We establish an open-source software tool for multimodal data visualization and analysis during DBS surgery. We show a general correspondence between features derived from neuroimaging and electrophysiological recordings and present examples that demonstrate the functionality of the tool. Conclusions: This novel software platform for multimodal data visualization and analysis bears translational potential to improve accuracy of DBS surgery. The toolbox is made openly available and is extendable to integrate with additional software packages

Identifying therapeutic targets from spontaneous beneficial brain lesions

Brain damage can occasionally result in paradoxical functional benefit, which could help identify therapeutic targets for neuromodulation. However, these beneficial lesions are rare and lesions in multiple different brain locations can improve the same symptom. Using a technique called lesion network mapping, we show that heterogeneous lesion locations resulting in tremor relief are all connected to common nodes in the cerebellum and thalamus, the latter of which is a proven deep brain stimulation target for tremor. These results suggest that lesion network mapping can identify the common substrate underlying therapeutic lesions and effective therapeutic targets. Ann Neurol 2018;83:153-15

Do We Need a Human post mortem Whole-Brain Anatomical Ground Truth in in vivo Magnetic Resonance Imaging?

Non-invasive in vivo neuroimaging techniques provide a wide array of possibilities to study human brain function. A number of approaches are available that improve our understanding of the anatomical location of brain activation patterns, including the development of probabilistic conversion tools to register individual in vivo data to population based neuroanatomical templates. Two elegant examples were published by Horn et al. (2017) in which a method was described to warp DBS electrode coordinates, and histological data to MNI-space (Ewert et al., 2017). The conversion of individual brain scans to a standard space is done assuming that individual anatomical scans provide a reliable image of the underlying neuroanatomy. It is unclear to what extent spatial distortions related to tissue properties, or MRI artifacts exist in these scans. Therefore, the question rises whether the anatomical information from the individual scans can be considered a real ground truth. To accommodate the knowledge-gap as a result of limited anatomical information, generative brain models have been developed circumventing these challenges through the application of assumption sets without recourse to any ground truth. We would like to argue that, although these efforts are valuable, the definition of an anatomical ground truth is preferred. Its definition requires a system in which non-invasive approaches can be validated using invasive methods of investigation. We argue that the application of post mortem MRI studies in combination with microscopy analyses brings an anatomical ground truth for the human brain within reach, which is of importance for all research within the human in vivo neuroimaging field

Lead-DBS v3.0: Mapping Deep Brain Stimulation Effects to Local Anatomy and Global Networks.

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

Comparison of patient-specific and normative connectivity profiles in deep brain stimulation

Objective: Brain connectivity profiles seeding from deep brain stimulation (DBS) electrodes have emerged as informative tools to estimate outcome variability across DBS patients. Given the limitations of acquiring and processing patient-specific diffusion-weighted imaging data, a number of studies have employed normative atlases of the human connectome. To date, it remains unclear whether patient-specific connectivity information would strengthen the accuracy of such analyses. Here, we compared similarities and differences between patient-specific, disease-matched and normative structural connectivity data and estimated the clinical improvement that they may generate. Methods: Data from 33 patients suffering from Parkinson’s disease who underwent surgery at three different centers were retrospectively collected. Stimulation-dependent connectivity profiles seeding from active contacts were estimated using three modalities, namely, either patient-specific diffusion-MRI data, disease-matched or normative group connectome data (acquired in healthy young subjects). Based on these profiles, models of optimal connectivity were constructed and used to estimate the clinical improvement in out-of-sample data. Results: All three modalities resulted in highly similar optimal connectivity profiles that could largely reproduce findings from prior research based on a novel multicenter cohort. In a data-driven approach that estimated optimal whole-brain connectivity profiles, out-of-sample predictions of clinical improvements were calculated. Using either patient-specific connectivity (R = 0.43 at p = 0.001), an age- and disease-matched group connectome (R = 0.25, p = 0.048) or a normative connectome based on healthy/young subjects (R = 0.31 at p = 0.028), significant predictions could be made, and the underlying optimal connectivity profiles were highly similar. Conclusion: Our results of patient-specific connectivity and normative connectomes lead to similar main conclusions about which brain areas are associated with clinical improvement. Nevertheless, although the results were not significantly different, they hint at the fact that patient-specific connectivity has potential for estimating slightly more variance when compared to group connectomes. Furthermore, the use of normative connectomes involves datasets with high signal-to-noise acquired on specialized MRI hardware, while clinical datasets such as the ones used here may not exactly match their quality. Our findings support the role of DBS electrode connectivity profiles as a promising method to investigate DBS effects and to potentially guide DBS programming.Zielsetzung: Konnektivitätsprofile des Gehirns, die von Elektroden zur Tiefenhirnstimulation (THS) ausgehen, haben sich als informativ für die Schätzung von Variabilität im Behandlungserfolg bei THS-PatientInnen erwiesen. Angesichts von Einschränkungen bei der Erhebung und Verarbeitung patientenspezifischer, diffusionsgewichteter Bilddaten wurden in einer Reihe von Studien normative Atlanten des menschlichen Konnektivitätsprofils verwendet. Bis heute ist unklar, ob patientenspezifische Konnektivitätsinformation die Genauigkeit solcher Analysen verbessern würde. Ziel dieser Studie war der Vergleich zwischen Ähnlichkeiten und Unterschieden patientenspezifischer, krankheits-gematchter und normativer, struktureller Konnektivitätsdaten, sowie der Fähigkeit dieser Methoden zur Vorhersage eines etwaigen klinischen Behandlungserfolges. Methoden: Die Analysen basierten auf retrospektiven Daten von 33 Parkinson-PatientInnen, welche an drei verschiedenen Zentren operiert worden waren. Stimulationsabhängige Konnektivitätsprofile mit Ursprung in aktiven DBS-Kontakten wurden mittels der drei Modalitäten geschätzt, also entweder basierend auf patientenspezifischen, diffusionsgewichteten MRT-Daten, oder auf krankheits-gematchten sowie auf normativen Gruppenkonnektivitätsdaten (erhoben an gesunden, jungen ProbandInnen). Auf Grundlage dieser Profile wurden Modelle optimaler Konnektivität konstruiert und zur Schätzung des klinischen Behandlungserfolgs in unabhängigen Daten herangezogen. Ergebnisse: Alle drei Modalitäten führten zu sehr ähnlichen optimalen Konnektivitätsprofilen, mit Hilfe derer sich auf Grundlage einer neuartigen multizentrischen Kohorte vorherige Forschungsbefunde weitgehend reproduzieren ließen. In einem datengesteuerten Ansatz, bei dem optimale Konnektivitätsprofile über das gesamte Gehirn hinweg geschätzt wurden, wurden Vorhersagen über den klinischen Behandlungserfolg in unabhängigen Daten berechnet. Unter Verwendung entweder der patientenspezifischen Konnektivität (R = 0,43 bei p = 0,001), eines alters- und krankheits-gematchten Gruppenkonnektivitätsprofils (R = 0,25, p = 0,048) oder eines normativen Konnektivitätsprofils basierend auf Daten gesunder/junger ProbandInnen (R = 0,31 bei p = 0,028) konnten signifikante Vorhersagen getroffen werden, wobei die zugrunde liegenden optimalen Konnektivitätsprofile große Ähnlichkeit aufwiesen. Schlussfolgerung: Unsere Ergebnisse, welche patientenspezifische sowie normative Konnektivitätsprofile einbeziehen, führen zu ähnlichen Hauptschlussfolgerungen darüber, welche Hirnareale mit klinischem Behandlungserfolg assoziiert sind. Obwohl sich die Ergebnisse nicht signifikant unterschieden, deuten sie dennoch darauf hin, dass patientenspezifische Konnektivität über Potenzial zur Schätzung geringfügig höherer Varianz im Vergleich zu gruppenbasierten Konnektivitäsprofilen verfügt. Darüber hinaus stützen sich Analysen, welche auf normativen Konnektivitätsprofile basieren, auf Datensätze mit hohem Signal-Rausch-Verhältnis, welche durch spezialisierte MRT-Technologie erfasst wurden, während klinische Datensätze, wie sie auch in dieser Studie herangezogen wurden, diesen an Qualität möglicherweise nicht gleichkommen. Unsere Befunde stützen die Rolle von Konnektivitätsprofilen, welche von THS-Elektroden ausgehen, als eine vielversprechende Methode zur Untersuchung von THS-Effekten und möglicherweise zur Verbesserung der THS-Programmierung

Deep brain stimulation for essential tremor versus essential tremor plus: should we target the same spot in the thalamus?

BackgroundAlthough ET is a phenomenologically heterogeneous condition, thalamic DBS appears to be equally effective across subtypes. We hypothesized stimulation sites optimized for individuals with essential tremor (ET) would differ from individuals with essential tremor plus syndrome (ET-plus). We examined group differences in optimal stimulation sites within the ventral thalamus and their overlap of with relevant white matter tracts. By capturing these differences, we sought to determine whether ET subtypes are associated with anatomically distinct neural pathways.MethodsA retrospective chart review was conducted on ET patients undergoing VIM DBS at MUSC between 01/2012 and 02/2022. Clinical, demographic, neuroimaging, and DBS stimulation parameter data were collected. Clinical characteristics and pre-DBS videos were reviewed to classify ET and ET-plus cohorts. Patients in ET-plus cohorts were further divided into ET with dystonia, ET with ataxia, and ET with others. DBS leads were reconstructed using Lead-DBS1 and the volume of tissue activated (VTA) overlap was performed using normative connectomes. Tremor improvement was measured by reduction in a subscore of tremor rating scale (TRS) post-DBS lateralized to the more affected limb.ResultsSixty-eight ET patients were enrolled after initial screening, of these 10 ET and 24 ET-plus patients were included in the final analyses. ET group had an earlier age at onset (p = 0.185) and underwent surgery at a younger age (p = 0.096). Both groups achieved effective tremor control. No significant differences were found in lead placement or VTA overlap within ventral thalamus. The VTA center of gravity (COG) in the ET-plus cohort was located dorsal to that of the ET cohort. No significant differences were found in VTA overlap with the dentato-rubral-thalamic (DRTT) tracts or the ansa lenticularis. Dystonia was more prevalent than ataxia in the ET-plus subgroups (n = 18 and n = 5, respectively). ET-plus with dystonia subgroup had a more medial COG compared to ET-plus with ataxia.ConclusionVIM DBS therapy is efficacious in patients with ET and ET-plus. There were no significant differences in optimal stimulation site or VTA overlap with white-matter tracts between ET, ET-plus and ET-plus subgroups