Lead-OR: a multimodal platform for deep brain stimulation surgery
- Charité - Universitätsmedizin Berlin, Germany
- University Health Network, Canada
Abstract
Background: Deep Brain Stimulation (DBS) electrode implant trajectories are stereotactically defined using preoperative neuroimaging. To validate the correct trajectory, microelectrode recordings (MER) or local field potential recordings (LFP) can be used to extend neuroanatomical information (defined by magnetic resonance imaging) 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.
Funding: Deutsche Forschungsgesellschaft (410169619, 424778381), Deutsches Zentrum für Luftund Raumfahrt (DynaSti), National Institutes of Health (2R01 MH113929), Foundation for OCD Research (FFOR).
Data availability
All processed data and code needed to reproducemain findings of the study aremade openly available in de-identified form (see figure legends). This can be found in https://github.com/simonoxen/Lead-OR_Supplementary and, when file size allowed, attached to the publication. Due to data privacy regulations of patient data, raw data cannot be publicly shared. Upon reasonable request to the corresponding author, data can be made available after setting up a data sharing agreement between our host institution (Charité - Universitätsmedizin Berlin) and the inquiring party. All code used to analyze the dataset is available within Lead-DBS /-OR software (https://github.com/netstim/leaddbs; https://github.com/netstim/SlicerNetstim)
Article and author information
Author details
Wolf-Julian Neumann
Funding
Deutsche Forschungsgemeinschaft (Emmy Noether Stipend 410169619)
- Andreas Horn
Deutsche Forschungsgemeinschaft (Project ID 424778371)
- Andreas Horn
Deutsche Forschungsgemeinschaft (Project ID 424778371)
- Wolf-Julian Neumann
Bundesministerium für Bildung und Forschung (Project iDBS FKZ01GQ1802)
- Wolf-Julian Neumann
Deutsches Zentrum für Luft- und Raumfahrt (DynaSti grant within the EU Joint Programme Neurodegenerative Disease Research,JPND)
- Andreas Horn
National Institutes of Health (2R01 MH113929)
- Andreas Horn
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: The collection and analysis of all patient data used for this article was approved by the Local Ethics committee of Charité - Universitätsmedizin Berlin (master vote EA2/145/21). All data were analyzed retrospectively and obtained in deidentified from Medical Records of Charité. Hence, following local guidelines in Berlin/Brandenburg as well as NIH guidelines for human subjects research, no explicit patient consent to analyze and publish was obtained/necessary.
Copyright
© 2022, Oxenford et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,696
- views
-
- 445
- downloads
-
- 12
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Lead-OR: a multimodal platform for deep brain stimulation surgery
eLife 11:e72929.
https://doi.org/10.7554/eLife.72929
Further reading
-
- Medicine
Background:
Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a severe and deadly adverse event following ERCP. The ideal method for predicting PEP risk before ERCP has yet to be identified. We aimed to establish a simple PEP risk score model (SuPER model: Support for PEP Reduction) that can be applied before ERCP.
Methods:
This multicenter study enrolled 2074 patients who underwent ERCP. Among them, 1037 patients each were randomly assigned to the development and validation cohorts. In the development cohort, the risk score model for predicting PEP was established via logistic regression analysis. In the validation cohort, the performance of the model was assessed.
Results:
In the development cohort, five PEP risk factors that could be identified before ERCP were extracted and assigned weights according to their respective regression coefficients: –2 points for pancreatic calcification, 1 point for female sex, and 2 points for intraductal papillary mucinous neoplasm, a native papilla of Vater, or the pancreatic duct procedures (treated as ‘planned pancreatic duct procedures’ for calculating the score before ERCP). The PEP occurrence rate was 0% among low-risk patients (≤0 points), 5.5% among moderate-risk patients (1–3 points), and 20.2% among high-risk patients (4–7 points). In the validation cohort, the C statistic of the risk score model was 0.71 (95% CI 0.64–0.78), which was considered acceptable. The PEP risk classification (low, moderate, and high) was a significant predictive factor for PEP that was independent of intraprocedural PEP risk factors (precut sphincterotomy and inadvertent pancreatic duct cannulation) (OR 4.2, 95% CI 2.8–6.3; p<0.01).
Conclusions:
The PEP risk score allows an estimation of the risk of PEP prior to ERCP, regardless of whether the patient has undergone pancreatic duct procedures. This simple risk model, consisting of only five items, may aid in predicting and explaining the risk of PEP before ERCP and in preventing PEP by allowing selection of the appropriate expert endoscopist and useful PEP prophylaxes.
Funding:
No external funding was received for this work.
-
- Medicine
Estrogen significantly impacts women’s health, and postmenopausal hypertension is a common issue characterized by blood pressure fluctuations. Current control strategies for this condition are limited in efficacy, necessitating further research into the underlying mechanisms. Although metabolomics has been applied to study various diseases, its use in understanding postmenopausal hypertension is scarce. Therefore, an ovariectomized rat model was used to simulate postmenopausal conditions. Estrogen levels, blood pressure, and aortic tissue metabolomics were analyzed. Animal models were divided into Sham, OVX, and OVX +E groups. Serum estrogen levels, blood pressure measurements, and aortic tissue metabolomics analyses were performed using radioimmunoassay, UHPLC-Q-TOF, and bioinformatics techniques. Based on the above research content, we successfully established a correlation between low estrogen levels and postmenopausal hypertension in rats. Notable differences in blood pressure parameters and aortic tissue metabolites were observed across the experimental groups. Specifically, metabolites that were differentially expressed, particularly L-alpha-aminobutyric acid (L-AABA), showed potential as a biomarker for postmenopausal hypertension, potentially exerting a protective function through macrophage activation and vascular remodeling. Enrichment analysis revealed alterations in sugar metabolism pathways, such as the Warburg effect and glycolysis, indicating their involvement in postmenopausal hypertension. Overall, this current research provides insights into the metabolic changes associated with postmenopausal hypertension, highlighting the role of L-AABA and sugar metabolism reprogramming in aortic tissue. The findings suggest a potential link between low estrogen levels, macrophage function, and vascular remodeling in the pathogenesis of postmenopausal hypertension. Further investigations are needed to validate these findings and explore their clinical implications for postmenopausal women.
