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Alzate Sanchez AM, Janssen MLF, Temel Y, Roberts MJ. Aging suppresses subthalamic neuronal activity in patients with Parkinson's disease. Eur J Neurosci 2024. [PMID: 38880896 DOI: 10.1111/ejn.16435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 05/06/2024] [Accepted: 05/17/2024] [Indexed: 06/18/2024]
Abstract
Age is a primary risk factor for Parkinson's disease (PD); however, the effects of aging on the Parkinsonian brain remain poorly understood, particularly for deep brain structures. We investigated intraoperative micro-electrode recordings from the subthalamic nucleus (STN) of PD patients aged between 42 and 76 years. Age was associated with decreased oscillatory beta power and non-oscillatory high-frequency power, independent of PD-related variables. Single unit firing and burst rates were also reduced, whereas the coefficient of variation and the structure of burst activity were unchanged. Phase synchronization (debiased weighed phase lag index [dWPLI]) between sites was pronounced in the beta band between electrodes in the superficial STN but was unaffected by age. Our results show that aging is associated with reduced neuronal activity without changes to its temporal structure. We speculate that the loss of activity in the STN may mediate the relationship between PD and age.
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Affiliation(s)
- Ana M Alzate Sanchez
- Mental Health and Neuroscience Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Marcus L F Janssen
- Mental Health and Neuroscience Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
- Department of Clinical Neurophysiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Yasin Temel
- Mental Health and Neuroscience Research Institute, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Mark J Roberts
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
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2
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Prasad AA, Wallén-Mackenzie Å. Architecture of the subthalamic nucleus. Commun Biol 2024; 7:78. [PMID: 38200143 PMCID: PMC10782020 DOI: 10.1038/s42003-023-05691-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 12/11/2023] [Indexed: 01/12/2024] Open
Abstract
The subthalamic nucleus (STN) is a major neuromodulation target for the alleviation of neurological and neuropsychiatric symptoms using deep brain stimulation (DBS). STN-DBS is today applied as treatment in Parkinson´s disease, dystonia, essential tremor, and obsessive-compulsive disorder (OCD). STN-DBS also shows promise as a treatment for refractory Tourette syndrome. However, the internal organization of the STN has remained elusive and challenges researchers and clinicians: How can this small brain structure engage in the multitude of functions that renders it a key hub for therapeutic intervention of a variety of brain disorders ranging from motor to affective to cognitive? Based on recent gene expression studies of the STN, a comprehensive view of the anatomical and cellular organization, including revelations of spatio-molecular heterogeneity, is now possible to outline. In this review, we focus attention to the neurobiological architecture of the STN with specific emphasis on molecular patterns discovered within this complex brain area. Studies from human, non-human primate, and rodent brains now reveal anatomically defined distribution of specific molecular markers. Together their spatial patterns indicate a heterogeneous molecular architecture within the STN. Considering the translational capacity of targeting the STN in severe brain disorders, the addition of molecular profiling of the STN will allow for advancement in precision of clinical STN-based interventions.
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Affiliation(s)
- Asheeta A Prasad
- University of Sydney, School of Medical Sciences, Faculty of Medicine and Health, Sydney, NSW, Australia.
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3
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Mohammadi MS, Planty-Bonjour A, Poupon F, Uszynski I, Poupon C, Destrieux C, Andersson F. ProbaStem, a pipeline towards the first high-resolution probabilistic atlas of the whole human brainstem. Brain Struct Funct 2024; 229:115-132. [PMID: 37924354 DOI: 10.1007/s00429-023-02726-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 10/16/2023] [Indexed: 11/06/2023]
Abstract
The brainstem plays an essential role in many vital functions, such as autonomic control, consciousness and sleep, motricity, somatic afferent function, and cognition. Its involvement in several neurological diseases and the definition of brainstem targets for deep brain stimulation (DBS) explain the need for brainstem atlases describing its structural organization and connectivity from several modalities, from histology to ultrahigh field ex vivo MRI. Nonetheless, these atlases are often limited to a subpart of the brainstem or only include a single subject, the brainstem variability being considered low. This paper proposes a pipeline to create a high-resolution multisubject probabilistic atlas of the whole human brainstem based on four ultrahigh field ex vivo MRI datasets. The variability of the brainstem structures appears higher than usually considered, both for the volume and position of the central gray matter structures of the brainstem. This justifies the creation of atlases that capture the anatomical variability across subjects. The one we present here only included four specimens, but can easily be incremented due to its highly flexible design.
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Affiliation(s)
| | - Alexia Planty-Bonjour
- UMR 1253, Inserm, iBrain, Université de Tours, Tours, France
- CHRU de Tours, Tours, France
| | - Fabrice Poupon
- CEA, CNRS, BAOBAB, Paris-Saclay University, Gif-sur-Yvette, France
| | - Ivy Uszynski
- CEA, CNRS, BAOBAB, Paris-Saclay University, Gif-sur-Yvette, France
| | - Cyril Poupon
- CEA, CNRS, BAOBAB, Paris-Saclay University, Gif-sur-Yvette, France
| | - Christophe Destrieux
- UMR 1253, Inserm, iBrain, Université de Tours, Tours, France.
- CHRU de Tours, Tours, France.
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4
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Noor MS, Howell B, McIntyre CC. Role of the volume conductor on simulations of local field potential recordings from deep brain stimulation electrodes. PLoS One 2023; 18:e0294512. [PMID: 38011104 PMCID: PMC10681243 DOI: 10.1371/journal.pone.0294512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 11/02/2023] [Indexed: 11/29/2023] Open
Abstract
OBJECTIVE Local field potential (LFP) recordings from deep brain stimulation (DBS) electrodes are commonly used in research analyses, and are beginning to be used in clinical practice. Computational models of DBS LFPs provide tools for investigating the biophysics and neural synchronization that underlie LFP signals. However, technical standards for DBS LFP model parameterization remain to be established. Therefore, the goal of this study was to evaluate the role of the volume conductor (VC) model complexity on simulated LFP signals in the subthalamic nucleus (STN). APPROACH We created a detailed human head VC model that explicitly represented the inhomogeneity and anisotropy associated with 12 different tissue structures. This VC model represented our "gold standard" for technical detail and electrical realism. We then incrementally decreased the complexity of the VC model and quantified the impact on the simulated LFP recordings. Identical STN neural source activity was used when comparing the different VC model variants. Results Ignoring tissue anisotropy reduced the simulated LFP amplitude by ~12%, while eliminating soft tissue heterogeneity had a negligible effect on the recordings. Simplification of the VC model to consist of a single homogenous isotropic tissue medium with a conductivity of 0.215 S/m contributed an additional ~3% to the error. SIGNIFICANCE Highly detailed VC models do generate different results than simplified VC models. However, with errors in the range of ~15%, the use of a well-parameterized simple VC model is likely to be acceptable in most contexts for DBS LFP modeling.
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Affiliation(s)
- M. Sohail Noor
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Bryan Howell
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
| | - Cameron C. McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, United States of America
- Department of Neurosurgery, Duke University, Durham, NC, United States of America
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5
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Taha A, Gilmore G, Abbass M, Kai J, Kuehn T, Demarco J, Gupta G, Zajner C, Cao D, Chevalier R, Ahmed A, Hadi A, Karat BG, Stanley OW, Park PJ, Ferko KM, Hemachandra D, Vassallo R, Jach M, Thurairajah A, Wong S, Tenorio MC, Ogunsanya F, Khan AR, Lau JC. Magnetic resonance imaging datasets with anatomical fiducials for quality control and registration. Sci Data 2023; 10:449. [PMID: 37438367 DOI: 10.1038/s41597-023-02330-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 06/26/2023] [Indexed: 07/14/2023] Open
Abstract
Tools available for reproducible, quantitative assessment of brain correspondence have been limited. We previously validated the anatomical fiducial (AFID) placement protocol for point-based assessment of image registration with millimetric (mm) accuracy. In this data descriptor, we release curated AFID placements for some of the most commonly used structural magnetic resonance imaging datasets and templates. The release of our accurate placements allows for rapid quality control of image registration, teaching neuroanatomy, and clinical applications such as disease diagnosis and surgical targeting. We release placements on individual subjects from four datasets (N = 132 subjects for a total of 15,232 fiducials) and 14 brain templates (4,288 fiducials), totalling more than 300 human rater hours of annotation. We also validate human rater accuracy of released placements to be within 1 - 2 mm (using more than 45,000 Euclidean distances), consistent with prior studies. Our data is compliant with the Brain Imaging Data Structure allowing for facile incorporation into neuroimaging analysis pipelines.
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Affiliation(s)
- Alaa Taha
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- School of Biomedical Engineering, Western University, London, Canada
| | - Greydon Gilmore
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- School of Biomedical Engineering, Western University, London, Canada
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Canada
| | - Mohamad Abbass
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Canada
- Graduate Program in Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Jason Kai
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Tristan Kuehn
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- School of Biomedical Engineering, Western University, London, Canada
| | - John Demarco
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Geetika Gupta
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Graduate Program in Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Chris Zajner
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Canada
| | - Daniel Cao
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Michael G. DeGroote School of Medicine, McMaster University, Hamilton, Canada
| | - Ryan Chevalier
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Canada
| | - Abrar Ahmed
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Canada
| | - Ali Hadi
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Canada
| | - Bradley G Karat
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Graduate Program in Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Olivia W Stanley
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Patrick J Park
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- School of Biomedical Engineering, Western University, London, Canada
| | - Kayla M Ferko
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Graduate Program in Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Dimuthu Hemachandra
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- School of Biomedical Engineering, Western University, London, Canada
| | - Reid Vassallo
- School of Biomedical Engineering, Faculty of Applied Science and Faculty of Medicine, The University of British Columbia, Vancouver, Canada
| | - Magdalena Jach
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Canada
| | - Arun Thurairajah
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Graduate Program in Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Sandy Wong
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Canada
| | - Mauricio C Tenorio
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- School of Biomedical Engineering, Western University, London, Canada
| | - Feyi Ogunsanya
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Canada
| | - Ali R Khan
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada
- School of Biomedical Engineering, Western University, London, Canada
- Graduate Program in Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Canada
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Canada
| | - Jonathan C Lau
- Imaging Research Laboratories, Robarts Research Institute, Western University, London, Canada.
- School of Biomedical Engineering, Western University, London, Canada.
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Canada.
- Graduate Program in Neuroscience, Schulich School of Medicine and Dentistry, Western University, London, Canada.
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Canada.
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Li Q, Lu Y, Zhang X, Chen Z, Feng J, Zeng X, Zhao S, Huang G, Li L, Xing C, Liang F, Guo T. Brain-Imaging Mechanisms on Female Abdominal Obesity Treated by "Shu-Mu" Acupoint Catgut Embedding and Compatibility Relation: Study Protocol for a 12-Week Randomized Controlled Trial. Diabetes Metab Syndr Obes 2023; 16:733-747. [PMID: 36936443 PMCID: PMC10017833 DOI: 10.2147/dmso.s400197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 03/07/2023] [Indexed: 03/12/2023] Open
Abstract
BACKGROUND Acupoint catgut embedding (ACE) has been proven to be effective and safe in the treatment of obesity, but few studies have been conducted involving its central mechanisms. Our previous study has demonstrated the effectiveness of Shu-Mu ACE in the treatment of abdominal obesity (AO). However, the neurological mechanism of Shu-Mu ACE for weight loss has not yet been elucidated. The mechanism of the combination of the Shu and Mu acupoints may be related to the central integrative effects of the brain. This paper aims to explore the potential neural mechanisms of Shu-Mu ACE in female patients with AO. METHODS AND ANALYSIS A total of 100 eligible female AO patients and 20 healthy female subjects will be recruited for this study. 100 AO patients will be randomly allocated to five groups: Shu-Mu ACE (Group A), Shu ACE (Group B), Mu ACE (Group C), sham ACE (Group D), and waiting-list (Group E). Treatment will be administrated once every two weeks for 12 weeks. The body mass index (BMI), waist circumference (WC), Visual Analog Scales (VAS) of appetite, Self-Rating Anxiety Scale (SAS), and Self-Rating Depression Scale (SDS) will be utilized to evaluate the clinical efficacy. Outcomes will be assessed at baseline and at each time point of treatment. Multimodal MRI will be performed at baseline and after 12-week treatment and the results will be used to investigate the neural mechanisms of ACE for obesity. Neurological changes and clinical data will be analysed for correlation. DISCUSSIONS This study hypothesized that Shu-Mu ACE therapy has a synergistic effect and may treat AO by modulating the neuropathological alterations in the brain. Our findings will demonstrate the neurological mechanism of AO treated by "Shu-Mu" Acupoint Catgut Embedding and compatibility relation. TRIAL REGISTRATION This trial is registered at the Chinese Clinical Trial Registration Center (No. ChiCTR2100048920).
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Affiliation(s)
- Qifu Li
- School of Second Clinical Medicine/The Second Affiliated Hospital, Yunnan University of Chinese Medicine, Kunming, People’s Republic of China
| | - Yi Lu
- The Department of Medical Imaging, The First Affiliated Hospital of Kunming Medical University, Kunming, People’s Republic of China
| | - Xinghe Zhang
- School of Second Clinical Medicine/The Second Affiliated Hospital, Yunnan University of Chinese Medicine, Kunming, People’s Republic of China
| | - Ziwen Chen
- College of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Kunming, People’s Republic of China
| | - Jialei Feng
- Institute for History of Medicine and Medical Literature, China Academy of Chinese Medical Sciences, Beijing, People’s Republic of China
| | - Xuanxiang Zeng
- School of Second Clinical Medicine/The Second Affiliated Hospital, Yunnan University of Chinese Medicine, Kunming, People’s Republic of China
| | - Siwen Zhao
- School of Second Clinical Medicine/The Second Affiliated Hospital, Yunnan University of Chinese Medicine, Kunming, People’s Republic of China
| | - Gaoyangzi Huang
- School of Second Clinical Medicine/The Second Affiliated Hospital, Yunnan University of Chinese Medicine, Kunming, People’s Republic of China
| | - Li Li
- The Third Affiliated Hospital, Yunnan University of Chinese Medicine, Kunming, People’s Republic of China
| | - Chonghui Xing
- The Sports Trauma Specialist Hospital of Yunnan Province, Kunming, People’s Republic of China
| | - Fanrong Liang
- College of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Kunming, People’s Republic of China
- Fanrong Liang, School of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, People’s Republic of China, Email
| | - Taipin Guo
- School of Second Clinical Medicine/The Second Affiliated Hospital, Yunnan University of Chinese Medicine, Kunming, People’s Republic of China
- Correspondence: Taipin Guo, School of Second Clinical Medicine/The Second Affiliated Hospital, Yunnan University of Chinese Medicine, Kunming, People’s Republic of China, Email
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7
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Du J, Zhou X, Liang Y, Zhao L, Dai C, Zhong Y, Liu H, Liu G, Mo L, Tan C, Liu X, Chen L. Levodopa responsiveness and white matter alterations in Parkinson's disease: A DTI-based study and brain network analysis: A cross-sectional study. Brain Behav 2022; 12:e2825. [PMID: 36423257 PMCID: PMC9759147 DOI: 10.1002/brb3.2825] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 09/24/2022] [Accepted: 11/01/2022] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Patients with Parkinson's disease (PD) present various responsiveness to levodopa, but the cause of such differences in levodopa responsiveness is unclear. Previous studies related the damage of brain white matter (WM) to levodopa responsiveness in PD patients, but no study investigated the relationship between the structural brain network change in PD patients and their levodopa responsiveness. METHODS PD patients were recruited and evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS). Each patient received a diffusion tensor imaging (DTI) scan and an acute levodopa challenge test. The improvement rate of UPDRS-III was calculated. PD patients were grouped into irresponsive group (improvement rate < 30%) and responsive group (improvement rate ≥ 30%). Tract-based spatial statistics (TBSS), deterministic tracing (DT), region of interest (ROI) analysis, and automatic fiber identification (AFQ) analyses were performed. The structural brain network was also constructed and the topological parameters were calculated. RESULTS Fifty-four PD patients were included. TBSS identified significant differences in fractional anisotropy (FA) values in the corpus callosum and other regions of the brain. DT and ROI analysis of the corpus callosum found a significant difference in FA between the two groups. Graph theory analysis showed statistical differences in global efficiency, local efficiency, and characteristic path length. CONCLUSION PD patients with poor responsiveness to levodopa had WM damage in multiple brain areas, especially the corpus callosum, which might cause disruption of information integration of the structural brain network.
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Affiliation(s)
- Juncong Du
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Xuan Zhou
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Yi Liang
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Lili Zhao
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Chengcheng Dai
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Yuke Zhong
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Hang Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Guohui Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Lijuan Mo
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Changhong Tan
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Xi Liu
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
| | - Lifen Chen
- Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China
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Baniasadi M, Petersen MV, Gonçalves J, Horn A, Vlasov V, Hertel F, Husch A. DBSegment: Fast and robust segmentation of deep brain structures considering domain generalization. Hum Brain Mapp 2022; 44:762-778. [PMID: 36250712 PMCID: PMC9842883 DOI: 10.1002/hbm.26097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/30/2022] [Accepted: 09/15/2022] [Indexed: 01/25/2023] Open
Abstract
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.
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Affiliation(s)
- Mehri Baniasadi
- National Department of Neurosurgery, Centre Hospitalier deLuxembourg Center for Systems Biomedicine, University of LuxembourgEsch‐sur‐AlzetteLuxembourg
| | - Mikkel V. Petersen
- Department of Clinical Medicine, Center of Functionally Integrative NeuroscienceUniversity of AarhusAarhusDenmark
| | - Jorge Gonçalves
- Luxembourg Center for Systems BiomedicineUniversity of LuxembourgEsch‐sur‐AlzetteLuxembourg
| | - Andreas Horn
- Neuromodulation and Movement Disorders Unit, Department of NeurologyCharité–Universitätsmedizin BerlinBerlinGermany,MGH Neurosurgery and Center for Neurotechnology and Neurorecovery at MGH Neurology Massachusetts General HospitalHarvard Medical SchoolBostonUSA,Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's HospitalHarvard Medical SchoolBostonUSA
| | - Vanja Vlasov
- Luxembourg Center for Systems BiomedicineUniversity of LuxembourgEsch‐sur‐AlzetteLuxembourg
| | - Frank Hertel
- National Department of NeurosurgeryCentre Hospitalier de LuxembourgLuxembourg
| | - Andreas Husch
- Luxembourg Center for Systems BiomedicineUniversity of LuxembourgEsch‐sur‐AlzetteLuxembourg
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9
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Okada T, Fujimoto K, Fushimi Y, Akasaka T, Thuy DHD, Shima A, Sawamoto N, Oishi N, Zhang Z, Funaki T, Nakamoto Y, Murai T, Miyamoto S, Takahashi R, Isa T. Neuroimaging at 7 Tesla: a pictorial narrative review. Quant Imaging Med Surg 2022; 12:3406-3435. [PMID: 35655840 PMCID: PMC9131333 DOI: 10.21037/qims-21-969] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/05/2022] [Indexed: 01/26/2024]
Abstract
Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.
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Affiliation(s)
- Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Thai Akasaka
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Dinh H. D. Thuy
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsushi Shima
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Medial Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Funaki
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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10
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Jin Z, Wang Y, Jokar M, Li Y, Cheng Z, Liu Y, Tang R, Shi X, Zhang Y, Min J, Liu F, He N, Yan F, Haacke EM. Automatic detection of neuromelanin and iron in the midbrain nuclei using a
magnetic resonance imaging
‐based brain template. Hum Brain Mapp 2022; 43:2011-2025. [PMID: 35072301 PMCID: PMC8933249 DOI: 10.1002/hbm.25770] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 12/01/2021] [Accepted: 12/22/2021] [Indexed: 12/17/2022] Open
Abstract
Parkinson disease (PD) is a chronic progressive neurodegenerative disorder characterized pathologically by early loss of neuromelanin (NM) in the substantia nigra pars compacta (SNpc) and increased iron deposition in the substantia nigra (SN). Degeneration of the SN presents as a 50 to 70% loss of pigmented neurons in the ventral lateral tier of the SNpc at the onset of symptoms. Also, using magnetic resonance imaging (MRI), iron deposition and volume changes of the red nucleus (RN), and subthalamic nucleus (STN) have been reported to be associated with disease status and rate of progression. Further, the STN serves as an important target for deep brain stimulation treatment in advanced PD patients. Therefore, an accurate in‐vivo delineation of the SN, its subregions and other midbrain structures such as the RN and STN could be useful to better study iron and NM changes in PD. Our goal was to use an MRI template to create an automatic midbrain deep gray matter nuclei segmentation approach based on iron and NM contrast derived from a single, multiecho magnetization transfer contrast gradient echo (MTC‐GRE) imaging sequence. The short echo TE = 7.5 ms data from a 3D MTC‐GRE sequence was used to find the NM‐rich region, while the second echo TE = 15 ms was used to calculate the quantitative susceptibility map for 87 healthy subjects (mean age ± SD: 63.4 ± 6.2 years old, range: 45–81 years). From these data, we created both NM and iron templates and calculated the boundaries of each midbrain nucleus in template space, mapped these boundaries back to the original space and then fine‐tuned the boundaries in the original space using a dynamic programming algorithm to match the details of each individual's NM and iron features. A dual mapping approach was used to improve the performance of the morphological mapping of the midbrain of any given individual to the template space. A threshold approach was used in the NM‐rich region and susceptibility maps to optimize the DICE similarity coefficients and the volume ratios. The results for the NM of the SN as well as the iron containing SN, STN, and RN all indicate a strong agreement with manually drawn structures. The DICE similarity coefficients and volume ratios for these structures were 0.85, 0.87, 0.75, and 0.92 and 0.93, 0.95, 0.89, 1.05, respectively, before applying any threshold on the data. Using this fully automatic template‐based deep gray matter mapping approach, it is possible to accurately measure the tissue properties such as volumes, iron content, and NM content of the midbrain nuclei.
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Affiliation(s)
- Zhijia Jin
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Ying Wang
- SpinTech MRI, Inc. Detroit Michigan USA
- Department of Radiology Wayne State University Detroit Michigan USA
| | | | - Yan Li
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Zenghui Cheng
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Yu Liu
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Rongbiao Tang
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Xiaofeng Shi
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Youmin Zhang
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Jihua Min
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Fangtao Liu
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Naying He
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
| | - Ewart Mark Haacke
- Department of Radiology, Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China
- SpinTech MRI, Inc. Detroit Michigan USA
- Department of Radiology Wayne State University Detroit Michigan USA
- Department of Biomedical Engineering Wayne State University Detroit Michigan USA
- Department of Neurology Wayne State University Detroit Michigan USA
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11
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Miletić S, Bazin PL, Isherwood SJS, Keuken MC, Alkemade A, Forstmann BU. Charting human subcortical maturation across the adult lifespan with in vivo 7 T MRI. Neuroimage 2022; 249:118872. [PMID: 34999202 DOI: 10.1016/j.neuroimage.2022.118872] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 12/20/2021] [Accepted: 01/03/2022] [Indexed: 12/26/2022] Open
Abstract
The human subcortex comprises hundreds of unique structures. Subcortical functioning is crucial for behavior, and disrupted function is observed in common neurodegenerative diseases. Despite their importance, human subcortical structures continue to be difficult to study in vivo. Here we provide a detailed account of 17 prominent subcortical structures and ventricles, describing their approximate iron and myelin contents, morphometry, and their age-related changes across the normal adult lifespan. The results provide compelling insights into the heterogeneity and intricate age-related alterations of these structures. They also show that the locations of many structures shift across the lifespan, which is of direct relevance for the use of standard magnetic resonance imaging atlases. The results further our understanding of subcortical morphometry and neuroimaging properties, and of normal aging processes which ultimately can improve our understanding of neurodegeneration.
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Affiliation(s)
- Steven Miletić
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
| | - Pierre-Louis Bazin
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands; Max Planck Institute for Human Cognitive and Brain Sciences, Departments of Neurophysics and Neurology, Stephanstraße 1A, Leipzig, Germany
| | - Scott J S Isherwood
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Max C Keuken
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Anneke Alkemade
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands
| | - Birte U Forstmann
- University of Amsterdam, Department of Psychology, Integrative Model-based Cognitive Neuroscience research unit (IMCN), Nieuwe Achtergracht 129B, Amsterdam 1001 NK, the Netherlands.
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12
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Prasuhn J, Strautz R, Lemmer F, Dreischmeier S, Kasten M, Hanssen H, Heldmann M, Brüggemann N. Neuroimaging Correlates of Substantia Nigra Hyperechogenicity in Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 12:1191-1200. [PMID: 35180131 DOI: 10.3233/jpd-213000] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
BACKGROUND Degeneration of dopaminergic neurons within the brainstem substantia nigra (SN) is both a pathological hallmark of Parkinson's disease (PD) and a major contributor to symptom expression. Therefore, non-invasive evaluation of the SN is critical for diagnosis and evaluation of disease progression. Hyperechogenicity (HE+) on midbrain transcranial sonography (TCS) supports the clinically established diagnosis of PD. Further, postmortem studies suggest involvement of neuromelanin (NM) loss and iron deposition in nigral neurodegeneration and HE+ emergence. However, the associations between HE+ and signs of nigral NM loss and iron deposition revealed by magnetic resonance imaging (MRI) have not been examined. OBJECTIVE To elucidate the magnetic resonance- (MR-) morphological representation of the HE+ by NM-weighted (NMI) and susceptibility-weighted MRI (SWI). METHODS Thirty-four PD patients and 29 healthy controls (HCs) received TCS followed by NMI and SWI. From MR images, two independent raters manually identified the SN, placed seeds in non-SN midbrain areas, and performed semi-automated SN segmentation with different thresholds based on seed mean values and standard deviations. Masks of the SN were then used to extract mean area, mean signal intensity, maximal signal area, maximum signal (for NMI), and minimum signal (for SWI). RESULTS There were no significant differences in NMI- and SWI-based parameters between patients and HCs, and no significant associations between HE+ extent and NMI- or SWI-based parameters. CONCLUSION HE+ on TCS appears unrelated to PD pathology revealed by NMI and SWI. Thus, TCS and MRI parameters should be considered complementary, and the pathophysiological correlates of the HE+ require further study.
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Affiliation(s)
- Jannik Prasuhn
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
| | - Robert Strautz
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Felicitas Lemmer
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Shalida Dreischmeier
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Meike Kasten
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
- Department of Psychiatry, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Henrike Hanssen
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
| | - Marcus Heldmann
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
- Institute of Psychology II, University of Lübeck, Lübeck, Germany
| | - Norbert Brüggemann
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, Lübeck, Germany
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13
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Manual delineation approaches for direct imaging of the subcortex. Brain Struct Funct 2021; 227:219-297. [PMID: 34714408 PMCID: PMC8741717 DOI: 10.1007/s00429-021-02400-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 09/26/2021] [Indexed: 11/20/2022]
Abstract
The growing interest in the human subcortex is accompanied by an increasing number of parcellation procedures to identify deep brain structures in magnetic resonance imaging (MRI) contrasts. Manual procedures continue to form the gold standard for parcellating brain structures and is used for the validation of automated approaches. Performing manual parcellations is a tedious process which requires a systematic and reproducible approach. For this purpose, we created a series of protocols for the anatomical delineation of 21 individual subcortical structures. The intelligibility of the protocols was assessed by calculating Dice similarity coefficients for ten healthy volunteers. In addition, dilated Dice coefficients showed that manual parcellations created using these protocols can provide high-quality training data for automated algorithms. Here, we share the protocols, together with three example MRI datasets and the created manual delineations. The protocols can be applied to create high-quality training data for automated parcellation procedures, as well as for further validation of existing procedures and are shared without restrictions with the research community.
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14
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Nair A, Razi A, Gregory S, Rutledge RR, Rees G, Tabrizi SJ. Imbalanced basal ganglia connectivity is associated with motor deficits and apathy in Huntington's disease. Brain 2021; 145:991-1000. [PMID: 34633421 PMCID: PMC9050569 DOI: 10.1093/brain/awab367] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 08/16/2021] [Accepted: 08/24/2021] [Indexed: 11/12/2022] Open
Abstract
The gating of movement depends on activity within the cortico-striato-thalamic loops. Within these loops, emerging from the cells of the striatum, run two opponent pathways—the direct and indirect basal ganglia pathways. Both are complex and polysynaptic, but the overall effect of activity within these pathways is thought to encourage and inhibit movement, respectively. In Huntington’s disease, the preferential early loss of striatal neurons forming the indirect pathway is thought to lead to disinhibition, giving rise to the characteristic motor features of the condition. But early Huntington’s disease is also associated with apathy, a loss of motivation and failure to engage in goal-directed movement. We hypothesized that in Huntington’s disease, motor signs and apathy may be selectively correlated with indirect and direct pathway dysfunction, respectively. We used spectral dynamic casual modelling of resting-state functional MRI data to model effective connectivity in a model of these cortico-striatal pathways. We tested both of these hypotheses in vivo for the first time in a large cohort of patients with prodromal Huntington’s disease. Using an advanced approach at the group level we combined parametric empirical Bayes and Bayesian model reduction procedures to generate a large number of competing models and compare them using Bayesian model comparison. With this automated Bayesian approach, associations between clinical measures and connectivity parameters emerge de novo from the data. We found very strong evidence (posterior probability > 0.99) to support both of our hypotheses. First, more severe motor signs in Huntington’s disease were associated with altered connectivity in the indirect pathway components of our model and, by comparison, loss of goal-direct behaviour or apathy, was associated with changes in the direct pathway component. The empirical evidence we provide here demonstrates that imbalanced basal ganglia connectivity may play an important role in the pathogenesis of some of commonest and disabling features of Huntington’s disease and may have important implications for therapeutics.
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Affiliation(s)
- Akshay Nair
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK.,UCL Institute of Cognitive Neuroscience, University College London, Alexandra House, 17-19 Queen Square, Bloomsbury, London, WC1N 3AZ, UK
| | - Adeel Razi
- Turner Institute for Brain and Mental Health, Monash Biomedical Imaging, Monash University, 770 Blackburn Road, Clayton 3800, Australia.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK
| | - Sarah Gregory
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK
| | - Robb R Rutledge
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK.,Max Planck UCL Centre for Computational Psychiatry and Ageing Research, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK.,Department of Psychology, Yale University, New Haven, CT 06511, USA
| | - Geraint Rees
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK.,UCL Institute of Cognitive Neuroscience, University College London, Alexandra House, 17-19 Queen Square, Bloomsbury, London, WC1N 3AZ, UK.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK
| | - Sarah J Tabrizi
- Huntington's Disease Centre, UCL Queen Square Institute of Neurology, University College London, Russell Square House, London, WC1B 5EH, UK.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK
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15
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Isaacs BR, Heijmans M, Kuijf ML, Kubben PL, Ackermans L, Temel Y, Keuken MC, Forstmann BU. Variability in subthalamic nucleus targeting for deep brain stimulation with 3 and 7 Tesla magnetic resonance imaging. NEUROIMAGE-CLINICAL 2021; 32:102829. [PMID: 34560531 PMCID: PMC8463907 DOI: 10.1016/j.nicl.2021.102829] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/12/2021] [Accepted: 09/12/2021] [Indexed: 12/13/2022]
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective surgical treatment for Parkinson's disease (PD). Side-effects may, however, be induced when the DBS lead is placed suboptimally. Currently, lower field magnetic resonance imaging (MRI) at 1.5 or 3 Tesla (T) is used for targeting. Ultra-high-field MRI (7 T and above) can obtain superior anatomical information and might therefore be better suited for targeting. This study aims to test whether optimized 7 T imaging protocols result in less variable targeting of the STN for DBS compared to clinically utilized 3 T images. Three DBS-experienced neurosurgeons determined the optimal STN DBS target site on three repetitions of 3 T-T2, 7 T-T2*, 7 T-R2* and 7 T-QSM images for five PD patients. The distance in millimetres between the three repetitive coordinates was used as an index of targeting variability and was compared between field strength, MRI contrast and repetition with a Bayesian ANOVA. Further, the target coordinates were registered to MNI space, and anatomical coordinates were compared between field strength, MRI contrast and repetition using a Bayesian ANOVA. The results indicate that the neurosurgeons are stable in selecting the DBS target site across MRI field strength, MRI contrast and repetitions. The analysis of the coordinates in MNI space however revealed that the actual selected location of the electrode is seemingly more ventral when using the 3 T scan compared to the 7 T scans.
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Affiliation(s)
- Bethany R Isaacs
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands; Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Margot Heijmans
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands.
| | - Mark L Kuijf
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurology, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Pieter L Kubben
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Linda Ackermans
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Yasin Temel
- Translational Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands; Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Max C Keuken
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
| | - Birte U Forstmann
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
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16
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Cerebellar Atrophy in Multiple System Atrophy (Cerebellar Type) and Its Implication for Network Connectivity. THE CEREBELLUM 2021; 19:636-644. [PMID: 32472475 DOI: 10.1007/s12311-020-01144-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
We sought to assess structural and functional patterns of cerebellum in multiple system atrophy (cerebellar type), and investigate the associations of structural and functional cerebellar gray matter abnormalities. We collected magnetic resonance imaging data of 18 patients with multiple system atrophy (cerebellar type) and 18 health control subjects. The gray matter loss across the motor and cognitive cerebellar territories in patients was assessed using voxel-based morphometry. And change in the connectivity between the cerebellum and large-scale cortical networks was assessed using resting-state functional MRI analysis. Furthermore, we assessed the relationship between the extent of cerebellar atrophy and reduced-activation in the cerebellar-cortical and subthalamo-cerebellar functional connectivities. We confirmed the gray matter loss across the motor and cognitive cerebellar territories in patients and found that the extent of cerebellar atrophy was correlated with decreased connectivity between the cerebellum and large-scale cortical networks, including the default, frontal parietal, and sensorimotor networks. The volume reduction in the motor cerebellum was closely associated with the clinical motor severity. A post hoc analysis showed reduced-activation in the subthalamo-cerebellar functional connectivity without the subthalamic nucleus atrophy. These results emphasized significant atrophy in the cerebellar subsystem and its association with the large-scale cortical networks in multiple system atrophy (cerebellar type), which may improve our understanding of the neural pathophysiology mechanisms of disease.
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17
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Hansen CB, Yang Q, Lyu I, Rheault F, Kerley C, Chandio BQ, Fadnavis S, Williams O, Shafer AT, Resnick SM, Zald DH, Cutting LE, Taylor WD, Boyd B, Garyfallidis E, Anderson AW, Descoteaux M, Landman BA, Schilling KG. Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography. Neuroinformatics 2021; 19:447-460. [PMID: 33196967 PMCID: PMC8124084 DOI: 10.1007/s12021-020-09497-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/02/2020] [Indexed: 12/21/2022]
Abstract
Brain atlases have proven to be valuable neuroscience tools for localizing regions of interest and performing statistical inferences on populations. Although many human brain atlases exist, most do not contain information about white matter structures, often neglecting them completely or labelling all white matter as a single homogenous substrate. While few white matter atlases do exist based on diffusion MRI fiber tractography, they are often limited to descriptions of white matter as spatially separate "regions" rather than as white matter "bundles" or fascicles, which are well-known to overlap throughout the brain. Additional limitations include small sample sizes, few white matter pathways, and the use of outdated diffusion models and techniques. Here, we present a new population-based collection of white matter atlases represented in both volumetric and surface coordinates in a standard space. These atlases are based on 2443 subjects, and include 216 white matter bundles derived from 6 different automated state-of-the-art tractography techniques. This atlas is freely available and will be a useful resource for parcellation and segmentation.
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Affiliation(s)
- Colin B Hansen
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Qi Yang
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Ilwoo Lyu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Francois Rheault
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Cailey Kerley
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bramsh Qamar Chandio
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Shreyas Fadnavis
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
| | - Owen Williams
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Andrea T Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA
| | - David H Zald
- Center for Advanced Human Brain Imaging Research, Rutgers University, Piscataway, NJ, USA
| | - Laurie E Cutting
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
| | - Warren D Taylor
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
| | - Brian Boyd
- Vanderbilt Kennedy Center, Vanderbilt University, Nashville, TN, USA
| | - Eleftherios Garyfallidis
- Department of Intelligent Systems Engineering, Indiana University, Bloomington, IN, USA
- Program of Neuroscience, Indiana University, Bloomington, IN, USA
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL), Université de Sherbrooke, Sherbrooke, Canada
| | - Bennett A Landman
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
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18
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The Human Basal Ganglia Mediate the Interplay between Reactive and Proactive Control of Response through Both Motor Inhibition and Sensory Modulation. Brain Sci 2021; 11:brainsci11050560. [PMID: 33925153 PMCID: PMC8146223 DOI: 10.3390/brainsci11050560] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 04/24/2021] [Accepted: 04/26/2021] [Indexed: 11/17/2022] Open
Abstract
The basal ganglia (BG) have long been known for contributing to the regulation of motor behaviour by means of a complex interplay between tonic and phasic inhibitory mechanisms. However, after having focused for a long time on phasic reactive mechanisms, it is only recently that psychological research in healthy humans has modelled tonic proactive mechanisms of control. Mutual calibration between anatomo-functional and psychological models is still needed to better understand the unclear role of the BG in the interplay between proactive and reactive mechanisms of control. Here, we implemented an event-related fMRI design allowing proper analysis of both the brain activity preceding the target-stimulus and the brain activity induced by the target-stimulus during a simple go/nogo task, with a particular interest in the ambiguous role of the basal ganglia. Post-stimulus activity was evoked in the left dorsal striatum, the subthalamus nucleus and internal globus pallidus by any stimulus when the situation was unpredictable, pinpointing its involvement in reactive, non-selective inhibitory mechanisms when action restraint is required. Pre-stimulus activity was detected in the ventral, not the dorsal, striatum, when the situation was unpredictable, and was associated with changes in functional connectivity with the early visual, not the motor, cortex. This suggests that the ventral striatum supports modulatory influence over sensory processing during proactive control.
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19
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Alkemade A, Forstmann BU. Imaging of the human subthalamic nucleus. HANDBOOK OF CLINICAL NEUROLOGY 2021; 180:403-416. [PMID: 34225944 DOI: 10.1016/b978-0-12-820107-7.00025-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
The human subthalamic nucleus (STN) is a small lens shaped iron rich nucleus, which has gained substantial interest as a target for deep brain stimulation surgery for a variety of movement disorders. The internal anatomy of the human STN has not been fully elucidated, and an intensive debate, discussing the level of overlap between putative limbic, associative, and motor zones within the STN is still ongoing. In this chapter, we have summarized anatomical information obtained using different neuroimaging modalities focusing on the anatomy of the STN. Additionally, we have highlighted a number of major challenges faced when using magnetic resonance imaging (MRI) approaches for the visualization of small iron rich deep brain structures such as the STN. In vivo MRI and postmortem microscopy efforts provide valuable complementary information on the internal structure of the STN, although the results are not always fully aligned. Finally, we provide an outlook on future efforts that could contribute to the development of an integrative research approach that will help with the reconciliation of seemingly divergent results across research approaches.
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Affiliation(s)
- Anneke Alkemade
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
| | - Birte U Forstmann
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
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20
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Bazin PL, Alkemade A, Mulder MJ, Henry AG, Forstmann BU. Multi-contrast anatomical subcortical structures parcellation. eLife 2020; 9:59430. [PMID: 33325368 PMCID: PMC7771958 DOI: 10.7554/elife.59430] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 12/15/2020] [Indexed: 02/07/2023] Open
Abstract
The human subcortex is comprised of more than 450 individual nuclei which lie deep in the brain. Due to their small size and close proximity, up until now only 7% have been depicted in standard MRI atlases. Thus, the human subcortex can largely be considered as terra incognita. Here, we present a new open-source parcellation algorithm to automatically map the subcortex. The new algorithm has been tested on 17 prominent subcortical structures based on a large quantitative MRI dataset at 7 Tesla. It has been carefully validated against expert human raters and previous methods, and can easily be extended to other subcortical structures and applied to any quantitative MRI dataset. In sum, we hope this novel parcellation algorithm will facilitate functional and structural neuroimaging research into small subcortical nuclei and help to chart terra incognita.
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Affiliation(s)
- Pierre-Louis Bazin
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, Netherlands.,Max-Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Anneke Alkemade
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, Netherlands
| | - Martijn J Mulder
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, Netherlands.,Psychology Department, Utrecht University, Utrecht, Netherlands
| | - Amanda G Henry
- Faculty of Archaeology, Leiden University, Leiden, Netherlands
| | - Birte U Forstmann
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, Netherlands
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21
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Isaacs BR, Mulder MJ, Groot JM, van Berendonk N, Lute N, Bazin PL, Forstmann BU, Alkemade A. 3 versus 7 Tesla magnetic resonance imaging for parcellations of subcortical brain structures in clinical settings. PLoS One 2020; 15:e0236208. [PMID: 33232325 PMCID: PMC7685480 DOI: 10.1371/journal.pone.0236208] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022] Open
Abstract
7 Tesla (7T) magnetic resonance imaging holds great promise for improved visualization of the human brain for clinical purposes. To assess whether 7T is superior regarding localization procedures of small brain structures, we compared manual parcellations of the red nucleus, subthalamic nucleus, substantia nigra, globus pallidus interna and externa. These parcellations were created on a commonly used clinical anisotropic clinical 3T with an optimized isotropic (o)3T and standard 7T scan. The clinical 3T MRI scans did not allow delineation of an anatomically plausible structure due to its limited spatial resolution. o3T and 7T parcellations were directly compared. We found that 7T outperformed the o3T MRI as reflected by higher Dice scores, which were used as a measurement of interrater agreement for manual parcellations on quantitative susceptibility maps. This increase in agreement was associated with higher contrast to noise ratios for smaller structures, but not for the larger globus pallidus segments. Additionally, control-analyses were performed to account for potential biases in manual parcellations by assessing semi-automatic parcellations. These results showed a higher consistency for structure volumes for 7T compared to optimized 3T which illustrates the importance of the use of isotropic voxels for 3D visualization of the surgical target area. Together these results indicate that 7T outperforms c3T as well as o3T given the constraints of a clinical setting.
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Affiliation(s)
- Bethany R. Isaacs
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Department of Experimental Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Martijn J. Mulder
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Psychology and Social Sciences, University of Utrecht, Utrecht, The Netherlands
| | - Josephine M. Groot
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Nikita van Berendonk
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Nicky Lute
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Clinical Neuropsychology, Vrije University, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
- Max Planck Institute for Human, Cognitive and Brain Sciences, Leipzig, Germany
| | - Birte U. Forstmann
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
| | - Anneke Alkemade
- University of Amsterdam, Integrative Model-Based Cognitive Neuroscience Research Unit, Amsterdam, The Netherlands
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22
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Bolier E, Bot M, van den Munckhof P, Pal G, Sani S, Verhagen Metman L. The Medial Subthalamic Nucleus Border as a New Anatomical Reference in Stereotactic Neurosurgery for Parkinson's Disease. Stereotact Funct Neurosurg 2020; 99:187-195. [PMID: 33207350 DOI: 10.1159/000510802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Accepted: 07/24/2020] [Indexed: 11/19/2022]
Abstract
INTRODUCTION The intersection of Bejjani's line with the well-delineated medial subthalamic nucleus (STN) border on MRI has recently been proposed as an individualized reference in subthalamic deep brain stimulation (DBS) surgery for Parkinson's disease (PD). We, therefore, aimed to investigate the applicability across centers of the medial STN border as a patient-specific reference point in STN DBS for PD and explore anatomical variability between left and right mesencephalic area within patients. Furthermore, we aim to evaluate a recently defined theoretic stimulation "hotspot" in a different center. METHODS Preoperative 3-Tesla T2 and susceptibility-weighted images (SWI) were used to identify the intersection of Bejjani's line with the medial STN border in left and right mesencephalic area. The average stereotactic coordinates of the center of stimulation relative to the medial STN border were compared with the predefined theoretic stimulation "hotspot." RESULTS Fifty-four patients provided 108 stereotactic coordinates of medial STN borders on both sequences. Significant difference in means was found in the Y-(anteroposterior) and Z-(dorsoventral) directions (T2 vs. SWI; p < 0.001). Mean coordinates in the Y-(anteroposterior) direction differed significantly between left and right mesencephalic area (T2: p < 0.001; SWI: p = 0.021). Sixty-six DBS leads were placed in 36 patients that had finished stimulation programming, and the average stereotactic coordinates of the center of stimulation relative to the medial STN border on T2 sequences were 3.1 mm lateral, 0.7 mm anterior, and 1.8 mm superior, in proximity of the predefined theoretic stimulation "hotspot." CONCLUSION The medial STN border is applicable across centers as a reference point for STN DBS surgery for PD and seems suitable in order to account for interindividual and intraindividual anatomical variability if one is aware of the discrepancies between T2-weighted imaging and SWI.
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Affiliation(s)
- Erik Bolier
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA, .,Department of Neurosurgery, Amsterdam University Medical Centers, Academic Medical Center, Amsterdam, The Netherlands,
| | - Maarten Bot
- Department of Neurosurgery, Amsterdam University Medical Centers, Academic Medical Center, Amsterdam, The Netherlands
| | - Pepijn van den Munckhof
- Department of Neurosurgery, Amsterdam University Medical Centers, Academic Medical Center, Amsterdam, The Netherlands
| | - Gian Pal
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Sepehr Sani
- Department of Neurosurgery, Rush University Medical Center, Chicago, Illinois, USA
| | - Leo Verhagen Metman
- Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
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23
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Prasuhn J, Heldmann M, Münte TF, Brüggemann N. A machine learning-based classification approach on Parkinson's disease diffusion tensor imaging datasets. Neurol Res Pract 2020; 2:46. [PMID: 33324945 PMCID: PMC7654034 DOI: 10.1186/s42466-020-00092-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 10/26/2020] [Indexed: 12/18/2022] Open
Abstract
Introduction The presence of motor signs and symptoms in Parkinson’s disease (PD) is the result of a long-lasting prodromal phase with an advancing neurodegenerative process. The identification of PD patients in an early phase is, however, crucial for developing disease-modifying drugs. The objective of our study is to investigate whether Diffusion Tensor Imaging (DTI) of the Substantia nigra (SN) analyzed by machine learning algorithms (ML) can be used to identify PD patients. Methods Our study proposes the use of computer-aided algorithms and a highly reproducible approach (in contrast to manually SN segmentation) to increase the reliability and accuracy of DTI metrics used for classification. Results The results of our study do not confirm the feasibility of the DTI approach, neither on a whole-brain level, ROI-labelled analyses, nor when focusing on the SN only. Conclusions Our study did not provide any evidence to support the hypothesis that DTI-based analysis, in particular of the SN, could be used to identify PD patients correctly.
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Affiliation(s)
- Jannik Prasuhn
- Department of Neurology, Institute of Neurogenetics, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany.,Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Marcus Heldmann
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany.,Institute of Psychology II, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Thomas F Münte
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany
| | - Norbert Brüggemann
- Department of Neurology, Institute of Neurogenetics, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany.,Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany
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24
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The Amsterdam Ultra-high field adult lifespan database (AHEAD): A freely available multimodal 7 Tesla submillimeter magnetic resonance imaging database. Neuroimage 2020; 221:117200. [DOI: 10.1016/j.neuroimage.2020.117200] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Accepted: 07/22/2020] [Indexed: 02/07/2023] Open
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25
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Brain Atrophy Following Deep Brain Stimulation: Management of a Moving Target. Tremor Other Hyperkinet Mov (N Y) 2020; 10:46. [PMID: 33133768 PMCID: PMC7583709 DOI: 10.5334/tohm.546] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Clinical vignette: A 51-year-old man with essential tremor (ET) had bilateral ventralis intermedius nucleus deep brain stimulation (VIM-DBS) placed to address refractory tremor. Despite well-placed DBS leads and adequate tremor response, he subsequently experienced worsening. Re-programming of the device and reconfirming the electrical thresholds for benefits and side effects were both performed. Six years following DBS implantation, repeat imaging revealed brain atrophy and a measured lead position change with a coincident change in clinical response. Clinical dilemma: What do we know about brain atrophy affecting lead placement and long-term DBS effectiveness? What are the potential strategies to combat narrowed therapeutic thresholds and to maximize DBS therapeutic benefit? Clinical solution: Decreasing the electrical field of stimulation and programming in a bipolar configuration are strategies to provide symptomatic tremor control and to minimize stimulation-induced side effects. Gaps in knowledge: Currently, effects of brain atrophy, and factors underpinning emergence of side effects and/or loss of benefit in chronic VIM-DBS remain largely unexplored.
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26
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García-Gomar MG, Concha L, Soto-Abraham J, Tournier JD, Aguado-Carrillo G, Velasco-Campos F. Long-Term Improvement of Parkinson Disease Motor Symptoms Derived From Lesions of Prelemniscal Fiber Tract Components. Oper Neurosurg (Hagerstown) 2020; 19:539-550. [PMID: 32629480 DOI: 10.1093/ons/opaa186] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2019] [Accepted: 04/15/2020] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Prelemniscal radiations (Raprl) are composed of different fiber tracts, connecting the brain stem and cerebellum with basal ganglia and cerebral cortex. In Parkinson disease (PD), lesions in Raprl induce improvement of tremor, rigidity, and bradykinesia in some patients, while others show improvement of only 1 or 2 symptoms, suggesting different fiber tracts mediate different symptoms. OBJECTIVE To search for correlations between improvements of specific symptoms with surgical lesions of specific fiber tract components of Raprl in patients with PD. METHODS A total of 10 patients were treated with unilateral radiofrequency lesions directed to Raprl. The improvement for tremor, rigidity, bradykinesia, posture, and gait was evaluated at 24 to 33 mo after operation through the Unified Parkinson's Disease Rating Scale (UPDRS) score, and the precise location and extension of lesions through structural magnetic resonance imaging and probabilistic tractography at 6 to 8 mo postsurgery. Correlation between percentage of fiber tract involvement and percentage of UPDRS-III score improvement was evaluated through Spearman's correlation coefficient. RESULTS Group average improvement was 86% for tremor, 62% for rigidity, 56% for bradykinesia, and 45% for gait and posture. Improvement in global UPDRS score correlated with extent of lesions in fibers connecting with contralateral cerebellar cortex and improvement of posture and gait with fibers connecting with contralateral deep cerebellar nuclei. Lesion of fibers connecting the globus pallidum with pedunculopontine nucleus induced improvement of gait and posture over other symptoms. CONCLUSION Partial lesion of Raprl fibers resulted in symptom improvement at 2-yr follow-up. Lesions of selective fiber components may result in selective improvement of specific symptoms.
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Affiliation(s)
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Campus Juriquilla, Juriquilla, Mexico
| | - Julian Soto-Abraham
- Unit for Stereotactic and Functional Neurosurgery, General Hospital of Mexico, Ciudad de México, Mexico
| | - Jacques D Tournier
- Department of Biomedical Engineering, School of Bioengineering and Imaging Sciences, King's College London, King's Health Partners, St. Thomas' Hospital, London, United Kingdom.,Centre for the Developing Brain, School of Bioengineering and Imaging Sciences, King's College London, King's Health Partners, St. Thomas' Hospital, London, United Kingdom
| | - Gustavo Aguado-Carrillo
- Unit for Stereotactic and Functional Neurosurgery, General Hospital of Mexico, Ciudad de México, Mexico
| | - Francisco Velasco-Campos
- Unit for Stereotactic and Functional Neurosurgery, General Hospital of Mexico, Ciudad de México, Mexico
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27
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Isaacs BR, Keuken MC, Alkemade A, Temel Y, Bazin PL, Forstmann BU. Methodological Considerations for Neuroimaging in Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease Patients. J Clin Med 2020; 9:E3124. [PMID: 32992558 PMCID: PMC7600568 DOI: 10.3390/jcm9103124] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 09/17/2020] [Accepted: 09/25/2020] [Indexed: 12/17/2022] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus is a neurosurgical intervention for Parkinson's disease patients who no longer appropriately respond to drug treatments. A small fraction of patients will fail to respond to DBS, develop psychiatric and cognitive side-effects, or incur surgery-related complications such as infections and hemorrhagic events. In these cases, DBS may require recalibration, reimplantation, or removal. These negative responses to treatment can partly be attributed to suboptimal pre-operative planning procedures via direct targeting through low-field and low-resolution magnetic resonance imaging (MRI). One solution for increasing the success and efficacy of DBS is to optimize preoperative planning procedures via sophisticated neuroimaging techniques such as high-resolution MRI and higher field strengths to improve visualization of DBS targets and vasculature. We discuss targeting approaches, MRI acquisition, parameters, and post-acquisition analyses. Additionally, we highlight a number of approaches including the use of ultra-high field (UHF) MRI to overcome limitations of standard settings. There is a trade-off between spatial resolution, motion artifacts, and acquisition time, which could potentially be dissolved through the use of UHF-MRI. Image registration, correction, and post-processing techniques may require combined expertise of traditional radiologists, clinicians, and fundamental researchers. The optimization of pre-operative planning with MRI can therefore be best achieved through direct collaboration between researchers and clinicians.
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Affiliation(s)
- Bethany R. Isaacs
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
- Department of Experimental Neurosurgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands;
| | - Max C. Keuken
- Municipality of Amsterdam, Services & Data, Cluster Social, 1000 AE Amsterdam, The Netherlands;
| | - Anneke Alkemade
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
| | - Yasin Temel
- Department of Experimental Neurosurgery, Maastricht University Medical Center, 6202 AZ Maastricht, The Netherlands;
| | - Pierre-Louis Bazin
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
- Max Planck Institute for Human Cognitive and Brain Sciences, D-04103 Leipzig, Germany
| | - Birte U. Forstmann
- Integrative Model-based Cognitive Neuroscience Research Unit, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; (A.A.); (P.-L.B.); (B.U.F.)
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28
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Xiao Y, Lau JC, Hemachandra D, Gilmore G, Khan AR, Peters TM. Image Guidance in Deep Brain Stimulation Surgery to Treat Parkinson's Disease: A Comprehensive Review. IEEE Trans Biomed Eng 2020; 68:1024-1033. [PMID: 32746050 DOI: 10.1109/tbme.2020.3006765] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Deep brain stimulation (DBS) is an effective therapy as an alternative to pharmaceutical treatments for Parkinson's disease (PD). Aside from factors such as instrumentation, treatment plans, and surgical protocols, the success of the procedure depends heavily on the accurate placement of the electrode within the optimal therapeutic targets while avoiding vital structures that can cause surgical complications and adverse neurologic effects. Although specific surgical techniques for DBS can vary, interventional guidance with medical imaging has greatly contributed to the development, outcomes, and safety of the procedure. With rapid development in novel imaging techniques, computational methods, and surgical navigation software, as well as growing insights into the disease and mechanism of action of DBS, modern image guidance is expected to further enhance the capacity and efficacy of the procedure in treating PD. This article surveys the state-of-the-art techniques in image-guided DBS surgery to treat PD, and discusses their benefits and drawbacks, as well as future directions on the topic.
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29
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Lau JC, Xiao Y, Haast RAM, Gilmore G, Uludağ K, MacDougall KW, Menon RS, Parrent AG, Peters TM, Khan AR. Direct visualization and characterization of the human zona incerta and surrounding structures. Hum Brain Mapp 2020; 41:4500-4517. [PMID: 32677751 PMCID: PMC7555067 DOI: 10.1002/hbm.25137] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Revised: 05/31/2020] [Accepted: 07/02/2020] [Indexed: 12/11/2022] Open
Abstract
The zona incerta (ZI) is a small gray matter region of the deep brain first identified in the 19th century, yet direct in vivo visualization and characterization has remained elusive. Noninvasive detection of the ZI and surrounding region could be critical to further our understanding of this widely connected but poorly understood deep brain region and could contribute to the development and optimization of neuromodulatory therapies. We demonstrate that high resolution (submillimetric) longitudinal (T1) relaxometry measurements at high magnetic field strength (7 T) can be used to delineate the ZI from surrounding white matter structures, specifically the fasciculus cerebellothalamicus, fields of Forel (fasciculus lenticularis, fasciculus thalamicus, and field H), and medial lemniscus. Using this approach, we successfully derived in vivo estimates of the size, shape, location, and tissue characteristics of substructures in the ZI region, confirming observations only previously possible through histological evaluation that this region is not just a space between structures but contains distinct morphological entities that should be considered separately. Our findings pave the way for increasingly detailed in vivo study and provide a structural foundation for precise functional and neuromodulatory investigation.
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Affiliation(s)
- Jonathan C Lau
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Ontario, Canada.,Imaging Research Laboratories, Robarts Research Institute Canada, Western University, London, Ontario, Canada.,Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario, Canada.,School of Biomedical Engineering, Western University, London, Ontario, Canada
| | - Yiming Xiao
- Imaging Research Laboratories, Robarts Research Institute Canada, Western University, London, Ontario, Canada.,Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Roy A M Haast
- Imaging Research Laboratories, Robarts Research Institute Canada, Western University, London, Ontario, Canada.,Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Greydon Gilmore
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Ontario, Canada.,School of Biomedical Engineering, Western University, London, Ontario, Canada
| | - Kâmil Uludağ
- IBS Center for Neuroscience Imaging Research, Sungkyunkwan University, Suwon, South Korea.,Department of Biomedical Engineering, N Center, Sungkyunkwan University, Suwon, South Korea.,Techna Institute and Koerner Scientist in MR Imaging, University Health Network, Toronto, Ontario, Canada
| | - Keith W MacDougall
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Ontario, Canada
| | - Ravi S Menon
- Imaging Research Laboratories, Robarts Research Institute Canada, Western University, London, Ontario, Canada.,Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Andrew G Parrent
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Ontario, Canada
| | - Terry M Peters
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Ontario, Canada.,Imaging Research Laboratories, Robarts Research Institute Canada, Western University, London, Ontario, Canada.,Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario, Canada.,School of Biomedical Engineering, Western University, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada
| | - Ali R Khan
- Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, London, Ontario, Canada.,Imaging Research Laboratories, Robarts Research Institute Canada, Western University, London, Ontario, Canada.,Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario, Canada.,School of Biomedical Engineering, Western University, London, Ontario, Canada.,Brain and Mind Institute, Western University, London, Ontario, Canada.,Department of Medical Biophysics, Western University, London, Ontario, Canada
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30
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Patriat R, Niederer J, Kaplan J, Amundsen Huffmaster S, Petrucci M, Eberly L, Harel N, MacKinnon C. Morphological changes in the subthalamic nucleus of people with mild-to-moderate Parkinson's disease: a 7T MRI study. Sci Rep 2020; 10:8785. [PMID: 32472044 PMCID: PMC7260237 DOI: 10.1038/s41598-020-65752-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 04/29/2020] [Indexed: 02/06/2023] Open
Abstract
This project investigated whether structural changes are present in the subthalamic nucleus (STN) of people with mild-to-moderate severity of Parkinson's disease (PD). Within-subject measures of STN volume and fractional anisotropy (FA) were derived from high-resolution 7Tesla magnetic resonance imaging (MRI) for 29 subjects with mild-to-moderate PD (median disease duration = 2.3±1.9 years) and 18 healthy matched controls. Manual segmentation of the STN was performed on 0.4 mm in-plane resolution images. FA maps were generated and FA values were averaged over the left and right STN separately for each subject. Motor sign severity was assessed using the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Linear effects models showed that STN volume was significantly smaller in the PD subjects compared to controls (p = 0.01). Further, after controlling for differences in STN volumes within or between groups, the PD group had lower FA values in the STN compared to controls (corrected p ≤ 0.008). These findings demonstrate that morphological changes occur in the STN, which likely impact the function of the hyperdirect and indirect pathways of the basal ganglia and movement control.
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Affiliation(s)
- Rémi Patriat
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA.
| | - Jacob Niederer
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Jordan Kaplan
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | | | - Matthew Petrucci
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Lynn Eberly
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, USA
| | - Colum MacKinnon
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
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31
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Wang ZM, Wei PH, Shan Y, Han M, Zhang M, Liu H, Gao JH, Lu J. Identifying and characterizing projections from the subthalamic nucleus to the cerebellum in humans. Neuroimage 2020; 210:116573. [PMID: 31968232 DOI: 10.1016/j.neuroimage.2020.116573] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 01/17/2020] [Accepted: 01/17/2020] [Indexed: 12/31/2022] Open
Abstract
A connection between the subthalamic nucleus (STN) and the cerebellum which has been shown to exist in non-human primates, was recently identified in humans. However, its anatomical features, network properties and function have yet to be elucidated in humans. In the present study, we quantified the STN-cerebellum pathway in humans and explored its function based on structural observations. Anatomical features and asymmetry index (AI) were explored using high definition fiber tractography data of 30 individuals from the Massachusetts General Hospital - Human Connectome Project adult diffusion database. Pearson's correlation analysis was performed to determine the interrelationship between the subdivisions of the STN-cerebellum and the global cortical-STN connections. The pathway was visualized bilaterally in all the subjects. Typically, after setting out from the STN, the STN-cerebellum projections incorporated into the nearby corticopontine tracts, passing through the cerebral peduncle, mediated by the pontine nucleus and then connecting in two opposite directions to join the bilateral middle cerebellar peduncle. On the group averaged level, 78.03% and 62.54% of fibers from the right and left STN respectively, distributed to Crus I in the cerebellum, part of the remaining fibers projected to Crus II, with most of the fibers crossing contralaterally. According to the AI evaluation, 60% of the participants were right STN dominant, 23% were left STN dominant, and 17% were relatively symmetric. Pearson's correlation analysis further indicated that the number of pathways from mesial Brodmann area 8 to the STN (hyperdirect pathway associated with decision making) was positively correlated with the number of fibers from the right STN to Crus I. The insertion and termination, the right-side dominance, and the positive correlation with the hyperdirect pathway all suggest that the STN-cerebellum pathway might be involved in decision-making processes.
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Affiliation(s)
- Zhen-Ming Wang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Peng-Hu Wei
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Yi Shan
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Meizhen Han
- Center for MRI Research, Peking University, Beijing, China
| | - Miao Zhang
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China
| | - Hesheng Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Jia-Hong Gao
- Center for MRI Research, Peking University, Beijing, China.
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China; Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, 100053, China; Department of Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
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32
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Ma R, Henry TR, Van de Moortele PF. Eliminating susceptibility induced hyperintensities in T1w MPRAGE brain images at 7 T. Magn Reson Imaging 2019; 63:274-279. [PMID: 31446038 DOI: 10.1016/j.mri.2019.08.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 08/02/2019] [Accepted: 08/15/2019] [Indexed: 01/01/2023]
Abstract
INTRODUCTION At ultrahigh field, local susceptibility induced hyperintensities are pronounced in brain areas close to air-tissue boundaries in the inferior frontal lobe and temporal lobes on T1w MPRAGE images. Resulting from incomplete inversion, these artefacts can introduce biases in brain volumetry and erroneously suggest the existence of local tissular anomaly. We propose a straightforward approach to eliminate these artefacts by applying a shift (ΔfIR) to the center frequency of the adiabatic inversion pulse while widening the bandwidth of the latter by shortening the pulse duration (ΔtIR). METHODS An MPRAGE sequence was customized allowing to change the duration (standard: 10,240 μs) and center frequency of the hyperbolic secant inversion RF pulse (IR). All measurements were performed on a 7 T whole body scanner (Siemens, Erlangen, Germany). 13 healthy volunteers (7 female and 6 male, average age (SD) = 38 ± 15 yrs) were recruited for the study, 3 of which were scanned for protocol optimization and the rest for performance evaluation. ΔB0 was mapped through the brain with a gradient echo sequence. The effects of ΔfIR and ΔtIR were studied separately and jointly to determine optimal parameter combinations to achieve the largest spatial extent of complete inversion throughout the brain. RESULTS Applying a positive ΔfIR restored inversion efficiency in the inferior frontal and temporal lobes, but also introduced undesired hyperintensities in the anterior temporal lobes. Widening the bandwidth alone could also partially reduce hyperintensities in the frontal area but with a limited efficiency. By simultaneously applying a positive ΔfIR of 300 Hz and shortening ΔtIR by 40%, these artefacts were eliminated across the whole cerebrum. CONCLUSION A robust elimination of susceptibility induced hyperintensities near air-tissue boundaries in T1w MPRAGE 7 T brain images is demonstrated. This technique only requires limited MR sequence modifications.
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Affiliation(s)
- Ruoyun Ma
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Thomas R Henry
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
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33
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Isaacs BR, Trutti AC, Pelzer E, Tittgemeyer M, Temel Y, Forstmann BU, Keuken MC. Cortico-basal white matter alterations occurring in Parkinson's disease. PLoS One 2019; 14:e0214343. [PMID: 31425517 PMCID: PMC6699705 DOI: 10.1371/journal.pone.0214343] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 07/17/2019] [Indexed: 01/01/2023] Open
Abstract
Magnetic resonance imaging studies typically use standard anatomical atlases for identification and analyses of (patho-)physiological effects on specific brain areas; these atlases often fail to incorporate neuroanatomical alterations that may occur with both age and disease. The present study utilizes Parkinson's disease and age-specific anatomical atlases of the subthalamic nucleus for diffusion tractography, assessing tracts that run between the subthalamic nucleus and a-priori defined cortical areas known to be affected by Parkinson's disease. The results show that the strength of white matter fiber tracts appear to remain structurally unaffected by disease. Contrary to that, Fractional Anisotropy values were shown to decrease in Parkinson's disease patients for connections between the subthalamic nucleus and the pars opercularis of the inferior frontal gyrus, anterior cingulate cortex, the dorsolateral prefrontal cortex and the pre-supplementary motor, collectively involved in preparatory motor control, decision making and task monitoring. While the biological underpinnings of fractional anisotropy alterations remain elusive, they may nonetheless be used as an index of Parkinson's disease. Moreover, we find that failing to account for structural changes occurring in the subthalamic nucleus with age and disease reduce the accuracy and influence the results of tractography, highlighting the importance of using appropriate atlases for tractography.
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Affiliation(s)
- Bethany. R. Isaacs
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
- Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Anne. C. Trutti
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
- Cognitive Psychology, University of Leiden, Leiden, the Netherlands
| | - Esther Pelzer
- Translational Neurocircuitry, Max Planck Institute for Metabolism Research, Cologne, Germany
- Department of Neurology, University Clinics, Cologne, Germany
| | - Marc Tittgemeyer
- Translational Neurocircuitry, Max Planck Institute for Metabolism Research, Cologne, Germany
- Department of Neurology, University Clinics, Cologne, Germany
| | - Yasin Temel
- Department of Neurosurgery, Maastricht University Medical Centre, Maastricht, The Netherlands
| | - Birte. U. Forstmann
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
| | - Max. C. Keuken
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, the Netherlands
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34
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García-Gomar MG, Strong C, Toschi N, Singh K, Rosen BR, Wald LL, Bianciardi M. In vivo Probabilistic Structural Atlas of the Inferior and Superior Colliculi, Medial and Lateral Geniculate Nuclei and Superior Olivary Complex in Humans Based on 7 Tesla MRI. Front Neurosci 2019; 13:764. [PMID: 31440122 PMCID: PMC6694208 DOI: 10.3389/fnins.2019.00764] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2019] [Accepted: 07/09/2019] [Indexed: 12/01/2022] Open
Abstract
Despite extensive neuroimaging research of primary sensory cortices involved in auditory and visual functions, subcortical structures within these domains, such as the inferior and superior colliculi, the medial and lateral geniculate nuclei and the superior olivary complex, are currently understudied with magnetic resonance imaging (MRI) in living humans. This is because a precise localization of these nuclei is hampered by the limited contrast and sensitivity of conventional neuroimaging methods for deep brain nuclei. In this work, we used 7 Tesla multi-modal (T2-weighted and diffusion fractional anisotropy) 1.1 mm isotropic resolution MRI to achieve high sensitivity and contrast for single-subject brainstem and thalamic nuclei delineation. After precise coregistration to stereotactic space, we generated an in vivo human probabilistic atlas of auditory (medial geniculate nucleus, inferior colliculus, and superior olivary complex) and visual (lateral geniculate nucleus and superior colliculus) subcortical nuclei. We foresee the use of this atlas as a tool to precisely identify the location and shape of auditory/visual deep nuclei in research as well as clinical human studies.
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Affiliation(s)
- María G García-Gomar
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, MGH and Harvard Medical School, Boston, MA, United States
| | - Christian Strong
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Nicola Toschi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, MGH and Harvard Medical School, Boston, MA, United States.,Medical Physics Section, Department of Biomedicine and Prevention, Faculty of Medicine, Tor Vergata University of Rome, Rome, Italy
| | - Kavita Singh
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, MGH and Harvard Medical School, Boston, MA, United States
| | - Bruce R Rosen
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, MGH and Harvard Medical School, Boston, MA, United States
| | - Lawrence L Wald
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, MGH and Harvard Medical School, Boston, MA, United States
| | - Marta Bianciardi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, MGH and Harvard Medical School, Boston, MA, United States
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35
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Affiliation(s)
- Gaurav Verma
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Priti Balchandani
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY
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36
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Neuroimaging Technological Advancements for Targeting in Functional Neurosurgery. Curr Neurol Neurosci Rep 2019; 19:42. [DOI: 10.1007/s11910-019-0961-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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37
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Mulder MJ, Keuken MC, Bazin PL, Alkemade A, Forstmann BU. Size and shape matter: The impact of voxel geometry on the identification of small nuclei. PLoS One 2019; 14:e0215382. [PMID: 30978242 PMCID: PMC6461289 DOI: 10.1371/journal.pone.0215382] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Accepted: 04/01/2019] [Indexed: 12/28/2022] Open
Abstract
How, and to what extent do size and shape of a voxel measured with magnetic resonance imaging (MRI) affect the ability to visualize small brain nuclei? Despite general consensus that voxel geometry affects volumetric properties of regions of interest, particularly those of small brain nuclei, no quantitative data on the influence of voxel size and shape on labeling accuracy is available. Using simulations, we investigated the selective influence of voxel geometry by reconstructing simulated ellipsoid structures with voxels varying in shape and size. For each reconstructed ellipsoid, we calculated differences in volume and similarity between the labeled volume and the predefined dimensions of the ellipsoid. Probability functions were derived from one or two individual raters and a simulated ground truth for reference. As expected, larger voxels (i.e., coarser resolution) and increasing anisotropy results in increased deviations of both volume and shape measures, which is of particular relevance for small brain structures. Our findings clearly illustrate the anatomical inaccuracies introduced by the application of large and/or anisotropic voxels. To ensure deviations occur within the acceptable range (Dice coefficient scores; DCS > 0.75, corresponding to < 57% volume deviation), the volume of isotropic voxels should not exceed 5% of the total volume of the region of interest. When high accuracy is required (DCS > 0.90, corresponding to a < 19% volume deviation), the volumes of isotropic voxels should not exceed 0.08%, of the total volume. Finally, when large anisotropic factors (>3) are used, and the ellipsoid is orthogonal to the slice axes, having its long axis in the imaging plane, the voxel volume should not exceed 0.005% of the total volume. This allows sufficient compensation of anisotropy effects, in order to reach accuracy in the acceptable range (DCS > 0.75, corresponding to >57% volume deviation).
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Affiliation(s)
- Martijn J Mulder
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands.,Experimental Psychology, Utrecht University, Utrecht, the Netherlands
| | - Max C Keuken
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands.,Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Anneke Alkemade
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
| | - Birte U Forstmann
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Amsterdam, The Netherlands
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Choi US, Kawaguchi H, Matsuoka Y, Kober T, Kida I. Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI. PLoS One 2019; 14:e0210803. [PMID: 30818328 PMCID: PMC6394968 DOI: 10.1371/journal.pone.0210803] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 01/02/2019] [Indexed: 01/09/2023] Open
Abstract
We proposed a method for segmentation of brain tissues-gray matter, white matter, and cerebrospinal fluid-using multi-contrast images, including a T1 map and a uniform T1-weighted image, from a magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE) sequence at 7 Tesla. The proposed method was evaluated with respect to the processing time and the similarity of the segmented masks of brain tissues with those obtained using FSL, FreeSurfer, and SPM12. The processing time of the proposed method (28 ± 0 s) was significantly shorter than those of FSL and SPM12 (444 ± 4 s and 159 ± 2 s for FSL and SPM12, respectively). In the similarity assessment, the tissue mask of the brain obtained by the proposed method showed higher consistency with those obtained using FSL than with those obtained using SPM12. The proposed method misclassified the subcortical structures and large vessels since it is based on the intensities of multi-contrast images obtained using MP2RAGE, which uses a similar segmentation approach as FSL but is not based on a template image or a parcellated brain atlas, which are used for FreeSurfer and SPM12, respectively. However, the proposed method showed good segmentation in the cerebellum and white matter in the medial part of the brain in comparison with the other methods. Thus, because the proposed method using different contrast images of MP2RAGE sequence showed the shortest processing time and similar segmentation ability as the other methods, it may be useful for both neuroimaging research and clinical diagnosis.
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Affiliation(s)
- Uk-Su Choi
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
- Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan
| | | | - Yuichiro Matsuoka
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
- Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
- Department of Radiology, University Hospital (CHUV), Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ikuhiro Kida
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
- Graduate School of Frontier Biosciences, Osaka University, Osaka, Japan
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39
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Kim J, Duchin Y, Shamir RR, Patriat R, Vitek J, Harel N, Sapiro G. Automatic localization of the subthalamic nucleus on patient-specific clinical MRI by incorporating 7 T MRI and machine learning: Application in deep brain stimulation. Hum Brain Mapp 2019; 40:679-698. [PMID: 30379376 PMCID: PMC6519731 DOI: 10.1002/hbm.24404] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Revised: 09/04/2018] [Accepted: 09/07/2018] [Indexed: 12/20/2022] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has shown clinical potential for relieving the motor symptoms of advanced Parkinson's disease. While accurate localization of the STN is critical for consistent across-patients effective DBS, clear visualization of the STN under standard clinical MR protocols is still challenging. Therefore, intraoperative microelectrode recordings (MER) are incorporated to accurately localize the STN. However, MER require significant neurosurgical expertise and lengthen the surgery time. Recent advances in 7 T MR technology facilitate the ability to clearly visualize the STN. The vast majority of centers, however, still do not have 7 T MRI systems, and fewer have the ability to collect and analyze the data. This work introduces an automatic STN localization framework based on standard clinical MRIs without additional cost in the current DBS planning protocol. Our approach benefits from a large database of 7 T MRI and its clinical MRI pairs. We first model in the 7 T database, using efficient machine learning algorithms, the spatial and geometric dependency between the STN and its adjacent structures (predictors). Given a standard clinical MRI, our method automatically computes the predictors and uses the learned information to predict the patient-specific STN. We validate our proposed method on clinical T2 W MRI of 80 subjects, comparing with experts-segmented STNs from the corresponding 7 T MRI pairs. The experimental results show that our framework provides more accurate and robust patient-specific STN localization than using state-of-the-art atlases. We also demonstrate the clinical feasibility of the proposed technique assessing the post-operative electrode active contact locations.
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Affiliation(s)
- Jinyoung Kim
- Surgical Information Sciences, Inc.MinneapolisMinnesota
| | - Yuval Duchin
- Surgical Information Sciences, Inc.MinneapolisMinnesota
| | | | - Remi Patriat
- Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesota
| | - Jerrold Vitek
- Department of NeurologyUniversity of MinnesotaMinneapolisMinnesota
| | - Noam Harel
- Surgical Information Sciences, Inc.MinneapolisMinnesota
- Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesota
- Department of NeurosurgeryUniversity of MinnesotaMinneapolisMinnesota
| | - Guillermo Sapiro
- Surgical Information Sciences, Inc.MinneapolisMinnesota
- Department of Electrical and Computer EngineeringDuke UniversityDurhamNorth Carolina
- Department of Biomedical EngineeringDuke UniversityDurhamNorth Carolina
- Department of Computer ScienceDuke UniversityDurhamNorth Carolina
- Department of MathematicsDuke UniversityDurhamNorth Carolina
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40
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Functional neuroanatomical review of the ventral tegmental area. Neuroimage 2019; 191:258-268. [PMID: 30710678 DOI: 10.1016/j.neuroimage.2019.01.062] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 01/22/2019] [Accepted: 01/23/2019] [Indexed: 12/19/2022] Open
Abstract
The ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) are assumed to play a key role in dopamine-related functions such as reward-related behaviour, motivation, addiction and motor functioning. Although dopamine-producing midbrain structures are bordering, they show significant differences in structure and function that argue for a distinction when studying the functions of the dopaminergic midbrain, especially by means of neuroimaging. First, unlike the SNc, the VTA is not a nucleus, which makes it difficult to delineate the structure due to lack of clear anatomical borders. Second, there is no consensus in the literature about the anatomical nomenclature to describe the VTA. Third, these factors in combination with limitations in magnetic resonance imaging (MRI) complicate VTA visualization. We suggest that developing an MRI-compatible probabilistic atlas of the VTA will help to overcome these issues. Such an atlas can be used to identify the individual VTA and serve as region-of-interest for functional MRI.
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41
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Kern DS, Picillo M, Thompson JA, Sammartino F, di Biase L, Munhoz RP, Fasano A. Interleaving Stimulation in Parkinson's Disease, Tremor, and Dystonia. Stereotact Funct Neurosurg 2019; 96:379-391. [PMID: 30654368 DOI: 10.1159/000494983] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2018] [Accepted: 10/24/2018] [Indexed: 11/19/2022]
Abstract
BACKGROUND/AIMS Interleaving stimulation (ILS) in deep brain stimulation (DBS) provides individualized stimulation of 2 contacts delivered in alternating order. Currently, limited information on the utility of ILS exists. The aims of this study were to determine the practical applications and outcomes of ILS DBS in Parkinson's disease (PD), tremor, and dystonia. METHODS We performed a single-center, unblinded, retrospective chart review of all patients with DBS attempted on ILS at our referral center assessing for rationale and outcomes. RESULTS Fifty patients (PD, n = 27; tremor, n = 7; dystonia, n = 16 patients) tried ILS for 2 rationales: management of adverse effects (n = 29) and to improve clinical efficacy (n = 21). A total of 19 patients demonstrated improvement with ILS for adverse effect management predominately for the treatment of dyskinesias (n = 12). In the vast majority of dyskinetic patients, a contact added into the rostral zona incerta with ILS was performed. Nine out of 21 patients demonstrated improved clinical efficacy with ILS with all 6 PD patients who tried ILS for this rationale demonstrating benefit. CONCLUSIONS In PD, ILS provided benefits for dyskinesias and parkinsonism, with minimal improvement of other adverse effects. In tremor and dystonia, marginal effects in terms of mitigation of adverse effects and improvement of clinical outcomes were evident.
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Affiliation(s)
- Drew S Kern
- Movement Disorders Center, Department of Neurology, University of Colorado, Denver, Colorado, USA, .,Movement Disorders Center, Department of Neurosurgery, University of Colorado, Denver, Colorado, USA,
| | - Marina Picillo
- Center for Neurodegenerative Diseases (CEMAND), Department of Medicine and Surgery, Neuroscience Section, University of Salerno, Salerno, Italy
| | - John A Thompson
- Movement Disorders Center, Department of Neurosurgery, University of Colorado, Denver, Colorado, USA
| | - Francesco Sammartino
- Division of Neurosurgery, University of Toronto, Toronto Western Hospital, Toronto, Ontario, Canada
| | - Lazzaro di Biase
- Neurology Unit, Campus Bio-Medico University, Rome, Italy.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Renato P Munhoz
- Edmond J. Safra Program in Parkinson's Disease and Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Division of Neurology, University of Toronto, Toronto, Ontario, Canada
| | - Alfonso Fasano
- Edmond J. Safra Program in Parkinson's Disease and Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Division of Neurology, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, Toronto, Ontario, Canada
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42
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Horn A, Li N, Dembek TA, Kappel A, Boulay C, Ewert S, Tietze A, Husch A, Perera T, Neumann WJ, Reisert M, Si H, Oostenveld R, Rorden C, Yeh FC, Fang Q, Herrington TM, Vorwerk J, Kühn AA. Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging. Neuroimage 2019; 184:293-316. [PMID: 30179717 PMCID: PMC6286150 DOI: 10.1016/j.neuroimage.2018.08.068] [Citation(s) in RCA: 445] [Impact Index Per Article: 89.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 08/13/2018] [Accepted: 08/28/2018] [Indexed: 01/09/2023] Open
Abstract
Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural/functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient's preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the preprocessing method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.
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Affiliation(s)
- Andreas Horn
- Movement Disorders & Neuromodulation Unit, Department for Neurology, Charité - University Medicine Berlin, Germany.
| | - Ningfei Li
- Movement Disorders & Neuromodulation Unit, Department for Neurology, Charité - University Medicine Berlin, Germany
| | - Till A Dembek
- Department of Neurology, University Hospital of Cologne, Germany
| | - Ari Kappel
- Wayne State University, Department of Neurosurgery, Detroit, Michigan, USA
| | | | - Siobhan Ewert
- Movement Disorders & Neuromodulation Unit, Department for Neurology, Charité - University Medicine Berlin, Germany
| | - Anna Tietze
- Institute of Neuroradiology, Charité - University Medicine Berlin, Germany
| | - Andreas Husch
- University of Luxembourg, Luxembourg Centre for Systems Biomedicine, Interventional Neuroscience Group, Belvaux, Luxembourg
| | - Thushara Perera
- Bionics Institute, East Melbourne, Victoria, Australia; Department of Medical Bionics, University of Melbourne, Parkville, Victoria, Australia
| | - Wolf-Julian Neumann
- Movement Disorders & Neuromodulation Unit, Department for Neurology, Charité - University Medicine Berlin, Germany; Institute of Neuroradiology, Charité - University Medicine Berlin, Germany
| | - Marco Reisert
- Medical Physics, Department of Radiology, Faculty of Medicine, University Freiburg, Germany
| | - Hang Si
- Numerical Mathematics and Scientific Computing, Weierstrass Institute for Applied Analysis and Stochastics (WIAS), Germany
| | - Robert Oostenveld
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, NL, Netherlands; NatMEG, Karolinska Institutet, Stockholm, SE, Sweden
| | - Christopher Rorden
- McCausland Center for Brain Imaging, University of South Carolina, Columbia, SC, USA
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh PA, USA
| | - Qianqian Fang
- Department of Bioengineering, Northeastern University, Boston, USA
| | - Todd M Herrington
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Johannes Vorwerk
- Scientific Computing & Imaging (SCI) Institute, University of Utah, Salt Lake City, USA
| | - Andrea A Kühn
- Movement Disorders & Neuromodulation Unit, Department for Neurology, Charité - University Medicine Berlin, Germany
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43
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Leatherday C, Dehkharghani S, Nahab F, Allen JW, Wu J, Hu R, Qiu D. Cerebral MR oximetry during acetazolamide augmentation: Beyond cerebrovascular reactivity in hemodynamic failure. J Magn Reson Imaging 2018; 50:175-182. [PMID: 30390367 DOI: 10.1002/jmri.26546] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 10/02/2018] [Accepted: 10/02/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Oxygen extraction fraction (OEF) elevation predicts increased ischemic stroke incidence among patients with carotid steno-occlusive disease, and can be estimated from quantitative susceptibility mapping (QSM) MRI. PURPOSE To explore QSM oximetry during acetazolamide (ACZ) challenge, hypothesizing that detectable OEF alterations will reflect hemodynamic compromise in unilateral cerebrovascular disease (CVD) patients. STUDY TYPE Retrospective. SUBJECTS Fourteen unilateral CVD patients, and 24 healthy controls (HC). FIELD STRENGTH/SEQUENCE Multiecho gradient echo (GRE) and T1 -weighted images at 3T. ASSESSMENT We constructed QSM images and R2* maps from multiecho GRE images. QSM-OEF maps were generated from the susceptibility difference between venous blood and background brain tissue. Intrasubject diseased/contralateral hemisphere OEF ratios in the middle cerebral artery (MCA) territories were calculated. Intravascular susceptibility in the straight sinus (SS) and MCA was also measured. STATISTICAL TESTS The result significance was determined using t-tests and Pearson's correlation. RESULTS Mean and standard deviation for the patient diseased/contralateral OEF ratios were 1.15 ± 0.14 at baseline and 1.23 ± 0.17 post-ACZ. Disease group R2* ratios were 0.95 ± 0.05 at baseline and 1.03 ± 0.08 post-ACZ. Left/right OEF and R2* ratios for the HC group were 0.98 ± 0.06 and 0.99 ± 0.038, respectively. Susceptibility (ppb) in the SS and MCA in patients was 162.63 ± 35.4 and -22.33 ± 13.70, respectively, at baseline, 124.56 ± 37.43 and -19.27 ± 23.14 post-ACZ. The HC group SS and MCA susceptibility was 146.10 ± 24.79 and -19.59 ± 12.37, respectively. Patient group OEF ratios were greater than 1.0 before and after ACZ challenge (P < 0.01 and < 0.001, respectively, one-sample t-test), and were greater than HC ratios (P < 0.001 unpaired t-test). OEF and R2* ratios increased from baseline to post-ACZ (P = 0.024, 0.004, respectively, paired t-test). Detectable blood oxygenation change was confirmed by finding SS susceptibility decreased from baseline to post-ACZ (P < 0.001, paired t-test), while MCA susceptibility did not change significantly (P = 0.67, paired t-test). DATA CONCLUSION These results suggest QSM is sensitive to dynamic OEF modulation during hemodynamic augmentation. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:175-182.
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Affiliation(s)
| | | | - Fadi Nahab
- Neurology, Emory University, Atlanta, Georgia, USA
| | - Jason W Allen
- Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA.,Neurology, Emory University, Atlanta, Georgia, USA
| | - Junjie Wu
- Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
| | - Ranliang Hu
- Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
| | - Deqiang Qiu
- Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
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Duchin Y, Shamir RR, Patriat R, Kim J, Vitek JL, Sapiro G, Harel N. Patient-specific anatomical model for deep brain stimulation based on 7 Tesla MRI. PLoS One 2018; 13:e0201469. [PMID: 30133472 PMCID: PMC6104927 DOI: 10.1371/journal.pone.0201469] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Accepted: 07/15/2018] [Indexed: 01/16/2023] Open
Abstract
Objective Deep brain stimulation (DBS) requires accurate localization of the anatomical target structure, and the precise placement of the DBS electrode within it. Ultra-high field 7 Tesla (T) MR images can be utilized to create patient-specific anatomical 3D models of the subthalamic nuclei (STN) to enhance pre-surgical DBS targeting as well as post-surgical visualization of the DBS lead position and orientation. We validated the accuracy of the 7T imaging-based patient-specific model of the STN and measured the variability of the location and dimensions across movement disorder patients. Methods 72 patients who underwent DBS surgery were scanned preoperatively on 7T MRI. Segmentations and 3D volume rendering of the STN were generated for all patients. For 21 STN-DBS cases, microelectrode recording (MER) was used to validate the segmentation. For 12 cases, we computed the correlation between the overlap of the STN and volume of tissue activated (VTA) and the monopolar review for a further validation of the model’s accuracy and its clinical relevancy. Results We successfully reconstructed and visualized the STN in all patients. Significant variability was found across individuals regarding the location of the STN center of mass as well as its volume, length, depth and width. Significant correlations were found between MER and the 7T imaging-based model of the STN (r = 0.86) and VTA-STN overlap and the monopolar review outcome (r = 0.61). Conclusion The results suggest that an accurate visualization and localization of a patient-specific 3D model of the STN can be generated based on 7T MRI. The imaging-based 7T MRI STN model was validated using MER and patient’s clinical outcomes. The significant variability observed in the STN location and shape based on a large number of patients emphasizes the importance of an accurate direct visualization of the STN for DBS targeting. An accurate STN localization can facilitate postoperative stimulation parameters for optimized patient outcome.
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Affiliation(s)
- Yuval Duchin
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States of America
- Surgical Information Sciences, Minneapolis, MN, United States of America
| | - Reuben R. Shamir
- Surgical Information Sciences, Minneapolis, MN, United States of America
| | - Remi Patriat
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States of America
| | - Jinyoung Kim
- Surgical Information Sciences, Minneapolis, MN, United States of America
- Departments of Electrical & Computer Engineering, Computer Science, Biomedical Engineering and Math, Duke University, Durham, NC, United States of America
| | - Jerrold L. Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States of America
| | - Guillermo Sapiro
- Departments of Electrical & Computer Engineering, Computer Science, Biomedical Engineering and Math, Duke University, Durham, NC, United States of America
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States of America
- * E-mail:
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Maling N, Lempka SF, Blumenfeld Z, Bronte-Stewart H, McIntyre CC. Biophysical basis of subthalamic local field potentials recorded from deep brain stimulation electrodes. J Neurophysiol 2018; 120:1932-1944. [PMID: 30020838 DOI: 10.1152/jn.00067.2018] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Clinical deep brain stimulation (DBS) technology is evolving to enable chronic recording of local field potentials (LFPs) that represent electrophysiological biomarkers of the underlying disease state. However, little is known about the biophysical basis of LFPs, or how the patient's unique brain anatomy and electrode placement impact the recordings. Therefore, we developed a patient-specific computational framework to analyze LFP recordings within a clinical DBS context. We selected a subject with Parkinson's disease implanted with a Medtronic Activa PC+S DBS system and reconstructed their subthalamic nucleus (STN) and DBS electrode location using medical imaging data. The patient-specific STN volume was populated with 235,280 multicompartment STN neuron models, providing a neuron density consistent with histological measurements. Each neuron received time-varying synaptic inputs and generated transmembrane currents that gave rise to the LFP signal recorded at DBS electrode contacts residing in a finite element volume conductor model. We then used the model to study the role of synchronous beta-band inputs to the STN neurons on the recorded power spectrum. Three bipolar pairs of simultaneous clinical LFP recordings were used in combination with an optimization algorithm to customize the neural activity parameters in the model to the patient. The optimized model predicted a 2.4-mm radius of beta-synchronous neurons located in the dorsolateral STN. These theoretical results enable biophysical dissection of the LFP signal at the cellular level with direct comparison to the clinical recordings, and the model system provides a scientific platform to help guide the design of DBS technology focused on the use of subthalamic beta activity in closed-loop algorithms. NEW & NOTEWORTHY The analysis of deep brain stimulation of local field potential (LFP) data is rapidly expanding from scientific curiosity to the basis for clinical biomarkers capable of improving the therapeutic efficacy of stimulation. With this growing clinical importance comes a growing need to understand the underlying electrophysiological fundamentals of the signals and the factors contributing to their modulation. Our model reconstructs the clinical LFP from first principles and highlights the importance of patient-specific factors in dictating the signals recorded.
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Affiliation(s)
- Nicholas Maling
- Department of Biomedical Engineering, Case Western Reserve University , Cleveland, Ohio
| | - Scott F Lempka
- Department of Biomedical Engineering, University of Michigan , Ann Arbor, Michigan
| | - Zack Blumenfeld
- Department of Neurology, Stanford University , Stanford, California
| | | | - Cameron C McIntyre
- Department of Biomedical Engineering, Case Western Reserve University , Cleveland, Ohio
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Keuken MC, Isaacs BR, Trampel R, van der Zwaag W, Forstmann BU. Visualizing the Human Subcortex Using Ultra-high Field Magnetic Resonance Imaging. Brain Topogr 2018; 31:513-545. [PMID: 29497874 PMCID: PMC5999196 DOI: 10.1007/s10548-018-0638-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 01/28/2018] [Indexed: 12/15/2022]
Abstract
With the recent increased availability of ultra-high field (UHF) magnetic resonance imaging (MRI), substantial progress has been made in visualizing the human brain, which can now be done in extraordinary detail. This review provides an extensive overview of the use of UHF MRI in visualizing the human subcortex for both healthy and patient populations. The high inter-subject variability in size and location of subcortical structures limits the usability of atlases in the midbrain. Fortunately, the combined results of this review indicate that a large number of subcortical areas can be visualized in individual space using UHF MRI. Current limitations and potential solutions of UHF MRI for visualizing the subcortex are also discussed.
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Affiliation(s)
- M C Keuken
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Postbus 15926, 1001NK, Amsterdam, The Netherlands.
- Cognitive Psychology Unit, Institute of Psychology and Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands.
| | - B R Isaacs
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Postbus 15926, 1001NK, Amsterdam, The Netherlands
- Maastricht University Medical Center, Maastricht, The Netherlands
| | - R Trampel
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | - B U Forstmann
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Postbus 15926, 1001NK, Amsterdam, The Netherlands
- Netherlands Institute for Neuroscience, An Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
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Zhang Y, Wei H, Cronin MJ, He N, Yan F, Liu C. Longitudinal atlas for normative human brain development and aging over the lifespan using quantitative susceptibility mapping. Neuroimage 2018; 171:176-189. [PMID: 29325780 PMCID: PMC5857468 DOI: 10.1016/j.neuroimage.2018.01.008] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2017] [Revised: 12/02/2017] [Accepted: 01/05/2018] [Indexed: 11/28/2022] Open
Abstract
Longitudinal brain atlases play an important role in the study of human brain development and cognition. Existing atlases are mainly based on anatomical features derived from T1-and T2-weighted MRI. A 4D developmental quantitative susceptibility mapping (QSM) atlas may facilitate the estimation of age-related iron changes in deep gray matter nuclei and myelin changes in white matter. To this end, group-wise co-registered QSM templates were generated over various age intervals from age 1-83 years old. Registration was achieved by combining both T1-weighted and QSM images. Based on the proposed template, we created an accurate deep gray matter nuclei parcellation map (DGM map). Notably, we segmented thalamus into 5 sub-regions, i.e. the anterior nuclei, the median nuclei, the lateral nuclei, the pulvinar and the internal medullary lamina. Furthermore, we built a "whole brain QSM parcellation map" by combining existing cortical parcellation and white-matter atlases with the proposed DGM map. Based on the proposed QSM atlas, the segmentation accuracy of iron-rich nuclei using QSM is significantly improved, especially for children and adolescent subjects. The age-related progression of magnetic susceptibility in each of the deep gray matter nuclei, the hippocampus, and the amygdala was estimated. Our automated atlas-based analysis provided a systematic confirmation of previous findings on susceptibility progression with age resulting from manual ROI drawings in deep gray matter nuclei. The susceptibility development in the hippocampus and the amygdala follow an iron accumulation model; while in the thalamus sub-regions, the susceptibility development exhibits a variety of trends. It is envisioned that the newly developed 4D QSM atlas will serve as a template for studying brain iron deposition and myelination/demyelination in both normal aging and various brain diseases.
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Affiliation(s)
- Yuyao Zhang
- Electrical Engineering and Computer Science, University of California at Berkeley, CA, USA
| | - Hongjiang Wei
- Electrical Engineering and Computer Science, University of California at Berkeley, CA, USA
| | - Matthew J Cronin
- Electrical Engineering and Computer Science, University of California at Berkeley, CA, USA
| | - Naying He
- Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Fuhua Yan
- Department of Radiology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Chunlei Liu
- Electrical Engineering and Computer Science, University of California at Berkeley, CA, USA; Helen Wills Neuroscience Institute, University of California at Berkeley, CA, USA.
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Duyn JH. Studying brain microstructure with magnetic susceptibility contrast at high-field. Neuroimage 2018; 168:152-161. [PMID: 28242317 PMCID: PMC5569005 DOI: 10.1016/j.neuroimage.2017.02.046] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Revised: 02/03/2017] [Accepted: 02/16/2017] [Indexed: 12/14/2022] Open
Abstract
A rapidly developing application of high field MRI is the study of brain anatomy and function with contrast based on the magnetic susceptibility of tissues. To study the subtle variations in susceptibility contrast between tissues and with changes in brain activity, dedicated scan techniques such as susceptibility-weighted MRI and blood-oxygen level dependent functional MRI have been developed. Particularly strong susceptibility contrast has been observed with systems that operate at 7T and above, and their recent widespread use has led to an improved understanding of contributing sources and mechanisms. To interpret magnetic susceptibility contrast, analysis approaches have been developed with the goal of extracting measures that report on local tissue magnetic susceptibility, a physical quantity that, under certain conditions, allows estimation of blood oxygenation, local tissue iron content, and quantification of its changes with disease. Interestingly, high field studies have also brought to light that not only the makeup of tissues affects MRI susceptibility contrast, but that also a tissue's sub-voxel structure at scales all the way down to the molecular level plays an important role as well. In this review, various ways will be discussed by which sub-voxel structure can affect the MRI signal in general, and magnetic susceptibility in particular, sometimes in a complex fashion. In the light of this complexity, it appears likely that accurate, brain-wide quantification of iron will require the combination of multiple contrasts that may include diffusion and magnetization transfer information with susceptibility-weighted contrast. On the other hand, this complexity also offers opportunities to use magnetic susceptibility contrast to inform about specific microstructural aspects of brain tissue. Details and several examples will be presented in this review.
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Affiliation(s)
- Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, National Institutes of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
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Lempka SF, Howell B, Gunalan K, Machado AG, McIntyre CC. Characterization of the stimulus waveforms generated by implantable pulse generators for deep brain stimulation. Clin Neurophysiol 2018; 129:731-742. [PMID: 29448149 DOI: 10.1016/j.clinph.2018.01.015] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2017] [Revised: 11/10/2017] [Accepted: 01/06/2018] [Indexed: 01/07/2023]
Abstract
OBJECTIVE To determine the circuit elements required to theoretically describe the stimulus waveforms generated by an implantable pulse generator (IPG) during clinical deep brain stimulation (DBS). METHODS We experimentally interrogated the Medtronic Activa PC DBS IPG and defined an equivalent circuit model that accurately captured the output of the IPG. We then compared the detailed circuit model of the clinical stimulus waveforms to simplified representations commonly used in computational models of DBS. We quantified the errors associated with these simplifications using theoretical activation thresholds of myelinated axons in response to DBS. RESULTS We found that the detailed IPG model generated substantial differences in activation thresholds compared to simplified models. These differences were largest for bipolar stimulation with long pulse widths. Average errors were ∼3 to 24% for voltage-controlled stimulation and ∼2 to 11% for current-controlled stimulation. CONCLUSIONS Our results demonstrate the importance of including basic circuit elements (e.g. blocking capacitors, lead wire resistance, electrode capacitance) in model analysis of DBS. SIGNIFICANCE Computational models of DBS are now commonly used in academic research, industrial technology development, and in the selection of clinical stimulation parameters. Incorporating a realistic representation of the IPG output is necessary to improve the accuracy and utility of these clinical and scientific tools.
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Affiliation(s)
- Scott F Lempka
- Center for Neurological Restoration, Cleveland Clinic, Cleveland, OH, USA; Research Service, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA; Biointerfaces Institute, University of Michigan, Ann Arbor, MI, USA.
| | - Bryan Howell
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Kabilar Gunalan
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Andre G Machado
- Center for Neurological Restoration, Cleveland Clinic, Cleveland, OH, USA; Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Cameron C McIntyre
- Research Service, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH, USA; Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
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50
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Zhuang X, Walsh RR, Sreenivasan K, Yang Z, Mishra V, Cordes D. Incorporating spatial constraint in co-activation pattern analysis to explore the dynamics of resting-state networks: An application to Parkinson's disease. Neuroimage 2018; 172:64-84. [PMID: 29355770 DOI: 10.1016/j.neuroimage.2018.01.019] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Revised: 12/23/2017] [Accepted: 01/10/2018] [Indexed: 12/28/2022] Open
Abstract
The dynamics of the brain's intrinsic networks have been recently studied using co-activation pattern (CAP) analysis. The CAP method relies on few model assumptions and CAP-based measurements provide quantitative information of network temporal dynamics. One limitation of existing CAP-related methods is that the computed CAPs share considerable spatial overlap that may or may not be functionally distinct relative to specific network dynamics. To more accurately describe network dynamics with spatially distinct CAPs, and to compare network dynamics between different populations, a novel data-driven CAP group analysis method is proposed in this study. In the proposed method, a dominant-CAP (d-CAP) set is synthesized across CAPs from multiple clustering runs for each group with the constraint of low spatial similarities among d-CAPs. Alternating d-CAPs with less overlapping spatial patterns can better capture overall network dynamics. The number of d-CAPs, the temporal fraction and spatial consistency of each d-CAP, and the subject-specific switching probability among all d-CAPs are then calculated for each group and used to compare network dynamics between groups. The spatial dissimilarities among d-CAPs computed with the proposed method were first demonstrated using simulated data. High consistency between simulated ground-truth and computed d-CAPs was achieved, and detailed comparisons between the proposed method and existing CAP-based methods were conducted using simulated data. In an effort to physiologically validate the proposed technique and investigate network dynamics in a relevant brain network disorder, the proposed method was then applied to data from the Parkinson's Progression Markers Initiative (PPMI) database to compare the network dynamics in Parkinson's disease (PD) and normal control (NC) groups. Fewer d-CAPs, skewed distribution of temporal fractions of d-CAPs, and reduced switching probabilities among final d-CAPs were found in most networks in the PD group, as compared to the NC group. Furthermore, an overall negative association between switching probability among d-CAPs and disease severity was observed in most networks in the PD group as well. These results expand upon previous findings from in vivo electrophysiological recording studies in PD. Importantly, this novel analysis also demonstrates that changes in network dynamics can be measured using resting-state fMRI data from subjects with early stage PD.
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Affiliation(s)
- Xiaowei Zhuang
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA
| | - Ryan R Walsh
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ 85013, USA
| | | | - Zhengshi Yang
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA
| | - Virendra Mishra
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA
| | - Dietmar Cordes
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV 89106, USA; Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO 80309, USA.
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