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Jurva A, Singh B, Qian H, Wang Z, Jacobs ML, Dhima K, Englot DJ, Roberson SW, Bick SK, Constantinidis C. Increased frontoparietal activity related to lower performance in neuropsychological assessment of working memory. Neuroimage 2025:121240. [PMID: 40288702 DOI: 10.1016/j.neuroimage.2025.121240] [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: 01/21/2025] [Revised: 04/18/2025] [Accepted: 04/24/2025] [Indexed: 04/29/2025] Open
Abstract
Executive functions, including working memory, are typically assessed clinically with neuropsychological instruments. In contrast, computerized tasks are used to test these cognitive functions in laboratory human and animal studies. Little is known of how neural activity captured by laboratory tasks relates to ability measured by clinical instruments and, by extension, clinical diagnoses of pathological conditions. We therefore sought to determine what aspects of neural activity elicited in laboratory tasks are predictive of performance in neuropsychological instruments. We recorded neural activity from intracranial electrodes implanted in human epilepsy patients as they performed laboratory working memory tasks. These patients had completed neuropsychological instruments preoperatively, including the Weschler Adult Intelligent Scale and the Wisconsin Card Sorting test. Our results revealed that increased high-gamma (70-150 Hz) power in the prefrontal and parietal cortex after presentation of visual stimuli to be remembered was indicative of lower performance in the neuropsychological tasks. On the other hand, we observed a positive correlation between high-frequency power amplitude in the delay period of the laboratory tasks and neuropsychological performance. Our results demonstrate how neural activity around task events relates to executive function and may be associated with clinical diagnosis of specific cognitive deficits.
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Affiliation(s)
- August Jurva
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235
| | - Balbir Singh
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235
| | - Helen Qian
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212
| | - Zhengyang Wang
- Program in Neuroscience, Vanderbilt University, Nashville, TN 3723515
| | - Monica L Jacobs
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN 37212
| | - Kaltra Dhima
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235; Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212
| | - Shawniqua Williams Roberson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235; Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212
| | - Sarah K Bick
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235; Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212.
| | - Christos Constantinidis
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235; Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37212; Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville, TN 37212.
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Bowersock JL, Wylie SA, Alhourani A, Zemmar A, Holiday V, Hedera P, Stewart T, Bridwell E, Hattab I, Ugiliweneza B, Neimat JS, van Wouwe NC. Theta and beta power in the subthalamic nucleus responds to conflict across subregions and hemispheres. Brain Commun 2025; 7:fcaf021. [PMID: 39882026 PMCID: PMC11775628 DOI: 10.1093/braincomms/fcaf021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2024] [Revised: 11/21/2024] [Accepted: 01/14/2025] [Indexed: 01/31/2025] Open
Abstract
The subthalamic nucleus is thought to play a crucial role in controlling impulsive actions. Networked among the basal ganglia and receiving input from several cortical areas, the subthalamic nucleus is well positioned to influence action selection when faced with competing and conflicting action outcomes. The purpose of this study was to test the dissociable roles of the dorsal and ventral aspects of the subthalamic nucleus during action conflict in patients with Parkinson's disease undergoing intraoperative neurophysiological recording and to explore a potential mechanism for this inhibitory control. We hypothesized that modulations of neurophysiological activity during action conflict would be more pronounced in the dorsal subthalamic nucleus compared with the ventral subthalamic nucleus, due to the dissociation of cortical afferents to subthalamic nucleus subregions and previous findings of deep brain stimulation targeting subthalamic nucleus subregions in Parkinson's disease. We recorded neurophysiological activity while 10 participants with Parkinson's disease performed the Simon task during deep brain stimulation surgery. Response-locked local field potentials in the theta and beta band (associated with conflict control and movement inhibition, respectively) were analysed across subthalamic nucleus subregions and hemispheres relative to the motor response (ipsilateral/contralateral). In the presence of action conflict, the dorsal subthalamic nucleus, connected to cortical motor regions, exhibited larger theta power relative to the ventral subthalamic nucleus subregion, which is linked to the limbic circuits (P < 0.05). This evidence supports independent subregion function in conflict control. However, both subregions had relatively increased beta power for conflict trials compared with non-conflict in the hemisphere ipsilateral to the motor response. The conflict-related beta modulation was not present in the contralateral hemisphere. This indicates the importance of the ipsilateral hemisphere in the inhibition of incorrect action impulses. Additionally, higher intertrial beta power in the ventral subregion correlated with reduced accuracy on conflict trials, which we propose, could serve as a biomarker for impaired task performance. The results of the study support the existence of a functional dissociation within subthalamic nucleus subregions, emphasizing the role of the dorsal subthalamic nucleus in modulating action conflict.
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Affiliation(s)
- Jessica L Bowersock
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Scott A Wylie
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Ahmad Alhourani
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Ajmal Zemmar
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Victoria Holiday
- Department of Neurology, University of Louisville Health, Louisville, KY 40202, USA
| | - Peter Hedera
- Department of Neurology, University of Louisville Health, Louisville, KY 40202, USA
| | - Travis Stewart
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Elizabeth Bridwell
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Isabelle Hattab
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Beatrice Ugiliweneza
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Joseph S Neimat
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Nelleke C van Wouwe
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
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Jurva A, Singh B, Qian H, Wang Z, Jacobs ML, Dhima K, Englot DJ, Roberson SW, Bick SK, Constantinidis C. Frontoparietal activity related to neuropsychological assessment of working memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.13.632797. [PMID: 39868084 PMCID: PMC11761696 DOI: 10.1101/2025.01.13.632797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
Executive functions, including working memory, are typically assessed clinically with neuropsychological instruments. In contrast, computerized tasks are used to test these cognitive functions in laboratory human and animal studies. Little is known of how neural activity captured by laboratory tasks relates to ability measured by clinical instruments and, by extension, clinical diagnoses of pathological conditions. We therefore sought to determine what aspects of neural activity elicited in laboratory tasks are predictive of performance in neuropsychological instruments. We recorded neural activity from intracranial electrodes implanted in human epilepsy patients as they performed laboratory working memory tasks. These patients had completed neuropsychological instruments preoperatively, including the Weschler Adult Intelligent Scale and the Wisconsin Card Sorting test. Our results revealed that increased high-gamma (70-150 Hz) power in the prefrontal and parietal cortex after presentation of visual stimuli to be remembered was indicative of lower performance in the neuropsychological tasks. On the other hand, we observed a positive correlation between high-frequency power amplitude in the delay period of the laboratory tasks and neuropsychological performance. Our results demonstrate how neural activity around task events relates to executive function and may be associated with clinical diagnosis of specific cognitive deficits.
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Zargari M, Hughes NC, Chen JW, Cole MW, Gupta R, Qian H, Summers J, Subramanian D, Li R, Dawant BM, Konrad PE, Ball TJ, Englot DJ, Dhima K, Bick SK. Electrode Location and Domain-Specific Cognitive Change Following Subthalamic Nucleus Deep Brain Stimulation for Parkinson's Disease. Neurosurgery 2024:00006123-990000000-01434. [PMID: 39513712 DOI: 10.1227/neu.0000000000003271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Accepted: 09/30/2024] [Indexed: 11/15/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease (PD) motor symptoms. DBS is also associated with postoperative cognitive change in some patients. Previous studies found associations between medial active electrode contacts and overall cognitive decline. Our current aim is to determine the relationship between active electrode contact location and domain-specific cognitive changes. METHODS A single-institution retrospective cohort study was conducted in patients with PD who underwent subthalamic nucleus (STN) DBS from August 05, 2010, to February 22, 2021, and received preoperative and postoperative neuropsychological testing. Standardized norm-referenced test z-scores were categorized into attention, executive function, language, verbal memory, and visuospatial domains. SD change scores were averaged to create domain-specific change scores. We identified anterior commissure/posterior commissure coordinates of active electrode contacts in atlas space. We evaluated differences in active electrode contact location between patients with a domain score decrease of at least 1 SD and less than 1 SD. We performed multiple variable linear regression controlling for age, sex, education, time from surgery to postoperative neuropsychological testing (follow-up duration), disease duration, preoperative unified Parkinson's disease rating scale off medication scores, and preoperative memory scores to determine the relationship between active electrode contact location and domain change. RESULTS A total of 83 patients (male: n = 60, 72.3%) were included with a mean age of 63.6 ± 8.3 years, median disease duration of 9.0 [6.0, 11.5] years, and median follow-up duration of 8.0 [7.0, 11.0] months. More superior active electrode contact location in the left STN (P = .002) and higher preoperative memory scores (P < .0001) were associated with worsening memory. Active electrode contact location was not associated with change in other domains. CONCLUSION In patients with PD who underwent STN DBS, we found an association between superior active electrode contacts in the left STN and verbal memory decline. Our study increases understanding of factors associated with cognitive change after DBS and may help inform postoperative programming.
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Affiliation(s)
- Michael Zargari
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt University, School of Medicine, Nashville, Tennessee, USA
| | - Natasha C Hughes
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt University, School of Medicine, Nashville, Tennessee, USA
| | - Jeffrey W Chen
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas, USA
| | - Matthew W Cole
- Vanderbilt University, School of Medicine, Nashville, Tennessee, USA
| | - Rishabh Gupta
- University of Minnesota - Twin Cities Medical School, Minneapolis, Minnesota, USA
| | - Helen Qian
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jessica Summers
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Deeptha Subramanian
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Rui Li
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Benoit M Dawant
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Peter E Konrad
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurosurgery, Rockefeller Neuroscience Institute, West Virginia University, Morgantown, West Virginia, USA
| | - Tyler J Ball
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Dario J Englot
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Kaltra Dhima
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sarah K Bick
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Psychiatry, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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Doss DJ, Shless JS, Bick SK, Makhoul GS, Negi AS, Bibro CE, Rashingkar R, Gummadavelli A, Chang C, Gallagher MJ, Naftel RP, Reddy SB, Williams Roberson S, Morgan VL, Johnson GW, Englot DJ. The interictal suppression hypothesis is the dominant differentiator of seizure onset zones in focal epilepsy. Brain 2024; 147:3009-3017. [PMID: 38874456 PMCID: PMC11370787 DOI: 10.1093/brain/awae189] [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: 10/20/2023] [Revised: 04/19/2024] [Accepted: 05/16/2024] [Indexed: 06/15/2024] Open
Abstract
Successful surgical treatment of drug-resistant epilepsy traditionally relies on the identification of seizure onset zones (SOZs). Connectome-based analyses of electrographic data from stereo electroencephalography (SEEG) may empower improved detection of SOZs. Specifically, connectome-based analyses based on the interictal suppression hypothesis posit that when the patient is not having a seizure, SOZs are inhibited by non-SOZs through high inward connectivity and low outward connectivity. However, it is not clear whether there are other motifs that can better identify potential SOZs. Thus, we sought to use unsupervised machine learning to identify network motifs that elucidate SOZs and investigate if there is another motif that outperforms the ISH. Resting-state SEEG data from 81 patients with drug-resistant epilepsy undergoing a pre-surgical evaluation at Vanderbilt University Medical Center were collected. Directed connectivity matrices were computed using the alpha band (8-13 Hz). Principal component analysis (PCA) was performed on each patient's connectivity matrix. Each patient's components were analysed qualitatively to identify common patterns across patients. A quantitative definition was then used to identify the component that most closely matched the observed pattern in each patient. A motif characteristic of the interictal suppression hypothesis (high-inward and low-outward connectivity) was present in all individuals and found to be the most robust motif for identification of SOZs in 64/81 (79%) patients. This principal component demonstrated significant differences in SOZs compared to non-SOZs. While other motifs for identifying SOZs were present in other patients, they differed for each patient, suggesting that seizure networks are patient specific, but the ISH is present in nearly all networks. We discovered that a potentially suppressive motif based on the interictal suppression hypothesis was present in all patients, and it was the most robust motif for SOZs in 79% of patients. Each patient had additional motifs that further characterized SOZs, but these motifs were not common across all patients. This work has the potential to augment clinical identification of SOZs to improve epilepsy treatment.
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Affiliation(s)
- Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
| | - Jared S Shless
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Sarah K Bick
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Ghassan S Makhoul
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
| | - Aarushi S Negi
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Camden E Bibro
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Rohan Rashingkar
- Department of Computer Science, Vanderbilt University Nashville, Nashville, TN 37235, USA
| | - Abhijeet Gummadavelli
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Catie Chang
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Computer Science, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Martin J Gallagher
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Robert P Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Shilpa B Reddy
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Shawniqua Williams Roberson
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Computer Science, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Radiology and Biomedical Imaging, Vanderbilt University Medical Center, Nashville, TN 37235, USA
| | - Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Department of Computer Science, Vanderbilt University Nashville, Nashville, TN 37235, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37235, USA
- Department of Radiology and Biomedical Imaging, Vanderbilt University Medical Center, Nashville, TN 37235, USA
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Doss DJ, Johnson GW, Makhoul GS, Rashingkar RV, Shless JS, Bibro CE, Paulo DL, Gummadavelli A, Ball TJ, Reddy SB, Naftel RP, Haas KF, Dawant BM, Constantinidis C, Roberson SW, Bick SK, Morgan VL, Englot DJ. Network signatures define consciousness state during focal seizures. Epilepsia 2024; 65:2686-2699. [PMID: 39056406 PMCID: PMC11534508 DOI: 10.1111/epi.18074] [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: 05/08/2024] [Revised: 07/12/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024]
Abstract
OBJECTIVE Epilepsy is a common neurological disorder affecting 1% of the global population. Loss of consciousness in focal impaired awareness seizures (FIASs) and focal-to-bilateral tonic-clonic seizures (FBTCSs) can be devastating, but the mechanisms are not well understood. Although ictal activity and interictal connectivity changes have been noted, the network states of focal aware seizures (FASs), FIASs, and FBTCSs have not been thoroughly evaluated with network measures ictally. METHODS We obtained electrographic data from 74 patients with stereoelectroencephalography (SEEG). Sliding window band power, functional connectivity, and segregation were computed on preictal, ictal, and postictal data. Five-minute epochs of wake, rapid eye movement sleep, and deep sleep were also extracted. Connectivity of subcortical arousal structures was analyzed in a cohort of patients with both SEEG and functional magnetic resonance imaging (fMRI). Given that custom neuromodulation of seizures is predicated on detection of seizure type, a convolutional neural network was used to classify seizure types. RESULTS We found that in the frontoparietal association cortex, an area associated with consciousness, both consciousness-impairing seizures (FIASs and FBTCSs) and deep sleep had increases in slow wave delta (1-4 Hz) band power. However, when network measures were employed, we found that only FIASs and deep sleep exhibited an increase in delta segregation and a decrease in gamma segregation. Furthermore, we found that only patients with FIASs had reduced subcortical-to-neocortical functional connectivity with fMRI versus controls. Finally, our deep learning network demonstrated an area under the curve of .75 for detecting consciousness-impairing seizures. SIGNIFICANCE This study provides novel insights into ictal network measures in FASs, FIASs, and FBTCSs. Importantly, although both FIASs and FBTCSs result in loss of consciousness, our results suggest that ictal network changes in FIASs uniquely resemble those that occur during deep sleep. Our results may inform novel neuromodulation strategies for preservation of consciousness in epilepsy.
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Affiliation(s)
- Derek J. Doss
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
| | - Graham W. Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
| | - Ghassan S. Makhoul
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
| | - Rohan V. Rashingkar
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jared S. Shless
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Camden E. Bibro
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Danika L. Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Abhijeet Gummadavelli
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Tyler J. Ball
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Shilpa B. Reddy
- Department of Pediatrics, Vanderbilt Children's Hospital, Nashville, Tennessee, USA
| | - Robert P. Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kevin F. Haas
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Benoit M. Dawant
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Christos Constantinidis
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, USA
- Department of Ophthalmology and Visual Sciences, Vanderbilt University, Nashville, Tennessee, USA
| | - Shawniqua Williams Roberson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sarah K. Bick
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Victoria L. Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Dario J. Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, USA
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Kusunose J, Rodriguez WJ, Luo H, Manuel TJ, Phipps MA, Yang PF, Grissom WA, Konrad PE, Chen LM, Dawant BM, Caskey CF. Design and Validation of a Patient-Specific Stereotactic Frame for Transcranial Ultrasound Therapy. IEEE TRANSACTIONS ON ULTRASONICS, FERROELECTRICS, AND FREQUENCY CONTROL 2024; 71:1030-1041. [PMID: 39024077 PMCID: PMC11465451 DOI: 10.1109/tuffc.2024.3420242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
Transcranial-focused ultrasound (tFUS) procedures such as neuromodulation and blood-brain barrier (BBB) opening require precise focus placement within the brain. MRI is currently the most reliable tool for focus localization but can be prohibitive for procedures requiring recurrent therapies. We designed, fabricated, and characterized a patient-specific, 3-D-printed, stereotactic frame for repeated tFUS therapy. The frame is compact, with minimal footprint, can be removed and re-secured between treatments while maintaining sub-mm accuracy, and will allow for precise and repeatable transcranial FUS treatment without the need for MR-guidance following the initial calibration scan. Focus localization and repeatability were assessed via MR-thermometry and MR-acoustic radiation force imaging (ARFI) on an ex vivo skull phantom and in vivo nonhuman primates (NHPs), respectively. Focal localization, registration, steering, and re-steering were accomplished during the initial MRI calibration scan session. Keeping steering coordinates fixed in subsequent therapy and imaging sessions, we found good agreement between steered foci and the intended target, with target registration error (TRE) of 1.2 ± 0.3 ( n = 4 , ex vivo) and 1.0 ± 0.5 ( n = 3 , in vivo) mm. Focus position (steered and non-steered) was consistent, with sub-mm variation in each dimension between studies. Our 3-D-printed, patient-specific stereotactic frame can reliably position and orient the ultrasound transducer for repeated targeting of brain regions using a single MR-based calibration. The compact frame allows for high-precision tFUS to be carried out outside the magnet and could help reduce the cost of tFUS treatments where repeated application of an ultrasound focus is required with high precision.
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Hughes NC, Qian H, Zargari M, Zhao Z, Singh B, Wang Z, Fulton JN, Johnson GW, Li R, Dawant BM, Englot DJ, Constantinidis C, Roberson SW, Bick SK. Reward Circuit Local Field Potential Modulations Precede Risk Taking. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.10.588629. [PMID: 38645237 PMCID: PMC11030333 DOI: 10.1101/2024.04.10.588629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Risk taking behavior is a symptom of multiple neuropsychiatric disorders and often lacks effective treatments. Reward circuitry regions including the amygdala, orbitofrontal cortex, insula, and anterior cingulate have been implicated in risk-taking by neuroimaging studies. Electrophysiological activity associated with risk taking in these regions is not well understood in humans. Further characterizing the neural signalling that underlies risk-taking may provide therapeutic insight into disorders associated with risk-taking. Eleven patients with pharmacoresistant epilepsy who underwent stereotactic electroencephalography with electrodes in the amygdala, orbitofrontal cortex, insula, and/or anterior cingulate participated. Patients participated in a gambling task where they wagered on a visible playing card being higher than a hidden card, betting $5 or $20 on this outcome, while local field potentials were recorded from implanted electrodes. We used cluster-based permutation testing to identify reward prediction error signals by comparing oscillatory power following unexpected and expected rewards. We also used cluster-based permutation testing to compare power preceding high and low bets in high-risk (<50% chance of winning) trials and two-way ANOVA with bet and risk level to identify signals associated with risky, risk averse, and optimized decisions. We used linear mixed effects models to evaluate the relationship between reward prediction error and risky decision signals across trials, and a linear regression model for associations between risky decision signal power and Barratt Impulsiveness Scale scores for each patient. Reward prediction error signals were identified in the amygdala (p=0.0066), anterior cingulate (p=0.0092), and orbitofrontal cortex (p=6.0E-4, p=4.0E-4). Risky decisions were predicted by increased oscillatory power in high-gamma frequency range during card presentation in the orbitofrontal cortex (p=0.0022), and by increased power following bet cue presentation across the theta-to-beta range in the orbitofrontal cortex ( p =0.0022), high-gamma in the anterior cingulate ( p =0.0004), and high-gamma in the insula ( p =0.0014). Risk averse decisions were predicted by decreased orbitofrontal cortex gamma power ( p =2.0E-4). Optimized decisions that maximized earnings were preceded by decreases within the theta to beta range in orbitofrontal cortex ( p =2.0E-4), broad frequencies in amygdala ( p =2.0E-4), and theta to low-gamma in insula ( p =4.0E-4). Insula risky decision power was associated with orbitofrontal cortex high-gamma reward prediction error signal ( p =0.0048) and with patient impulsivity ( p =0.00478). Our findings identify and help characterize reward circuitry activity predictive of risk-taking in humans. These findings may serve as potential biomarkers to inform the development of novel treatment strategies such as closed loop neuromodulation for disorders of risk taking.
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Willett A, Wylie SA, Bowersock JL, Dawant BM, Rodriguez W, Ugiliweneza B, Neimat JS, van Wouwe NC. Focused stimulation of dorsal versus ventral subthalamic nucleus enhances action-outcome learning in patients with Parkinson's disease. Brain Commun 2024; 6:fcae111. [PMID: 38646144 PMCID: PMC11032193 DOI: 10.1093/braincomms/fcae111] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 02/01/2024] [Accepted: 04/01/2024] [Indexed: 04/23/2024] Open
Abstract
Deep brain stimulation of the subthalamic nucleus is an effective treatment for the clinical motor symptoms of Parkinson's disease, but may alter the ability to learn contingencies between stimuli, actions and outcomes. We investigated how stimulation of the functional subregions in the subthalamic nucleus (motor and cognitive regions) modulates stimulus-action-outcome learning in Parkinson's disease patients. Twelve Parkinson's disease patients with deep brain stimulation of the subthalamic nucleus completed a probabilistic stimulus-action-outcome task while undergoing ventral and dorsal subthalamic nucleus stimulation (within subjects, order counterbalanced). The task orthogonalized action choice and outcome valence, which created four action-outcome learning conditions: action-reward, inhibit-reward, action-punishment avoidance and inhibit-punishment avoidance. We compared the effects of deep brain stimulation on learning rates across these conditions as well as on computed Pavlovian learning biases. Dorsal stimulation was associated with higher overall learning proficiency relative to ventral subthalamic nucleus stimulation. Compared to ventral stimulation, stimulating the dorsal subthalamic nucleus led to a particular advantage in learning to inhibit action to produce desired outcomes (gain reward or avoid punishment) as well as better learning proficiency across all conditions providing reward opportunities. The Pavlovian reward bias was reduced with dorsal relative to ventral subthalamic nucleus stimulation, which was reflected by improved inhibit-reward learning. Our results show that focused stimulation in the dorsal compared to the ventral subthalamic nucleus is relatively more favourable for learning action-outcome contingencies and reduces the Pavlovian bias that could lead to reward-driven behaviour. Considering the effects of deep brain stimulation of the subthalamic nucleus on learning and behaviour could be important when optimizing stimulation parameters to avoid side effects like impulsive reward-driven behaviour.
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Affiliation(s)
- Andrew Willett
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Scott A Wylie
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Jessica L Bowersock
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Benoit M Dawant
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - William Rodriguez
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN 37235, USA
| | - Beatrice Ugiliweneza
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Joseph S Neimat
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
| | - Nelleke C van Wouwe
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202, USA
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10
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Singh B, Wang Z, Madiah LM, Gatti SE, Fulton JN, Johnson GW, Li R, Dawant BM, Englot DJ, Bick SK, Roberson SW, Constantinidis C. Brain-wide human oscillatory local field potential activity during visual working memory. iScience 2024; 27:109130. [PMID: 38380249 PMCID: PMC10877957 DOI: 10.1016/j.isci.2024.109130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 01/10/2024] [Accepted: 02/01/2024] [Indexed: 02/22/2024] Open
Abstract
Oscillatory activity in the local field potential (LFP) is thought to be a marker of cognitive processes. To understand how it differentiates tasks and brain areas in humans, we recorded LFPs in 15 adults with intracranial depth electrodes, as they performed visual-spatial and shape working memory tasks. Stimulus appearance produced widespread, broad-band activation, including in occipital, parietal, temporal, insular, and prefrontal cortex, and the amygdala and hippocampus. Occipital cortex was characterized by most elevated power in the high-gamma (100-150 Hz) range during the visual stimulus presentation. The most consistent feature of the delay period was a systematic pattern of modulation in the beta frequency (16-40 Hz), which included a decrease in power of variable timing across areas, and rebound during the delay period. These results reveal the widespread nature of oscillatory activity across a broad brain network and region-specific signatures of oscillatory processes associated with visual working memory.
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Affiliation(s)
- Balbir Singh
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Zhengyang Wang
- Neuroscience Program, Vanderbilt University, Nashville, TN, USA
| | - Leen M. Madiah
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - S. Elizabeth Gatti
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Jenna N. Fulton
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Graham W. Johnson
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Rui Li
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Benoit M. Dawant
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Dario J. Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sarah K. Bick
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shawniqua Williams Roberson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christos Constantinidis
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Neuroscience Program, Vanderbilt University, Nashville, TN, USA
- Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
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11
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Paulo DL, Johnson GW, Doss DJ, Allen JH, González HFJ, Shults R, Li R, Ball TJ, Bick SK, Hassell TJ, D'Haese PF, Konrad PE, Dawant BM, Narasimhan S, Englot DJ. Intraoperative physiology augments atlas-based data in awake deep brain stimulation. J Neurol Neurosurg Psychiatry 2023; 95:86-96. [PMID: 37679029 PMCID: PMC11101241 DOI: 10.1136/jnnp-2023-331248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 07/25/2023] [Indexed: 09/09/2023]
Abstract
BACKGROUND Deep brain stimulation (DBS) is commonly performed with patients awake to perform intraoperative microelectrode recordings and/or macrostimulation testing to guide final electrode placement. Supplemental information from atlas-based databases derived from prior patient data and visualised as efficacy heat maps transformed and overlaid onto preoperative MRIs can be used to guide preoperative target planning and intraoperative final positioning. Our quantitative analysis of intraoperative testing and corresponding changes made to final electrode positioning aims to highlight the value of intraoperative neurophysiological testing paired with image-based data to optimise final electrode positioning in a large patient cohort. METHODS Data from 451 patients with movement disorders treated with 822 individual DBS leads at a single institution from 2011 to 2021 were included. Atlas-based data was used to guide surgical targeting. Intraoperative testing data and coordinate data were retrospectively obtained from a large patient database. Medical records were reviewed to obtain active contact usage and neurologist-defined outcomes at 1 year. RESULTS Microelectrode recording firing profiles differ per track, per target and inform the locations where macrostimulation testing is performed. Macrostimulation performance correlates with the final electrode track chosen. Centroids of atlas-based efficacy heat maps per target were close in proximity to and may predict active contact usage at 1 year. Overall, patient outcomes at 1 year were improved for patients with better macrostimulation response. CONCLUSIONS Atlas-based imaging data is beneficial for target planning and intraoperative guidance, and in conjunction with intraoperative neurophysiological testing during awake DBS can be used to individualize and optimise final electrode positioning, resulting in favourable outcomes.
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Affiliation(s)
- Danika L Paulo
- Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Graham W Johnson
- Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Derek J Doss
- Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Jackson H Allen
- Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Hernán F J González
- Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
- Vanderbilt University School of Medicine, Nashville, Tennessee, USA
- Neurosurgery, UCSD, La Jolla, California, USA
| | - Robert Shults
- Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Rui Li
- Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Tyler J Ball
- Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sarah K Bick
- Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Travis J Hassell
- Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Pierre-François D'Haese
- Neuroradiology, West Virginia University Rockefeller Neuroscience Institute, Morgantown, West Virginia, USA
| | - Peter E Konrad
- Neurosurgery, West Virginia University Rockefeller Neuroscience Institute, Morgantown, West Virginia, USA
| | - Benoit M Dawant
- Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Saramati Narasimhan
- Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Dario J Englot
- Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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12
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Cao Z, Guo M, Cao X, Liu T, Hu S, Xiao Y, Zhang M, Liu H. Progress in TLE treatment from 2003 to 2023: scientific measurement and visual analysis based on CiteSpace. Front Neurol 2023; 14:1223457. [PMID: 37854064 PMCID: PMC10580429 DOI: 10.3389/fneur.2023.1223457] [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: 05/16/2023] [Accepted: 08/30/2023] [Indexed: 10/20/2023] Open
Abstract
Objective Temporal lobe epilepsy (TLE) is the most common cause of drug-resistant epilepsy and can be treated surgically to control seizures. In this study, we analyzed the relevant research literature in the field of temporal lobe epilepsy (TLE) treatment to understand the background, hotspots, and trends in TLE treatment research. Methods We discussed the trend, frontier, and hotspot of scientific output in TLE treatment research in the world in the last 20 years by searching the core collection of the Web of Science database. Excel and CiteSpace software were used to analyze the basic data of the literature. Result We identified a total of 2,051 publications on TLE treatment from 75 countries between 2003 and 2023. We found that the publication rate was generally increasing. The United States was the most publishing country; among the research institutions on TLE treatment, the University of California system published the most relevant literature and collaborated the most with other institutions. The co-citation of literature, keyword co-occurrence, and its clustering analysis showed that the early studies focused on open surgical treatment, mainly by lobectomy. In recent years, the attention given to stereotactic, microsurgery, and other surgical techniques has gradually increased, and the burst analysis indicated that new research hotspots may appear in the future in the areas of improved surgical procedures and mechanism research.
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Affiliation(s)
- Zhan Cao
- Department of Neurology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Mingjie Guo
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Henan University, Kaifeng, China
| | - Xun Cao
- Medical College of Zhengzhou University, Zhengzhou, China
| | - Tiantian Liu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shaowen Hu
- Department of Urinary Surgery, Huaihe Hospital of Henan University, Kaifeng, China
| | - Yafei Xiao
- Department of Gastrointestinal Surgery, Huaihe Hospital of Henan University, Kaifeng, China
| | - Min Zhang
- Department of Neurology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Hengfang Liu
- Department of Neurology, The Fifth Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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13
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Singh B, Wang Z, Madiah LM, Gatti SE, Fulton JN, Johnson GW, Li R, Dawant BM, Englot DJ, Bick SK, Roberson SW, Constantinidis C. Brain-wide human oscillatory LFP activity during visual working memory. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.06.556554. [PMID: 37732263 PMCID: PMC10508766 DOI: 10.1101/2023.09.06.556554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Oscillatory activity is thought to be a marker of cognitive processes, although its role and distribution across the brain during working memory has been a matter of debate. To understand how oscillatory activity differentiates tasks and brain areas in humans, we recorded local field potentials (LFPs) in 12 adults as they performed visual-spatial and shape-matching memory tasks. Tasks were designed to engage working memory processes at a range of delay intervals between stimulus delivery and response initiation. LFPs were recorded using intracranial depth electrodes implanted to localize seizures for management of intractable epilepsy. Task-related LFP power analyses revealed an extensive network of cortical regions that were activated during the presentation of visual stimuli and during their maintenance in working memory, including occipital, parietal, temporal, insular, and prefrontal cortical areas, and subcortical structures including the amygdala and hippocampus. Across most brain areas, the appearance of a stimulus produced broadband power increase, while gamma power was evident during the delay interval of the working memory task. Notable differences between areas included that occipital cortex was characterized by elevated power in the high gamma (100-150 Hz) range during the 500 ms of visual stimulus presentation, which was less pronounced or absent in other areas. A decrease in power centered in beta frequency (16-40 Hz) was also observed after the stimulus presentation, whose magnitude differed across areas. These results reveal the interplay of oscillatory activity across a broad network, and region-specific signatures of oscillatory processes associated with visual working memory.
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Affiliation(s)
- Balbir Singh
- Department of Biomedical Engineering, Vanderbilt University
| | | | - Leen M Madiah
- Department of Biomedical Engineering, Vanderbilt University
| | | | - Jenna N Fulton
- Department of Neurology, Vanderbilt University Medical Center
| | - Graham W Johnson
- Department of Neurological Surgery, Vanderbilt University Medical Center
| | - Rui Li
- Department of Electrical and Computer Engineering, Vanderbilt University
| | - Benoit M Dawant
- Department of Electrical and Computer Engineering, Vanderbilt University
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University
- Department of Neurological Surgery, Vanderbilt University Medical Center
| | - Sarah K Bick
- Department of Biomedical Engineering, Vanderbilt University
- Department of Neurological Surgery, Vanderbilt University Medical Center
| | - Shawniqua Williams Roberson
- Department of Biomedical Engineering, Vanderbilt University
- Department of Neurology, Vanderbilt University Medical Center
| | - Christos Constantinidis
- Department of Biomedical Engineering, Vanderbilt University
- Neuroscience Program, Vanderbilt University
- Department of Ophthalmology and Visual Sciences, Vanderbilt University Medical Center
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14
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Doss DJ, Johnson GW, Narasimhan S, Shless JS, Jiang JW, González HFJ, Paulo DL, Lucas A, Davis KA, Chang C, Morgan VL, Constantinidis C, Dawant BM, Englot DJ. Deep Learning Segmentation of the Nucleus Basalis of Meynert on 3T MRI. AJNR Am J Neuroradiol 2023; 44:1020-1025. [PMID: 37562826 PMCID: PMC10494939 DOI: 10.3174/ajnr.a7950] [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: 11/11/2022] [Accepted: 06/25/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND AND PURPOSE The nucleus basalis of Meynert is a key subcortical structure that is important in arousal and cognition and has been explored as a deep brain stimulation target but is difficult to study due to its small size, variability among patients, and lack of contrast on 3T MR imaging. Thus, our goal was to establish and evaluate a deep learning network for automatic, accurate, and patient-specific segmentations with 3T MR imaging. MATERIALS AND METHODS Patient-specific segmentations can be produced manually; however, the nucleus basalis of Meynert is difficult to accurately segment on 3T MR imaging, with 7T being preferred. Thus, paired 3T and 7T MR imaging data sets of 21 healthy subjects were obtained. A test data set of 6 subjects was completely withheld. The nucleus was expertly segmented on 7T, providing accurate labels for the paired 3T MR imaging. An external data set of 14 patients with temporal lobe epilepsy was used to test the model on brains with neurologic disorders. A 3D-Unet convolutional neural network was constructed, and a 5-fold cross-validation was performed. RESULTS The novel segmentation model demonstrated significantly improved Dice coefficients over the standard probabilistic atlas for both healthy subjects (mean, 0.68 [SD, 0.10] versus 0.45 [SD, 0.11], P = .002, t test) and patients (0.64 [SD, 0.10] versus 0.37 [SD, 0.22], P < .001). Additionally, the model demonstrated significantly decreased centroid distance in patients (1.18 [SD, 0.43] mm, 3.09 [SD, 2.56] mm, P = .007). CONCLUSIONS We developed the first model, to our knowledge, for automatic and accurate patient-specific segmentation of the nucleus basalis of Meynert. This model may enable further study into the nucleus, impacting new treatments such as deep brain stimulation.
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Affiliation(s)
- D J Doss
- From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee
| | - G W Johnson
- From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee
| | - S Narasimhan
- From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee
- Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee
| | - J S Shless
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee
| | - J W Jiang
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee
| | - H F J González
- From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee
| | - D L Paulo
- Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee
| | - A Lucas
- Department of Bioengineering (A.L.), University of Pennsylvania, Philadelphia, Pennsylvania
| | - K A Davis
- Department of Neuroscience (K.A.D.), University of Pennsylvania, Philadelphia, Pennsylvania
- Center for Neuroengineering and Therapeutics (K.A.D.), University of Pennsylvania, Philadelphia, Pennsylvania
- Neurology (K.A.D.), University of Pennsylvania, Philadelphia, Pennsylvania
| | - C Chang
- From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee
- Department of Electrical and Computer Engineering (C. Chang, B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Department of Computer Science (C. Chang), Vanderbilt University, Nashville, Tennessee
| | - V L Morgan
- From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee
- Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Neurology (V.L.M.), Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Radiological Sciences (V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee
| | - C Constantinidis
- From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee
- Department of Ophthalmology and Visual Sciences (C. Constantinidis), Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Neuroscience (C. Constantinidis), Vanderbilt University, Nashville, Tennessee
| | - B M Dawant
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee
- Department of Electrical and Computer Engineering (C. Chang, B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
| | - D J Englot
- From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee
- Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee
- Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Electrical and Computer Engineering (C. Chang, B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee
- Department of Radiological Sciences (V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee
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15
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Johnson GW, Doss DJ, Morgan VL, Paulo DL, Cai LY, Shless JS, Negi AS, Gummadavelli A, Kang H, Reddy SB, Naftel RP, Bick SK, Williams Roberson S, Dawant BM, Wallace MT, Englot DJ. The Interictal Suppression Hypothesis in focal epilepsy: network-level supporting evidence. Brain 2023; 146:2828-2845. [PMID: 36722219 PMCID: PMC10316780 DOI: 10.1093/brain/awad016] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 12/24/2022] [Accepted: 01/08/2023] [Indexed: 02/02/2023] Open
Abstract
Why are people with focal epilepsy not continuously having seizures? Previous neuronal signalling work has implicated gamma-aminobutyric acid balance as integral to seizure generation and termination, but is a high-level distributed brain network involved in suppressing seizures? Recent intracranial electrographic evidence has suggested that seizure-onset zones have increased inward connectivity that could be associated with interictal suppression of seizure activity. Accordingly, we hypothesize that seizure-onset zones are actively suppressed by the rest of the brain network during interictal states. Full testing of this hypothesis would require collaboration across multiple domains of neuroscience. We focused on partially testing this hypothesis at the electrographic network level within 81 individuals with drug-resistant focal epilepsy undergoing presurgical evaluation. We used intracranial electrographic resting-state and neurostimulation recordings to evaluate the network connectivity of seizure onset, early propagation and non-involved zones. We then used diffusion imaging to acquire estimates of white-matter connectivity to evaluate structure-function coupling effects on connectivity findings. Finally, we generated a resting-state classification model to assist clinicians in detecting seizure-onset and propagation zones without the need for multiple ictal recordings. Our findings indicate that seizure onset and early propagation zones demonstrate markedly increased inwards connectivity and decreased outwards connectivity using both resting-state (one-way ANOVA, P-value = 3.13 × 10-13) and neurostimulation analyses to evaluate evoked responses (one-way ANOVA, P-value = 2.5 × 10-3). When controlling for the distance between regions, the difference between inwards and outwards connectivity remained stable up to 80 mm between brain connections (two-way repeated measures ANOVA, group effect P-value of 2.6 × 10-12). Structure-function coupling analyses revealed that seizure-onset zones exhibit abnormally enhanced coupling (hypercoupling) of surrounding regions compared to presumably healthy tissue (two-way repeated measures ANOVA, interaction effect P-value of 9.76 × 10-21). Using these observations, our support vector classification models achieved a maximum held-out testing set accuracy of 92.0 ± 2.2% to classify early propagation and seizure-onset zones. These results suggest that seizure-onset zones are actively segregated and suppressed by a widespread brain network. Furthermore, this electrographically observed functional suppression is disproportionate to any observed structural connectivity alterations of the seizure-onset zones. These findings have implications for the identification of seizure-onset zones using only brief electrographic recordings to reduce patient morbidity and augment the presurgical evaluation of drug-resistant epilepsy. Further testing of the interictal suppression hypothesis can provide insight into potential new resective, ablative and neuromodulation approaches to improve surgical success rates in those suffering from drug-resistant focal epilepsy.
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Affiliation(s)
- Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Danika L Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Jared S Shless
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Aarushi S Negi
- Department of Neuroscience, Vanderbilt University, Nashville, TN 37232, USA
| | - Abhijeet Gummadavelli
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA
| | - Shilpa B Reddy
- Department of Pediatrics, Vanderbilt Children’s Hospital, Nashville, TN 37232, USA
| | - Robert P Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Sarah K Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Benoit M Dawant
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Mark T Wallace
- Department of Hearing and Speech Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Psychology, Vanderbilt University, Nashville, TN 37232, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
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16
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Johnson GW, Cai LY, Doss DJ, Jiang JW, Negi AS, Narasimhan S, Paulo DL, González HFJ, Roberson SW, Bick SK, Chang CE, Morgan VL, Wallace MT, Englot DJ. Localizing seizure onset zones in surgical epilepsy with neurostimulation deep learning. J Neurosurg 2023; 138:1002-1007. [PMID: 36152321 PMCID: PMC10619627 DOI: 10.3171/2022.8.jns221321] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 08/04/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVE In drug-resistant temporal lobe epilepsy, automated tools for seizure onset zone (SOZ) localization that use brief interictal recordings could supplement presurgical evaluations and improve care. Thus, the authors sought to localize SOZs by training a multichannel convolutional neural network on stereoelectroencephalography (SEEG) cortico-cortical evoked potentials. METHODS The authors performed single-pulse electrical stimulation in 10 drug-resistant temporal lobe epilepsy patients implanted with SEEG. Using 500,000 unique poststimulation SEEG epochs, the authors trained a multichannel 1-dimensional convolutional neural network to determine whether an SOZ had been stimulated. RESULTS SOZs were classified with mean sensitivity of 78.1% and specificity of 74.6% according to leave-one-patient-out testing. To achieve maximum accuracy, the model required a 0- to 350-msec poststimulation time period. Post hoc analysis revealed that the model accurately classified unilateral versus bilateral mesial temporal lobe seizure onset, as well as neocortical SOZs. CONCLUSIONS This was the first demonstration, to the authors' knowledge, that a deep learning framework can be used to accurately classify SOZs with single-pulse electrical stimulation-evoked responses. These findings suggest that accurate classification of SOZs relies on a complex temporal evolution of evoked responses within 350 msec of stimulation. Validation in a larger data set could provide a practical clinical tool for the presurgical evaluation of drug-resistant epilepsy.
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Affiliation(s)
- Graham W. Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
| | - Leon Y. Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
| | - Derek J. Doss
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
| | - Jasmine W. Jiang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Aarushi S. Negi
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Saramati Narasimhan
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Danika L. Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Hernán F. J. González
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
| | - Shawniqua Williams Roberson
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sarah K. Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Catie E. Chang
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville
| | - Victoria L. Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Mark T. Wallace
- Department of Hearing & Speech Sciences, Vanderbilt University, Nashville
- Department of Psychology, Vanderbilt University, Nashville
- Departments of Psychiatry and Behavioral Sciences, Vanderbilt University, Nashville
- Department of Pharmacology, Vanderbilt University, Nashville
| | - Dario J. Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
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17
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Stuhlreyer J, Roder C, Krug F, Zöllner C, Flor H, Klinger R. A digital application and augmented physician rounds reduce postoperative pain and opioid consumption after primary total knee replacement (TKR): a randomized clinical trial. BMC Med 2022; 20:469. [PMID: 36464680 PMCID: PMC9721029 DOI: 10.1186/s12916-022-02638-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 10/03/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Severe postoperative pain not only is a considerable burden for patients but also leads to overprescription of opioids, resulting in considerable health concerns. The remarkable development of new technologies in the health care system provides novel treatment opportunities in this area and could exploit the additional placebo effect, provide added value for patients, and at the same time support hospital staff. We aimed to test the pain- and opioid intake-reducing effects of enhanced postoperative pain management by boosting pain medication by using a technical application and/or augmented physician rounds. METHODS In a four-arm, randomized clinical trial, 96 patients (24 patients per group) scheduled for a total knee replacement (TKR) were randomized into four groups for four postoperative days: an "application" group (APP) with information via an iPad-based application; a "doctor" group (DOC) with augmented physician rounds; a combination group (APP+DOC), which received both interventions; and a "treatment as usual" group (TAU) as a baseline with no additional intervention besides the standard care which consists of standardized medication, regular physician rounds, and physiotherapy. Postoperative pain and opioid requirements pre- and postoperatively until hospital discharge were recorded. RESULTS The difference between post- and preoperative pain was significantly different between the groups (P=.02, partial η2=.10). APP+DOC experienced greater postoperative pain relief than DOC (mean: 2.3 vs. 0.7, 95% CI: 0.08-3.09; P=.04) and TAU (mean 2.3 vs. 0.1; 95% CI: 0.69-3.71; P=.005), respectively, the difference compared to APP (mean 2.3 vs. 1.7; 95% CI -1.98-1.76) was not significant. Opioid consumption differed significantly between groups (P=.01, partial η2=.12). APP+DOC (72.9 mg) and DOC (75.4 mg) consumed less oxycodone than APP (83.3 mg) and TAU (87.9 mg; 95% CI: 2.9-22.1; P=.003). APP+DOC consumed significantly less oxycodone than DOC (d=0.2-0.4). There were no significant group differences in NSAID and Morphine sulfate consumption. Patients in APP+DOC were more satisfied with their treatment than patients in TAU (P=.03, partial η2=.09). CONCLUSIONS The combination of an innovative digital app, which implements open drug administration and augmented physician rounds that support the doctor-patient relationship can significantly improve postoperative pain management. TRIAL REGISTRATION The protocol was approved by the local ethics committee of the ethical commission of the German Psychological Society (Deutsche Gesellschaft für Psychologie; DGPs). The study was registered at DRKS.de (identifier: DRKS00009554).
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Affiliation(s)
- Julia Stuhlreyer
- Department of Anesthesiology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Christian Roder
- Department of Orthopedics and Trauma Surgery, Schön Clinic Hamburg Eilbek, Hamburg, Germany
| | - Florian Krug
- Department of Orthopedics and Trauma Surgery, Schön Clinic Hamburg Eilbek, Hamburg, Germany
| | - Christian Zöllner
- Department of Anesthesiology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Regine Klinger
- Department of Anesthesiology, University Medical Centre Hamburg-Eppendorf, Hamburg, Germany.
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18
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Dietz N, Alhourani A, Wylie SA, McDonnell JL, Phibbs FT, Dawant BM, Rodriguez WJ, Bradley EB, Neimat JS, van Wouwe NC. Effects of deep brain stimulation target on the activation and suppression of action impulses. Clin Neurophysiol 2022; 144:50-58. [PMID: 36242948 PMCID: PMC11075516 DOI: 10.1016/j.clinph.2022.09.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/21/2022] [Accepted: 09/24/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE Deep brain stimulation (DBS) is an effective treatment to improve motor symptoms in Parkinson's disease (PD). The Globus Pallidus (GPi) and the Subthalamic Nucleus (STN) are the most targeted brain regions for stimulation and produce similar improvements in PD motor symptoms. However, our understanding of stimulation effects across targets on inhibitory action control processes is limited. We compared the effects of STN (n = 20) and GPi (n = 13) DBS on inhibitory control in PD patients. METHODS We recruited PD patients undergoing DBS at the Vanderbilt Movement Disorders Clinic and measured their performance on an inhibitory action control task (Simon task) before surgery (optimally treated medication state) and after surgery in their optimally treated state (medication plus their DBS device turned on). RESULTS DBS to both STN and GPi targets induced an increase in fast impulsive errors while simultaneously producing more proficient reactive suppression of interference from action impulses. CONCLUSIONS Stimulation in GPi produced similar effects as STN DBS, indicating that stimulation to either target increases the initial susceptibility to act on strong action impulses while concomitantly improving the ability to suppress ongoing interference from activated impulses. SIGNIFICANCE Action impulse control processes are similarly impacted by stimulating dissociable nodes in frontal-basal ganglia circuitry.
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Affiliation(s)
- Nicholas Dietz
- Department of Neurosurgery, University of Louisville, 220 Abraham Flexner Way, Louisville, KY 40202, USA
| | - Ahmad Alhourani
- Department of Neurosurgery, University of Louisville, 220 Abraham Flexner Way, Louisville, KY 40202, USA
| | - Scott A Wylie
- Department of Neurosurgery, University of Louisville, 220 Abraham Flexner Way, Louisville, KY 40202, USA
| | - Jessica L McDonnell
- Department of Neurosurgery, University of Louisville, 220 Abraham Flexner Way, Louisville, KY 40202, USA
| | - Fenna T Phibbs
- Department of Neurology, Vanderbilt University Medical Center, 1301 Medical Center Drive, Suite 3930, Nashville, TN 37232, USA
| | - Benoit M Dawant
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - William J Rodriguez
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Elise B Bradley
- Department of Neurology, Vanderbilt University Medical Center, 1301 Medical Center Drive, Suite 3930, Nashville, TN 37232, USA
| | - Joseph S Neimat
- Department of Neurosurgery, University of Louisville, 220 Abraham Flexner Way, Louisville, KY 40202, USA
| | - Nelleke C van Wouwe
- Department of Neurosurgery, University of Louisville, 220 Abraham Flexner Way, Louisville, KY 40202, USA; Department of Neurology, Vanderbilt University Medical Center, 1301 Medical Center Drive, Suite 3930, Nashville, TN 37232, USA.
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19
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Cometa A, Falasconi A, Biasizzo M, Carpaneto J, Horn A, Mazzoni A, Micera S. Clinical neuroscience and neurotechnology: An amazing symbiosis. iScience 2022; 25:105124. [PMID: 36193050 PMCID: PMC9526189 DOI: 10.1016/j.isci.2022.105124] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
In the last decades, clinical neuroscience found a novel ally in neurotechnologies, devices able to record and stimulate electrical activity in the nervous system. These technologies improved the ability to diagnose and treat neural disorders. Neurotechnologies are concurrently enabling a deeper understanding of healthy and pathological dynamics of the nervous system through stimulation and recordings during brain implants. On the other hand, clinical neurosciences are not only driving neuroengineering toward the most relevant clinical issues, but are also shaping the neurotechnologies thanks to clinical advancements. For instance, understanding the etiology of a disease informs the location of a therapeutic stimulation, but also the way stimulation patterns should be designed to be more effective/naturalistic. Here, we describe cases of fruitful integration such as Deep Brain Stimulation and cortical interfaces to highlight how this symbiosis between clinical neuroscience and neurotechnology is closer to a novel integrated framework than to a simple interdisciplinary interaction.
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Affiliation(s)
- Andrea Cometa
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
| | - Antonio Falasconi
- Friedrich Miescher Institute for Biomedical Research, 4058 Basel, Switzerland
- Biozentrum, University of Basel, 4056 Basel, Switzerland
| | - Marco Biasizzo
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
| | - Jacopo Carpaneto
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
| | - Andreas Horn
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- MGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Department of Neurology, 10117 Berlin, Germany
| | - Alberto Mazzoni
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
| | - Silvestro Micera
- The Biorobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56127 Pisa, Italy
- Translational Neural Engineering Lab, School of Engineering, École Polytechnique Fèdèrale de Lausanne, 1015 Lausanne, Switzerland
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20
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Cai B, Xiong C, Sun Z, Liang P, Wang K, Guo Y, Niu C, Song B, Cheng E, Luo X. Accurate preoperative path planning with coarse-to-refine segmentation for image guided deep brain stimulation. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2022.103867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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21
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Muller J, Alizadeh M, Matias CM, Thalheimer S, Romo V, Martello J, Liang TW, Mohamed FB, Wu C. Use of probabilistic tractography to provide reliable distinction of the motor and sensory thalamus for prospective targeting during asleep deep brain stimulation. J Neurosurg 2022; 136:1371-1380. [PMID: 34624856 DOI: 10.3171/2021.5.jns21552] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 05/11/2021] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Accurate electrode placement is key to effective deep brain stimulation (DBS). The ventral intermediate nucleus (VIM) of the thalamus is an established surgical target for the treatment of essential tremor (ET). Retrospective tractography-based analysis of electrode placement has associated successful outcomes with modulation of motor input to VIM, but no study has yet evaluated the feasibility and efficacy of prospective presurgical tractography-based targeting alone. Therefore, the authors sought to demonstrate the safety and efficacy of probabilistic tractography-based VIM targeting in ET patients and to perform a systematic comparison of probabilistic and deterministic tractography. METHODS Fourteen patients with ET underwent preoperative diffusion imaging. Probabilistic tractography was applied for preoperative targeting, and deterministic tractography was performed as a comparison between methods. Tractography was performed using the motor and sensory areas as initiation seeds, the ipsilateral thalamus as an inclusion mask, and the contralateral dentate nucleus as a termination mask. Tract-density maps consisted of voxels with 10% or less of the maximum intensity and were superimposed onto anatomical images for presurgical planning. Target planning was based on probabilistic tract-density images and indirect target coordinates. Patients underwent robotic image-guided, image-verified implantation of directional DBS systems. Postoperative tremor scores with and without DBS were recorded. The center of gravity and Dice similarity coefficients were calculated and compared between tracking methods. RESULTS Prospective probabilistic targeting of VIM was successful in all 14 patients. All patients experienced significant tremor reduction. Formal postoperative tremor scores were available for 9 patients, who demonstrated a mean 68.0% tremor reduction. Large differences between tracking methods were observed across patients. Probabilistic tractography-identified VIM fibers were more anterior, lateral, and superior than deterministic tractography-identified fibers, whereas probabilistic tractography-identified ventralis caudalis fibers were more posterior, lateral, and superior than deterministic tractography-identified fibers. Deterministic methods were unable to clearly distinguish between motor and sensory fibers in the majority of patients, but probabilistic methods produced distinct separation. CONCLUSIONS Probabilistic tractography-based VIM targeting is safe and effective for the treatment of ET. Probabilistic tractography is more precise than deterministic tractography for the delineation of VIM and the ventralis caudalis nucleus of the thalamus. Deterministic algorithms tended to underestimate separation between motor and sensory fibers, which may have been due to its limitations with crossing fibers. Larger studies across multiple centers are necessary to further validate this method.
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Affiliation(s)
- Jennifer Muller
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Mahdi Alizadeh
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Caio M Matias
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Sara Thalheimer
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Victor Romo
- 3Department of Anesthesia, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Justin Martello
- 4Department of Neurology, Christiana Care Health System, Newark, Delaware; and
| | - Tsao-Wei Liang
- 5Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Feroze B Mohamed
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Chengyuan Wu
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
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22
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Andree A, Li N, Butenko K, Kober M, Chen JZ, Higuchi T, Fauser M, Storch A, Ip CW, Kühn AA, Horn A, van Rienen U. Deep brain stimulation electrode modeling in rats. Exp Neurol 2022; 350:113978. [PMID: 35026227 DOI: 10.1016/j.expneurol.2022.113978] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 11/13/2021] [Accepted: 01/06/2022] [Indexed: 11/26/2022]
Abstract
Deep Brain Stimulation (DBS) is an efficacious treatment option for an increasing range of brain disorders. To enhance our knowledge about the mechanisms of action of DBS and to probe novel targets, basic research in animal models with DBS is an essential research base. Beyond nonhuman primate, pig, and mouse models, the rat is a widely used animal model for probing DBS effects in basic research. Reconstructing DBS electrode placement after surgery is crucial to associate observed effects with modulating a specific target structure. Post-mortem histology is a commonly used method for reconstructing the electrode location. In humans, however, neuroimaging-based electrode localizations have become established. For this reason, we adapt the open-source software pipeline Lead-DBS for DBS electrode localizations from humans to the rat model. We validate our localization results by inter-rater concordance and a comparison with the conventional histological method. Finally, using the open-source software pipeline OSS-DBS, we demonstrate the subject-specific simulation of the VTA and the activation of axon models aligned to pathways representing neuronal fibers, also known as the pathway activation model. Both activation models yield a characterization of the impact of DBS on the target area. Our results suggest that the proposed neuroimaging-based method can precisely localize DBS electrode placements that are essentially rater-independent and yield results comparable to the histological gold standard. The advantages of neuroimaging-based electrode localizations are the possibility of acquiring them in vivo and combining electrode reconstructions with advanced imaging metrics, such as those obtained from diffusion or functional magnetic resonance imaging (MRI). This paper introduces a freely available open-source pipeline for DBS electrode reconstructions in rats. The presented initial validation results are promising.
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Affiliation(s)
- Andrea Andree
- Institute of General Electrical Engineering, University of Rostock, Albert-Einstein-Straße 2, 18059 Rostock, Germany.
| | - Ningfei Li
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Movement Disorders and Neuromodulation Unit, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany.
| | - Konstantin Butenko
- Institute of General Electrical Engineering, University of Rostock, Albert-Einstein-Straße 2, 18059 Rostock, Germany; Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Movement Disorders and Neuromodulation Unit, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany.
| | - Maria Kober
- Department of Neurology, University of Rostock, Gehlsheimer Straße 20, 18147 Rostock, Germany.
| | - Jia Zhi Chen
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080 Würzburg, Germany.
| | - Takahiro Higuchi
- Department of Nuclear Medicine and Comprehensive Heart Failure Center, University Hospital of Würzburg, Oberdürrbacher Straße 6, 97080 Würzburg, Germany.
| | - Mareike Fauser
- Department of Neurology, University of Rostock, Gehlsheimer Straße 20, 18147 Rostock, Germany.
| | - Alexander Storch
- Department of Neurology, University of Rostock, Gehlsheimer Straße 20, 18147 Rostock, Germany; German Centre for Neurodegenerative Diseases (DZNE) Rostock/Greifswald, Gehlsheimer Straße 20, 18147 Rostock, Germany; Department Ageing of Individuals and Society, University of Rostock, Gehlsheimer Straße 20, 18147 Rostock, Germany.
| | - Chi Wang Ip
- Department of Neurology, University Hospital of Würzburg, Josef-Schneider-Straße 11, 97080 Würzburg, Germany.
| | - Andrea A Kühn
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Movement Disorders and Neuromodulation Unit, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany.
| | - Andreas Horn
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Movement Disorders and Neuromodulation Unit, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; Center for Brain Circuit Therapeutics, Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, United States; MAMGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
| | - Ursula van Rienen
- Institute of General Electrical Engineering, University of Rostock, Albert-Einstein-Straße 2, 18059 Rostock, Germany; Department Ageing of Individuals and Society, University of Rostock, Gehlsheimer Straße 20, 18147 Rostock, Germany; Department Life, Light & Matter, University of Rostock, Albert-Einstein-Straße 25, 18059 Rostock, Germany.
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Adair DSP, Gomes KS, Kiss ZHT, Gobbi DG, Starreveld YP. Tactics: an open-source platform for planning, simulating and validating stereotactic surgery. Comput Assist Surg (Abingdon) 2021; 25:1-14. [PMID: 32401082 DOI: 10.1080/24699322.2020.1760354] [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] [Indexed: 10/24/2022] Open
Abstract
Frame-based stereotaxy is widely used for planning and implanting deep-brain electrodes. In 2013, as part of a clinical study on deep-brain stimulation for treatment-resistant depression, our group identified a need for software to simulate and plan stereotactic procedures. Shortcomings in extant commercial systems encouraged us to develop Tactics. Tactics is purpose-designed for frame-based stereotactic placement of electrodes. The workflow is far simpler than commercial systems. By simulating specific electrode placement, immediate in-context view of each electrode contact, and the cortical entry site are available within seconds. Post implantation, electrode placement is verified by linearly registering post-operative images. Tactics has been particularly helpful for invasive electroencephalography electrodes where as many as 20 electrodes are planned and placed within minutes. Currently, no commercial system has a workflow supporting the efficient placement of this many electrodes. Tactics includes a novel implementation of automated frame localization and a user-extensible mechanism for importing electrode specifications for visualization of individual electrode contacts. The system was systematically validated, through comparison against gold-standard techniques and quantitative analysis of targeting accuracy using a purpose-built imaging phantom mountable by a stereotactic frame. Internal to our research group, Tactics has been used to plan over 300 depth-electrode targets and trajectories in over 50 surgical cases, and to plan dozens of stereotactic biopsies. Source code and pre-built binaries for Tactics are public and open-source, enabling use and contribution by the extended community.
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Affiliation(s)
- David S P Adair
- Department of Radiology and Calgary Image Processing and Analysis Centre, University of Calgary, Calgary, Canada
| | - Keith S Gomes
- Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Zelma H T Kiss
- Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - David G Gobbi
- Department of Radiology and Calgary Image Processing and Analysis Centre, University of Calgary, Calgary, Canada
| | - Yves P Starreveld
- Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
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Eichberg DG, Menaker SA, Jermakowicz WJ, Shah AH, Luther EM, Jamshidi AM, Semonche AM, Di L, Komotar RJ, Ivan ME. Multiple Iterations of Magnetic Resonance-Guided Laser Interstitial Thermal Ablation of Brain Metastases: Single Surgeon's Experience and Review of the Literature. Oper Neurosurg (Hagerstown) 2021; 19:195-204. [PMID: 31828344 DOI: 10.1093/ons/opz375] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 09/29/2019] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Prior treatment with magnetic resonance-guided, laser-induced thermal therapy (LITT) is widely assumed not to be a contraindication for further treatment of brain lesions, including further iterations of LITT. However, the safety and efficacy of repeat LITT treatments have never been formally investigated. OBJECTIVE To evaluate treatment with multiple iterations of LITT. METHODS All patients treated with LITT at least twice at our institution were included in the study. Outcomes and neurological examinations from before and after surgery were retrospectively examined from clinic notes. Perilesonal edema was determined at various timepoints using volumetric data derived from manual tracings of fluid-attenuated inversion recovery (FLAIR) enhancement on magnetic resonance imaging (MRI). Finally, a literature review of prior cases of repeat LITT was performed. RESULTS A total of 9 patients underwent 18 treatments with LITT; all but 1 of whom were treated for metastatic brain lesions. One patient had a transient cerebrospinal fluid leak, whereas a second patient had a superficial wound infection, both of which resolved with standard medical care. The remaining 7 patients tolerated all LITT procedures without complication. Analysis of perilesional edema volume demonstrated a correlation with the amount of energy delivered during LITT. Literature review found 5 published papers describing 9 patients who underwent LITT more than once, the majority of whom tolerated repeat LITT well. CONCLUSION LITT is a safe and promising treatment modality and may be used multiple times without issue. There appears to be an association between the amount of energy delivered during a LITT session and the degree of postoperative perilesional edema.
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Affiliation(s)
- Daniel G Eichberg
- Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, Florida
| | - Simon A Menaker
- Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, Florida
| | - Walter J Jermakowicz
- Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, Florida
| | - Ashish H Shah
- Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, Florida
| | - Evan M Luther
- Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, Florida
| | - Aria M Jamshidi
- Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, Florida
| | - Alexa M Semonche
- Department of Neurological Surgery, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey
| | - Long Di
- Morsani College of Medicine, University of South Florida, Tampa, Florida
| | - Ricardo J Komotar
- Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, Florida
| | - Michael E Ivan
- Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, Florida
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Higueras-Esteban A, Delgado-Martínez I, Serrano L, Principe A, Pérez Enriquez C, González Ballester MÁ, Rocamora R, Conesa G, Serra L. SYLVIUS: A multimodal and multidisciplinary platform for epilepsy surgery. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 203:106042. [PMID: 33743489 DOI: 10.1016/j.cmpb.2021.106042] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 03/03/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND AND OBJECTIVE We present SYLVIUS, a software platform intended to facilitate and improve the complex workflow required to diagnose and surgically treat drug-resistant epilepsies. In complex epilepsies, additional invasive information from exploration with stereoencephalography (SEEG) with deep electrodes may be needed, for which the input from different diagnostic methods and clinicians from several specialties is required to ensure diagnostic efficacy and surgical safety. We aim to provide a software platform with optimal data flow among the different stages of epilepsy surgery to provide smooth and integrated decision making. METHODS The SYLVIUS platform provides a clinical workflow designed to ensure seamless and safe patient data sharing across specialities. It integrates tools for stereo visualization, data registration, transfer of electrode plans referred to distinct datasets, automated postoperative contact segmentation, and novel DWI tractography analysis. Nineteen cases were retrospectively evaluated to track modifications from an initial plan to obtain a final surgical plan, using SYLVIUS. RESULTS The software was used to modify trajectories in all 19 consulted cases, which were then imported into the robotic system for the surgical intervention. When available, SYLVIUS provided extra multimodal information, which resulted in a greater number of trajectory modifications. CONCLUSIONS The architecture presented in this paper streamlines epilepsy surgery allowing clinicians to have a digital clinical tool that allows recording of the different stages of the procedure, in a common multimodal 2D/3D setting for participation of different clinicians in defining and validating surgical plans for SEEG cases.
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Affiliation(s)
- Alfredo Higueras-Esteban
- Galgo Medical SL, Neurosurgery Dept, Barcelona, Spain; Universitat Pompeu Fabra, BCN Medtech, Dept. of Information and Communication Technologies, Barcelona, Spain.
| | | | - Laura Serrano
- IMIM-Hospital del Mar, Neurosurgery, Barcelona, Spain
| | | | | | - Miguel Ángel González Ballester
- Universitat Pompeu Fabra, BCN Medtech, Dept. of Information and Communication Technologies, Barcelona, Spain; ICREA, Barcelona, Spain
| | | | | | - Luis Serra
- Galgo Medical SL, Neurosurgery Dept, Barcelona, Spain
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John KD, Wylie SA, Dawant BM, Rodriguez WJ, Phibbs FT, Bradley EB, Neimat JS, van Wouwe NC. Deep brain stimulation effects on verbal fluency dissociated by target and active contact location. Ann Clin Transl Neurol 2021; 8:613-622. [PMID: 33596331 PMCID: PMC7951101 DOI: 10.1002/acn3.51304] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Revised: 12/17/2020] [Accepted: 12/23/2020] [Indexed: 11/24/2022] Open
Abstract
OBJECTIVE Deep brain stimulation (DBS) improves motor symptoms in Parkinson's disease (PD), but it can also disrupt verbal fluency with significant costs to quality of life. The current study investigated how variability of bilateral active electrode coordinates along the superior/inferior, anterior/posterior, and lateral/medial axes in the subthalamic nucleus (STN) or the globus pallidus interna (GPi) contribute to changes in verbal fluency. We predicted that electrode location in the left hemisphere would be linked to changes in fluency, especially in the STN. METHODS Forty PD participants treated with bilateral DBS targeting STN (n = 23) or GPi (n = 17) completed verbal fluency testing in their optimally treated state before and after DBS therapy. Normalized atlas coordinates from left and right active electrode positions along superior/inferior, anterior/posterior, and lateral/medial axes were used to predict changes in fluency postoperatively, separately for patients with STN and GPi targets. RESULTS Consistent with prior studies, fluency significantly declined pre- to postsurgery (in both DBS targets). In STN-DBS patients, electrode position along the inferior to superior axis in the left STN was a significant predictor of fluency changes; relatively more superior left active electrode was associated with the largest fluency declines in STN. Electrode coordinates in right STN or GPi (left or right) did not predict fluency changes. INTERPRETATION We discuss these findings in light of putative mechanisms and potential clinical impact.
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Affiliation(s)
- Kevin D. John
- Department of Neurological SurgeryUniversity of LouisvilleLouisvilleKYUSA
| | - Scott A. Wylie
- Department of Neurological SurgeryUniversity of LouisvilleLouisvilleKYUSA
| | - Benoit M. Dawant
- Department of Electrical Engineering and Computer ScienceVanderbilt UniversityNashvilleTNUSA
| | - William J. Rodriguez
- Department of Electrical Engineering and Computer ScienceVanderbilt UniversityNashvilleTNUSA
| | - Fenna T. Phibbs
- Department of NeurologyVanderbilt University Medical CenterNashvilleTNUSA
| | - Elise B. Bradley
- Department of NeurologyVanderbilt University Medical CenterNashvilleTNUSA
| | - Joseph S. Neimat
- Department of Neurological SurgeryUniversity of LouisvilleLouisvilleKYUSA
| | - Nelleke C. van Wouwe
- Department of Neurological SurgeryUniversity of LouisvilleLouisvilleKYUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTNUSA
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van Wouwe NC, Neimat JS, van den Wildenberg WPM, Hughes SB, Lopez AM, Phibbs FT, Schall JD, Rodriguez WJ, Bradley EB, Dawant BM, Wylie SA. Subthalamic Nucleus Subregion Stimulation Modulates Inhibitory Control. Cereb Cortex Commun 2020; 1:tgaa083. [PMID: 33381760 PMCID: PMC7750129 DOI: 10.1093/texcom/tgaa083] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 10/29/2020] [Accepted: 10/29/2020] [Indexed: 11/12/2022] Open
Abstract
Patients with Parkinson's disease (PD) often experience reductions in the proficiency to inhibit actions. The motor symptoms of PD can be effectively treated with deep brain stimulation (DBS) of the subthalamic nucleus (STN), a key structure in the frontal-striatal network that may be directly involved in regulating inhibitory control. However, the precise role of the STN in stopping control is unclear. The STN consists of functional subterritories linked to dissociable cortical networks, although the boundaries of the subregions are still under debate. We investigated whether stimulating the dorsal and ventral subregions of the STN would show dissociable effects on ability to stop. We studied 12 PD patients with STN DBS. Patients with two adjacent contacts positioned within the bounds of the dorsal and ventral STN completed two testing sessions (OFF medication) with low amplitude stimulation (0.4 mA) at either the dorsal or ventral contacts bilaterally, while performing the stop task. Ventral, but not dorsal, DBS improved stopping latencies. Go reactions were similar between dorsal and ventral DBS STN. Stimulation in the ventral, but not dorsal, subregion of the STN improved stopping speed, confirming the involvement of the STN in stopping control and supporting the STN functional subregions.
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Affiliation(s)
- Nelleke C van Wouwe
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202 USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Joseph S Neimat
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202 USA
| | - Wery P M van den Wildenberg
- Department of Psychology, University of Amsterdam, Amsterdam 1018 WS, The Netherlands
- Amsterdam Brain and Cognition (ABC), University of Amsterdam, Amsterdam 1001 NK, The Netherlands
| | - Shelby B Hughes
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Alexander M Lopez
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Fenna T Phibbs
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Jeffrey D Schall
- Department of Psychology, Vanderbilt University, Nashville, TN 37240, USA
| | - William J Rodriguez
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Elise B Bradley
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Benoit M Dawant
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Scott A Wylie
- Department of Neurological Surgery, University of Louisville, Louisville, KY 40202 USA
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Narasimhan S, Kundassery KB, Gupta K, Johnson GW, Wills KE, Goodale SE, Haas K, Rolston JD, Naftel RP, Morgan VL, Dawant BM, González HFJ, Englot DJ. Seizure-onset regions demonstrate high inward directed connectivity during resting-state: An SEEG study in focal epilepsy. Epilepsia 2020; 61:2534-2544. [PMID: 32944945 PMCID: PMC7899016 DOI: 10.1111/epi.16686] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 08/15/2020] [Accepted: 08/17/2020] [Indexed: 01/06/2023]
Abstract
OBJECTIVE In patients with medically refractory focal epilepsy, stereotactic-electroencephalography (SEEG) can aid in localizing epileptogenic regions for surgical treatment. SEEG, however, requires long hospitalizations to record seizures, and ictal interpretation can be incomplete or inaccurate. Our recent work showed that non-directed resting-state analyses may identify brain regions as epileptogenic or uninvolved. Our present objective is to map epileptogenic networks in greater detail and more accurately identify seizure-onset regions using directed resting-state SEEG connectivity. METHODS In 25 patients with focal epilepsy who underwent SEEG, 2 minutes of resting-state, artifact-free, SEEG data were selected and functional connectivity was estimated. Using standard clinical interpretation, brain regions were classified into four categories: ictogenic, early propagation, irritative, or uninvolved. Three non-directed connectivity measures (mutual information [MI] strength, and imaginary coherence between and within regions) and four directed measures (partial directed coherence [PDC] and directed transfer function [DTF], inward and outward strength) were calculated. Logistic regression was used to generate a predictive model of ictogenicity. RESULTS Ictogenic regions had the highest and uninvolved regions had the lowest MI strength. Although both PDC and DTF inward strengths were highest in ictogenic regions, outward strengths did not differ among categories. A model incorporating directed and nondirected connectivity measures demonstrated an area under the receiver-operating characteristic (ROC) curve (AUC) of 0.88 in predicting ictogenicity of individual regions. The AUC of this model was 0.93 when restricted to patients with favorable postsurgical seizure outcomes. SIGNIFICANCE Directed connectivity measures may help identify epileptogenic networks without requiring ictal recordings. Greater inward but not outward connectivity in ictogenic regions at rest may represent broad inhibitory input to prevent seizure generation.
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Affiliation(s)
- Saramati Narasimhan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Keshav B. Kundassery
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Kanupriya Gupta
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Graham W. Johnson
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Kristin E. Wills
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sarah E. Goodale
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Kevin Haas
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - John D. Rolston
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah
| | - Robert P. Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Victoria L. Morgan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Benoit M. Dawant
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee
| | - Hernán F. J. González
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Dario J. Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee
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Scorza D, El Hadji S, Cortés C, Bertelsen Á, Cardinale F, Baselli G, Essert C, Momi ED. Surgical planning assistance in keyhole and percutaneous surgery: A systematic review. Med Image Anal 2020; 67:101820. [PMID: 33075642 DOI: 10.1016/j.media.2020.101820] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 08/07/2020] [Accepted: 09/07/2020] [Indexed: 11/29/2022]
Abstract
Surgical planning of percutaneous interventions has a crucial role to guarantee the success of minimally invasive surgeries. In the last decades, many methods have been proposed to reduce clinician work load related to the planning phase and to augment the information used in the definition of the optimal trajectory. In this survey, we include 113 articles related to computer assisted planning (CAP) methods and validations obtained from a systematic search on three databases. First, a general formulation of the problem is presented, independently from the surgical field involved, and the key steps involved in the development of a CAP solution are detailed. Secondly, we categorized the articles based on the main surgical applications, which have been object of study and we categorize them based on the type of assistance provided to the end-user.
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Affiliation(s)
- Davide Scorza
- Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain; Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milan, Italy; Biodonostia Health Research Institute, Donostia-San Sebastián, Spain.
| | - Sara El Hadji
- Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milan, Italy.
| | - Camilo Cortés
- Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain; Biodonostia Health Research Institute, Donostia-San Sebastián, Spain
| | - Álvaro Bertelsen
- Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Donostia-San Sebastián, Spain; Biodonostia Health Research Institute, Donostia-San Sebastián, Spain
| | - Francesco Cardinale
- Claudio Munari Centre for Epilepsy and Parkinson surgery, Azienda Socio-Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda (ASST GOM Niguarda), Milan, Italy
| | - Giuseppe Baselli
- Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milan, Italy
| | - Caroline Essert
- ICube Laboratory, CNRS, UMR 7357, Université de Strasbourg, Strasbourg, France
| | - Elena De Momi
- Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milan, Italy
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Radiofrequency Ablation Through Previously Effective Deep Brain Stimulation Leads for Parkinson Disease: A Retrospective Series. World Neurosurg 2020; 144:e750-e765. [PMID: 32949803 DOI: 10.1016/j.wneu.2020.09.060] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 09/11/2020] [Accepted: 09/12/2020] [Indexed: 11/21/2022]
Abstract
BACKGROUND Although deep brain stimulation (DBS) of the subthalamic nucleus (STN) or globus pallidus internus (GPi) is the surgical method of choice to treat the canonical symptoms of Parkinson disease, occasionally surgical sites become infected or the hardware erodes, necessitating explantation. Usual practice is to remove and reimplant replacement leads after tissue healing, leaving patients without the clinical benefits of DBS for several months, and at risk for DBS withdrawal in some, and some patients are no longer good surgical candidates for reimplantation. Radiofrequency ablation through the DBS lead is an option for these patients. METHODS We performed a retrospective chart review of all patients who underwent radiofrequency ablation of the STN or GPi through indwelling DBS leads performed before hardware removal at our institution. We generated patient-specific anatomic models to determine lesion locations and volumes. RESULTS Six patients underwent radiofrequency ablation of the STN (n = 4) and GPi (n = 2) through indwelling DBS leads. All 6 of these patients initially showed comparable motor symptom relief to that experienced with DBS before lesioning, with 4 patients sustaining meaningful long-term (≥2 years) improvement. Better outcomes were achieved in those patients with a higher percentage of the planned target lesioned. CONCLUSIONS Radiofrequency ablation through indwelling DBS leads before explantation could be considered a viable alternative to subsequent reimplantation or stereotactic lesion in patients with Parkinson disease in whom hardware explantation is necessary, if the patient achieved substantive symptom relief with DBS. This approach avoids symptom exacerbation while awaiting revision surgery.
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Automated detection of subthalamic nucleus in deep brain stimulation surgery for Parkinson’s disease using microelectrode recordings and wavelet packet features. J Neurosci Methods 2020; 343:108826. [DOI: 10.1016/j.jneumeth.2020.108826] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 06/22/2020] [Indexed: 01/02/2023]
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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: 3.2] [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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Goodale SE, González HFJ, Johnson GW, Gupta K, Rodriguez WJ, Shults R, Rogers BP, Rolston JD, Dawant BM, Morgan VL, Englot DJ. Resting-State SEEG May Help Localize Epileptogenic Brain Regions. Neurosurgery 2020; 86:792-801. [PMID: 31814011 PMCID: PMC7225010 DOI: 10.1093/neuros/nyz351] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 06/18/2019] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Stereotactic electroencephalography (SEEG) is a minimally invasive neurosurgical method to localize epileptogenic brain regions in epilepsy but requires days in the hospital with interventions to trigger several seizures. OBJECTIVE To make initial progress in the development of network analysis methods to identify epileptogenic brain regions using brief, resting-state SEEG data segments, without requiring seizure recordings. METHODS In a cohort of 15 adult focal epilepsy patients undergoing SEEG, we evaluated functional connectivity (alpha-band imaginary coherence) across sampled regions using brief (2 min) resting-state data segments. Bootstrapped logistic regression was used to generate a model to predict epileptogenicity of individual regions. RESULTS Compared to nonepileptogenic structures, we found increased functional connectivity within epileptogenic regions (P < .05) and between epileptogenic areas and other structures (P < .01, paired t-tests, corrected). Epileptogenic areas also demonstrated higher clustering coefficient (P < .01) and betweenness centrality (P < .01), and greater decay of functional connectivity with distance (P < .05, paired t-tests, corrected). Our functional connectivity model to predict epileptogenicity of individual regions demonstrated an area under the curve of 0.78 and accuracy of 80.4%. CONCLUSION Our study represents a preliminary step towards defining resting-state SEEG functional connectivity patterns to help localize epileptogenic brain regions ahead of neurosurgical treatment without requiring seizure recordings.
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Affiliation(s)
- Sarah E Goodale
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Hernán F J González
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
| | - Kanupriya Gupta
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee
| | - William J Rodriguez
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee
| | - Robert Shults
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Baxter P Rogers
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - John D Rolston
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah
| | - Benoit M Dawant
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
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Abstract
Surgery in Parkinson disease is effective for a select group of patients when optimal medical management is not sufficient. Functional neurosurgery can be used as either a salvage therapy in patients with disabling symptoms or to maintain quality of life and independence before progression to severe disability in high-functioning patients. With recent technological advancements in imaging and targeting as well as novel neuromodulation paradigms, there are numerous options for targeted brain lesions and deep brain stimulation. Surgical decision making and postoperative management in Parkinson disease therefore often requires a multidisciplinary team effort with neurology, neurosurgery, neuropsychology, and psychiatry.
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Affiliation(s)
- Kyle T Mitchell
- Duke University Movement Disorders Center, DUMC 3333, 932 Morreene Road, Durham, NC 27705, USA.
| | - Jill L Ostrem
- UCSF Movement Disorders and Neuromodulation Center, 1635 Divisadero Street Suite 520, Box 1838, San Francisco, CA 94115, USA
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Shah A, Vogel D, Alonso F, Lemaire JJ, Pison D, Coste J, Wårdell K, Schkommodau E, Hemm S. Stimulation maps: visualization of results of quantitative intraoperative testing for deep brain stimulation surgery. Med Biol Eng Comput 2020; 58:771-784. [PMID: 32002754 PMCID: PMC7156362 DOI: 10.1007/s11517-020-02130-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 01/06/2020] [Indexed: 11/27/2022]
Abstract
Deep brain stimulation (DBS) is an established therapy for movement disorders such as essential tremor (ET). Positioning of the DBS lead in the patient's brain is crucial for effective treatment. Extensive evaluations of improvement and adverse effects of stimulation at different positions for various current amplitudes are performed intraoperatively. However, to choose the optimal position of the lead, the information has to be "mentally" visualized and analyzed. This paper introduces a new technique called "stimulation maps," which summarizes and visualizes the high amount of relevant data with the aim to assist in identifying the optimal DBS lead position. It combines three methods: outlines of the relevant anatomical structures, quantitative symptom evaluation, and patient-specific electric field simulations. Through this combination, each voxel in the stimulation region is assigned one value of symptom improvement, resulting in the division of stimulation region into areas with different improvement levels. This technique was applied retrospectively to five ET patients in the University Hospital in Clermont-Ferrand, France. Apart from identifying the optimal implant position, the resultant nine maps show that the highest improvement region is frequently in the posterior subthalamic area. The results demonstrate the utility of the stimulation maps in identifying the optimal implant position. Graphical abstract.
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Affiliation(s)
- Ashesh Shah
- Institute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | - Dorian Vogel
- Institute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
| | - Fabiola Alonso
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
| | - Jean-Jacques Lemaire
- CNRS, SIGMA Clermont, Institut Pascal, Université Clermont Auvergne, Clermont-Ferrand, France
- Service de Neurochirurgie, Hôpital Gabriel-Montpied, Centre Hospitalier Universitaire de Clermont-Ferrand, Clermont-Ferrand, France
| | - Daniela Pison
- Institute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | - Jérôme Coste
- CNRS, SIGMA Clermont, Institut Pascal, Université Clermont Auvergne, Clermont-Ferrand, France
- Service de Neurochirurgie, Hôpital Gabriel-Montpied, Centre Hospitalier Universitaire de Clermont-Ferrand, Clermont-Ferrand, France
| | - Karin Wårdell
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
| | - Erik Schkommodau
- Institute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | - Simone Hemm
- Institute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden.
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Cloud-Based Stereotactic and Functional Neurosurgery and Registries. Stereotact Funct Neurosurg 2020. [DOI: 10.1007/978-3-030-34906-6_11] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Sammartino F, Rege R, Krishna V. Reliability of Intraoperative Testing During Deep Brain Stimulation Surgery. Neuromodulation 2019; 23:525-529. [PMID: 31823438 DOI: 10.1111/ner.13081] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 09/29/2019] [Accepted: 10/30/2019] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Deep brain stimulation (DBS) is an effective treatment for medically refractory Parkinson's disease (PD). During DBS surgery, intraoperative testing is performed to confirm optimal lead placement by determining the stimulation thresholds for symptom improvement and side effects. However, the reliability of intraoperative testing in predicting distant postoperative thresholds is unknown. In this study, we hypothesized that intraoperative testing reliably estimates postoperative thresholds for both symptom improvement and side effects. METHODS We retrospectively analyzed a prospective database with intraoperative and postoperative thresholds for symptom improvement and side effects from a cohort of 66 PD patients who underwent STN DBS. We recorded the stimulation locations relative to the mid-commissural point. Within-patient stimulation pairs were generated by clustering the intraoperative stimulation locations closest to the DBS contacts. We computed the distance between stimulation locations and atlas-based pyramidal tract (PT) and medial lemniscus (ML) masks. A leave-one-out cross-validation analysis was performed to determine the reliability of intraoperative testing in predicting postoperative thresholds while controlling for the distance from the relevant tracks. RESULTS Intraoperative testing reliably predicted (area under ROC >0.8) postoperative thresholds for tremor and rigidity improvements, as well as stimulation-induced motor contractions and paresthesias. The reliability was poor for improvement in bradykinesia. CONCLUSION Intraoperative testing reliably predicts postoperative thresholds. These results are relevant during the informed consent process and patient counseling for DBS surgery. These will also guide the development of future methods for intraoperative feedback, especially during asleep DBS.
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Affiliation(s)
| | - Rahul Rege
- Department of Neurosurgery, The Ohio State University, Columbus, OH
| | - Vibhor Krishna
- Department of Neurosurgery, The Ohio State University, Columbus, OH
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Plassard AJ, Bao S, D'Haese PF, Pallavaram S, Claassen DO, Dawant BM, Landman BA. Multi-modal imaging with specialized sequences improves accuracy of the automated subcortical grey matter segmentation. Magn Reson Imaging 2019; 61:131-136. [PMID: 31121202 PMCID: PMC6980439 DOI: 10.1016/j.mri.2019.05.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Revised: 04/23/2019] [Accepted: 05/19/2019] [Indexed: 10/26/2022]
Abstract
The basal ganglia and limbic system, particularly the thalamus, putamen, internal and external globus pallidus, substantia nigra, and sub-thalamic nucleus, comprise a clinically relevant signal network for Parkinson's disease. In order to manually trace these structures, a combination of high-resolution and specialized sequences at 7 T are used, but it is not feasible to routinely scan clinical patients in those scanners. Targeted imaging sequences at 3 T have been presented to enhance contrast in a select group of these structures. In this work, we show that a series of atlases generated at 7 T can be used to accurately segment these structures at 3 T using a combination of standard and optimized imaging sequences, though no one approach provided the best result across all structures. In the thalamus and putamen, a median Dice Similarity Coefficient (DSC) over 0.88 and a mean surface distance <1.0 mm were achieved using a combination of T1 and an optimized inversion recovery imaging sequences. In the internal and external globus pallidus a DSC over 0.75 and a mean surface distance <1.2 mm were achieved using a combination of T1 and inversion recovery imaging sequences. In the substantia nigra and sub-thalamic nucleus a DSC of over 0.6 and a mean surface distance of <1.0 mm were achieved using the inversion recovery imaging sequence. On average, using T1 and optimized inversion recovery together significantly improved segmentation results than over individual modality (p < 0.05 Wilcoxon sign-rank test).
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Affiliation(s)
- Andrew J Plassard
- Computer Science, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA
| | - Shunxing Bao
- Computer Science, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA.
| | - Pierre F D'Haese
- Electrical Engineering, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA
| | - Srivatsan Pallavaram
- Electrical Engineering, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA
| | - Daniel O Claassen
- Neurology, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA
| | - Benoit M Dawant
- Computer Science, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Electrical Engineering, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA
| | - Bennett A Landman
- Computer Science, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Electrical Engineering, Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN 37235, USA
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A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson’s disease. Clin Neurophysiol 2019; 130:145-154. [DOI: 10.1016/j.clinph.2018.09.018] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Revised: 08/28/2018] [Accepted: 09/17/2018] [Indexed: 12/17/2022]
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Isaacs DA, Butler J, Sukul V, Rodriguez W, Pallavaram S, Tolleson C, Fang JY, Phibbs FT, Yu H, Konrad PE, Hedera P. Confined Thalamic Deep Brain Stimulation in Refractory Essential Tremor. Stereotact Funct Neurosurg 2018; 96:296-304. [PMID: 30453287 DOI: 10.1159/000493546] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 09/05/2018] [Indexed: 11/19/2022]
Abstract
BACKGROUND Thalamic ventral intermediate nucleus (VIM) deep brain stimulation (DBS) is an effective therapy for medication-refractory essential tremor (ET). However, 13-40% of patients with an initially robust tremor efficacy lose this benefit over time despite reprogramming attempts. At our institution, a cohort of ET patients with VIM DBS underwent implantation of a second anterior (ventralis oralis anterior; VOA) DBS lead to permit "confined stimulation." We sought to assess whether confined stimulation conferred additional tremor capture compared to VIM or VOA stimulation alone. METHODS Seven patients participated in a protocol-based programming session during which a video-recorded Fahn-Tolosa-Marin Part A (FTM-A) tremor rating scale was used in the following 4 DBS states: off stimulation, VIM stimulation alone, VOA stimulation alone, and dual lead (confined) stimulation. RESULTS The average (SD) baseline FTM-A off score was 17.6 (4.0). VIM stimulation alone lowered the average FTM-A total score to 6.9 (4.0). Confined stimulation further attenuated the tremor, reducing the total score to 5.7 (2.8). CONCLUSIONS Confined thalamic DBS can provide additional symptomatic benefits in patients with unsatisfactory tremor control from VIM or VOA stimulation alone.
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Affiliation(s)
- David A Isaacs
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jonathan Butler
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Riverside Regional Medical Center, Newport News, Virginia, USA
| | - Vishad Sukul
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Neurosurgery, Albany Medical Center, Albany, New York, USA
| | - William Rodriguez
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Srivatsan Pallavaram
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA.,Alpha Omega Co. USA, Inc., Alpharetta, Georgia, USA
| | - Christopher Tolleson
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Medicine, University of Tennessee Medical Center, Knoxville, Tennessee, USA
| | - John Y Fang
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Fenna T Phibbs
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Hong Yu
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peter E Konrad
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peter Hedera
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA,
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Shah AA, Alonso F, Vogel D, Wardell K, Coste J, Lemaire JJ, Pison D, Hemm S. Analysis of adverse effects of stimulation during DBS surgery by patient-specific FEM simulations. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2018:2222-2225. [PMID: 30440847 DOI: 10.1109/embc.2018.8512796] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Deep brain stimulation (DBS) represents today a well-established treatment for movement disorders. Nevertheless the exact mechanism of action of DBS remains incompletely known. During surgery, numerous stimulation tests are frequently performed in order to evaluate therapeutic and adverse effects before choosing the optimal implantation site for the DBS lead. Anatomical structures responsible for the induced adverse effects have been investigated previously, but only based on stimulation data obtained with the implanted DBS lead. The present study introduces a methodology to identify these anatomical structures during intraoperative stimulation tests based on patient-specific electric field simulations and visualization on the patient specific anatomy. The application to 4 patients undergoing DBS surgery and presenting dysarthria, paresthesia or pyramidal effects shows the different anatomical structures, which might be responsible for the adverse effects. Several of the identified structures have been previously described in the literature. To draw any statistically significant conclusions, the methodology has to be applied to further patients. Together with the visualization of the therapeutic effects, this new approach could assist the neurosurgeons in the future in choosing the optimal implant position.
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Winter M, Costabile JD, Abosch A, Thompson JA. Method for localizing intraoperative recordings from deep brain stimulation surgery using post-operative structural MRI. NEUROIMAGE-CLINICAL 2018; 20:1123-1128. [PMID: 30380519 PMCID: PMC6205403 DOI: 10.1016/j.nicl.2018.10.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 10/10/2018] [Accepted: 10/16/2018] [Indexed: 11/15/2022]
Abstract
Background Implantation of deep brain stimulation (DBS) electrodes for the treatment of involuntary movement disorders, such as Parkinson's disease, routinely relies on the use of intraoperative electrophysiological confirmation to identify the optimal therapeutic target in the brain. However, only a few options exist to visualize the relative anatomic localization of intraoperative electrophysiological recordings with respect to post-operative imaging. We have developed a novel processing pipeline to visualize intraoperative electrophysiological signals registered to post-operative neuroanatomical imaging. New method We developed a processing pipeline built on the use of ITK-SNAP and custom MATLAB scripts to visualize the anatomical localization of intraoperative electrophysiological recordings mapped onto the post-operative MRI following implantation of DBS electrodes. This method combines the user-defined relevant electrophysiological parameters measured during the surgery with a manual segmentation of the DBS electrode from post-operative MRI; mapping the microelectrode recording (MER) depths along the DBS lead track. Results We demonstrate the use of our processing pipeline on data from Parkinson's disease patients undergoing DBS implantation targeted to the subthalamic nucleus (STN). The primary processing components of the pipeline are: extrapolation of the lead wire and alignment of intraoperative electrophysiology. Conclusion We describe the use of a processing pipeline to aid clinicians and researchers engaged in deep brain stimulation work to correlate and visualize the intraoperative recording data with the post-operative DBS trajectory. Pipeline that refines a manually segmented DBS wire from post-operative MR imaging. MATLAB function library for alignment of intraoperative electrophysiological data with MRI. Provides visualization schemes that convey the relative change in magnitude for an electrophysiological parameter
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Affiliation(s)
- McKenzie Winter
- Department of Cell and Developmental Biology, Modern Human Anatomy, United States
| | - Jamie D Costabile
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, United States
| | - Aviva Abosch
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, United States
| | - John A Thompson
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, United States.
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Malekmohammadi M, Shahriari Y, AuYong N, O’Keeffe A, Bordelon Y, Hu X, Pouratian N. Pallidal stimulation in Parkinson disease differentially modulates local and network β activity. J Neural Eng 2018; 15:056016. [PMID: 29972146 PMCID: PMC6125208 DOI: 10.1088/1741-2552/aad0fb] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
β hypersynchrony within the basal ganglia-thalamocortical (BGTC) network has been suggested as a hallmark of Parkinson disease (PD) pathophysiology. Subthalamic nucleus (STN)-DBS has been shown to alter cortical-subcortical synchronization. It is unclear whether this is a generalizable phenomenon of therapeutic stimulation across targets. OBJECTIVES We aimed to evaluate whether DBS of the globus pallidus internus (GPi) results in cortical-subcortical desynchronization, despite the lack of monosynaptic connections between GPi and sensorimotor cortex. APPROACH We recorded local field potentials from the GPi and electrocorticographic signals from the ipsilateral sensorimotor cortex, off medications in nine PD patients, undergoing DBS implantation. We analyzed both local oscillatory power and functional connectivity (coherence and debiased weighted phase lag index (dWPLI)) with and without stimulation while subjects were resting with eyes open. MAIN RESULTS DBS significantly suppressed low β power within the GPi (-26.98% ± 15.14%), p < 0.05) without modulation of sensorimotor cortical β power (low or high). In contrast, stimulation suppressed pallidocortical high β coherence (-38.89% ± 6.19%, p = 0.02) and dWPLI (-61.40% ± 8.75%, p = 0.02). Changes in cortical-subcortical functional connectivity were spatially specific to the motor cortex. SIGNIFICANCE We highlight the role of DBS in desynchronizing network activity, particularly in the high β band. The current study of GPi-DBS suggests these network-level effects are not necessarily dependent and potentially may be independent of the hyperdirect pathway. Importantly, these results draw a sharp distinction between the potential significance of low β oscillations locally within the basal ganglia and high β oscillations across the BGTC motor circuit.
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Affiliation(s)
| | - Yalda Shahriari
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, RI, USA
- Department of Physiological Nursing, University of California, San Francisco, CA, USA
| | - Nicholas AuYong
- Department of Neurosurgery, University of California, Los Angeles, CA, USA
| | - Andrew O’Keeffe
- Department of Neurosurgery, University of California, Los Angeles, CA, USA
| | - Yvette Bordelon
- Department of Neurology, University of California, Los Angeles, CA, USA
| | - Xiao Hu
- Department of Physiological Nursing, University of California, San Francisco, CA, USA
| | - Nader Pouratian
- Department of Neurosurgery, University of California, Los Angeles, CA, USA
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Haegelen C, Baumgarten C, Houvenaghel JF, Zhao Y, Péron J, Drapier S, Jannin P, Morandi X. Functional atlases for analysis of motor and neuropsychological outcomes after medial globus pallidus and subthalamic stimulation. PLoS One 2018; 13:e0200262. [PMID: 30005077 PMCID: PMC6044526 DOI: 10.1371/journal.pone.0200262] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2017] [Accepted: 06/24/2018] [Indexed: 11/18/2022] Open
Abstract
Anatomical atlases have been developed to improve the targeting of basal ganglia in deep brain stimulation. However, the sole anatomy cannot predict the functional outcome of this surgery. Deep brain stimulation is often a compromise between several functional outcomes: motor, fluency and neuropsychological outcomes in particular. In this study, we have developed anatomo-clinical atlases for the targeting of subthalamic and medial globus pallidus deep brain stimulation. The activated electrode coordinates of 42 patients implanted in the subthalamic nucleus and 29 patients in the medial globus pallidus were studied. The atlas was built using the representation of the volume of tissue theoretically activated by the stimulation. The UPDRS score was used to represent the motor outcome. The Stroop test was represented as well as semantic and phonemic fluencies. For the subthalamic nucleus, best motor outcomes were obtained when the supero-lateral part of the nucleus was stimulated whereas the semantic fluency was impaired in this same region. For the medial globus pallidus, best outcomes were obtained when the postero ventral part of the nucleus was stimulated whereas the phonemic fluency was impaired in this same region. There was no significant neuropsychological impairment. We have proposed new anatomo-clinical atlases to visualize the motor and neuropsychological consequences at 6 months of subthalamic nucleus and pallidal stimulation in patients with Parkinson's disease.
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Affiliation(s)
- Claire Haegelen
- Department of Neurosurgery, CHU Pontchaillou, Rennes, France
- INSERM, LTSI U1099, Faculté de Médecine, Rennes, France
- University of Rennes I, Rennes, France
- * E-mail:
| | - Clément Baumgarten
- INSERM, LTSI U1099, Faculté de Médecine, Rennes, France
- University of Rennes I, Rennes, France
| | - Jean-François Houvenaghel
- Department of Neurology, CHU Pontchaillou, Rennes, France
- Behavior and Basal Ganglia host team 4712, University of Rennes 1, Rennes, France
| | - Yulong Zhao
- INSERM, LTSI U1099, Faculté de Médecine, Rennes, France
- University of Rennes I, Rennes, France
| | - Julie Péron
- Swiss Centre for Affective Sciences, Geneva, Switzerland
| | - Sophie Drapier
- Department of Neurology, CHU Pontchaillou, Rennes, France
- Behavior and Basal Ganglia host team 4712, University of Rennes 1, Rennes, France
| | - Pierre Jannin
- INSERM, LTSI U1099, Faculté de Médecine, Rennes, France
- University of Rennes I, Rennes, France
| | - Xavier Morandi
- Department of Neurosurgery, CHU Pontchaillou, Rennes, France
- INSERM, LTSI U1099, Faculté de Médecine, Rennes, France
- University of Rennes I, Rennes, France
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Holden MS, Zhao Y, Haegelen C, Essert C, Fernandez-Vidal S, Bardinet E, Ungi T, Fichtinger G, Jannin P. Self-guided training for deep brain stimulation planning using objective assessment. Int J Comput Assist Radiol Surg 2018; 13:1129-1139. [DOI: 10.1007/s11548-018-1753-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 03/26/2018] [Indexed: 10/17/2022]
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47
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Mills-Joseph R, Krishna V, Deogaonkar M, Rezai AR. Deep Brain Stimulation in Parkinson’s Disease. Neuromodulation 2018. [DOI: 10.1016/b978-0-12-805353-9.00074-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Krishna V, Sammartino F, Rezai AR. The Use of New Surgical Technologies for Deep Brain Stimulation. Neuromodulation 2018. [DOI: 10.1016/b978-0-12-805353-9.00034-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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D’Haese PF, Konrad PE, Dawant BM. Big Data and Deep Brain Stimulation. Neuromodulation 2018. [DOI: 10.1016/b978-0-12-805353-9.00013-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Bakhshmand SM, Eagleson R, de Ribaupierre S. Multimodal connectivity based eloquence score computation and visualisation for computer-aided neurosurgical path planning. Healthc Technol Lett 2017; 4:152-156. [PMID: 29184656 PMCID: PMC5683204 DOI: 10.1049/htl.2017.0073] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2017] [Accepted: 07/31/2017] [Indexed: 11/20/2022] Open
Abstract
Non-invasive assessment of cognitive importance has been a major challenge for planning of neurosurgical procedures. In the past decade, in vivo brain imaging modalities have been considered for estimating the ‘eloquence’ of brain areas. In order to estimate the impact of damage caused by an access path towards a target region inside of the skull, multi-modal metrics are introduced in this paper. Accordingly, this estimated damage is obtained by combining multi-modal metrics. In other words, this damage is an aggregate of intervened grey matter volume and axonal fibre numbers, weighted by their importance within the assigned anatomical and functional networks. To validate these metrics, an exhaustive search algorithm is implemented for characterising the solution space and visually representing connectional cost associated with a path initiated from underlying points. In this presentation, brain networks are built from resting state functional magnetic resonance imaging (fMRI) and deterministic tractography. their results demonstrate that the proposed approach is capable of refining traditional heuristics, such as choosing the minimal distance from the lesion, by supplementing connectional importance of the resected tissue. This provides complementary information to help the surgeon in avoiding important functional hubs and their anatomical linkages; which are derived from neuroimaging modalities and incorporated to the related anatomical landmarks.
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Affiliation(s)
- Saeed M Bakhshmand
- Biomedical Engineering Graduate Program, University of Western Ontario, London, ON, Canada
| | - Roy Eagleson
- Biomedical Engineering Graduate Program, University of Western Ontario, London, ON, Canada.,Department of Electrical and Computer Engineering, University of Western Ontario, London, ON, Canada
| | - Sandrine de Ribaupierre
- Biomedical Engineering Graduate Program, University of Western Ontario, London, ON, Canada.,Department of Clinical Neurological Sciences, University of Western Ontario, London, ON, Canada
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