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Dadario NB, Sughrue ME. Simpson's Grading Scale for WHO Grade I Meningioma Resection in the Modern Neurosurgical Era: Are We Really Asking the Right Question? J Neurol Surg B Skull Base 2024; 85:145-155. [PMID: 38449587 PMCID: PMC10914467 DOI: 10.1055/a-2021-8852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 01/21/2023] [Indexed: 01/31/2023] Open
Abstract
The Simpson grading scale for the classification of the extent of meningioma resection provided a tremendous movement forward in 1957 suggesting increasing the extent of resection improves recurrence rates. However, equal, if not greater, movements forward have been made in the neurosurgical community over the last half a century owing to improvements in neuroimaging capabilities, microsurgical techniques, and radiotherapeutic strategies. Sughrue et al proposed the idea that these advancements have altered what a "recurrence" and "subtotal resection" truly means in modern neurosurgery compared with Simpson's era, and that a mandated use of the Simpson Scale is likely less clinically relevant today. A subsequent period of debate ensued in the literature which sought to re-examine the clinical value of using the Simpson Scale in modern neurosurgery. While a large body of evidence has recently been provided, these data generally continue to support the clinical importance of gross tumor resection as well as the value of adjuvant radiation therapy and the importance of recently updated World Health Organization classifications. However, there remains a negligible interval benefit in performing overly aggressive surgery and heroic maneuvers to remove the last bit of tumor, dura, and/or bone just for the simple act of achieving a lower Simpson score. Ultimately, meningioma surgery may be better contextualized as a continuous set of weighted risk-benefit decisions throughout the entire operation.
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Affiliation(s)
- Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, United States
| | - Michael E. Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Randwick, New South Wales, Australia
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
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Ahsan SA, Dadario NB, Dhaliwal J, Briggs RG, Osipowicz K, Ahsan SM, Chendeb K, Conner AK, O'Neal CM, Glenn CA, Sughrue ME. A parcellation-based connectomic model of hemispatial neglect. J Neuroimaging 2024; 34:267-279. [PMID: 38115162 DOI: 10.1111/jon.13176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 11/23/2023] [Accepted: 11/28/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND AND PURPOSE Hemispatial neglect is characterized by a reduced awareness to stimuli on the contralateral side. Current literature suggesting that damage to the right parietal lobe and attention networks may cause hemispatial neglect is conflicting and can be improved by investigating a connectomic model of the "neglect system" and the anatomical specificity of regions involved in it. METHODS A meta-analysis of voxel-based morphometry magnetic resonance imaging (MRI) studies of hemispatial neglect was used to identify regions associated with neglect. We applied parcellation schemes to these regions and performed diffusion spectrum imaging (DSI) tractography to determine their connectivity. By overlaying neglect areas and maps of the attention networks, we studied the relationship between them. RESULTS The meta-analysis generated a list of 13 right hemisphere parcellations. These 13 neglect-related parcellations were predominantly linked by the superior longitudinal fasciculus (SLF) throughout a fronto-parietal-temporal network. We found that the dorsal and ventral attention networks showed partial overlap with the neglect system and included various other higher-order networks. CONCLUSIONS We provide an anatomically specific connectomic model of the neurobehavioral substrates underlying hemispatial neglect. Our model suggests a fronto-parietal-temporal network linked via the SLF supports the functions impaired in neglect and implicates various higher-order networks which are not limited to the attention networks.
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Affiliation(s)
- Syed A Ahsan
- Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, USA
| | | | - Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Karol Osipowicz
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | - Syed M Ahsan
- Faculty of Medicine, University of New England, Armidale, New South Wales, Australia
| | - Kassem Chendeb
- Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Andrew K Conner
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Christen M O'Neal
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Chad A Glenn
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Michael E Sughrue
- Center for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia
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Hormovas J, Dadario NB, Tang SJ, Nicholas P, Dhanaraj V, Young I, Doyen S, Sughrue ME. Parcellation-Based Connectivity Model of the Judgement Core. J Pers Med 2023; 13:1384. [PMID: 37763153 PMCID: PMC10532823 DOI: 10.3390/jpm13091384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/12/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Judgement is a higher-order brain function utilized in the evaluation process of problem solving. However, heterogeneity in the task methodology based on the many definitions of judgement and its expansive and nuanced applications have prevented the identification of a unified cortical model at a level of granularity necessary for clinical translation. Forty-six task-based fMRI studies were used to generate activation-likelihood estimations (ALE) across moral, social, risky, and interpersonal judgement paradigms. Cortical parcellations overlapping these ALEs were used to delineate patterns in neurocognitive network engagement for the four judgement tasks. Moral judgement involved the bilateral superior frontal gyri, right temporal gyri, and left parietal lobe. Social judgement demonstrated a left-dominant frontoparietal network with engagement of right-sided temporal limbic regions. Moral and social judgement tasks evoked mutual engagement of the bilateral DMN. Both interpersonal and risk judgement were shown to involve a right-sided frontoparietal network with accompanying engagement of the left insular cortex, converging at the right-sided CEN. Cortical activation in normophysiological judgement function followed two separable patterns involving the large-scale neurocognitive networks. Specifically, the DMN was found to subserve judgement centered around social inferences and moral cognition, while the CEN subserved tasks involving probabilistic reasoning, risk estimation, and strategic contemplation.
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Affiliation(s)
- Jorge Hormovas
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Level 7 Prince of Wales Private Hospital, Randwick, NSW 2031, Australia; (J.H.); (V.D.)
| | - Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, 125 Paterson St., New Brunswick, NJ 08901, USA;
| | - Si Jie Tang
- School of Medicine, 21772 University of California Davis Medical Center, 2315 Stockton Blvd., Sacramento, CA 95817, USA
| | - Peter Nicholas
- Omniscient Neurotechnology, Level 10/580 George Street, Haymarket, NSW 2000, Australia; (P.N.); (I.Y.); (S.D.)
| | - Vukshitha Dhanaraj
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Level 7 Prince of Wales Private Hospital, Randwick, NSW 2031, Australia; (J.H.); (V.D.)
| | - Isabella Young
- Omniscient Neurotechnology, Level 10/580 George Street, Haymarket, NSW 2000, Australia; (P.N.); (I.Y.); (S.D.)
| | - Stephane Doyen
- Omniscient Neurotechnology, Level 10/580 George Street, Haymarket, NSW 2000, Australia; (P.N.); (I.Y.); (S.D.)
| | - Michael E. Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Level 7 Prince of Wales Private Hospital, Randwick, NSW 2031, Australia; (J.H.); (V.D.)
- Omniscient Neurotechnology, Level 10/580 George Street, Haymarket, NSW 2000, Australia; (P.N.); (I.Y.); (S.D.)
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Dadario NB, Piper K, Young IM, Sherman JH, Sughrue ME. Functional connectivity reveals different brain networks underlying the idiopathic foreign accent syndrome. Neurol Sci 2023; 44:3087-3097. [PMID: 36995471 DOI: 10.1007/s10072-023-06762-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 03/16/2023] [Indexed: 03/31/2023]
Abstract
Foreign accent syndrome (FAS) is characterized by new onset speech that is perceived as foreign. Available data from acquired cases suggests focal brain damage in language and sensorimotor brain networks, but little remains known about abnormal functional connectivity in idiopathic cases of FAS without structural damage. Here, connectomic analyses were completed on three patients with idiopathic FAS to investigate unique functional connectivity abnormalities underlying accent change for the first time. Machine learning (ML)-based algorithms generated personalized brain connectomes based on a validated parcellation scheme from the Human Connectome Project (HCP). Diffusion tractography was performed on each patient to rule out structural fiber damage to the language system. Resting-state-fMRI was assessed with ML-based software to examine functional connectivity between individual parcellations within language and sensorimotor networks and subcortical structures. Functional connectivity matrices were created and compared against a dataset of 200 healthy subjects to identify abnormally connected parcellations. Three female patients (28-42 years) who presented with accent changes from Australian English to Irish (n = 2) or American English to British English (n = 1) demonstrated fully intact language system structural connectivity. All patients demonstrated functional connectivity anomalies within language and sensorimotor networks in numerous left frontal regions and between subcortical structures in one patient. Few commonalities in functional connectivity anomalies were identified between all three patients, specifically 3 internal-network parcellation pairs. No common inter-network functional connectivity anomalies were identified between all patients. The current study demonstrates specific language, and sensorimotor functional connectivity abnormalities can exist and be quantitatively shown in the absence of structural damage for future study.
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Affiliation(s)
- Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
| | - Keaton Piper
- Department of Neurosurgery, University of South Florida, Tampa, FL, USA
| | | | - Jonathan H Sherman
- Department of Neurosurgery, West Virginia University, Martinsburg, WV, USA
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Suite 3, Level 7 Barker St, Randwick, New South Wales, 2031, Australia.
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Abstract
Recent advancements in computational approaches and neuroimaging techniques have refined our understanding of the precuneus. While previously believed to be largely a visual processing region, the importance of the precuneus in complex cognitive functions has been previously less familiar due to a lack of focal lesions in this deeply seated region, but also a poor understanding of its true underlying anatomy. Fortunately, recent studies have revealed significant information on the structural and functional connectivity of this region, and this data has provided a more detailed mechanistic understanding of the importance of the precuneus in healthy and pathologic states. Through improved resting-state functional MRI analyses, it has become clear that the function of the precuneus can be better understood based on its functional association with large scale brain networks. Dual default mode network systems have been well explained in recent years in supporting episodic memory and theory of mind; however, a novel 'para-cingulate' network, which is a subnetwork of the larger central executive network, with likely significant roles in self-referential processes and related psychiatric symptoms is introduced here and requires further clarification. Importantly, detailed anatomic studies on the precuneus structural connectivity inside and beyond the cingulate cortex has demonstrated the presence of large structural white matter connections, which provide an additional layer of meaning to the structural-functional significance of this region and its association with large scale brain networks. Together, the structural-functional connectivity of the precuneus has provided central elements which can model various neurodegenerative diseases and psychiatric disorders, such as Alzheimer's disease and depression.
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Affiliation(s)
- Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 07102, USA
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Chen R, Dadario NB, Cook B, Sun L, Wang X, Li Y, Hu X, Zhang X, Sughrue ME. Connectomic insight into unique stroke patient recovery after rTMS treatment. Front Neurol 2023; 14:1063408. [PMID: 37483442 PMCID: PMC10359072 DOI: 10.3389/fneur.2023.1063408] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 06/13/2023] [Indexed: 07/25/2023] Open
Abstract
An improved understanding of the neuroplastic potential of the brain has allowed advancements in neuromodulatory treatments for acute stroke patients. However, there remains a poor understanding of individual differences in treatment-induced recovery. Individualized information on connectivity disturbances may help predict differences in treatment response and recovery phenotypes. We studied the medical data of 22 ischemic stroke patients who received MRI scans and started repetitive transcranial magnetic stimulation (rTMS) treatment on the same day. The functional and motor outcomes were assessed at admission day, 1 day after treatment, 30 days after treatment, and 90 days after treatment using four validated standardized stroke outcome scales. Each patient underwent detailed baseline connectivity analyses to identify structural and functional connectivity disturbances. An unsupervised machine learning (ML) agglomerative hierarchical clustering method was utilized to group patients according to outcomes at four-time points to identify individual phenotypes in recovery trajectory. Differences in connectivity features were examined between individual clusters. Patients were a median age of 64, 50% female, and had a median hospital length of stay of 9.5 days. A significant improvement between all time points was demonstrated post treatment in three of four validated stroke scales utilized. ML-based analyses identified distinct clusters representing unique patient trajectories for each scale. Quantitative differences were found to exist in structural and functional connectivity analyses of the motor network and subcortical structures between individual clusters which could explain these unique trajectories on the Barthel Index (BI) scale but not on other stroke scales. This study demonstrates for the first time the feasibility of using individualized connectivity analyses in differentiating unique phenotypes in rTMS treatment responses and recovery. This personalized connectomic approach may be utilized in the future to better understand patient recovery trajectories with neuromodulatory treatment.
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Affiliation(s)
- Rong Chen
- The First Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, United States
| | - Brennan Cook
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, United States
| | - Lichun Sun
- The First Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Xiaolong Wang
- The First Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Yujie Li
- The First Affiliated Hospital of Hainan Medical University, Haikou, Hainan, China
| | - Xiaorong Hu
- Xijia Medical Technology Company Limited, Shenzhen, China
| | - Xia Zhang
- Xijia Medical Technology Company Limited, Shenzhen, China
- International Joint Research Center on Precision Brain Medicine, XD Group Hospital, Xi'an, Shaanxi, China
| | - Michael E. Sughrue
- International Joint Research Center on Precision Brain Medicine, XD Group Hospital, Xi'an, Shaanxi, China
- Omniscient Neurotechnology, Sydney, NSW, Australia
- Cingulum Health, Sydney, NSW, Australia
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Dadario NB, Tanglay O, Sughrue ME. Deconvoluting human Brodmann area 8 based on its unique structural and functional connectivity. Front Neuroanat 2023; 17:1127143. [PMID: 37426900 PMCID: PMC10323427 DOI: 10.3389/fnana.2023.1127143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 05/23/2023] [Indexed: 07/11/2023] Open
Abstract
Brodmann area 8 (BA8) is traditionally defined as the prefrontal region of the human cerebrum just anterior to the premotor cortices and enveloping most of the superior frontal gyrus. Early studies have suggested the frontal eye fields are situated at its most caudal aspect, causing many to consider BA8 as primarily an ocular center which controls contralateral gaze and attention. However, years of refinement in cytoarchitectural studies have challenged this traditional anatomical definition, providing a refined definition of its boundaries with neighboring cortical areas and the presence of meaningful subdivisions. Furthermore, functional imaging studies have suggested its involvement in a diverse number of higher-order functions, such as motor, cognition, and language. Thus, our traditional working definition of BA8 has likely been insufficient to truly understand the complex structural and functional significance of this area. Recently, large-scale multi-modal neuroimaging approaches have allowed for improved mapping of the neural connectivity of the human brain. Insight into the structural and functional connectivity of the brain connectome, comprised of large-scale brain networks, has allowed for greater understanding of complex neurological functioning and pathophysiological diseases states. Simultaneously, the structural and functional connectivity of BA8 has recently been highlighted in various neuroimaging studies and detailed anatomic dissections. However, while Brodmann's nomenclature is still widely used today, such as for clinical discussions and the communication of research findings, the importance of the underlying connectivity of BA8 requires further review.
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Affiliation(s)
- Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, United States
| | - Onur Tanglay
- Omniscient Neurotechnology, Sydney, NSW, Australia
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Taylor H, Nicholas P, Hoy K, Bailey N, Tanglay O, Young IM, Dobbin L, Doyen S, Sughrue ME, Fitzgerald PB. Functional connectivity analysis of the depression connectome provides potential markers and targets for transcranial magnetic stimulation. J Affect Disord 2023; 329:539-547. [PMID: 36841298 DOI: 10.1016/j.jad.2023.02.082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 02/02/2023] [Accepted: 02/19/2023] [Indexed: 02/27/2023]
Abstract
BACKGROUND Despite efforts to improve targeting accuracy of the dorsolateral prefrontal cortex (DLPFC) as a repetitive transcranial magnetic stimulation (rTMS) target for Major Depressive Disorder (MDD), the heterogeneity in clinical response remains unexplained. OBJECTIVE We sought to compare the patterns of functional connectivity from the DLPFC treatment site in patients with MDD who were TMS responders to those who were TMS non-responders. METHODS Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI, and diffusion weighted imaging scans were obtained from 37 participants before they underwent a course of rTMS to left Brodmann area 46. A novel machine learning method was utilized to identify brain regions associated with each item of the Beck's Depression Inventory II (BDI-II), and for 26 participants who underwent rTMS treatment over the left Brodmann area 46, identify regions differentiating rTMS responders and non-responders. RESULTS Nine parcels of the Human Connectome Project Multimodal Parcellation Atlas matched to at least three items of the Beck's Depression Inventory II (BDI-II) as predictors of response to rTMS, with many in the temporal, parietal and cingulate cortices. Additionally, pre-treatment mapping for 17 items of the BDI-II demonstrated significant variability in symptom to parcel mapping. When parcels associated with symptom presence and symptom resolution were compared, 15 parcels were uniquely associated with resolution (potential targets), and 12 parcels were associated with both symptom presence and resolution (blockers or biomarkers). CONCLUSIONS Machine learning approaches show promise for the development of pathoanatomical diagnosis and treatment algorithms for MDD. Prospective studies are required to facilitate clinical translation.
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Affiliation(s)
- Hugh Taylor
- Omniscient Neurotechnology, Sydney, Australia
| | | | - Kate Hoy
- Central Clinical School Department of Psychiatry, Monash University, Camberwell, Victoria, Australia; Bionics Institute, 384-388 Albert St, East Melbourne, Vic 3002, Australia
| | - Neil Bailey
- Central Clinical School Department of Psychiatry, Monash University, Camberwell, Victoria, Australia; Monarch Research Institute Monarch Mental Health Group, Sydney, New South Wales, Australia; School of Medicine and Psychology, The Australian National University, Canberra, ACT, Australia
| | | | | | | | | | | | - Paul B Fitzgerald
- School of Medicine and Psychology, The Australian National University, Canberra, ACT, Australia
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Gou C, Yang S, Hou Q, Rudder P, Tanglay O, Young I, Peng T, He W, Yang L, Osipowicz K, Doyen S, Mansouri N, Sughrue ME, Wang X. Functional connectivity of the language area in migraine: a preliminary classification model. BMC Neurol 2023; 23:142. [PMID: 37016325 PMCID: PMC10071619 DOI: 10.1186/s12883-023-03183-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 03/25/2023] [Indexed: 04/06/2023] Open
Abstract
BACKGROUND Migraine is a complex disorder characterized by debilitating headaches. Despite its prevalence, its pathophysiology remains unknown, with subsequent gaps in diagnosis and treatment. We combined machine learning with connectivity analysis and applied a whole-brain network approach to identify potential targets for migraine diagnosis and treatment. METHODS Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI(rfMRI), and diffusion weighted scans were obtained from 31 patients with migraine, and 17 controls. A recently developed machine learning technique, Hollow Tree Super (HoTS) was used to classify subjects into diagnostic groups based on functional connectivity (FC) and derive networks and parcels contributing to the model. PageRank centrality analysis was also performed on the structural connectome to identify changes in hubness. RESULTS Our model attained an area under the receiver operating characteristic curve (AUC-ROC) of 0.68, which rose to 0.86 following hyperparameter tuning. FC of the language network was most predictive of the model's classification, though patients with migraine also demonstrated differences in the accessory language, visual and medial temporal regions. Several analogous regions in the right hemisphere demonstrated changes in PageRank centrality, suggesting possible compensation. CONCLUSIONS Although our small sample size demands caution, our preliminary findings demonstrate the utility of our method in providing a network-based perspective to diagnosis and treatment of migraine.
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Affiliation(s)
- Chen Gou
- Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, 637000, China
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Shuangfeng Yang
- Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, 637000, China
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Qianmei Hou
- Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, 637000, China
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Peter Rudder
- Omniscient Neurotechnology, Sydney, NSW, 2000, Australia
| | - Onur Tanglay
- Omniscient Neurotechnology, Sydney, NSW, 2000, Australia
| | - Isabella Young
- Omniscient Neurotechnology, Sydney, NSW, 2000, Australia
| | - Tingting Peng
- Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, 637000, China
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Weiwei He
- Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, 637000, China
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China
| | - Liuyi Yang
- Shenzhen Xijia Medical Technology Company, Shenzhen, Guangdong Province, 518052, China
| | | | - Stephane Doyen
- Omniscient Neurotechnology, Sydney, NSW, 2000, Australia
| | - Negar Mansouri
- Omniscient Neurotechnology, Sydney, NSW, 2000, Australia
| | | | - Xiaoming Wang
- Institute of Neurological Diseases, North Sichuan Medical College, Nanchong, 637000, China.
- Department of Neurology, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, China.
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Young IM, Taylor HM, Nicholas PJ, Mackenzie A, Tanglay O, Dadario NB, Osipowicz K, Davis E, Doyen S, Teo C, Sughrue ME. An agile, data-driven approach for target selection in rTMS therapy for anxiety symptoms: Proof of concept and preliminary data for two novel targets. Brain Behav 2023; 13:e2914. [PMID: 36949668 PMCID: PMC10175990 DOI: 10.1002/brb3.2914] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 12/04/2022] [Accepted: 01/22/2023] [Indexed: 03/24/2023] Open
Abstract
INTRODUCTION Data-driven approaches to transcranial magnetic stimulation (TMS) might yield more consistent and symptom-specific results based on individualized functional connectivity analyses compared to previous traditional approaches due to more precise targeting. We provide a proof of concept for an agile target selection paradigm based on using connectomic methods that can be used to detect patient-specific abnormal functional connectivity, guide treatment aimed at the most abnormal regions, and optimize the rapid development of new hypotheses for future study. METHODS We used the resting-state functional MRI data of 28 patients with medically refractory generalized anxiety disorder to perform agile target selection based on abnormal functional connectivity patterns between the Default Mode Network (DMN) and Central Executive Network (CEN). The most abnormal areas of connectivity within these regions were selected for subsequent targeted TMS treatment by a machine learning based on an anomalous functional connectivity detection matrix. Areas with mostly hyperconnectivity were stimulated with continuous theta burst stimulation and the converse with intermittent theta burst stimulation. An image-guided accelerated theta burst stimulation paradigm was used for treatment. RESULTS Areas 8Av and PGs demonstrated consistent abnormalities, particularly in the left hemisphere. Significant improvements were demonstrated in anxiety symptoms, and few, minor complications were reported (fatigue (n = 2) and headache (n = 1)). CONCLUSIONS Our study suggests that a left-lateralized DMN is likely the primary functional network disturbed in anxiety-related disorders, which can be improved by identifying and targeting abnormal regions with a rapid, data-driven, agile aTBS treatment on an individualized basis.
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Grants
- Omniscient Neurotechnology provided support in the form of salaries for authors IY, HT, PN, AM, OT, KO, SD, MS, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. This research did not receive any other specific grant from funding agencies in the public, commercial, or not-for-profit sectors
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Affiliation(s)
- Isabella M Young
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
- Cingulum Health, Sydney, New South Wales, Australia
| | - Hugh M Taylor
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | | | - Alana Mackenzie
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | - Onur Tanglay
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | - Nicholas B Dadario
- Rutgers Robert Wood Johnson School of Medicine, New Brunswick, New Jersey
| | - Karol Osipowicz
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | - Ethan Davis
- Cingulum Health, Sydney, New South Wales, Australia
| | - Stephane Doyen
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | - Charles Teo
- Cingulum Health, Sydney, New South Wales, Australia
| | - Michael E Sughrue
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
- Cingulum Health, Sydney, New South Wales, Australia
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Osipowicz K, Profyris C, Mackenzie A, Nicholas P, Rudder P, Taylor HM, Young IM, Joyce AW, Dobbin L, Tanglay O, Thompson L, Mashilwane T, Sughrue ME, Doyen S. Real world demonstration of hand motor mapping using the structural connectivity atlas. Clin Neurol Neurosurg 2023; 228:107679. [PMID: 36965417 DOI: 10.1016/j.clineuro.2023.107679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 03/12/2023] [Accepted: 03/14/2023] [Indexed: 03/18/2023]
Abstract
BACKGROUND Locating the hand-motor-cortex (HMC) is an essential component within many neurosurgeries. Despite advancements in these localization methods there are still downfalls for each. Additionally, the importance of presurgical planning calls for increasingly accurate and efficient methods of locating specific cortical regions. OBJECTIVE In this study we aimed to test the ability of the Structural Connectivity Atlas (SCA), a machine-learning based method to parcellate the human cortex, to locate the HMC in a small cohort study. METHODS Using MRI and DTI images obtained from adult subjects (n = 11), personalized brain maps were created for each individual based on a SCA paired with the Brainnetome region for the HMC. Subjects received single pulse TMS, over the HMC region through the use of a neuronavigation system. If they responded with motor movement, this was recorded. The SCA identified HMC region was compared to the visual-determined HMC through identifying the Omega fold on the Precentral Gyrus, which was completed by a trained neuroanatomist. A Kendall's Tau B correlation was conducted between anatomical match and visual movement. RESULTS This study concluded that the SCA was capable of locating the HMC in healthy and distorted brains. Overall, the SCA defined the anatomical area of the HMC in 90 % of subjects and triggered a motor response in 61 %. CONCLUSION The SCA could be suitable for incorporation into presurgical planning practices due to its ability to map anatomically abnormal brains. Further studies on larger cohorts and targeting different areas of cortex could be beneficial.
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12
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Dadario NB, Tanglay O, Stafford JF, Davis EJ, Young IM, Fonseka RD, Briggs RG, Yeung JT, Teo C, Sughrue ME. Topology of the lateral visual system: The fundus of the superior temporal sulcus and parietal area H connect nonvisual cerebrum to the lateral occipital lobe. Brain Behav 2023; 13:e2945. [PMID: 36912573 PMCID: PMC10097165 DOI: 10.1002/brb3.2945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 02/13/2023] [Accepted: 02/17/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND AND PURPOSE Mapping the topology of the visual system is critical for understanding how complex cognitive processes like reading can occur. We aim to describe the connectivity of the visual system to understand how the cerebrum accesses visual information in the lateral occipital lobe. METHODS Using meta-analytic software focused on task-based functional MRI studies, an activation likelihood estimation (ALE) of the visual network was created. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co-registered onto the ALE to identify the hub-like regions of the visual network. Diffusion Spectrum Imaging-based fiber tractography was performed to determine the structural connectivity of these regions with extraoccipital cortices. RESULTS The fundus of the superior temporal sulcus (FST) and parietal area H (PH) were identified as hub-like regions for the visual network. FST and PH demonstrated several areas of coactivation beyond the occipital lobe and visual network. Furthermore, these parcellations were highly interconnected with other cortical regions throughout extraoccipital cortices related to their nonvisual functional roles. A cortical model demonstrating connections to these hub-like areas was created. CONCLUSIONS FST and PH are two hub-like areas that demonstrate extensive functional coactivation and structural connections to nonvisual cerebrum. Their structural interconnectedness with language cortices along with the abnormal activation of areas commonly located in the temporo-occipital region in dyslexic individuals suggests possible important roles of FST and PH in the integration of information related to language and reading. Future studies should refine our model by examining the functional roles of these hub areas and their clinical significance.
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Affiliation(s)
- Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA
| | - Onur Tanglay
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | - Jordan F Stafford
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | | | | | - R Dineth Fonseka
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia
| | - Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | | | - Charles Teo
- Cingulum Health, Sydney, New South Wales, Australia
| | - Michael E Sughrue
- Omniscient Neurotechnology, Sydney, New South Wales, Australia.,Cingulum Health, Sydney, New South Wales, Australia.,Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia
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13
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Wang Y, Wang J, Su W, Hu H, Xia M, Zhang T, Xu L, Zhang X, Taylor H, Osipowicz K, Young IM, Lin YH, Nicholas P, Tanglay O, Sughrue ME, Tang Y, Doyen S. Symptom-circuit mappings of the schizophrenia connectome. Psychiatry Res 2023; 323:115122. [PMID: 36889161 DOI: 10.1016/j.psychres.2023.115122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 02/15/2023] [Accepted: 02/18/2023] [Indexed: 02/27/2023]
Abstract
OBJECTIVE This paper aims to model the anatomical circuits underlying schizophrenia symptoms, and to explore patterns of abnormal connectivity among brain networks affected by psychopathology. METHODS T1 magnetic resonance imaging (MRI), diffusion weighted imaging (DWI), and resting-state functional MRI (rsfMRI) were obtained from a total of 126 patients with schizophrenia who were recruited for the study. The images were processed using the Omniscient software (https://www.o8t. com). We further apply the use of the Hollow-tree Super (HoTS) method to gain insights into what brain regions had abnormal connectivity that might be linked to the symptoms of schizophrenia. RESULTS The Positive and Negative Symptom Scale is characterised into 6 factors. Each symptom is mapped with specific anatomical abnormalities and circuits. Comparison between factors reveals co-occurrence in parcels in Factor 1 and Factor 2. Multiple large-scale networks are involved in SCZ symptomatology, with functional connectivity within Default Mode Network (DMN) and Central Executive Network (CEN) regions most frequently associated with measures of psychopathology. CONCLUSION We present a summary of the relevant anatomy for regions of the cortical areas as part of a larger effort to understand its contribution in schizophrenia. This unique machine learning-type approach maps symptoms to specific brain regions and circuits by bridging the diagnostic subtypes and analysing the features of the connectome.
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Affiliation(s)
- Yingchan Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
| | - Wenjun Su
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Hao Hu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Mengqing Xia
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Lihua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Xia Zhang
- Xijia Medical Technology Company Limited, Shenzhen 518000, China; International Joint Research Center on Precision Brain Medicine, XD Group Hospital, Xi'an 710082, China
| | - Hugh Taylor
- Omniscient Neurotechnology, Sydney, Australia
| | | | | | - Yueh-Hsin Lin
- Department of Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | | | | | - Michael E Sughrue
- International Joint Research Center on Precision Brain Medicine, XD Group Hospital, Xi'an 710082, China; Omniscient Neurotechnology, Sydney, Australia
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
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14
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Tanglay O, Dadario NB, Chong EHN, Tang SJ, Young IM, Sughrue ME. Graph Theory Measures and Their Application to Neurosurgical Eloquence. Cancers (Basel) 2023; 15:556. [PMID: 36672504 PMCID: PMC9857081 DOI: 10.3390/cancers15020556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 01/04/2023] [Accepted: 01/14/2023] [Indexed: 01/18/2023] Open
Abstract
Improving patient safety and preserving eloquent brain are crucial in neurosurgery. Since there is significant clinical variability in post-operative lesions suffered by patients who undergo surgery in the same areas deemed compensable, there is an unknown degree of inter-individual variability in brain 'eloquence'. Advances in connectomic mapping efforts through diffusion tractography allow for utilization of non-invasive imaging and statistical modeling to graphically represent the brain. Extending the definition of brain eloquence to graph theory measures of hubness and centrality may help to improve our understanding of individual variability in brain eloquence and lesion responses. While functional deficits cannot be immediately determined intra-operatively, there has been potential shown by emerging technologies in mapping of hub nodes as an add-on to existing surgical navigation modalities to improve individual surgical outcomes. This review aims to outline and review current research surrounding novel graph theoretical concepts of hubness, centrality, and eloquence and specifically its relevance to brain mapping for pre-operative planning and intra-operative navigation in neurosurgery.
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Affiliation(s)
- Onur Tanglay
- UNSW School of Clinical Medicine, Faulty of Medicine and Health, University of New South Wales, Sydney, NSW 2052, Australia
- Omniscient Neurotechnology, Level 10/580 George Street, Sydney, NSW 2000, Australia
| | - Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, 125 Paterson St, New Brunswick, NJ 08901, USA
| | - Elizabeth H. N. Chong
- Yong Loo Lin School of Medicine, National University of Singapore, 10 Medical Dr, Singapore 117597, Singapore
| | - Si Jie Tang
- School of Medicine, University of California Davis, Sacramento, CA 95817, USA
| | - Isabella M. Young
- Omniscient Neurotechnology, Level 10/580 George Street, Sydney, NSW 2000, Australia
| | - Michael E. Sughrue
- Omniscient Neurotechnology, Level 10/580 George Street, Sydney, NSW 2000, Australia
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15
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Bian R, Huo M, Liu W, Mansouri N, Tanglay O, Young I, Osipowicz K, Hu X, Zhang X, Doyen S, Sughrue ME, Liu L. Connectomics underlying motor functional outcomes in the acute period following stroke. Front Aging Neurosci 2023; 15:1131415. [PMID: 36875697 PMCID: PMC9975347 DOI: 10.3389/fnagi.2023.1131415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Accepted: 01/30/2023] [Indexed: 02/17/2023] Open
Abstract
Objective Stroke remains the number one cause of morbidity in many developing countries, and while effective neurorehabilitation strategies exist, it remains difficult to predict the individual trajectories of patients in the acute period, making personalized therapies difficult. Sophisticated and data-driven methods are necessary to identify markers of functional outcomes. Methods Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI (rsfMRI), and diffusion weighted scans were obtained from 79 patients following stroke. Sixteen models were constructed to predict performance across six tests of motor impairment, spasticity, and activities of daily living, using either whole-brain structural or functional connectivity. Feature importance analysis was also performed to identify brain regions and networks associated with performance in each test. Results The area under the receiver operating characteristic curve ranged from 0.650 to 0.868. Models utilizing functional connectivity tended to have better performance than those utilizing structural connectivity. The Dorsal and Ventral Attention Networks were among the top three features in several structural and functional models, while the Language and Accessory Language Networks were most commonly implicated in structural models. Conclusions Our study highlights the potential of machine learning methods combined with connectivity analysis in predicting outcomes in neurorehabilitation and disentangling the neural correlates of functional impairments, though further longitudinal studies are necessary.
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Affiliation(s)
- Rong Bian
- Department of Rehabilitation, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Ming Huo
- University of Health and Rehabilitation Sciences, Qingdao, China
| | - Wan Liu
- Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | | | - Onur Tanglay
- Omniscient Neurotechnology, Sydney, NSW, Australia
| | | | | | - Xiaorong Hu
- Xijia Medical Technology Company Limited, Shenzhen, China
| | - Xia Zhang
- Xijia Medical Technology Company Limited, Shenzhen, China.,International Joint Research Center on Precision Brain Medicine, Xidian Group Hospital, Xi'an, China
| | | | - Michael E Sughrue
- Omniscient Neurotechnology, Sydney, NSW, Australia.,International Joint Research Center on Precision Brain Medicine, Xidian Group Hospital, Xi'an, China
| | - Li Liu
- Department of Rehabilitation, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
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16
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Kim SJ, Tanglay O, Chong EHN, Young IM, Fonseka RD, Taylor H, Nicholas P, Doyen S, Sughrue ME. Functional connectivity in ADHD children doing Go/No-Go tasks: An fMRI systematic review and meta-analysis. Transl Neurosci 2023; 14:20220299. [PMID: 38410259 PMCID: PMC10896184 DOI: 10.1515/tnsci-2022-0299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 07/01/2023] [Accepted: 07/10/2023] [Indexed: 02/28/2024] Open
Abstract
Attention deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders diagnosed in childhood. Two common features of ADHD are impaired behavioural inhibition and sustained attention. The Go/No-Go experimental paradigm with concurrent functional magnetic resonance imaging (fMRI) scanning has previously revealed important neurobiological correlates of ADHD such as the supplementary motor area and the prefrontal cortex. The coordinate-based meta-analysis combined with quantitative techniques, such as activation likelihood estimate (ALE) generation, provides an unbiased and objective method of summarising these data to understand the brain network architecture and connectivity in ADHD children. Go/No-Go task-based fMRI studies involving children and adolescent subjects were selected. Coordinates indicating foci of activation were collected to generate ALEs using threshold values (voxel-level: p < 0.001; cluster-level: p < 0.05). ALEs were matched to one of seven canonical brain networks based on the cortical parcellation scheme derived from the Human Connectome Project. Fourteen studies involving 457 children met the eligibility criteria. No significant convergence of Go/No-Go related brain activation was found for ADHD groups. Three significant ALE clusters were detected for brain activation relating to controls or ADHD < controls. Significant clusters were related to specific areas of the default mode network (DMN). Network-based analysis revealed less extensive DMN, dorsal attention network, and limbic network activation in ADHD children compared to controls. The presence of significant ALE clusters may be due to reduced homogeneity in the selected sample demographic and experimental paradigm. Further investigations regarding hemispheric asymmetry in ADHD subjects would be beneficial.
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Affiliation(s)
- Sihyong J Kim
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Onur Tanglay
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
- Omniscient Neurotechnology, Sydney, Australia
| | - Elizabeth H N Chong
- National University of Singapore Yong Loo Lin School of Medicine, Singapore, Singapore
| | | | - Rannulu D Fonseka
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Hugh Taylor
- Omniscient Neurotechnology, Sydney, Australia
| | | | | | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
- Omniscient Neurotechnology, Sydney, Australia
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17
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Young IM, Dadario NB, Tanglay O, Chen E, Cook B, Taylor HM, Crawford L, Yeung JT, Nicholas PJ, Doyen S, Sughrue ME. Connectivity Model of the Anatomic Substrates and Network Abnormalities in Major Depressive Disorder: A Coordinate Meta-Analysis of Resting-State Functional Connectivity. Journal of Affective Disorders Reports 2023. [DOI: 10.1016/j.jadr.2023.100478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
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18
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Muacevic A, Adler JR, Young IM, Yeung JT, Teo C, Sughrue ME. Delayed, Progressive Multivessel Occlusion After Resection of a Recurrent Glioma. Cureus 2022; 14:e33019. [PMID: 36721529 PMCID: PMC9879796 DOI: 10.7759/cureus.33019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/27/2022] [Indexed: 12/29/2022] Open
Abstract
Glioblastoma multiforme (GBM) is one of the most common primary brain tumors with an aggressive natural history consistent with a median survival of less than two years. Most clinical research has primarily focused on improving overall survival through aggressive cytoreductive surgery and adjuvant radiochemotherapy. However, far less clinical guidance has been given for unexpected instances of neurologic decline following safe glioma resection in the setting of vascular etiology. Here, we report a 50-year-old man who presented to our clinic with a seizure. His preoperative magnetic resonance imaging (MRI) demonstrated a left hippocampal glioblastoma. Ten months following total resection, the patient presented again with rapid loss of vision and hemorrhagic papilledema. An MRI demonstrated a recurrence of his glioma, which was partially resected with no complications. Eight days after surgery, the patient suddenly became unresponsive and imaging revealed moderate blood in the resection cavity, which was evacuated in the operating room. Follow-up scans showed a posterior cerebral artery infarction, and two days later, a middle cerebral artery infarction, upon which care was withdrawn. We do not propose a mechanism by which this delayed ischemia occurred, especially as the middle cerebral artery was not damaged during surgery, however, we note that delayed ischemia may be one mechanism of damage following glioma resection, which should be studied further to improve patient outcomes.
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19
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Young IM, Osipowicz K, Mackenzie A, Clarke O, Taylor H, Nicholas P, Ryan M, Holle J, Tanglay O, Doyen S, Sughrue ME. Comparison of consistency between image guided and craniometric transcranial magnetic stimulation coil placement. Brain Stimul 2022; 15:1465-1466. [PMID: 36309343 DOI: 10.1016/j.brs.2022.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 10/16/2022] [Accepted: 10/20/2022] [Indexed: 12/30/2022] Open
Affiliation(s)
| | | | | | | | - Hugh Taylor
- Omniscient Neurotechnology, Sydney, 2000, Australia
| | | | - Mark Ryan
- Cingulum Health, Rosebery, 2018, Australia
| | | | - Onur Tanglay
- Omniscient Neurotechnology, Sydney, 2000, Australia
| | | | - Michael E Sughrue
- Omniscient Neurotechnology, Sydney, 2000, Australia; Cingulum Health, Rosebery, 2018, Australia.
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20
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Shen Y, Lu Q, Zhang T, Yan H, Mansouri N, Osipowicz K, Tanglay O, Young I, Doyen S, Lu X, Zhang X, Sughrue ME, Wang T. Use of machine learning to identify functional connectivity changes in a clinical cohort of patients at risk for dementia. Front Aging Neurosci 2022; 14:962319. [PMID: 36118683 PMCID: PMC9475065 DOI: 10.3389/fnagi.2022.962319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveProgressive conditions characterized by cognitive decline, including mild cognitive impairment (MCI) and subjective cognitive decline (SCD) are clinical conditions representing a major risk factor to develop dementia, however, the diagnosis of these pre-dementia conditions remains a challenge given the heterogeneity in clinical trajectories. Earlier diagnosis requires data-driven approaches for improved and targeted treatment modalities.MethodsNeuropsychological tests, baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI (rsfMRI), and diffusion weighted scans were obtained from 35 patients with SCD, 19 with MCI, and 36 age-matched healthy controls (HC). A recently developed machine learning technique, Hollow Tree Super (HoTS) was utilized to classify subjects into diagnostic categories based on their FC, and derive network and parcel-based FC features contributing to each model. The same approach was used to identify features associated with performance in a range of neuropsychological tests. We concluded our analysis by looking at changes in PageRank centrality (a measure of node hubness) between the diagnostic groups.ResultsSubjects were classified into diagnostic categories with a high area under the receiver operating characteristic curve (AUC-ROC), ranging from 0.73 to 0.84. The language networks were most notably associated with classification. Several central networks and sensory brain regions were predictors of poor performance in neuropsychological tests, suggesting maladaptive compensation. PageRank analysis highlighted that basal and limbic deep brain region, along with the frontal operculum demonstrated a reduction in centrality in both SCD and MCI patients compared to controls.ConclusionOur methods highlight the potential to explore the underlying neural networks contributing to the cognitive changes and neuroplastic responses in prodromal dementia.
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Affiliation(s)
- Ying Shen
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China
| | - Qian Lu
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China
| | - Tianjiao Zhang
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hailang Yan
- Department of Radiology, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China
| | | | | | - Onur Tanglay
- Omniscient Neurotechnology, Sydney, NSW, Australia
| | | | | | - Xi Lu
- Department of Rehabilitation Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Xia Zhang
- International Joint Research Center on Precision Brain Medicine, XD Group Hospital, Xi’an, China
- Shenzhen Xijia Medical Technology Company, Shenzhen, China
| | - Michael E. Sughrue
- Omniscient Neurotechnology, Sydney, NSW, Australia
- International Joint Research Center on Precision Brain Medicine, XD Group Hospital, Xi’an, China
- Michael E. Sughrue,
| | - Tong Wang
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Tong Wang,
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Lu Q, Zhang W, Yan H, Mansouri N, Tanglay O, Osipowicz K, Joyce AW, Young IM, Zhang X, Doyen S, Sughrue ME, He C. Connectomic disturbances underlying insomnia disorder and predictors of treatment response. Front Hum Neurosci 2022; 16:960350. [PMID: 36034119 PMCID: PMC9399490 DOI: 10.3389/fnhum.2022.960350] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 07/19/2022] [Indexed: 01/23/2023] Open
Abstract
ObjectiveDespite its prevalence, insomnia disorder (ID) remains poorly understood. In this study, we used machine learning to analyze the functional connectivity (FC) disturbances underlying ID, and identify potential predictors of treatment response through recurrent transcranial magnetic stimulation (rTMS) and pharmacotherapy.Materials and methods51 adult patients with chronic insomnia and 42 healthy age and education matched controls underwent baseline anatomical T1 magnetic resonance imaging (MRI), resting-stage functional MRI (rsfMRI), and diffusion weighted imaging (DWI). Imaging was repeated for 24 ID patients following four weeks of treatment with pharmacotherapy, with or without rTMS. A recently developed machine learning technique, Hollow Tree Super (HoTS) was used to classify subjects into ID and control groups based on their FC, and derive network and parcel-based FC features contributing to each model. The number of FC anomalies within each network was also compared between responders and non-responders using median absolute deviation at baseline and follow-up.ResultsSubjects were classified into ID and control with an area under the receiver operating characteristic curve (AUC-ROC) of 0.828. Baseline FC anomaly counts were higher in responders than non-responders. Response as measured by the Insomnia Severity Index (ISI) was associated with a decrease in anomaly counts across all networks, while all networks showed an increase in anomaly counts when response was measured using the Pittsburgh Sleep Quality Index. Overall, responders also showed greater change in all networks, with the Default Mode Network demonstrating the greatest change.ConclusionMachine learning analysis into the functional connectome in ID may provide useful insight into diagnostic and therapeutic targets.
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Affiliation(s)
- Qian Lu
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China
| | - Wentong Zhang
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China
| | - Hailang Yan
- Department of Radiology, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China
| | | | - Onur Tanglay
- Omniscient Neurotechnology, Sydney, NSW, Australia
| | | | | | | | - Xia Zhang
- International Joint Research Center on Precision Brain Medicine, XD Group Hospital, Xi’an, China
- Shenzhen Xijia Medical Technology Company, Shenzhen, China
| | | | - Michael E. Sughrue
- Omniscient Neurotechnology, Sydney, NSW, Australia
- International Joint Research Center on Precision Brain Medicine, XD Group Hospital, Xi’an, China
- Michael E. Sughrue,
| | - Chuan He
- Department of Rehabilitation Medicine, The Affiliated Jiangsu Shengze Hospital of Nanjing Medical University, Suzhou, China
- *Correspondence: Chuan He,
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22
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Lan Q, Sughrue ME, Briggs RG. Minimally invasive keyhole techniques for resection of giant intracranial tumors. Chin Neurosurg J 2022; 8:19. [PMID: 35932083 PMCID: PMC9354442 DOI: 10.1186/s41016-022-00289-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 07/05/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
While keyhole neurosurgery is increasingly utilized in the operating room, there are few reports regarding the use of keyhole techniques to resect giant intracranial tumors. The feasibility and technique of that were discussed in this paper.
Methods
We retrospectively reviewed 95 consecutive patients who were admitted to our service between February 2012 and September 2017 with a maximum intracranial tumor diameter >5 cm. Keyhole approaches were used to resect these tumors in each case, including supraorbital, subtemporal, suboccipital, retromastoid, frontal, temporal, occipital, parietal, pterional, a combined temporo-parietal keyhole approach, and an approach via the longitudinal fissure.
Results
We achieved gross total resection in 68/95 cases (71.6%) and subtotal resection in 27/95 cases (28.4%). No surgical death or severe disabilities such as coma and limb dyskinesia occurred following surgery. At the time of discharge, 8 patients had complications related to impaired cranial nerve function. In addition, 2 patients developed hydrocephalus requiring ventriculo-peritoneal shunt placement, and 4 patients developed a postoperative CSF leak requiring surgical intervention.
Conclusion
With meticulous design and reasonable selection, resection of giant intracranial tumors utilizing minimally invasive keyhole approaches can be done safely with satisfactory surgical outcomes.
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Briggs RG, Young IM, Dadario NB, Fonseka RD, Hormovas J, Allan P, Larsen ML, Lin YH, Tanglay O, Maxwell BD, Conner AK, Stafford JF, Glenn CA, Teo C, Sughrue ME. Parcellation-based tractographic modeling of the salience network through meta-analysis. Brain Behav 2022; 12:e2646. [PMID: 35733239 PMCID: PMC9304834 DOI: 10.1002/brb3.2646] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 02/09/2022] [Accepted: 04/07/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND The salience network (SN) is a transitory mediator between active and passive states of mind. Multiple cortical areas, including the opercular, insular, and cingulate cortices have been linked in this processing, though knowledge of network connectivity has been devoid of structural specificity. OBJECTIVE The current study sought to create an anatomically specific connectivity model of the neural substrates involved in the salience network. METHODS A literature search of PubMed and BrainMap Sleuth was conducted for resting-state and task-based fMRI studies relevant to the salience network according to PRISMA guidelines. Publicly available meta-analytic software was utilized to extract relevant fMRI data for the creation of an activation likelihood estimation (ALE) map and relevant parcellations from the human connectome project overlapping with the ALE data were identified for inclusion in our SN model. DSI-based fiber tractography was then performed on publicaly available data from healthy subjects to determine the structural connections between cortical parcellations comprising the network. RESULTS Nine cortical regions were found to comprise the salience network: areas AVI (anterior ventral insula), MI (middle insula), FOP4 (frontal operculum 4), FOP5 (frontal operculum 5), a24pr (anterior 24 prime), a32pr (anterior 32 prime), p32pr (posterior 32 prime), and SCEF (supplementary and cingulate eye field), and 46. The frontal aslant tract was found to connect the opercular-insular cluster to the middle cingulate clusters of the network, while mostly short U-fibers connected adjacent nodes of the network. CONCLUSION Here we provide an anatomically specific connectivity model of the neural substrates involved in the salience network. These results may serve as an empiric basis for clinical translation in this region and for future study which seeks to expand our understanding of how specific neural substrates are involved in salience processing and guide subsequent human behavior.
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Affiliation(s)
- Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | | | - Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, USA
| | - R Dineth Fonseka
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia
| | - Jorge Hormovas
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia
| | - Parker Allan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Micah L Larsen
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Yueh-Hsin Lin
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia
| | - Onur Tanglay
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia
| | - B David Maxwell
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Andrew K Conner
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Jordan F Stafford
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Chad A Glenn
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Charles Teo
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia.,Omniscient Neurotechnology, Sydney, New South Wales, Australia
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Shahab QS, Young IM, Dadario NB, Tanglay O, Nicholas PJ, Lin YH, Fonseka RD, Yeung JT, Bai MY, Teo C, Doyen S, Sughrue ME. A connectivity model of the anatomic substrates underlying Gerstmann syndrome. Brain Commun 2022; 4:fcac140. [PMID: 35706977 PMCID: PMC9189613 DOI: 10.1093/braincomms/fcac140] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 04/05/2022] [Accepted: 05/26/2022] [Indexed: 11/29/2022] Open
Abstract
The Gerstmann syndrome is a constellation of neurological deficits that include agraphia, acalculia, left–right discrimination and finger agnosia. Despite a growing interest in this clinical phenomenon, there remains controversy regarding the specific neuroanatomic substrates involved. Advancements in data-driven, computational modelling provides an opportunity to create a unified cortical model with greater anatomic precision based on underlying structural and functional connectivity across complex cognitive domains. A literature search was conducted for healthy task-based functional MRI and PET studies for the four cognitive domains underlying Gerstmann’s tetrad using the electronic databases PubMed, Medline, and BrainMap Sleuth (2.4). Coordinate-based, meta-analytic software was utilized to gather relevant regions of interest from included studies to create an activation likelihood estimation (ALE) map for each cognitive domain. Machine-learning was used to match activated regions of the ALE to the corresponding parcel from the cortical parcellation scheme previously published under the Human Connectome Project (HCP). Diffusion spectrum imaging-based tractography was performed to determine the structural connectivity between relevant parcels in each domain on 51 healthy subjects from the HCP database. Ultimately 102 functional MRI studies met our inclusion criteria. A frontoparietal network was found to be involved in the four cognitive domains: calculation, writing, finger gnosis, and left–right orientation. There were three parcels in the left hemisphere, where the ALE of at least three cognitive domains were found to be overlapping, specifically the anterior intraparietal area, area 7 postcentral (7PC) and the medial intraparietal sulcus. These parcels surround the anteromedial portion of the intraparietal sulcus. Area 7PC was found to be involved in all four domains. These regions were extensively connected in the intraparietal sulcus, as well as with a number of surrounding large-scale brain networks involved in higher-order functions. We present a tractographic model of the four neural networks involved in the functions which are impaired in Gerstmann syndrome. We identified a ‘Gerstmann Core’ of extensively connected functional regions where at least three of the four networks overlap. These results provide clinically actionable and precise anatomic information which may help guide clinical translation in this region, such as during resective brain surgery in or near the intraparietal sulcus, and provides an empiric basis for future study.
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Affiliation(s)
- Qazi S. Shahab
- University of New South Wales School of Medicine, , 2052, Sydney, Australia
| | | | - Nicholas B. Dadario
- Rutgers Robert Wood Johnson Medical School , New Brunswick, New Jersey 08901, United States of America
| | - Onur Tanglay
- Omniscient Neurotechnology , Sydney, 2000, Australia
| | | | - Yueh-Hsin Lin
- Prince of Wales Private Hospital Centre for Minimally Invasive Neurosurgery, , Randwick, 2031, Australia
| | - R. Dineth Fonseka
- Prince of Wales Private Hospital Centre for Minimally Invasive Neurosurgery, , Randwick, 2031, Australia
| | - Jacky T. Yeung
- Prince of Wales Private Hospital Centre for Minimally Invasive Neurosurgery, , Randwick, 2031, Australia
| | - Michael Y. Bai
- Prince of Wales Private Hospital Centre for Minimally Invasive Neurosurgery, , Randwick, 2031, Australia
| | - Charles Teo
- Prince of Wales Private Hospital Centre for Minimally Invasive Neurosurgery, , Randwick, 2031, Australia
| | | | - Michael E. Sughrue
- Omniscient Neurotechnology , Sydney, 2000, Australia
- Prince of Wales Private Hospital Centre for Minimally Invasive Neurosurgery, , Randwick, 2031, Australia
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25
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Dong N, Fu C, Li R, Zhang W, Liu M, Xiao W, Taylor HM, Nicholas PJ, Tanglay O, Young IM, Osipowicz KZ, Sughrue ME, Doyen SP, Li Y. Machine Learning Decomposition of the Anatomy of Neuropsychological Deficit in Alzheimer’s Disease and Mild Cognitive Impairment. Front Aging Neurosci 2022; 14:854733. [PMID: 35592700 PMCID: PMC9110794 DOI: 10.3389/fnagi.2022.854733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 03/22/2022] [Indexed: 12/03/2022] Open
Abstract
Objective Alzheimer’s Disease (AD) is a progressive condition characterized by cognitive decline. AD is often preceded by mild cognitive impairment (MCI), though the diagnosis of both conditions remains a challenge. Early diagnosis of AD, and prediction of MCI progression require data-driven approaches to improve patient selection for treatment. We used a machine learning tool to predict performance in neuropsychological tests in AD and MCI based on functional connectivity using a whole-brain connectome, in an attempt to identify network substrates of cognitive deficits in AD. Methods Neuropsychological tests, baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI, and diffusion weighted imaging scans were obtained from 149 MCI, and 85 AD patients; and 140 cognitively unimpaired geriatric participants. A novel machine learning tool, Hollow Tree Super (HoTS) was utilized to extract feature importance from each machine learning model to identify brain regions that were associated with deficit and absence of deficit for 11 neuropsychological tests. Results 11 models attained an area under the receiver operating curve (AUC-ROC) greater than 0.65, while five models had an AUC-ROC ≥ 0.7. 20 parcels of the Human Connectome Project Multimodal Parcelation Atlas matched to poor performance in at least two neuropsychological tests, while 14 parcels were associated with good performance in at least two tests. At a network level, most parcels predictive of both presence and absence of deficit were affiliated with the Central Executive Network, Default Mode Network, and the Sensorimotor Networks. Segregating predictors by the cognitive domain associated with each test revealed areas of coherent overlap between cognitive domains, with the parcels providing possible markers to screen for cognitive impairment. Conclusion Approaches such as ours which incorporate whole-brain functional connectivity and harness feature importance in machine learning models may aid in identifying diagnostic and therapeutic targets in AD.
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Affiliation(s)
- Ningxin Dong
- Department of Medical Imaging, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Changyong Fu
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Renren Li
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Wei Zhang
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Meng Liu
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Weixin Xiao
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | | | | | - Onur Tanglay
- Omniscient Neurotechnology, Sydney, NSW, Australia
| | | | | | - Michael E. Sughrue
- Omniscient Neurotechnology, Sydney, NSW, Australia
- International Joint Research Center on Precision Brain Medicine, XD Group Hospital, Xi’an, China
| | | | - Yunxia Li
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
- *Correspondence: Yunxia Li,
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Nicholas PJ, To A, Tanglay O, Young IM, Sughrue ME, Doyen S. Using a ResNet-18 Network to Detect Features of Alzheimer’s Disease on Functional Magnetic Resonance Imaging: A Failed Replication. Comment on Odusami et al. Analysis of Features of Alzheimer’s Disease: Detection of Early Stage from Functional Brain Changes in Magnetic Resonance Images Using a Finetuned ResNet18 Network. Diagnostics 2021, 11, 1071. Diagnostics (Basel) 2022; 12:diagnostics12051094. [PMID: 35626249 PMCID: PMC9139912 DOI: 10.3390/diagnostics12051094] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 02/01/2022] [Accepted: 02/17/2022] [Indexed: 11/30/2022] Open
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27
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Dadario NB, Sughrue ME. Should Neurosurgeons Try to Preserve Non-Traditional Brain Networks? A Systematic Review of the Neuroscientific Evidence. J Pers Med 2022; 12:jpm12040587. [PMID: 35455703 PMCID: PMC9029431 DOI: 10.3390/jpm12040587] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 03/30/2022] [Accepted: 04/03/2022] [Indexed: 12/25/2022] Open
Abstract
The importance of large-scale brain networks in higher-order human functioning is well established in neuroscience, but has yet to deeply penetrate neurosurgical thinking due to concerns of clinical relevance. Here, we conducted the first systematic review examining the clinical importance of non-traditional, large-scale brain networks, including the default mode (DMN), central executive (CEN), salience (SN), dorsal attention (DAN), and ventral attention (VAN) networks. Studies which reported evidence of neurologic, cognitive, or emotional deficits in relation to damage or dysfunction in these networks were included. We screened 22,697 articles on PubMed, and 551 full-text articles were included and examined. Cognitive deficits were the most common symptom of network disturbances in varying amounts (36–56%), most frequently related to disruption of the DMN (n = 213) or some combination of DMN, CEN, and SN networks (n = 182). An increased proportion of motor symptoms was seen with CEN disruption (12%), and emotional (35%) or language/speech deficits (24%) with SN disruption. Disruption of the attention networks (VAN/DAN) with each other or the other networks mostly led to cognitive deficits (56%). A large body of evidence is available demonstrating the clinical importance of non-traditional, large-scale brain networks and suggests the need to preserve these networks is relevant for neurosurgical patients.
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Affiliation(s)
- Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA;
| | - Michael E. Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Randwick, NSW 2031, Australia
- Omniscient Neurotechnology, Sydney, NSW 2000, Australia
- Correspondence:
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Einstein EH, Dadario NB, Khilji H, Silverstein JW, Sughrue ME, D'Amico RS. Transcranial magnetic stimulation for post-operative neurorehabilitation in neuro-oncology: a review of the literature and future directions. J Neurooncol 2022; 157:435-443. [PMID: 35338454 DOI: 10.1007/s11060-022-03987-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 03/14/2022] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Transcranial magnetic stimulation (TMS) is a neuromodulation technology capable of targeted stimulation and inhibition of cortical areas. Repetitive TMS (rTMS) has demonstrated efficacy in the treatment of several neuropsychiatric disorders, and novel uses of rTMS for neurorehabilitation in patients with acute and chronic neurologic deficits are being investigated. However, studies to date have primarily focused on neurorehabilitation in stroke patients, with little data supporting its use for neurorehabilitation in brain tumor patients. METHODS We performed a review of the current available literature regarding uses of rTMS for neurorehabilitation in post-operative neuro-oncologic patients. RESULTS Data have demonstrated that rTMS is safe in the post-operative neuro-oncologic patient population, with minimal adverse effects and no documented seizures. The current evidence also demonstrates potential effectiveness in terms of neurorehabilitation of motor and language deficits. CONCLUSIONS Although data are overall limited, both safety and effectiveness have been demonstrated for the use of rTMS for neurorehabilitation in the neuro-oncologic population. More randomized controlled trials and specific comparisons of contralateral versus ipsilateral rTMS protocols should be explored. Further work may also focus on individualized, patient-specific TMS treatment protocols for optimal functional recovery.
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Affiliation(s)
- Evan H Einstein
- Department of Neurological Surgery, Lenox Hill Hospital/Donald and Barbara Zucker School of Medicine at Hofstra, New York, NY, USA.
| | - Nicholas B Dadario
- Robert Wood Johnson School of Medicine, Rutgers University, New Brunswick, NJ, USA
| | - Hamza Khilji
- Department of Neurological Surgery, Lenox Hill Hospital/Donald and Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
| | - Justin W Silverstein
- Department of Neurology, Lenox Hill Hospital/Donald and Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
- Neuro Protective Solutions, New York, NY, USA
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, NSW, Australia
| | - Randy S D'Amico
- Department of Neurological Surgery, Lenox Hill Hospital/Donald and Barbara Zucker School of Medicine at Hofstra, New York, NY, USA
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29
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Dadario NB, Nicholas P, Henkin A, Sin B, Dyer K, Sughrue ME, Doyen S. The Z-Shift: A Need for Quality Management System Level Testing and Standardization in Neuroimaging Pipelines. AJNR Am J Neuroradiol 2022; 43:320-323. [PMID: 35241419 PMCID: PMC8910812 DOI: 10.3174/ajnr.a7435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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30
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Poologaindran A, Profyris C, Young IM, Dadario NB, Ahsan SA, Chendeb K, Briggs RG, Teo C, Romero-Garcia R, Suckling J, Sughrue ME. Interventional neurorehabilitation for promoting functional recovery post-craniotomy: a proof-of-concept. Sci Rep 2022; 12:3039. [PMID: 35197490 PMCID: PMC8866464 DOI: 10.1038/s41598-022-06766-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 02/02/2022] [Indexed: 02/06/2023] Open
Abstract
The human brain is a highly plastic ‘complex’ network—it is highly resilient to damage and capable of self-reorganisation after a large perturbation. Clinically, neurological deficits secondary to iatrogenic injury have very few active treatments. New imaging and stimulation technologies, though, offer promising therapeutic avenues to accelerate post-operative recovery trajectories. In this study, we sought to establish the safety profile for ‘interventional neurorehabilitation’: connectome-based therapeutic brain stimulation to drive cortical reorganisation and promote functional recovery post-craniotomy. In n = 34 glioma patients who experienced post-operative motor or language deficits, we used connectomics to construct single-subject cortical networks. Based on their clinical and connectivity deficit, patients underwent network-specific transcranial magnetic stimulation (TMS) sessions daily over five consecutive days. Patients were then assessed for TMS-related side effects and improvements. 31/34 (91%) patients were successfully recruited and enrolled for TMS treatment within two weeks of glioma surgery. No seizures or serious complications occurred during TMS rehabilitation and 1-week post-stimulation. Transient headaches were reported in 4/31 patients but improved after a single session. No neurological worsening was observed while a clinically and statistically significant benefit was noted in 28/31 patients post-TMS. We present two clinical vignettes and a video demonstration of interventional neurorehabilitation. For the first time, we demonstrate the safety profile and ability to recruit, enroll, and complete TMS acutely post-craniotomy in a high seizure risk population. Given the lack of randomisation and controls in this study, prospective randomised sham-controlled stimulation trials are now warranted to establish the efficacy of interventional neurorehabilitation following craniotomy.
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Affiliation(s)
- Anujan Poologaindran
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.,The Alan Turing Institute, British Library, London, UK
| | - Christos Profyris
- Netcare Linksfield Hospital, Johannesburg, South Africa.,Department of Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Isabella M Young
- Department of Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Nicholas B Dadario
- Department of Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia.,Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, USA
| | - Syed A Ahsan
- Department of Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Kassem Chendeb
- Department of Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Robert G Briggs
- Department of Neurosurgery, University of Southern California, Los Angeles, CA, USA
| | - Charles Teo
- Department of Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Rafael Romero-Garcia
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - John Suckling
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.,The Alan Turing Institute, British Library, London, UK
| | - Michael E Sughrue
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK. .,Department of Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia.
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Doyen S, Nicholas P, Poologaindran A, Crawford L, Young IM, Romero‐Garcia R, Sughrue ME. Cover Image. Hum Brain Mapp 2022. [DOI: 10.1002/hbm.25485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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Tanglay O, Young IM, Dadario NB, Taylor HM, Nicholas PJ, Doyen S, Sughrue ME. Eigenvector PageRank difference as a measure to reveal topological characteristics of the brain connectome for neurosurgery. J Neurooncol 2022; 157:49-61. [PMID: 35119590 DOI: 10.1007/s11060-021-03935-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 12/23/2021] [Indexed: 12/16/2022]
Abstract
PURPOSE Applying graph theory to the human brain has the potential to help prognosticate the impacts of intracerebral surgery. Eigenvector (EC) and PageRank (PR) centrality are two related, but uniquely different measures of nodal centrality which may be utilized together to reveal varying neuroanatomical characteristics of the brain connectome. METHODS We obtained diffusion neuroimaging data from a healthy cohort (UCLA consortium for neuropsychiatric phenomics) and applied a personalized parcellation scheme to them. We ranked parcels based on weighted EC and PR, and then calculated the difference (EP difference) and correlation between the two metrics. We also compared the difference between the two metrics to the clustering coefficient. RESULTS While EC and PR were consistent for top and bottom ranking parcels, they differed for mid-ranking parcels. Parcels with a high EC centrality but low PR tended to be in the medial temporal and temporooccipital regions, whereas PR conferred greater importance to multi-modal association areas in the frontal, parietal and insular cortices. The EP difference showed a weak correlation with clustering coefficient, though there was significant individual variation. CONCLUSIONS The relationship between PageRank and eigenvector centrality can identify distinct topological characteristics of the brain connectome such as the presence of unimodal or multimodal association cortices. These results highlight how different graph theory metrics can be used alone or in combination to reveal unique neuroanatomical features for further clinical study.
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Affiliation(s)
- Onur Tanglay
- Omniscient Neurotechnology, Sydney, Australia.,Centre for Minimally Invasive Neurosurgery, Prince of Wales Hospital, Randwick, NSW, 2031, Australia
| | | | - Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, 08901, USA
| | | | | | | | - Michael E Sughrue
- Omniscient Neurotechnology, Sydney, Australia. .,Centre for Minimally Invasive Neurosurgery, Prince of Wales Hospital, Randwick, NSW, 2031, Australia.
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Dadario NB, Zaman A, Pandya M, Dlouhy BJ, Gunawardena MP, Sughrue ME, Teo C. Endoscopic-assisted surgical approach for butterfly glioma surgery. J Neurooncol 2022; 156:635-644. [PMID: 35032284 DOI: 10.1007/s11060-022-03945-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/04/2022] [Indexed: 11/24/2022]
Abstract
PURPOSE Gliomas that spread along the white matter tracts of the corpus callosum to both hemispheres have traditionally been considered surgically challenging largely due to the relative complexity of safely achieving complete resections. We present a series of endoscopic-assisted resections of butterfly gliomas with post-operative radiological assessment of EOR and clinical outcome data. METHODS Retrospective review of patients who underwent surgical resection of a butterfly glioma from 2007 to 2020. Butterfly gliomas were defined as gliomas, which appeared to arise from the corpus callosum with significant bilateral extension. All records were retrospectively reviewed with operative/clinical outcomes and complications recorded. RESULTS 70 patients who underwent an endoscopic-assisted transcortical or interhemispheric approach for butterfly glioma resection met inclusion criteria. A unilateral transcortical approach was used in 86% of cases and an interhemispheric approach in 14%. The endoscope enhanced the visualization of the contralateral hemisphere and allowed for resection of tumor, not reached by standard microscopic visualization, in 100% of cases. 90% of resections resulted in greater than a 95% resection rate. Neurological deficits mostly consisted of motor (10%) and memory (6%) deficits and were most common with posterior tumors of the splenium. CONCLUSION The endoscopic-assisted transcortical or interhemispheric approach for butterfly glioma resection is effective in achieving a greater than 95% resection with minimal complications. An angled approach allows careful maneuvering around complex anatomic structures and difficult corners, and should be examined further for its clinical benefits in a prospective manner.
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Affiliation(s)
- Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
| | - Ashraf Zaman
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Hospital, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia.,Garvan Institute of Medical Research, Sydney, Australia.,Faculty of Medicine, University of New South Wales, Sydney, Australia
| | | | - Brian J Dlouhy
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Hospital, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia.,Department of Neurosurgery, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, Iowa, 52242, USA
| | - Manuri P Gunawardena
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Hospital, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Hospital, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia
| | - Charles Teo
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Hospital, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia.
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34
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Dadario NB, Teo C, Sughrue ME. Insular gliomas and tractographic visualization of the connectome. Neurosurg Focus Video 2022; 6:V4. [PMID: 36284592 PMCID: PMC9555346 DOI: 10.3171/2021.10.focvid21194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 10/28/2021] [Indexed: 06/16/2023]
Abstract
In this video, the authors present a connectome-guided surgical resection of an insular glioma in a 39-year-old woman. Preoperative study with constrained spherical deconvolution (CSD)-based tractography revealed the surrounding brain connectome architecture around the tumor relevant for safe surgical resection. Connectomic information provided detailed maps of the surrounding language and salience networks, including eloquent white matter fibers and cortical regions, which were visualized intraoperatively with image guidance and artificial intelligence (AI)-based brain mapping software. Microsurgical dissection is presented with detailed discussion of the safe boundaries and angles of resection when entering the insular operculum defined by connectomic information. The video can be found here: https://stream.cadmore.media/r10.3171/2021.10.FOCVID21194.
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Affiliation(s)
- Nicholas B. Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey
| | - Charles Teo
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Randwick, New South Wales; and
| | - Michael E. Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Randwick, New South Wales; and
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
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Yeung JT, Young IM, Doyen S, Teo C, Sughrue ME. Changes in the Brain Connectome Following Repetitive Transcranial Magnetic Stimulation for Stroke Rehabilitation. Cureus 2021; 13:e19105. [PMID: 34858752 PMCID: PMC8614179 DOI: 10.7759/cureus.19105] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/27/2021] [Indexed: 11/09/2022] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a promising approach for post-stroke rehabilitation but there lacks a rationale strategy to plan, execute, and monitor treatment. We present a case of targeted rTMS using the Omniscient Infinitome software to devise targets for treatment in a post-stroke patient and describe the functional connectomic changes after treatment. A 19-year-old female with no medical history presented 19 months after suffering a left middle cerebral artery (MCA) superior division ischemic stroke, resulting in language impairment and diminished right upper extremity motor function. She underwent a resting-state MRI (rsMRI) with tractography and images were processed using the Omniscient Infinitome software. Analysis using the anomaly detection within the software enabled us to identify three targets for rTMS (left area 1, left area 45, and right area SFL). These areas were treated with 25 sessions of intermittent Theta Burst Stimulation (iTBS) over five days at 80% of motor threshold concomitantly with targeted physical therapy and speech therapy. At five months follow-up, her language and right upper extremity functions significantly improved. Her connectomic analysis revealed substantial neural changes, including normalization of the sensorimotor network, substantially thicker callosal fiber bundle connecting the two hemispheres, and increased cortical recruitment in her language network. We present the first description of robust connectomic alterations in a post-stroke patient following targeted rTMS treatment. Further studies on the use of rTMS with an emphasis on functional connectomics are warranted.
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Affiliation(s)
- Jacky T Yeung
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, AUS
| | | | | | - Charles Teo
- Neurological Surgery, Prince of Wales Private Hospital, University of New South Wales, Sydney, AUS.,Research, Omniscient Neurotechnology, Sydney, AUS
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, AUS.,Research, Omniscient Neurotechnology, Sydney, AUS
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O’Connor KP, Palejwala AH, Milton CK, Lu VM, Glenn CA, Sughrue ME, Conner AK. Laser Interstitial Thermal Therapy Case Series: Choosing the Correct Number of Fibers Depending on Lesion Size. Neurosurgery 2021. [DOI: 10.1093/neuros/opaa264_s159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Doyen S, Nicholas P, Poologaindran A, Crawford L, Young IM, Romero-Garcia R, Sughrue ME. Connectivity-based parcellation of normal and anatomically distorted human cerebral cortex. Hum Brain Mapp 2021; 43:1358-1369. [PMID: 34826179 PMCID: PMC8837585 DOI: 10.1002/hbm.25728] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 11/03/2021] [Accepted: 11/13/2021] [Indexed: 12/29/2022] Open
Abstract
For over a century, neuroscientists have been working toward parcellating the human cortex into distinct neurobiological regions. Modern technologies offer many parcellation methods for healthy cortices acquired through magnetic resonance imaging. However, these methods are suboptimal for personalized neurosurgical application given that pathology and resection distort the cerebrum. We sought to overcome this problem by developing a novel connectivity‐based parcellation approach that can be applied at the single‐subject level. Utilizing normative diffusion data, we first developed a machine‐learning (ML) classifier to learn the typical structural connectivity patterns of healthy subjects. Specifically, the Glasser HCP atlas was utilized as a prior to calculate the streamline connectivity between each voxel and each parcel of the atlas. Using the resultant feature vector, we determined the parcel identity of each voxel in neurosurgical patients (n = 40) and thereby iteratively adjusted the prior. This approach enabled us to create patient‐specific maps independent of brain shape and pathological distortion. The supervised ML classifier re‐parcellated an average of 2.65% of cortical voxels across a healthy dataset (n = 178) and an average of 5.5% in neurosurgical patients. Our patient dataset consisted of subjects with supratentorial infiltrating gliomas operated on by the senior author who then assessed the validity and practical utility of the re‐parcellated diffusion data. We demonstrate a rapid and effective ML parcellation approach to parcellation of the human cortex during anatomical distortion. Our approach overcomes limitations of indiscriminately applying atlas‐based registration from healthy subjects by employing a voxel‐wise connectivity approach based on individual data.
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Affiliation(s)
- Stephane Doyen
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | - Peter Nicholas
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | - Anujan Poologaindran
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.,The Alan Turing Institute, British Library, London, UK
| | - Lewis Crawford
- Omniscient Neurotechnology, Sydney, New South Wales, Australia
| | | | - Rafeael Romero-Garcia
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
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Noor H, Zaman A, Teo C, Sughrue ME. PODNL1 Methylation Serves as a Prognostic Biomarker and Associates with Immune Cell Infiltration and Immune Checkpoint Blockade Response in Lower-Grade Glioma. Int J Mol Sci 2021; 22:ijms222212572. [PMID: 34830454 PMCID: PMC8625785 DOI: 10.3390/ijms222212572] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 11/15/2021] [Accepted: 11/18/2021] [Indexed: 12/27/2022] Open
Abstract
Lower-grade glioma (LGG) is a diffuse infiltrative tumor of the central nervous system, which lacks targeted therapy. We investigated the role of Podocan-like 1 (PODNL1) methylation in LGG clinical outcomes using the TCGA-LGG transcriptomics dataset. We identified four PODNL1 CpG sites, cg07425555, cg26969888, cg18547299, and cg24354933, which were associated with unfavorable overall survival (OS) and disease-free survival (DFS) in univariate and multivariate analysis after adjusting for age, gender, tumor-grade, and IDH1-mutation. In multivariate analysis, the OS and DFS hazard ratios ranged from 0.44 to 0.58 (p < 0.001) and 0.62 to 0.72 (p < 0.001), respectively, for the four PODNL1 CpGs. Enrichment analysis of differential gene and protein expression and analysis of 24 infiltrating immune cell types showed significantly increased infiltration in LGGs and its histological subtypes with low-methylation levels of the PODNL1 CpGs. High PODNL1 expression and low-methylation subgroups of the PODNL1 CpG sites were associated with significantly increased PD-L1, PD-1, and CTLA4 expressions. PODNL1 methylation may thus be a potential indicator of immune checkpoint blockade response, and serve as a biomarker for determining prognosis and immune subtypes in LGG.
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Affiliation(s)
- Humaira Noor
- Cure Brain Cancer Biomarkers and Translational Research Group, Prince of Wales Clinical School, University of New South Wales, Sydney, NSW 2031, Australia
- Adult Cancer Program, Lowy Cancer Research Centre, UNSW Sydney, Randwick, NSW 2031, Australia
- Faculty of Medicine, University of New South Wales, Randwick, NSW 2031, Australia;
- Correspondence:
| | - Ashraf Zaman
- Faculty of Medicine, University of New South Wales, Randwick, NSW 2031, Australia;
- Garvan-Weizmann Centre for Cellular Genomics, Garvan Institute of Medical Research, Darlinghurst, Sydney, NSW 2010, Australia
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Randwick, NSW 2031, Australia; (C.T.); (M.E.S.)
| | - Charles Teo
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Randwick, NSW 2031, Australia; (C.T.); (M.E.S.)
| | - Michael E. Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Randwick, NSW 2031, Australia; (C.T.); (M.E.S.)
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Doyen S, Taylor H, Nicholas P, Crawford L, Young I, Sughrue ME. Hollow-tree super: A directional and scalable approach for feature importance in boosted tree models. PLoS One 2021; 16:e0258658. [PMID: 34695143 PMCID: PMC8544862 DOI: 10.1371/journal.pone.0258658] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 10/03/2021] [Indexed: 12/02/2022] Open
Abstract
Purpose Current limitations in methodologies used throughout machine-learning to investigate feature importance in boosted tree modelling prevent the effective scaling to datasets with a large number of features, particularly when one is investigating both the magnitude and directionality of various features on the classification into a positive or negative class. This manuscript presents a novel methodology, “Hollow-tree Super” (HOTS), designed to resolve and visualize feature importance in boosted tree models involving a large number of features. Further, this methodology allows for accurate investigation of the directionality and magnitude various features have on classification and incorporates cross-validation to improve the accuracy and validity of the determined features of importance. Methods Using the Iris dataset, we first highlight the characteristics of HOTS by comparing it to other commonly used techniques for feature importance, including Gini Importance, Partial Dependence Plots, and Permutation Importance, and explain how HOTS resolves the weaknesses present in these three strategies for investigating feature importance. We then demonstrate how HOTS can be utilized in high dimensional spaces such as neuroscientific setting, by taking 60 Schizophrenic subjects from the publicly available SchizConnect database and applying the method to determine which regions of the brain were most important for the positive and negative classification of schizophrenia as determined by the positive and negative syndrome scale (PANSS). Results HOTS effectively replicated and supported the findings of feature importance for classification of the Iris dataset when compared to Gini importance, Partial Dependence Plots and Permutation importance, determining ‘petal length’ as the most important feature for positive and negative classification. When applied to the Schizconnect dataset, HOTS was able to resolve from 379 independent features, the top 10 most important features for classification, as well as their directionality for classification and magnitude compared to other features. Cross-validation supported that these same 10 features were consistently used in the decision-making process across multiple trees, and these features were localised primarily to the occipital and parietal cortices, commonly disturbed brain regions in those afflicted with Schizophrenia. Conclusion HOTS effectively overcomes previous challenges of identifying feature importance at scale, and can be utilized across a swathe of disciplines. As computational power and data quantity continues to expand, it is imperative that a methodology is developed that is able to handle the demands of working with large datasets that contain a large number of features. This approach represents a unique way to investigate both the directionality and magnitude of feature importance when working at scale within a boosted tree model that can be easily visualized within commonly used software.
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Affiliation(s)
| | - Hugh Taylor
- Omniscient Neurotechnology, Sydney, Australia
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Abstract
The surgical management of brain tumors is based on the principle that the extent of resection improves patient outcomes. Traditionally, neurosurgeons have considered that lesions in “non-eloquent” cerebrum can be more aggressively surgically managed compared to lesions in “eloquent” regions with more known functional relevance. Furthermore, advancements in multimodal imaging technologies have improved our ability to extend the rate of resection while minimizing the risk of inducing new neurologic deficits, together referred to as the “onco-functional balance.” However, despite the common utilization of invasive techniques such as cortical mapping to identify eloquent tissue responsible for language and motor functions, glioma patients continue to present post-operatively with poor cognitive morbidity in higher-order functions. Such observations are likely related to the difficulty in interpreting the highly-dimensional information these technologies present to us regarding cognition in addition to our classically poor understanding of the functional and structural neuroanatomy underlying complex higher-order cognitive functions. Furthermore, reduction of the brain into isolated cortical regions without consideration of the complex, interacting brain networks which these regions function within to subserve higher-order cognition inherently prevents our successful navigation of true eloquent and non-eloquent cerebrum. Fortunately, recent large-scale movements in the neuroscience community, such as the Human Connectome Project (HCP), have provided updated neural data detailing the many intricate macroscopic connections between cortical regions which integrate and process the information underlying complex human behavior within a brain “connectome.” Connectomic data can provide us better maps on how to understand convoluted cortical and subcortical relationships between tumor and human cerebrum such that neurosurgeons can begin to make more informed decisions during surgery to maximize the onco-functional balance. However, connectome-based neurosurgery and related applications for neurorehabilitation are relatively nascent and require further work moving forward to optimize our ability to add highly valuable connectomic data to our surgical armamentarium. In this manuscript, we review four concepts with detailed examples which will help us better understand post-operative cognitive outcomes and provide a guide for how to utilize connectomics to reduce cognitive morbidity following cerebral surgery.
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Affiliation(s)
- Nicholas B Dadario
- Robert Wood Johnson School of Medicine, Rutgers University, New Brunswick, NJ, United States
| | - Bledi Brahimaj
- Department of Neurosurgery, Rush University Medical Center, Chicago, IL, United States
| | - Jacky Yeung
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, NSW, Australia
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, NSW, Australia
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Tanglay O, Young IM, Dadario NB, Briggs RG, Fonseka RD, Dhanaraj V, Hormovas J, Lin YH, Sughrue ME. Anatomy and white-matter connections of the precuneus. Brain Imaging Behav 2021; 16:574-586. [PMID: 34448064 DOI: 10.1007/s11682-021-00529-1] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/26/2021] [Indexed: 10/20/2022]
Abstract
Purpose Advances in neuroimaging have provided an understanding of the precuneus'(PCu) involvement in functions such as visuospatial processing and cognition. While the PCu has been previously determined to be apart of a higher-order default mode network (DMN), recent studies suggest the presence of possible dissociations from this model in order to explain the diverse functions the PCu facilitates, such as in episodic memory. An improved structural model of the white-matter anatomy of the PCu can demonstrate its unique cerebral connections with adjacent regions which can provide additional clarity on its role in integrating information across higher-order cerebral networks like the DMN. Furthermore, this information can provide clinically actionable anatomic information that can support clinical decision making to improve neurologic outcomes such as during cerebral surgery. Here, we sought to derive the relationship between the precuneus and underlying major white-mater bundles by characterizing its macroscopic connectivity. Methods Structural tractography was performed on twenty healthy adult controls from the Human Connectome Project (HCP) utilizing previously demonstrated methodology. All precuneus connections were mapped in both cerebral hemispheres and inter-hemispheric differences in resultant tract volumes were compared with an unpaired, corrected Mann-Whitney U test and a laterality index (LI) was completed. Ten postmortem dissections were then performed to serve as ground truth by using a modified Klingler technique with careful preservation of relevant white matter bundles. Results The precuneus is a heterogenous cortical region with five major types of connections that were present bilaterally. (1) Short association fibers connect the gyri of the precuneus and connect the precuneus to the superior parietal lobule and the occipital cortex. (2) Four distinct parts of the cingulum bundle connect the precuneus to the frontal lobe and the temporal lobe. (3) The middle longitudinal fasciculus from the precuneus connects to the superior temporal gyrus and the dorsolateral temporal pole. (4) Parietopontine fibers travel as part of the corticopontine fibers to connect the precuneus to pontine regions. (5) An extensive commissural bundle connects the precuneus bilaterally. Conclusion We present a summary of the anatomic connections of the precuneus as part of an effort to understand the function of the precuneus and highlight key white-matter pathways to inform surgical decision-making. Our findings support recent models suggesting unique fiber connections integrating at the precuneus which may suggest finer subsystems of the DMN or unique networks, but further study is necessary to refine our model in greater quantitative detail.
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Affiliation(s)
- Onur Tanglay
- Centre for Minimally Invasive Neurosurgery, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia
| | | | - Nicholas B Dadario
- Robert Wood Johnson School of Medicine, Rutgers University, New Brunswick, NJ, USA
| | - Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - R Dineth Fonseka
- Centre for Minimally Invasive Neurosurgery, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia
| | - Vukshitha Dhanaraj
- Centre for Minimally Invasive Neurosurgery, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia
| | - Jorge Hormovas
- Centre for Minimally Invasive Neurosurgery, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia
| | - Yueh-Hsin Lin
- Centre for Minimally Invasive Neurosurgery, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Suite 19, Level 7 Prince of Wales Private Hospital, Barker Street, Randwick, Sydney, NSW, 2031, Australia.
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Yeung JT, Taylor HM, Nicholas PJ, Young IM, Jiang I, Doyen S, Sughrue ME, Teo C. Using Quicktome for Intracerebral Surgery: Early Retrospective Study and Proof of Concept. World Neurosurg 2021; 154:e734-e742. [PMID: 34358688 DOI: 10.1016/j.wneu.2021.07.127] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 07/26/2021] [Accepted: 07/27/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Neurosurgeons have limited tools in their armamentarium to visualize critical brain networks during surgical planning. Quicktome was designed using machine-learning to generate robust visualization of important brain networks that can be used with standard neuronavigation to minimize those deficits. We sought to see whether Quicktome could help localize important cerebral networks and tracts during intracerebral surgery. METHODS We report on all patients who underwent keyhole intracranial surgery with available Quicktome-enabled neuronavigation. We retrospectively analyzed the locations of the lesions and determined functional networks at risks, including chief executive network, default mode network, salience, corticospinal/sensorimotor, language, neglect, and visual networks. We report on the postoperative neurologic outcomes of the patients and retrospectively determined whether the outcomes could be explained by Quicktome's functional localizations. RESULTS Fifteen high-risk patients underwent craniotomies for intra-axial tumors, with the exception of one meningioma and one case of leukoencephalopathy. Eight patients were male. The median age was 49.6 years. Quicktome was readily integrated in our existing navigation system in every case. New postoperative neurologic deficits occurred in 8 patients. All new deficits, except for one resulting from a postoperative stroke, were expected and could be explained by preoperative findings by Quicktome. In addition, in those who did not have new neurologic deficits, Quicktome offered explanations for their outcomes. CONCLUSIONS Quicktome helps to visualize complex functional connectomic networks and tracts by seamlessly integrating into existing neuronavigation platforms. The added information may assist in reducing neurological deficits and offer explanations for postsurgical outcomes.
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Affiliation(s)
- Jacky T Yeung
- Centre for Minimally Invasive Neurosurgery, Randwick, NSW, Australia
| | | | | | | | - Ivy Jiang
- Omniscient Neurotechnology, Sydney, Australia
| | | | | | - Charles Teo
- Centre for Minimally Invasive Neurosurgery, Randwick, NSW, Australia; Omniscient Neurotechnology, Sydney, Australia
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Stephens TM, Young IM, O'Neal CM, Dadario NB, Briggs RG, Teo C, Sughrue ME. Akinetic mutism reversed by inferior parietal lobule repetitive theta burst stimulation: Can we restore default mode network function for therapeutic benefit? Brain Behav 2021; 11:e02180. [PMID: 34145791 PMCID: PMC8413751 DOI: 10.1002/brb3.2180] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Revised: 03/24/2021] [Accepted: 04/06/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Transcranial magnetic stimulation is a noninvasive treatment used to modulate cortical excitability. Its use over the last two decades has expanded, ranging from psychiatric disorders to traumatic brain injury and poststroke rehabilitation. OBJECTIVES We present the case of a 59-year-old male patient who presented in a decreased state of consciousness due to a right frontal glioblastoma, wherein his state was not improved by a successful surgery and could not be explained by any other condition. Due to his poor prognosis, we examine the benefits of receiving transcranial magnetic stimulation treatment to improve his akinetic mutism. METHODS We utilized independent component analysis with resting-state functional magnetic resonance imaging (rsfMRI) to better understand his cortical functionality. The imaging suggested absence of the default mode network (DMN). The patient underwent five sessions of navigated intermittent theta burst stimulation to the ipsilesional inferior parietal lobule and inferior frontal gyrus, with the aim of improving his default mode network functionality. RESULTS No other treatments resulted in an improvement of this patient's condition; however, 3 weeks following transcranial magnetic stimulation treatment, the patient was more alert and interactive, and his follow-up rsfMRI scan demonstrated a partially intact default mode network. CONCLUSION This case raises important questions regarding the clinical utility of transcranial magnetic stimulation to improve the connectivity of important cerebral networks and subsequent related functional recovery.
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Affiliation(s)
- Tressie M Stephens
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Japan
| | | | - Christen M O'Neal
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Japan
| | | | - Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Japan
| | - Charles Teo
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, NSW, Australia
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, NSW, Australia
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Briggs RG, Tanglay O, Dadario NB, Young IM, Fonseka RD, Hormovas J, Dhanaraj V, Lin YH, Kim SJ, Bouvette A, Chakraborty AR, Milligan TM, Abraham CJ, Anderson CD, O'Donoghue DL, Sughrue ME. The Unique Fiber Anatomy of Middle Temporal Gyrus Default Mode Connectivity. Oper Neurosurg (Hagerstown) 2021; 21:E8-E14. [PMID: 33929019 DOI: 10.1093/ons/opab109] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 02/03/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The middle temporal gyrus (MTG) is understood to play a role in language-related tasks such as lexical comprehension and semantic cognition. However, a more specific understanding of its key white matter connections could promote the preservation of these functions during neurosurgery. OBJECTIVE To provide a detailed description of the underlying white matter tracts associated with the MTG to improve semantic preservation during neurosurgery. METHODS Tractography was performed using diffusion imaging obtained from 10 healthy adults from the Human Connectome Project. All tracts were mapped between cerebral hemispheres with a subsequent laterality index calculated based on resultant tract volumes. Ten postmortem dissections were performed for ex vivo validation of the tractography based on qualitative visual agreement. RESULTS We identified 2 major white matter bundles leaving the MTG: the inferior longitudinal fasciculus and superior longitudinal fasciculus. In addition to long association fibers, a unique linear sequence of U-shaped fibers was identified, possibly representing a form of visual semantic transfer down the temporal lobe. CONCLUSION We elucidate the underlying fiber-bundle anatomy of the MTG, an area highly involved in the brain's language network. Improved understanding of the unique, underlying white matter connections in and around this area may augment our overall understanding of language processing as well as the involvement of higher order cerebral networks like the default mode network in these functions.
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Affiliation(s)
- Robert G Briggs
- Department of Neurosurgery , University of Southern California, Los Angeles, California, USA
| | - Onur Tanglay
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Nicholas B Dadario
- Rutgers Robert Wood Johnson School of Medicine, New Brunswick, New Jersey, USA
| | | | - R Dineth Fonseka
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Jorge Hormovas
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Vukshitha Dhanaraj
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Yueh-Hsin Lin
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Sihyong J Kim
- Rutgers Robert Wood Johnson School of Medicine, New Brunswick, New Jersey, USA
| | - Adam Bouvette
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma, USA
| | - Arpan R Chakraborty
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma, USA
| | - Ty M Milligan
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma, USA
| | - Carol J Abraham
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma, USA
| | - Christopher D Anderson
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma, USA
| | - Daniel L O'Donoghue
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma, USA
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
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Lin YH, Dadario NB, Hormovas J, Young IM, Briggs RG, MacKenzie AE, Palejwala AH, Fonseka RD, Kim SJ, Tanglay O, Fletcher LR, Abraham CJ, Conner AK, O'Donoghue DL, Sughrue ME. Anatomy and White Matter Connections of the Superior Parietal Lobule. Oper Neurosurg (Hagerstown) 2021; 21:E199-E214. [PMID: 34246196 DOI: 10.1093/ons/opab174] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 03/19/2021] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND The superior parietal lobule (SPL) is involved in somatosensory and visuospatial integration with additional roles in attention, written language, and working memory. A detailed understanding of the exact location and nature of associated white matter tracts could improve surgical decisions and subsequent postoperative morbidity related to surgery in and around this gyrus. OBJECTIVE To characterize the fiber tracts of the SPL based on relationships to other well-known neuroanatomic structures through diffusion spectrum imaging (DSI)-based fiber tracking validated by gross anatomical dissection as ground truth. METHODS Neuroimaging data of 10 healthy, adult control subjects was obtained from a publicly accessible database published in Human Connectome Project for subsequent tractographic analyses. White matter tracts were mapped between both cerebral hemispheres, and a lateralization index was calculated based on resultant tract volumes. Post-mortem dissections of 10 cadavers identified the location of major tracts and validated our tractography results based on qualitative visual agreement. RESULTS We identified 9 major connections of the SPL: U-fiber, superior longitudinal fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, middle longitudinal fasciculus, extreme capsule, vertical occipital fasciculus, cingulum, and corpus callosum. There was no significant fiber lateralization detected. CONCLUSION The SPL is an important region implicated in a variety of tasks involving visuomotor and visuospatial integration. Improved understanding of the fiber bundle anatomy elucidated in this study can provide invaluable information for surgical treatment decisions related to this region.
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Affiliation(s)
- Yueh-Hsin Lin
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Nicholas B Dadario
- Rutgers Robert Wood Johnson School of Medicine, New Brunswick, New Jersey, USA
| | - Jorge Hormovas
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | | | - Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma
| | - Alana E MacKenzie
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Ali H Palejwala
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma
| | - R Dineth Fonseka
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Sihyong J Kim
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Onur Tanglay
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Luke R Fletcher
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma
| | - Carol J Abraham
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma
| | - Andrew K Conner
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma
| | - Daniel L O'Donoghue
- Department of Cell Biology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
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Briggs RG, Lin YH, Dadario NB, Young IM, Conner AK, Xu W, Tanglay O, Kim SJ, Fonseka RD, Bonney PA, Chakraborty AR, Nix CE, Flecher LR, Yeung JT, Teo C, Sughrue ME. Optimal timing of post-operative enoxaparin after neurosurgery: A single institution experience. Clin Neurol Neurosurg 2021; 207:106792. [PMID: 34233235 DOI: 10.1016/j.clineuro.2021.106792] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Revised: 06/26/2021] [Accepted: 06/28/2021] [Indexed: 10/21/2022]
Abstract
PURPOSE Venous thromboembolism (VTE) is a well-known problem in patients with intracranial tumors, especially high-grade gliomas. Optimal management of VTE complications is critical given that the development of deep vein thrombosis (DVT) and/or pulmonary embolism can exacerbate medical comorbidities and increase mortality. However, little is known about the optimum time to initiate post-operative anticoagulant prophylaxis. Therefore, there is a keen interest amongst neurosurgeons to develop evidence-based protocols to prevent VTE in post-operative brain tumor patients. METHODS We retrospectively identified adult patients who underwent elective craniotomy for intracranial tumor resection between 2012 and 2017. Patients were categorized according to the time at which they began receiving prophylactic enoxaparin in the immediate post-operative period, within one day (POD 1), two days (POD 2), three days (POD 3), five days (POD 5), or seven days (POD 7). RESULTS A total of 1087 patients had a craniotomy for intracranial tumor resection between 2012 and 2017. Multivariate binomial logistic regression analysis demonstrated that initiation of prophylactic enoxaparin within 72 h of surgery was protective against the likelihood of developing a lower extremity DVT (OR: 0.32; CI: 0.10-0.95; p = 0.049) while controlling for possible risk factors for DVTs identified on univariate analysis. Furthermore, complication rates between the anticoagulation and non-anticoagulation groups were not statistically significant. CONCLUSION Initiating anticoagulant prophylaxis with subcutaneous enoxaparin sodium 40 mg once per day within 72 h of surgery can be done safely while reducing the risk of developing lower extremity DVT.
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Affiliation(s)
- Robert G Briggs
- Department of Neurosurgery, University of Southern California, Los Angeles, California
| | - Yueh-Hsin Lin
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Nicholas B Dadario
- Rutgers Robert Wood Johnson School of Medicine, New Brunswick, New Jersey
| | | | - Andrew K Conner
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma
| | - Wenjai Xu
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma
| | - Onur Tanglay
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Sihyong J Kim
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - R Dineth Fonseka
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Phillip A Bonney
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma
| | - Arpan R Chakraborty
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma
| | - Cameron E Nix
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma
| | - Lyke R Flecher
- Department of Neurosurgery, University of Oklahoma Health Science Center, Oklahoma City, Oklahoma
| | - Jacky T Yeung
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Charles Teo
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia.
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O'Neal CM, Ahsan SA, Dadario NB, Fonseka RD, Young IM, Parker A, Maxwell BD, Yeung JT, Briggs RG, Teo C, Sughrue ME. A connectivity model of the anatomic substrates underlying ideomotor apraxia: A meta-analysis of functional neuroimaging studies. Clin Neurol Neurosurg 2021; 207:106765. [PMID: 34237682 DOI: 10.1016/j.clineuro.2021.106765] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/10/2021] [Accepted: 06/15/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Patients with ideomotor apraxia (IMA) present with selective impairments in higher-order motor cognition and execution without damage to any motor or sensory pathways. Although extensive research has been conducted to determine the regions of interest (ROIs) underlying these unique impairments, previous models are heterogeneous and may be further clarified based on their structural connectivity, which has been far less described. OBJECTIVE The goal of this research is to propose an anatomically concise network model for the neurophysiologic basis of IMA, specific to the voluntary pantomime, imitation and tool execution, based on intrinsic white matter connectivity. METHODS We utilized meta-analytic software to identify relevant ROIs in ideomotor apraxia as reported in the literature based on functional neuroimaging data with healthy participants. After generating an activation likelihood estimation (ALE) of relevant ROIs, cortical parcellations overlapping the ALE were used to construct an anatomically precise model of anatomic substrates using the parcellation scheme outlined by the Human Connectome Project (HCP). Deterministic tractography was then performed on 25 randomly selected, healthy HCP subjects to determine the structural connectivity underlying the identified ROIs. RESULTS 10 task-based fMRI studies met our inclusion criteria and the ALE analysis demonstrated 6 ROIs to constitute the IMA network: SCEF, FOP4, MIP, AIP, 7AL, and 7PC. These parcellations represent a fronto-parietal network consisting mainly of intra-parietal, U-shaped association fibers (40%) and long-range inferior fronto-occipital fascicle (IFOF) fibers (50%). These findings support previous functional models based on dual-stream motor processing. CONCLUSION We constructed a preliminary model demonstrating the underlying structural interconnectedness of anatomic substrates involved in higher-order motor functioning which is seen impaired in IMA. Our model provides support for previous dual-stream processing frameworks discussed in the literature, but further clarification is necessary with voxel-based lesion studies of IMA to further refine these findings.
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Affiliation(s)
- Christen M O'Neal
- Department of Neurosurgery, University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA
| | - Syed A Ahsan
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | | | - R Dineth Fonseka
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | | | - Allan Parker
- Department of Neurosurgery, University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA
| | - B David Maxwell
- Department of Neurosurgery, University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA
| | - Jacky T Yeung
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Centre, Oklahoma City, OK, USA
| | - Charles Teo
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, Australia.
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Palejwala AH, Dadario NB, Young IM, O'Connor K, Briggs RG, Conner AK, O'Donoghue DL, Sughrue ME. Anatomy and White Matter Connections of the Lingual Gyrus and Cuneus. World Neurosurg 2021; 151:e426-e437. [PMID: 33894399 DOI: 10.1016/j.wneu.2021.04.050] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 04/12/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND The medial occipital lobe, composed of the lingual gyrus and cuneus, is necessary for both basic and higher level visual processing. It is also known to facilitate cross-modal, nonvisual functions, such as linguistic processing and verbal memory, after the loss of the visual senses. A detailed cortical model elucidating the white matter connectivity associated with this area could improve our understanding of the interacting brain networks that underlie complex human processes and postoperative outcomes related to vision and language. METHODS Generalized q-sampling imaging tractography, validated by gross anatomic dissection for qualitative visual agreement, was performed on 10 healthy adult controls obtained from the Human Connectome Project. RESULTS Major white matter connections were identified by tractography and validated by gross dissection, which connected the medial occipital lobe with itself and the adjacent cortices, especially the temporal lobe. The short- and long-range connections identified consisted mainly of U-shaped association fibers, intracuneal fibers, and inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, middle longitudinal fasciculus, and lingual-fusiform connections. CONCLUSIONS The medial occipital lobe is an extremely interconnected system, supporting its ability to perform coordinated basic visual processing, but also serves as a center for many long-range association fibers, supporting its importance in nonvisual functions, such as language and memory. The presented data represent clinically actionable anatomic information that can be used in multimodal navigation of white matter lesions in the medial occipital lobe to prevent neurologic deficits and improve patients' quality of life after cerebral surgery.
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Affiliation(s)
- Ali H Palejwala
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Nicholas B Dadario
- Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, USA
| | | | - Kyle O'Connor
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Robert G Briggs
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Andrew K Conner
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Daniel L O'Donoghue
- Department of Cell Biology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Michael E Sughrue
- Centre for Minimally Invasive Neurosurgery, Prince of Wales Private Hospital, Sydney, New South Wales, Australia.
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Rosen AC, Bhat JV, Cardenas VA, Ehrlich TJ, Horwege AM, Mathalon DH, Roach BJ, Glover GH, Badran BW, Forman SD, George MS, Thase ME, Yurgelun-Todd D, Sughrue ME, Doyen SP, Nicholas PJ, Scott JC, Tian L, Yesavage JA. Targeting location relates to treatment response in active but not sham rTMS stimulation. Brain Stimul 2021; 14:703-709. [PMID: 33866020 PMCID: PMC8884259 DOI: 10.1016/j.brs.2021.04.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 03/25/2021] [Accepted: 04/01/2021] [Indexed: 11/28/2022] Open
Abstract
Background: Precise targeting of brain functional networks is believed critical for treatment efficacy of rTMS (repetitive pulse transcranial magnetic stimulation) in treatment resistant major depression. Objective: To use imaging data from a “failed” clinical trial of rTMS in Veterans to test whether treatment response was associated with rTMS coil location in active but not sham stimulation, and compare fMRI functional connectivity between those stimulation locations. Methods: An imaging substudy of 49 Veterans (mean age, 56 years; range, 27e78 years; 39 male) from a randomized, sham-controlled, double-blinded clinical trial of rTMS treatment, grouping participants by clinical response, followed by group comparisons of treatment locations identified by individualized fiducial markers on structural MRI and resting state fMRI derived networks. Results: The average stimulation location for responders versus nonresponders differed in the active but not in the sham condition (P = .02). The average responder location derived from the active condition showed significant negative functional connectivity with the subgenual cingulate (P < .001) while the nonresponder location did not (P = .17), a finding replicated in independent cohorts of 84 depressed and 35 neurotypical participants. The responder and nonresponder stimulation locations evoked different seed based networks (FDR corrected clusters, all P < .03), revealing additional brain regions related to rTMS treatment outcome. Conclusion: These results provide evidence from a randomized controlled trial that clinical response to rTMS is related to accuracy in targeting the region within DLPFC that is negatively correlated with subgenual cingulate. These results support the validity of a neuro-functionally informed rTMS therapy target in Veterans.
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Affiliation(s)
- A C Rosen
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Psychiatry, Stanford University, Stanford, CA, 94305, USA.
| | - J V Bhat
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Palo Alto Veterans Institute for Research, Palo Alto, CA, 94304, USA
| | - V A Cardenas
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - T J Ehrlich
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; University of Michigan, Ann Arbor, USA
| | - A M Horwege
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - D H Mathalon
- Mental Health Service, San Francisco Veterans Affairs Health Care System, University of California, San Francisco, CA, USA; Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - B J Roach
- Mental Health Service, San Francisco Veterans Affairs Health Care System, University of California, San Francisco, CA, USA; Northern California Institute for Research and Education, San Francisco Veterans Affairs Medical Center, University of California, San Francisco, CA, USA
| | - G H Glover
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - B W Badran
- Brain Stimulation Division, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA
| | - S D Forman
- Department of Veterans Affairs, VA Pittsburgh Healthcare System, Pittsburgh, PA, USA; Western Psychiatric Institute and Clinic, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - M S George
- Brain Stimulation Division, Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA; Ralph H. Johnson VA Medical Center, Charleston, SC, USA
| | - M E Thase
- VISN4 Mental Illness Research, Education, and Clinical Center at the Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - D Yurgelun-Todd
- Rocky Mountain Network Mental Illness Research Education and Clinical Centers (VISN 19), VA Salt Lake City Health Care System, Salt Lake City, UT, USA; Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - M E Sughrue
- Omniscient Neurotechnologies, Sydney, Australia; Prince of Wales Hospital, Randwick, NSW, Australia
| | - S P Doyen
- Omniscient Neurotechnologies, Sydney, Australia
| | | | - J C Scott
- VISN4 Mental Illness Research, Education, and Clinical Center at the Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - L Tian
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - J A Yesavage
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA; Department of Psychiatry, Stanford University, Stanford, CA, 94305, USA
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Milton CK, Dhanaraj V, Young IM, Taylor HM, Nicholas PJ, Briggs RG, Bai MY, Fonseka RD, Hormovas J, Lin Y, Tanglay O, Conner AK, Glenn CA, Teo C, Doyen S, Sughrue ME. Parcellation-based anatomic model of the semantic network. Brain Behav 2021; 11:e02065. [PMID: 33599397 PMCID: PMC8035438 DOI: 10.1002/brb3.2065] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Revised: 12/16/2020] [Accepted: 01/17/2021] [Indexed: 01/08/2023] Open
Abstract
INTRODUCTION The semantic network is an important mediator of language, enabling both speech production and the comprehension of multimodal stimuli. A major challenge in the field of neurosurgery is preventing semantic deficits. Multiple cortical areas have been linked to semantic processing, though knowledge of network connectivity has lacked anatomic specificity. Using attentional task-based fMRI studies, we built a neuroanatomical model of this network. METHODS One hundred and fifty-five task-based fMRI studies related to categorization of visual words and objects, and auditory words and stories were used to generate an activation likelihood estimation (ALE). Cortical parcellations overlapping the ALE were used to construct a preliminary model of the semantic network based on the cortical parcellation scheme previously published under the Human Connectome Project. Deterministic fiber tractography was performed on 25 randomly chosen subjects from the Human Connectome Project, to determine the connectivity of the cortical parcellations comprising the network. RESULTS The ALE analysis demonstrated fourteen left hemisphere cortical regions to be a part of the semantic network: 44, 45, 55b, IFJa, 8C, p32pr, SFL, SCEF, 8BM, STSdp, STSvp, TE1p, PHT, and PBelt. These regions showed consistent interconnections between parcellations. Notably, the anterior temporal pole, a region often implicated in semantic function, was absent from our model. CONCLUSIONS We describe a preliminary cortical model for the underlying structural connectivity of the semantic network. Future studies will further characterize the neurotractographic details of the semantic network in the context of medical application.
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Affiliation(s)
- Camille K. Milton
- Department of NeurosurgeryUniversity of Oklahoma Health Sciences CenterOklahoma CityOKUSA
| | - Vukshitha Dhanaraj
- Department of NeurosurgeryPrince of Wales Private HospitalSydneyNSWAustralia
| | | | | | | | - Robert G. Briggs
- Department of NeurosurgeryUniversity of Oklahoma Health Sciences CenterOklahoma CityOKUSA
| | - Michael Y. Bai
- Department of NeurosurgeryPrince of Wales Private HospitalSydneyNSWAustralia
| | - Rannulu D. Fonseka
- Department of NeurosurgeryPrince of Wales Private HospitalSydneyNSWAustralia
| | - Jorge Hormovas
- Department of NeurosurgeryPrince of Wales Private HospitalSydneyNSWAustralia
| | - Yueh‐Hsin Lin
- Department of NeurosurgeryPrince of Wales Private HospitalSydneyNSWAustralia
| | - Onur Tanglay
- Department of NeurosurgeryPrince of Wales Private HospitalSydneyNSWAustralia
| | - Andrew K. Conner
- Department of NeurosurgeryUniversity of Oklahoma Health Sciences CenterOklahoma CityOKUSA
| | - Chad A. Glenn
- Department of NeurosurgeryUniversity of Oklahoma Health Sciences CenterOklahoma CityOKUSA
| | - Charles Teo
- Department of NeurosurgeryPrince of Wales Private HospitalSydneyNSWAustralia
| | | | - Michael E. Sughrue
- Department of NeurosurgeryPrince of Wales Private HospitalSydneyNSWAustralia
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