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Ahtam B, Yun HJ, Vyas R, Pienaar R, Wilson JH, Goswami CP, Berto LF, Warfield SK, Sahin M, Grant PE, Peters JM, Im K. Morphological Features of Language Regions in Individuals with Tuberous Sclerosis Complex. J Autism Dev Disord 2024; 54:3155-3175. [PMID: 37222965 DOI: 10.1007/s10803-023-06004-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2023] [Indexed: 05/25/2023]
Abstract
A significant number of individuals with tuberous sclerosis complex (TSC) exhibit language difficulties. Here, we examined the language-related brain morphometry in 59 participants (7 participants with TSC and comorbid autism spectrum disorder (ASD) (TSC + ASD), 13 with TSC but no ASD (TSC-ASD), 10 with ASD-only (ASD), and 29 typically developing (TD) controls). A hemispheric asymmetry was noted in surface area and gray matter volume of several cortical language areas in TD, ASD, and TSC-ASD groups, but not in TSC + ASD group. TSC + ASD group demonstrated increased cortical thickness and curvature values in multiple language regions for both hemispheres, compared to other groups. After controlling for tuber load in the TSC groups, within-group differences stayed the same but the differences between TSC-ASD and TSC + ASD were no longer statistically significant. These preliminary findings suggest that comorbid ASD in TSC as well as tuber load in TSC is associated with changes in the morphometry of language regions. Future studies with larger sample sizes will be needed to confirm these findings.
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Affiliation(s)
- Banu Ahtam
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA.
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA.
| | - Hyuk Jin Yun
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Rutvi Vyas
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Rudolph Pienaar
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Josephine H Wilson
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Caroline P Goswami
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Laura F Berto
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Simon K Warfield
- Department of Radiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Mustafa Sahin
- Rosamund Stone Zander Translational Neuroscience Center, Department of Neurology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Harvard Medical School, Harvard University, Boston, MA, 02115, USA
| | - P Ellen Grant
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Division of Neuroradiology, Department of Radiology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Jurriaan M Peters
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
| | - Kiho Im
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
- Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, 300 Longwood Avenue, Boston, MA, 02115, USA
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Mofatteh M, Mashayekhi MS, Arfaie S, Chen Y, Mirza AB, Fares J, Bandyopadhyay S, Henich E, Liao X, Bernstein M. Augmented and virtual reality usage in awake craniotomy: a systematic review. Neurosurg Rev 2022; 46:19. [PMID: 36529827 PMCID: PMC9760592 DOI: 10.1007/s10143-022-01929-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 11/21/2022] [Accepted: 12/12/2022] [Indexed: 12/23/2022]
Abstract
Augmented and virtual reality (AR, VR) are becoming promising tools in neurosurgery. AR and VR can reduce challenges associated with conventional approaches via the simulation and mimicry of specific environments of choice for surgeons. Awake craniotomy (AC) enables the resection of lesions from eloquent brain areas while monitoring higher cortical and subcortical functions. Evidence suggests that both surgeons and patients benefit from the various applications of AR and VR in AC. This paper investigates the application of AR and VR in AC and assesses its prospective utility in neurosurgery. A systematic review of the literature was performed using PubMed, Scopus, and Web of Science databases in accordance with the PRISMA guidelines. Our search results yielded 220 articles. A total of six articles consisting of 118 patients have been included in this review. VR was used in four papers, and the other two used AR. Tumour was the most common pathology in 108 patients, followed by vascular lesions in eight patients. VR was used for intraoperative mapping of language, vision, and social cognition, while AR was incorporated in preoperative training of white matter dissection and intraoperative visualisation and navigation. Overall, patients and surgeons were satisfied with the applications of AR and VR in their cases. AR and VR can be safely incorporated during AC to supplement, augment, or even replace conventional approaches in neurosurgery. Future investigations are required to assess the feasibility of AR and VR in various phases of AC.
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Affiliation(s)
- Mohammad Mofatteh
- School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, UK.
| | | | - Saman Arfaie
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA, USA
| | - Yimin Chen
- Department of Neurology, Foshan Sanshui District People's Hospital, Foshan, China
| | | | - Jawad Fares
- Department of Neurological Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Northwestern Medicine Malnati Brain Tumor Institute, Feinberg School of Medicine, Lurie Comprehensive Cancer Center, Northwestern University, Chicago, IL, USA
| | - Soham Bandyopadhyay
- Nuffield Department of Surgical Sciences, Oxford University Global Surgery Group, University of Oxford, Oxford, UK
- Clinical Neurosciences, Clinical & Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, Hampshire, UK
- Wessex Neurological Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Edy Henich
- Department of Medicine, McGill University, Montreal, Quebec, Canada
| | - Xuxing Liao
- Department of Neurosurgery, Foshan Sanshui District People's Hospital, Foshan, China
| | - Mark Bernstein
- Division of Neurosurgery, Department of Surgery, University of Toronto, University Health Network, Toronto, Ontario, Canada
- Temmy Latner Center for Palliative Care, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
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Shakhatreh L, Janmohamed M, Baker AA, Willard A, Laing J, Rychkova M, Chen Z, Kwan P, O'Brien TJ, Perucca P. Interictal and seizure-onset EEG patterns in malformations of cortical development: A systematic review. Neurobiol Dis 2022; 174:105863. [PMID: 36165814 DOI: 10.1016/j.nbd.2022.105863] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 09/07/2022] [Accepted: 09/17/2022] [Indexed: 11/16/2022] Open
Abstract
OBJECTIVES Malformations of cortical development (MCDs) are common causes of drug-resistant epilepsy. The mechanisms underlying the associated epileptogenesis and ictogenesis remain poorly elucidated. EEG can help in understanding these mechanisms. We systematically reviewed studies reporting scalp or intracranial EEG features of MCDs to characterise interictal and seizure-onset EEG patterns across different MCD types. METHODS We conducted a systematic review in accordance with PRISMA guidelines. MEDLINE, PubMed, and Cochrane databases were searched for studies describing interictal and seizure-onset EEG patterns in MCD patients. A classification framework was implemented to group EEG features into 20 predefined patterns, comprising nine interictal (five, scalp EEG; four, intracranial EEG) and 11 seizure-onset (five, scalp EEG; six, intracranial EEG) patterns. Logistic regression was used to estimate the odds ratios (OR) of each seizure-onset pattern being associated with specific MCD types. RESULTS Our search yielded 1682 studies, of which 27 comprising 936 MCD patients were included. Of the nine interictal EEG patterns, five (three, scalp EEG; two, intracranial EEG) were detected in ≥2 MCD types, while four (rhythmic epileptiform discharges type 1 and type 2 on scalp EEG; repetitive bursting spikes and sporadic spikes on intracranial EEG) were seen only in focal cortical dysplasia (FCD). Of the 11 seizure-onset patterns, eight (three, scalp EEG; five, intracranial EEG) were found in ≥2 MCD types, whereas three were observed only in FCD (suppression on scalp EEG; delta brush on intracranial EEG) or tuberous sclerosis complex (TSC; focal fast wave on scalp EEG). Among scalp EEG seizure-onset patterns, paroxysmal fast activity (OR = 0.13; 95% CI: 0.03-0.53; p = 0.024) and repetitive epileptiform discharges (OR = 0.18; 95% CI: 0.05-0.61; p = 0.036) were less likely to occur in TSC than FCD. Among intracranial EEG seizure-onset patterns, low-voltage fast activity was more likely to be detected in heterotopia (OR = 19.3; 95% CI: 6.22-60.1; p < 0.001), polymicrogyria (OR = 6.70; 95% CI: 2.25-20.0; p = 0.004) and TSC (OR = 4.27; 95% CI: 1.88-9.70; p = 0.005) than FCD. SIGNIFICANCE Different MCD types can share similar interictal or seizure-onset EEG patterns, reflecting common underlying biological mechanisms. However, selected EEG patterns appear to point to distinct MCD types, suggesting certain differences in their neuronal networks.
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Affiliation(s)
- Lubna Shakhatreh
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia; Department of Neurology, Alfred Health, Melbourne, Australia.
| | - Mubeen Janmohamed
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia; Department of Neurology, Alfred Health, Melbourne, Australia
| | - Ana Antonic Baker
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia
| | - Anna Willard
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia; Department of Neurology, Alfred Health, Melbourne, Australia
| | - Joshua Laing
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, Alfred Health, Melbourne, Australia
| | - Maria Rychkova
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia
| | - Zhibin Chen
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia
| | - Patrick Kwan
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia; Department of Neurology, Alfred Health, Melbourne, Australia; Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, Melbourne, Australia
| | - Terence J O'Brien
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia; Department of Neurology, Alfred Health, Melbourne, Australia; Department of Medicine (The Royal Melbourne Hospital), The University of Melbourne, Melbourne, Australia
| | - Piero Perucca
- Department of Neuroscience, The Central Clinical School, Monash University, Melbourne, Australia; Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia; Department of Neurology, Alfred Health, Melbourne, Australia; Bladin-Berkovic Comprehensive Epilepsy Program, Department of Neurology, Austin Health, Melbourne, Australia; Epilepsy Research Centre, Department of Medicine (Austin Health), The University of Melbourne, Melbourne, Australia
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Augmented reality visualization in brain lesions: a prospective randomized controlled evaluation of its potential and current limitations in navigated microneurosurgery. Acta Neurochir (Wien) 2022; 164:3-14. [PMID: 34904183 PMCID: PMC8761141 DOI: 10.1007/s00701-021-05045-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 09/01/2021] [Indexed: 11/16/2022]
Abstract
Background Augmented reality (AR) has the potential to support complex neurosurgical interventions by including visual information seamlessly. This study examines intraoperative visualization parameters and clinical impact of AR in brain tumor surgery. Methods Fifty-five intracranial lesions, operated either with AR-navigated microscope (n = 39) or conventional neuronavigation (n = 16) after randomization, have been included prospectively. Surgical resection time, duration/type/mode of AR, displayed objects (n, type), pointer-based navigation checks (n), usability of control, quality indicators, and overall surgical usefulness of AR have been assessed. Results AR display has been used in 44.4% of resection time. Predominant AR type was navigation view (75.7%), followed by target volumes (20.1%). Predominant AR mode was picture-in-picture (PiP) (72.5%), followed by 23.3% overlay display. In 43.6% of cases, vision of important anatomical structures has been partially or entirely blocked by AR information. A total of 7.7% of cases used MRI navigation only, 30.8% used one, 23.1% used two, and 38.5% used three or more object segmentations in AR navigation. A total of 66.7% of surgeons found AR visualization helpful in the individual surgical case. AR depth information and accuracy have been rated acceptable (median 3.0 vs. median 5.0 in conventional neuronavigation). The mean utilization of the navigation pointer was 2.6 × /resection hour (AR) vs. 9.7 × /resection hour (neuronavigation); navigation effort was significantly reduced in AR (P < 0.001). Conclusions The main benefit of HUD-based AR visualization in brain tumor surgery is the integrated continuous display allowing for pointer-less navigation. Navigation view (PiP) provides the highest usability while blocking the operative field less frequently. Visualization quality will benefit from improvements in registration accuracy and depth impression. German clinical trials registration number. DRKS00016955. Supplementary Information The online version contains supplementary material available at 10.1007/s00701-021-05045-1.
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