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Kim M, Seo JW, Kim MS, Lee KH, Kim M. White matter tract density index is associated with disability in multiple sclerosis. Neurobiol Dis 2024; 198:106548. [PMID: 38825050 DOI: 10.1016/j.nbd.2024.106548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 05/29/2024] [Accepted: 05/31/2024] [Indexed: 06/04/2024] Open
Abstract
BACKGROUND The association between common neuroradiological markers of multiple sclerosis (MS) and clinical disability is weak. Given that the disability in patients with MS may depend on the underlying structural connectivity of the brain, our study aimed to examine the association between white matter tracts affected by MS and the patients' disability using a new tract density index (TDI). METHOD This study included 53 patients diagnosed with MS, examined between 2019 and 2020. Manual lesion segmentation was performed on fluid-attenuated inversion recovery (FLAIR) images, and the density of white matter tracts encompassing the lesion (i.e., TDI) was calculated. Correlation analysis was employed to assess the association between TDI and disability. Additionally, the relationship between disability, TDI, and lesion-derived network metrics was examined by computing a partial correlation network. RESULTS The TDI significantly correlated with the expanded disability status scale (EDSS) (r = 0.30, p = 0.03). Furthermore, the patient's disability is linked solely through TDI to lesion-derived network metrics -a key metric that 'bridges' the gap between the brain lesion and disability. CONCLUSIONS In this study, MS lesions encompassing regions with high white matter tract density were associated and linked with severe physical disability. These findings indicate that TDI may be an outcome predictor that may connect radiologic findings to clinical practice.
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Affiliation(s)
- Minhoe Kim
- Computer Convergence Software Department, Korea University, Sejong, Republic of Korea
| | - Ji Won Seo
- Department of Radiology, Research Institute and Hospital of National Cancer Center, Goyang-si, Republic of Korea
| | - Myung Sub Kim
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kyung Hoon Lee
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
| | - Minchul Kim
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
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2
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Nono AST, Anziano M, Mouthon M, Chabwine JN, Spierer L. The Role of Anatomic Connectivity in Inhibitory Control Revealed by Combining Connectome-based Lesion-symptom Mapping with Event-related Potentials. Brain Topogr 2024:10.1007/s10548-024-01057-z. [PMID: 38858320 DOI: 10.1007/s10548-024-01057-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 05/10/2024] [Indexed: 06/12/2024]
Abstract
Inhibitory control refers to the ability to suppress cognitive or motor processes. Current neurocognitive models indicate that this function mainly involves the anterior cingulate cortex and the inferior frontal cortex. However, how the communication between these areas influence inhibitory control performance and their functional response remains unknown. We addressed this question by injecting behavioral and electrophysiological markers of inhibitory control recorded during a Go/NoGo task as the 'symptoms' in a connectome-based lesion-symptom mapping approach in a sample of 96 first unilateral stroke patients. This approach enables us to identify the white matter tracts whose disruption by the lesions causally influences brain functional activity during inhibitory control. We found a central role of left frontotemporal and frontobasal intrahemispheric connections, as well as of the connections between the left temporoparietal and right temporal areas in inhibitory control performance. We also found that connections between the left temporal and right superior parietal areas modulate the conflict-related N2 event-related potential component and between the left temporal parietal area and right temporal and occipital areas for the inhibition P3 component. Our study supports the role of a distributed bilateral network in inhibitory control and reveals that combining lesion-symptom mapping approaches with functional indices of cognitive processes could shed new light on post-stroke functional reorganization. It may further help to refine the interpretation of classical electrophysiological markers of executive control in stroke patients.
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Affiliation(s)
- Alex S T Nono
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland
| | - Marco Anziano
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland
| | - Michael Mouthon
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland
| | - Joelle N Chabwine
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland
- Neurology Unit, Department of Internal Medicine and Specialties, Fribourg Hospital, Fribourg, Switzerland
| | - Lucas Spierer
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, PER 09, Chemin du Musée 5, 1700, Fribourg, Switzerland.
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3
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Moore MJ, Byrne J, Gibson EC, Ford L, Robinson GA. Hayling and stroop tests tap dissociable deficits and network-level neural correlates. Brain Struct Funct 2024; 229:879-896. [PMID: 38478051 PMCID: PMC11004053 DOI: 10.1007/s00429-024-02767-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 01/24/2024] [Indexed: 04/10/2024]
Abstract
Although many executive function screens have been developed, it is not yet clear whether these assessments are equally effective in detecting post-stroke deficits of initiation and inhibition. This study presents a comparative analysis of the Stroop and Hayling tests aiming to evaluate whether these tests measure the same underlying cognitive functions and to identify the neural correlates of the deficits detected by both tasks. Sixty six stroke survivors and 70 healthy ageing controls completed the Hayling and Stroop tests. Stroke patients were found to exhibit qualitative performance differences across analogous Stroop and Hayling Test metrics intended to tap initiation and inhibition. The Stroop test was found to have high specificity to abnormal performance, but low sensitivity relative to the Hayling Test. Minimal overlap was present between the network-level correlates of analogous Stroop and Hayling Test metrics. Hayling Task strategy use metrics were significantly associated with distinct patterns of disconnection in stroke survivors, providing novel insight into the neural correlates of fine-grained behavioural patterns. Overall, these findings strongly suggest that the functions tapped by the Stroop and Hayling Test are both behaviourally and anatomically dissociable. The Hayling Test was found to offer improved sensitivity and detail relative to the Stroop test. This novel demonstration of the Hayling Test within the stroke population suggests that this task represents an effective measure for quantifying post-stroke initiation and inhibition deficits.
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Affiliation(s)
- Margaret Jane Moore
- Queensland Brain Institute, The University of Queensland, St Lucia, Brisbane, Australia
| | - Jessica Byrne
- Neuropsychology Research Unit, School of Psychology, The University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia
| | - Emily C Gibson
- Neuropsychology Research Unit, School of Psychology, The University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia
| | - Lucy Ford
- Queensland Brain Institute, The University of Queensland, St Lucia, Brisbane, Australia
- Neuropsychology Research Unit, School of Psychology, The University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia
| | - Gail A Robinson
- Queensland Brain Institute, The University of Queensland, St Lucia, Brisbane, Australia.
- Neuropsychology Research Unit, School of Psychology, The University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia.
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4
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Hobden G, Moore MJ, Mair G, Pendlebury ST, Demeyere N. Poststroke Executive Function in Relation to White Matter Damage on Clinically Acquired CT Brain Imaging. Cogn Behav Neurol 2024; 37:23-31. [PMID: 37724754 DOI: 10.1097/wnn.0000000000000355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 04/21/2023] [Indexed: 09/21/2023]
Abstract
BACKGROUND Executive function (EF) impairments are prevalent post stroke and are associated with white matter (WM) damage on MRI. However, less is known about the relationship between poststroke EF and WM damage on CT imaging. OBJECTIVE To investigate the relationship between poststroke EF and WM damage associated with stroke lesions and WM hypointensities (WMHs) on clinically acquired CT imaging. METHOD This study analyzed data from the Oxford Cognitive Screening Program, which recruited individuals aged ≥18 years with a confirmed stroke from an acute stroke unit. The individuals completed a follow-up assessment 6 months post stroke. We included individuals with a CT scan showing a visible stroke who completed follow-up EF assessment using the Oxford Cognitive Screen-Plus rule-finding task. We manually delineated stroke lesions and quantified then dichotomized WM damage caused by the stroke using the HCP-842 atlas. We visually rated then dichotomized WMHs using the Age-Related White Matter Changes Scale. RESULTS Among 87 stroke survivors (M age = 73.60 ± 11.75; 41 female; 61 ischemic stroke), multivariable linear regression showed that stroke damage to the medial lemniscus ( B = -8.86, P < 0.001) and the presence of WMHs ( B = -5.42, P = 0.005) were associated with poorer EF 6 months post stroke after adjusting for covariates including age and education. CONCLUSION Poorer EF was associated with WM damage caused by stroke lesions and WMHs on CT. These results confirm the importance of WM integrity for EF post stroke and demonstrate the prognostic utility of CT-derived imaging markers for poststroke cognitive outcomes.
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Affiliation(s)
- Georgina Hobden
- Department of Experimental Psychology, University of Oxford, Oxford, England
| | - Margaret Jane Moore
- Department of Experimental Psychology, University of Oxford, Oxford, England
- Queensland Brain Institute, University of Queensland, Queensland, Australia
| | - Grant Mair
- Centre for Clinical Brain Sciences, University of Edinburgh, and Neuroradiology, Department of Clinical Neurosciences, National Health Service Lothian, Edinburgh, Scotland
| | - Sarah T Pendlebury
- Wolfson Centre for Prevention of Stroke and Dementia, Wolfson Building, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England
- National Institute for Health Research Oxford Biomedical Research Centre and Departments of General (Internal) Medicine and Geratology, John Radcliffe Hospital, Oxford, England
| | - Nele Demeyere
- Department of Experimental Psychology, University of Oxford, Oxford, England
- Wolfson Centre for Prevention of Stroke and Dementia, Wolfson Building, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, England
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5
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Jiang Y, Gong G. Common and distinct patterns underlying different linguistic tasks: multivariate disconnectome symptom mapping in poststroke patients. Cereb Cortex 2024; 34:bhae008. [PMID: 38265297 DOI: 10.1093/cercor/bhae008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 01/04/2023] [Accepted: 01/05/2023] [Indexed: 01/25/2024] Open
Abstract
Numerous studies have been devoted to neural mechanisms of a variety of linguistic tasks (e.g. speech comprehension and production). To date, however, whether and how the neural patterns underlying different linguistic tasks are similar or differ remains elusive. In this study, we compared the neural patterns underlying 3 linguistic tasks mainly concerning speech comprehension and production. To address this, multivariate regression approaches with lesion/disconnection symptom mapping were applied to data from 216 stroke patients with damage to the left hemisphere. The results showed that lesion/disconnection patterns could predict both poststroke scores of speech comprehension and production tasks; these patterns exhibited shared regions on the temporal pole of the left hemisphere as well as unique regions contributing to the prediction for each domain. Lower scores in speech comprehension tasks were associated with lesions/abnormalities in the superior temporal gyrus and middle temporal gyrus, while lower scores in speech production tasks were associated with lesions/abnormalities in the left inferior parietal lobe and frontal lobe. These results suggested an important role of the ventral and dorsal stream pathways in speech comprehension and production (i.e. supporting the dual stream model) and highlighted the applicability of the novel multivariate disconnectome-based symptom mapping in cognitive neuroscience research.
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Affiliation(s)
- Yaya Jiang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Gaolang Gong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China
- Chinese Institute for Brain Research, Beijing 102206, China
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6
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Doganci N, Yahia Coll S, Marti E, Ptak R. Anatomical predictors of mental rotation with bodily and non-bodily stimuli: A lesion-symptom study. Neuropsychologia 2024; 193:108775. [PMID: 38135209 DOI: 10.1016/j.neuropsychologia.2023.108775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/19/2023] [Accepted: 12/19/2023] [Indexed: 12/24/2023]
Abstract
Mental rotation (MR) is widely regarded as a quintessential example of an embodied cognitive process. This viewpoint stems from the functional parallels between MR and the physical rotation of tangible objects, as well as participants' inclination to employ motor-based strategies when tackling MR tasks involving bodily stimuli. These commonalities imply that MR may depend on brain regions crucial for the planning and execution of motor programs. However, there is disagreement regarding the anatomy of MR between findings from functional imaging and lesion studies involving brain-injured patients. The former indicate the involvement of the right-hemispheric parietal cortex, while the latter underscore the significance of posterior areas in the left hemisphere. In this study, we aimed to discern the neural underpinnings of MR using lesion-symptom mapping (LSM) for both bodily (hands) and non-bodily (letters) stimuli. Behavioral results from the two MR tasks revealed impaired MR of bodily stimuli in patients with left hemisphere damage. LSM results pinpointed the left primary motor and somatosensory cortices, along with the superior parietal lobule, as the anatomical substrates of MR for both bodily and non-bodily stimuli. Furthermore, damage to the left angular gyrus, supramarginal gyrus, supplementary motor area, and retrosplenial cortex was associated with MR of non-bodily stimuli. These findings support the causal involvement of the left hemisphere in MR and underscore the existence of a common anatomical substrate in brain regions pertinent to motor planning and execution.
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Affiliation(s)
- Naz Doganci
- Laboratory of Cognitive Neurorehabilitation, Faculty of medicine, University of Geneva, 1206, Geneva, Switzerland.
| | - Sélim Yahia Coll
- Laboratory of Cognitive Neurorehabilitation, Faculty of medicine, University of Geneva, 1206, Geneva, Switzerland
| | - Emilie Marti
- Laboratory of Cognitive Neurorehabilitation, Faculty of medicine, University of Geneva, 1206, Geneva, Switzerland
| | - Radek Ptak
- Laboratory of Cognitive Neurorehabilitation, Faculty of medicine, University of Geneva, 1206, Geneva, Switzerland; Division of Neurorehabilitation, University Hospitals of Geneva, Rue Gabrielle-Perret-Gentil 4, 1205, Geneva, Switzerland.
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7
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Moore MJ, Demeyere N, Rorden C, Mattingley JB. Lesion mapping in neuropsychological research: A practical and conceptual guide. Cortex 2024; 170:38-52. [PMID: 37940465 DOI: 10.1016/j.cortex.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2023] [Revised: 10/10/2023] [Accepted: 10/10/2023] [Indexed: 11/10/2023]
Affiliation(s)
- Margaret J Moore
- Queensland Brain Institute, The University of Queensland, St. Lucia, Australia.
| | - Nele Demeyere
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Colombia, SC, USA
| | - Jason B Mattingley
- Queensland Brain Institute, The University of Queensland, St. Lucia, Australia; School of Psychology, The University of Queensland, St. Lucia, Australia
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8
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Yoon KJ, Park CH, Rho MH, Kim M. Disconnection-Based Prediction of Poststroke Dysphagia. AJNR Am J Neuroradiol 2023; 45:57-65. [PMID: 38164540 PMCID: PMC10756566 DOI: 10.3174/ajnr.a8074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 10/24/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND AND PURPOSE Dysphagia is a common deficit after a stroke and is associated with serious complications. It is not yet fully clear which brain regions are directly related to swallowing. Previous lesion symptom mapping studies may have overlooked structural disconnections that could be responsible for poststroke dysphagia. Here, we aimed to predict and explain the relationship between poststroke dysphagia and the topologic distribution of structural disconnection via a multivariate predictive framework. MATERIALS AND METHODS We enrolled first-ever ischemic stroke patients classified as full per-oral nutrition (71 patients) and nonoral nutrition necessary (43 patients). After propensity score matching, 43 patients for each group were enrolled (full per-oral nutrition group with 17 women, 68 ± 15 years; nonoral nutrition necessary group with 13 women, 75 ± 11 years). The structural disconnectome was estimated by using the lesion segmented from acute phase diffusion-weighted images. The prediction of poststroke dysphagia by using the structural disconnectome and demographics was performed in a leave-one-out manner. RESULTS Using both direct and indirect disconnection matrices of the motor network, the disconnectome-based prediction model could predict poststroke dysphagia above the level of chance (accuracy = 68.6%, permutation P = .001). When combined with demographic data, the classification accuracy reached 72.1%. The edges connecting the right insula and left motor strip were the most informative in prediction. CONCLUSIONS Poststroke dysphagia could be predicted by using the structural disconnectome derived from acute phase diffusion-weighted images. Specifically, the direct and indirect disconnection within the motor network was the most informative in predicting poststroke dysphagia.
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Affiliation(s)
- Kyung Jae Yoon
- From the Department of Physical and Rehabilitation Medicine (K.J.Y., C.-H.P.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine
- Medical Research Institute (K.J.Y., C.-H.P.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine
| | - Chul-Hyun Park
- From the Department of Physical and Rehabilitation Medicine (K.J.Y., C.-H.P.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine
- Medical Research Institute (K.J.Y., C.-H.P.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine
| | - Myung-Ho Rho
- Department of Radiology (M.-H.R., M.K.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Minchul Kim
- Department of Radiology (M.-H.R., M.K.), Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
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9
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Kim M, Choi KS, Hyun RC, Hwang I, Kwon YN, Sung JJ, Kim SM, Kim JH. Structural disconnection is associated with disability in the neuromyelitis optica spectrum disorder. Brain Imaging Behav 2023; 17:664-673. [PMID: 37676409 DOI: 10.1007/s11682-023-00792-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/28/2023] [Indexed: 09/08/2023]
Abstract
OBJECTIVES Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune inflammatory disease of the central nervous system. Accumulating evidence suggests there is a distinct pattern of brain lesions characteristic of NMOSD, and brain MRI has potential prognostic implications. However, the question of how the brain lesions in NMOSD are associated with its distinct clinical course remains incompletely understood. Here, we aimed to investigate the association between neurological impairment and brain lesions via brain structural disconnection. METHODS Twenty patients were diagnosed with NMOSD according to the 2015 International Panel for NMO Diagnosis criteria. The white matter lesions were manually drawn section by section. Whole-brain structural disconnection was estimated, and connectome-based predictive modeling (CPM) was used to estimate the patient's Expanded Disability Status Scale score (EDSS) from their disconnection severity matrix. Furthermore, correlational tractography was performed to assess the fractional anisotropy (FA) and axial diffusivity (AD) of white matter fibers, which negatively correlated with the EDSS score. RESULTS CPM successfully predicted the EDSS using the disconnection severity matrix (r = 0.506, p = 0.028; q2 = 0.274). Among the important edges in the prediction process, the majority of edges connected the motor to the frontoparietal network. Correlational tractography identified a decreased FA and AD value according to EDSS scores in periependymal white matter tracts. DISCUSSION Structural disconnection-based predictive modeling and local connectome analysis showed that frontoparietal and periependymal white matter disconnection is predictive and associated with the EDSS score of NMOSD patients.
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Affiliation(s)
- Minchul Kim
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kyu Sung Choi
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Ryoo Chang Hyun
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Inpyeong Hwang
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Young Nam Kwon
- Department of Neurology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Jung-Joon Sung
- Department of Neurology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea
| | - Sung Min Kim
- Department of Neurology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea.
| | - Ji-Hoon Kim
- Department of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, Seoul, 110-744, Republic of Korea.
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10
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Moore MJ, Hearne L, Demeyere N, Mattingley JB. Comprehensive voxel-wise, tract-based, and network lesion mapping reveals unique architectures of right and left visuospatial neglect. Brain Struct Funct 2023; 228:2067-2087. [PMID: 37697138 PMCID: PMC10587018 DOI: 10.1007/s00429-023-02702-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 08/27/2023] [Indexed: 09/13/2023]
Abstract
Visuospatial neglect is a common, post-stroke cognitive impairment which is widely considered to be a disconnection syndrome. However, the patterns of disconnectivity associated with visuospatial neglect remain unclear. Here, we had 480 acute stroke survivors [age = 72.8 (SD = 13.3), 44.3% female, 7.5 days post-stroke (SD = 11.3)] undertake routine clinical imaging and standardised visuospatial neglect testing. The data were used to conduct voxel-wise, tract-level, and network-level lesion-mapping analyses aimed at localising the neural correlates of left and right egocentric (body-centred) and allocentric (object-centred) visuospatial neglect. Only minimal anatomical homogeneity was present between the correlates of right and left egocentric neglect across all analysis types. This finding challenges previous work suggesting that right and left visuospatial neglect are anatomically homologous, and instead suggests that egocentric neglect may involve damage to a shared, but hemispherically asymmetric attention network. By contrast, egocentric and allocentric neglect was associated with disconnectivity in a distinct but overlapping set of network edges, with both deficits related to damage across the dorsal and ventral attention networks. Critically, this finding suggests that the distinction between egocentric and allocentric neglect is unlikely to reflect a simple dichotomy between dorsal versus ventral networks dysfunction, as is commonly asserted. Taken together, the current findings provide a fresh perspective on the neural circuitry involved in regulating visuospatial attention, and provide important clues to understanding the cognitive and perceptual processes involved in this common and debilitating neuropsychological syndrome.
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Affiliation(s)
- Margaret Jane Moore
- Queensland Brain Institute, University of Queensland, St. Lucia, QLD, 4072, Australia.
| | - Luke Hearne
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Nele Demeyere
- Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - Jason B Mattingley
- Queensland Brain Institute, University of Queensland, St. Lucia, QLD, 4072, Australia
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Ding J, Middleton EL, Mirman D. Impaired discourse content in aphasia is associated with frontal white matter damage. Brain Commun 2023; 5:fcad310. [PMID: 38025278 PMCID: PMC10664411 DOI: 10.1093/braincomms/fcad310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 09/04/2023] [Accepted: 11/09/2023] [Indexed: 12/01/2023] Open
Abstract
Aphasia is a common consequence of stroke with severe impacts on employability, social interactions and quality of life. Producing discourse-relevant information in a real-world setting is the most important aspect of recovery because it is critical to successful communication. This study sought to identify the lesion correlates of impaired production of relevant information in spoken discourse in a large, unselected sample of participants with post-stroke aphasia. Spoken discourse (n = 80) and structural brain scans (n = 66) from participants with aphasia following left hemisphere stroke were analysed. Each participant provided 10 samples of spoken discourse elicited in three different genres, and 'correct information unit' analysis was used to quantify the informativeness of speech samples. The lesion correlates were identified using multivariate lesion-symptom mapping, voxel-wise disconnection and tract-wise analyses. Amount and speed of relevant information were highly correlated across different genres and with total lesion size. The analyses of lesion correlates converged on the same pattern: impaired production of relevant information was associated with damage to anterior dorsal white matter pathways, specifically the arcuate fasciculus, frontal aslant tract and superior longitudinal fasciculus. Damage to these pathways may be a useful biomarker for impaired informative spoken discourse and informs development of neurorehabilitation strategies.
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Affiliation(s)
- Junhua Ding
- Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | | | - Daniel Mirman
- Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
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Salvalaggio A, Pini L, Gaiola M, Velco A, Sansone G, Anglani M, Fekonja L, Chioffi F, Picht T, Thiebaut de Schotten M, Zagonel V, Lombardi G, D’Avella D, Corbetta M. White Matter Tract Density Index Prediction Model of Overall Survival in Glioblastoma. JAMA Neurol 2023; 80:1222-1231. [PMID: 37747720 PMCID: PMC10520843 DOI: 10.1001/jamaneurol.2023.3284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 07/07/2023] [Indexed: 09/26/2023]
Abstract
Importance The prognosis of overall survival (OS) in patients with glioblastoma (GBM) may depend on the underlying structural connectivity of the brain. Objective To examine the association between white matter tracts affected by GBM and patients' OS by means of a new tract density index (TDI). Design, Setting, and Participants This prognostic study in patients with a histopathologic diagnosis of GBM examined a discovery cohort of 112 patients who underwent surgery between February 1, 2015, and November 30, 2020 (follow-up to May 31, 2023), in Italy and 70 patients in a replicative cohort (n = 70) who underwent surgery between September 1, 2012, and November 30, 2015 (follow-up to May 31, 2023), in Germany. Statistical analyses were performed from June 1, 2021, to May 31, 2023. Thirteen and 12 patients were excluded from the discovery and the replicative sets, respectively, because of magnetic resonance imaging artifacts. Exposure The density of white matter tracts encompassing GBM. Main Outcomes and Measures Correlation, linear regression, Cox proportional hazards regression, Kaplan-Meier, and prediction analysis were used to assess the association between the TDI and OS. Results were compared with common prognostic factors of GBM, including age, performance status, O6-methylguanine-DNA methyltransferase methylation, and extent of surgery. Results In the discovery cohort (n = 99; mean [SD] age, 62.2 [11.5] years; 29 female [29.3%]; 70 male [70.7%]), the TDI was significantly correlated with OS (r = -0.34; P < .001). This association was more stable compared with other prognostic factors. The TDI showed a significant regression pattern (Cox: hazard ratio, 0.28 [95% CI, 0.02-0.55; P = .04]; linear: t = -2.366; P = .02). and a significant Kaplan-Meier stratification of patients as having lower or higher OS based on the TDI (log-rank test = 4.52; P = .03). Results were confirmed in the replicative cohort (n = 58; mean [SD] age, 58.5 [11.1] years, 14 female [24.1%]; 44 male [75.9%]). High (24-month cutoff) and low (18-month cutoff) OS was predicted based on the TDI computed in the discovery cohort (accuracy = 87%). Conclusions and Relevance In this study, GBMs encompassing regions with low white matter tract density were associated with longer OS. These findings indicate that the TDI is a reliable presurgical outcome predictor that may be considered in clinical trials and clinical practice. These findings support a framework in which the outcome of GBM depends on the patient's brain organization.
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Affiliation(s)
- Alessandro Salvalaggio
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Lorenzo Pini
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Matteo Gaiola
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
| | - Aron Velco
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
| | - Giulio Sansone
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
| | | | - Lucius Fekonja
- Department of Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany
- Cluster of Excellence “Matters of Activity. Image Space Material,” Humboldt University, Berlin, Germany
| | - Franco Chioffi
- Division of Neurosurgery, Azienda Ospedaliera Università di Padova, Padova, Italy
| | - Thomas Picht
- Department of Neurosurgery, Charité Universitätsmedizin Berlin, Berlin, Germany
- Cluster of Excellence “Matters of Activity. Image Space Material,” Humboldt University, Berlin, Germany
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France
- Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France
| | - Vittorina Zagonel
- Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Giuseppe Lombardi
- Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Domenico D’Avella
- Academic Neurosurgery, Department of Neurosciences, University of Padova, Padova, Italy
| | - Maurizio Corbetta
- Clinica Neurologica, Department of Neuroscience, University of Padova, Padova, Italy
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Venetian Institute of Molecular Medicine, Fondazione Biomedica, Padova, Italy
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13
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Röhrig L, Rosenzopf H, Wöhrstein S, Karnath H. The need for hemispheric separation in pairwise structural disconnection studies. Hum Brain Mapp 2023; 44:5212-5220. [PMID: 37539793 PMCID: PMC10543104 DOI: 10.1002/hbm.26445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/05/2023] [Accepted: 07/21/2023] [Indexed: 08/05/2023] Open
Abstract
The development of new approaches indirectly measuring the structural disconnectome has recently led to an increase in studies investigating pairwise structural disconnections following brain damage. Previous studies jointly analyzed patients with left hemispheric and patients with right hemispheric lesions when investigating a behavior of interest. An alternative approach would be to perform analyses separated by hemisphere, which has been applied in only a minority of studies to date. The present simulation study investigated whether joint or separate analyses (or both equally) are appropriate to reveal the ground truth disconnections. In fact, both approaches resulted in very different patterns of disconnection. In contrast to analyses separated by hemisphere, joint analyses introduced a bias to the disadvantage of intra-hemispheric disconnections. Intra-hemispheric disconnections were statistically underpowered in the joint analysis and thus surpassed the significance threshold with more difficulty compared to inter-hemispheric disconnections. This statistical imbalance was also shown by a greater number of significant inter-hemispheric than significant intra-hemispheric disconnections. This bias from joint analyses is based on mechanisms similar to those underlying the "partial injury problem." We therefore conclude that pairwise structural disconnections in patients with unilateral left hemispheric and with unilateral right hemispheric lesions exhibiting a specific behavior (or disorder) of interest should be studied separately by hemisphere rather than in a joint analysis.
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Affiliation(s)
- Lisa Röhrig
- Center of Neurology, Division of Neuropsychology, Hertie‐Institute for Clinical Brain ResearchUniversity of TübingenTübingenGermany
| | - Hannah Rosenzopf
- Center of Neurology, Division of Neuropsychology, Hertie‐Institute for Clinical Brain ResearchUniversity of TübingenTübingenGermany
| | - Sofia Wöhrstein
- Center of Neurology, Division of Neuropsychology, Hertie‐Institute for Clinical Brain ResearchUniversity of TübingenTübingenGermany
| | - Hans‐Otto Karnath
- Center of Neurology, Division of Neuropsychology, Hertie‐Institute for Clinical Brain ResearchUniversity of TübingenTübingenGermany
- Department of PsychologyUniversity of South CarolinaColumbiaSouth CarolinaUSA
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14
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Sperber C, Gallucci L, Umarova R. Reply: The correlation of behavioural deficits post-stroke: a trivial issue? Brain 2023; 146:e86-e88. [PMID: 37224518 DOI: 10.1093/brain/awad174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 05/06/2023] [Indexed: 05/26/2023] Open
Affiliation(s)
- Christoph Sperber
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, 3010 Bern, Switzerland
| | - Laura Gallucci
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, 3010 Bern, Switzerland
| | - Roza Umarova
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, 3010 Bern, Switzerland
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15
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Rosenzopf H, Klingbeil J, Wawrzyniak M, Röhrig L, Sperber C, Saur D, Karnath HO. Thalamocortical disconnection involved in pusher syndrome. Brain 2023; 146:3648-3661. [PMID: 36943319 DOI: 10.1093/brain/awad096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 02/13/2023] [Accepted: 03/02/2023] [Indexed: 03/23/2023] Open
Abstract
The presence of both isolated thalamic and isolated cortical lesions have been reported in the context of pusher syndrome-a disorder characterized by a disturbed perception of one's own upright body posture, following unilateral left- or right-sided stroke. In recent times, indirect quantification of functional and structural disconnection increases the knowledge derived from focal brain lesions by inferring subsequent brain network damage from the respective lesion. We applied both measures to a sample of 124 stroke patients to investigate brain disconnection in pusher syndrome. Our results suggest a hub-like function of the posterior and lateral portions of the thalamus in the perception of one's own postural upright. Lesion network symptom mapping investigating functional disconnection indicated cortical diaschisis in cerebellar, frontal, parietal and temporal areas in patients with thalamic lesions suffering from pusher syndrome, but there was no evidence for functional diaschisis in pusher patients with cortical stroke and no evidence for the convergence of thalamic and cortical lesions onto a common functional network. Structural disconnection mapping identified posterior thalamic disconnection to temporal, pre-, post- and paracentral regions. Fibre tracking between the thalamic and cortical pusher lesion hotspots indicated that in cortical lesions of patients with pusher syndrome, it is disconnectivity to the posterior thalamus caused by accompanying white matter damage, rather than the direct cortical lesions themselves, that lead to the emergence of pusher syndrome. Our analyses thus offer the first evidence for a direct thalamo-cortical (or cortico-thalamic) interconnection and, more importantly, shed light on the location of the respective thalamo-cortical disconnections. Pusher syndrome seems to be a consequence of direct damage or of disconnection of the posterior thalamus.
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Affiliation(s)
- Hannah Rosenzopf
- Center of Neurology, Division of Neuropsychology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany
| | - Julian Klingbeil
- Neuroimaging Lab, Department of Neurology, University of Leipzig, 04103 Leipzig, Germany
| | - Max Wawrzyniak
- Neuroimaging Lab, Department of Neurology, University of Leipzig, 04103 Leipzig, Germany
| | - Lisa Röhrig
- Center of Neurology, Division of Neuropsychology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany
| | - Christoph Sperber
- Center of Neurology, Division of Neuropsychology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany
| | - Dorothee Saur
- Neuroimaging Lab, Department of Neurology, University of Leipzig, 04103 Leipzig, Germany
| | - Hans-Otto Karnath
- Center of Neurology, Division of Neuropsychology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076 Tübingen, Germany
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
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16
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Buijink AW, Snijders AH, Helmich RC. Dystonic Tremor Disappearance after Internal Capsule Stroke. Mov Disord Clin Pract 2023; 10:1203-1206. [PMID: 37635775 PMCID: PMC10450227 DOI: 10.1002/mdc3.13790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 03/07/2023] [Accepted: 05/05/2023] [Indexed: 08/29/2023] Open
Affiliation(s)
- Arthur W.G. Buijink
- Department of NeurologyAmsterdam University Medical Centers, Amsterdam Neuroscience, University of AmsterdamAmsterdamThe Netherlands
| | - Anke H. Snijders
- Department of Neurology, Center of Expertise for Parkinson & Movement DisordersDonders Institute for Brain, Cognition and Behaviour, Radboud University Medical CentreNijmegenThe Netherlands
| | - Rick C. Helmich
- Department of Neurology, Center of Expertise for Parkinson & Movement DisordersDonders Institute for Brain, Cognition and Behaviour, Radboud University Medical CentreNijmegenThe Netherlands
- Centre for Cognitive NeuroimagingDonders Institute for Brain, Cognition and Behaviour, Radboud UniversityNijmegenThe Netherlands
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17
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Anziano M, Mouthon M, Thoeny H, Sperber C, Spierer L. Mental flexibility depends on a largely distributed white matter network: Causal evidence from connectome-based lesion-symptom mapping. Cortex 2023; 165:38-56. [PMID: 37253289 DOI: 10.1016/j.cortex.2023.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/20/2022] [Accepted: 04/06/2023] [Indexed: 06/01/2023]
Abstract
Mental flexibility (MF) refers to the capacity to dynamically switch from one task to another. Current neurocognitive models suggest that since this function requires interactions between multiple remote brain areas, the integrity of the anatomic tracts connecting these brain areas is necessary to maintain performance. We tested this hypothesis by assessing with a connectome-based lesion-symptom mapping approach the effects of white matter lesions on the brain's structural connectome and their association with performance on the trail making test, a neuropsychological test of MF, in a sample of 167 first unilateral stroke patients. We found associations between MF deficits and damage of i) left lateralized fronto-temporo-parietal connections and interhemispheric connections between left temporo-parietal and right parietal areas; ii) left cortico-basal connections; and iii) left cortico-pontine connections. We further identified a relationship between MF and white matter disconnections within cortical areas composing the cognitive control, default mode and attention functional networks. These results for a central role of white matter integrity in MF extend current literature by providing causal evidence for a functional interdependence among the regional cortical and subcortical structures composing the MF network. Our results further emphasize the necessity to consider connectomics in lesion-symptom mapping analyses to establish comprehensive neurocognitive models of high-order cognitive functions.
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Affiliation(s)
- Marco Anziano
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland.
| | - Michael Mouthon
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland
| | - Harriet Thoeny
- Department of Diagnostic and Interventional Radiology, Cantonal Hospital of Fribourg, University of Fribourg, Fribourg, Switzerland
| | - Christoph Sperber
- Department of Neurology, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Lucas Spierer
- Laboratory for Neurorehabilitation Science, Medicine Section, Faculty of Science and Medicine, University of Fribourg, Fribourg, Switzerland
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18
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Tuncer MS, Fekonja LS, Ott S, Pfnür A, Karbe AG, Engelhardt M, Faust K, Picht T, Coburger J, Dührsen L, Vajkoczy P, Onken J. Role of interhemispheric connectivity in recovery from postoperative supplementary motor area syndrome in glioma patients. J Neurosurg 2023; 139:324-333. [PMID: 36461815 DOI: 10.3171/2022.10.jns221303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 10/18/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVE Surgical resection of gliomas involving the supplementary motor area (SMA) frequently results in SMA syndrome, a symptom complex characterized by transient akinesia and mutism. Because the factors influencing patient functional outcomes after surgery remain elusive, the authors investigated network-based predictors in a multicentric cohort of glioma patients. METHODS The participants were 50 patients treated for glioma located in the SMA at one of the three centers participating in the study. Postoperative functional outcomes (motor deficits, mutism) and duration of symptoms were assessed during hospitalization. Long-term outcome was assessed 3 months after surgery. MRI-based lesion-symptom mapping was performed to estimate the severity of gray matter damage and white matter disconnection. RESULTS The median duration of acute symptoms was 3 days (range 1-42 days). Long-term deficits involving fine motor movements and speech were found at follow-up in 27 patients (54%). Disconnection of the central callosal fibers was associated with prolonged acute symptoms (p < 0.05). Postoperative mutism was significantly related to disconnection severity of the left frontopontine tract, frontal aslant tract, cingulum, and corticostriatal tract (p < 0.05). Disconnection of midposterior callosal fibers and lesion loads within the left medial Brodmann area 4 were associated with long-term motor deficits (p < 0.05). CONCLUSIONS This study provides evidence for the pathophysiology and predictive factors of postoperative SMA syndrome by demonstrating the relation of the disconnection of callosal fibers with prolonged symptom duration (central segment) and long-term motor deficits (midposterior segment). These data may be useful for presurgical risk assessment and adequate consultation for patients prior to undergoing resection of glioma located within the SMA region.
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Affiliation(s)
- Mehmet Salih Tuncer
- 1Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin
| | - Lucius S Fekonja
- 1Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin
- 2Cluster of Excellence: "Matters of Activity. Image Space Material," Humboldt University, Berlin
| | - Stefanie Ott
- 3Department of Neurosurgery, Universitätsklinikum Hamburg-Eppendorf, Hamburg
| | - Andreas Pfnür
- 4Department of Neurosurgery, Universitätsklinikum Ulm, Günzburg
| | - Anna-Gila Karbe
- 1Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin
| | - Melina Engelhardt
- 1Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin
- 5Einstein Center for Neurosciences, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin; and
| | - Katharina Faust
- 1Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin
| | - Thomas Picht
- 1Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin
- 2Cluster of Excellence: "Matters of Activity. Image Space Material," Humboldt University, Berlin
- 5Einstein Center for Neurosciences, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin; and
| | - Jan Coburger
- 4Department of Neurosurgery, Universitätsklinikum Ulm, Günzburg
| | - Lasse Dührsen
- 3Department of Neurosurgery, Universitätsklinikum Hamburg-Eppendorf, Hamburg
| | - Peter Vajkoczy
- 1Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin
| | - Julia Onken
- 1Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin
- 6German Cancer Consortium (DKTK), Partner Site Berlin, Germany
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19
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Smits AR, van Zandvoort MJE, Ramsey NF, de Haan EHF, Raemaekers M. Reliability and validity of DTI-based indirect disconnection measures. Neuroimage Clin 2023; 39:103470. [PMID: 37459698 PMCID: PMC10368919 DOI: 10.1016/j.nicl.2023.103470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 07/04/2023] [Accepted: 07/06/2023] [Indexed: 07/30/2023]
Abstract
White matter connections enable the interaction within and between brain networks. Brain lesions can cause structural disconnections that disrupt networks and thereby cognitive functions supported by them. In recent years, novel methods have been developed to quantify the extent of structural disconnection after focal lesions, using tractography data from healthy controls. These methods, however, are indirect and their reliability and validity have yet to be fully established. In this study, we present our implementation of this approach, in a tool supplemented by uncertainty metrics for the predictions overall and at voxel-level. These metrics give an indication of the reliability and are used to compare predictions with direct measures from patients' diffusion tensor imaging (DTI) data in a sample of 95 first-ever stroke patients. Results show that, except for small lesions, the tool can predict fiber loss with high reliability and compares well to direct patient DTI estimates. Clinical utility of the method was demonstrated using lesion data from a subset of patients suffering from hemianopia. Both tract-based measures outperformed lesion localization in mapping visual field defects and showed a network consistent with the known anatomy of the visual system. This study offers an important contribution to the validation of structural disconnection mapping. We show that indirect measures of structural disconnection can be a reliable and valid substitute for direct estimations of fiber loss after focal lesions. Moreover, based on these results, we argue that indirect structural disconnection measures may even be preferable to lower-quality single subject diffusion MRI when based on high-quality healthy control datasets.
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Affiliation(s)
- A R Smits
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, the Netherlands; Department of Psychology, University of Amsterdam, the Netherlands.
| | - M J E van Zandvoort
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, the Netherlands; Department of Experimental Psychology, Helmholtz Institute, Utrecht University, the Netherlands
| | - N F Ramsey
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, the Netherlands
| | - E H F de Haan
- Department of Psychology, University of Amsterdam, the Netherlands; St. Hugh's College, Oxford University, United Kingdom
| | - M Raemaekers
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, the Netherlands
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20
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Ng S, Valdes PA, Moritz-Gasser S, Lemaitre AL, Duffau H, Herbet G. Intraoperative functional remapping unveils evolving patterns of cortical plasticity. Brain 2023; 146:3088-3100. [PMID: 37029961 DOI: 10.1093/brain/awad116] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 03/18/2023] [Accepted: 03/23/2023] [Indexed: 04/09/2023] Open
Abstract
The efficiency with which the brain reorganizes following injury not only depends on the extent and the severity of the lesion, but also on its temporal features. It is established that diffuse low-grade gliomas (DLGG), brain tumours with a slow-growth rate, induce a compensatory modulation of the anatomo-functional architecture, making this kind of tumours an ideal lesion model to study the dynamics of neuroplasticity. Direct electrostimulation (DES) mapping is a well-tried procedure used during awake resection surgeries to identify and spare cortical epicentres which are critical for a range of functions. Because DLGG is a chronic disease, it inevitably relapses years after the initial surgery, and thus requires a second surgery to reduce tumour volume again. In this context, contrasting the cortical mappings obtained during two sequential neurosurgeries offers a unique opportunity to both identify and characterize the dynamic (i.e. re-evolving) patterns of cortical re-arrangements. Here, we capitalized on an unprecedented series of 101 DLGG patients who benefited from two DES-guided neurosurgeries usually spaced several years apart, resulting in a large DES dataset of 2082 cortical sites. All sites (either non-functional or associated with language, speech, motor, somatosensory and semantic processing) were recorded in Montreal Neurological Institute (MNI) space. Next, we used a multi-step approach to generate probabilistic neuroplasticity maps that reflected the dynamic rearrangements of cortical mappings from one surgery to another, both at the population and individual level. Voxel-wise neuroplasticity maps revealed regions with a relatively high potential of evolving reorganizations at the population level, including the supplementary motor area (SMA, Pmax = 0.63), the dorsolateral prefrontal cortex (dlPFC, Pmax = 0.61), the anterior ventral premotor cortex (vPMC, Pmax = 0.43) and the middle superior temporal gyrus (STG Pmax = 0.36). Parcel-wise neuroplasticity maps confirmed this potential for the dlPFC (Fisher's exact test, PFDR-corrected = 6.6 × 10-5), the anterior (PFDR-corrected = 0.0039) and the ventral precentral gyrus (PFDR-corrected = 0.0058). A series of clustering analyses revealed a topological migration of clusters, especially within the left dlPFC and STG (language sites); the left vPMC (speech arrest/dysarthria sites) and the right SMA (negative motor response sites). At the individual level, these dynamic changes were confirmed for the dlPFC (bilateral), the left vPMC and the anterior left STG (threshold free cluster enhancement, 5000 permutations, family-wise error-corrected). Taken as a whole, our results provide a critical insight into the dynamic potential of DLGG-induced continuing rearrangements of the cerebral cortex, with considerable implications for re-operations.
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Affiliation(s)
- Sam Ng
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, F-34095 Montpellier, France
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, F-34094 Montpellier, France
| | - Pablo A Valdes
- Department of Neurosurgery, University of Texas Medical Branch, Galveston, TX 78701-2982, USA
| | - Sylvie Moritz-Gasser
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, F-34095 Montpellier, France
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, F-34094 Montpellier, France
| | - Anne-Laure Lemaitre
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, F-34095 Montpellier, France
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, F-34094 Montpellier, France
| | - Hugues Duffau
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, F-34095 Montpellier, France
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, F-34094 Montpellier, France
| | - Guillaume Herbet
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, F-34095 Montpellier, France
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, F-34094 Montpellier, France
- Praxiling Laboratory, UMR 5267, CNRS, UPVM, F-34199 Montpellier, France
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21
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Yoo JH, Chong B, Barber PA, Stinear C, Wang A. Predicting Motor Outcomes Using Atlas-Based Voxel Features of Post-Stroke Neuroimaging: A Scoping Review. Neurorehabil Neural Repair 2023:15459683231173668. [PMID: 37191349 DOI: 10.1177/15459683231173668] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/17/2023]
Abstract
BACKGROUND Atlas-based voxel features have the potential to aid motor outcome prognostication after stroke, but are seldom used in clinically feasible prediction models. This could be because neuroimaging feature development is a non-standardized, complex, multistep process. This is a barrier to entry for researchers and poses issues for reproducibility and validation in a field of research where sample sizes are typically small. OBJECTIVES The primary aim of this review is to describe the methodologies currently used in motor outcome prediction studies using atlas-based voxel neuroimaging features. Another aim is to identify neuroanatomical regions commonly used for motor outcome prediction. METHODS A Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol was constructed and OVID Medline and Scopus databases were searched for relevant studies. The studies were then screened and details about imaging modality, image acquisition, image normalization, lesion segmentation, region of interest determination, and imaging measures were extracted. RESULTS Seventeen studies were included and examined. Common limitations were a lack of detailed reporting on image acquisition and the specific brain templates used for normalization and a lack of clear reasoning behind the atlas or imaging measure selection. A wide variety of sensorimotor regions relate to motor outcomes and there is no consensus use of one single sensorimotor atlas for motor outcome prediction. CONCLUSION There is an ongoing need to validate imaging predictors and further improve methodological techniques and reporting standards in neuroimaging feature development for motor outcome prediction post-stroke.
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Affiliation(s)
- Ji-Hun Yoo
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Benjamin Chong
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
- Department of Medicine, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Peter Alan Barber
- Department of Medicine, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Cathy Stinear
- Department of Medicine, The University of Auckland, Auckland, New Zealand
| | - Alan Wang
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
- Department of Medicine, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
- Centre for Medical Imaging, The University of Auckland, Auckland, New Zealand
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22
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Burkhardt E, Zemmoura I, Hirsch F, Lemaitre AL, Deverdun J, Moritz-Gasser S, Duffau H, Herbet G. The central role of the left inferior longitudinal fasciculus in the face-name retrieval network. Hum Brain Mapp 2023; 44:3254-3270. [PMID: 37051699 PMCID: PMC10171495 DOI: 10.1002/hbm.26279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 02/18/2023] [Accepted: 03/06/2023] [Indexed: 04/14/2023] Open
Abstract
Unsuccessful retrieval of proper names (PNs) is commonly observed in patients suffering from neurological conditions such as stroke or epilepsy. While a large body of works has suggested that PN retrieval relies on a cortical network centered on the left anterior temporal lobe (ATL), much less is known about the white matter connections underpinning this process. Sparse studies provided evidence for a possible role of the uncinate fasciculus, but the inferior longitudinal fasciculus (ILF) might also contribute, since it mainly projects into the ATL, interconnects it with the posterior lexical interface and is engaged in common name (CN) retrieval. To ascertain this hypothesis, we assessed 58 patients having undergone a neurosurgery for a left low-grade glioma by means of a famous face naming (FFN) task. The behavioural data were processed following a multilevel lesion approach, including location-based analyses, voxel-based lesion-symptom mapping (VLSM) and disconnection-symptom mapping. Different statistical models were generated to control for sociodemographic data, familiarity, biographical knowledge and control cognitive performances (i.e., semantic and episodic memory and CN retrieval). Overall, VLSM analyses indicated that damage to the mid-to-anterior part of the ventro-basal temporal cortex was especially associated with PN retrieval deficits. As expected, tract-oriented analyses showed that the left ILF was the most strongly associated pathway. Our results provide evidence for the pivotal role of the ILF in the PN retrieval network. This novel finding paves the way for a better understanding of the pathophysiological bases underlying PN retrieval difficulties in the various neurological conditions marked by white matter abnormalities.
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Affiliation(s)
- Eléonor Burkhardt
- Praxiling Laboratory, UMR5267, CNRS & Paul Valéry University, Montpellier, France
| | - Ilyess Zemmoura
- UMR1253, iBrain, University of Tours, INSERM, Tours, France
- Department of Neurosurgery, Bretonneau Hospital, CHRU de Tours, Tours, France
| | - Fabrice Hirsch
- Praxiling Laboratory, UMR5267, CNRS & Paul Valéry University, Montpellier, France
| | - Anne-Laure Lemaitre
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France
| | - Jeremy Deverdun
- Department of Neuroradiology, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France
- I2FH, Institut d'Imagerie Fonctionnelle Humaine, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France
| | - Sylvie Moritz-Gasser
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France
| | - Hugues Duffau
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France
| | - Guillaume Herbet
- Praxiling Laboratory, UMR5267, CNRS & Paul Valéry University, Montpellier, France
- Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France
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23
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de Zubicaray GI, Brownsett SLE, Copland DA, Drummond K, Jeffree RL, Olson S, Murton E, Ong B, Robinson GA, Tolkacheva V, McMahon KL. Chronic aphasias after left-hemisphere resective surgery. BRAIN AND LANGUAGE 2023; 239:105244. [PMID: 36889018 DOI: 10.1016/j.bandl.2023.105244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 01/23/2023] [Accepted: 02/23/2023] [Indexed: 05/10/2023]
Abstract
Surgical resection of brain tumours is associated with an increased risk of aphasia. However, relatively little is known about outcomes in the chronic phase (i.e., >6 months). Using voxel-based lesion symptom mapping (VLSM) in 46 patients, we investigated whether chronic language impairments are related to the location of surgical resection, residual tumour characteristics (e.g., peri-resection treatment effects, progressive infiltration, oedema) or both. Approximately 72% of patients scored below the cut-off for aphasia. Action naming and spoken sentence comprehension deficits were associated with lesions in the left anterior temporal and inferior parietal lobes, respectively. Voxel-wise analyses revealed significant associations between ventral language pathways and action naming deficits. Reading impairments were also associated with increasing disconnection of cerebellar pathways. The results indicate chronic post-surgical aphasias reflect a combination of resected tissue and tumour infiltration of language-related white matter tracts, implicating progressive disconnection as the critical mechanism of impairment.
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Affiliation(s)
- Greig I de Zubicaray
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, QLD 4059, Australia.
| | - Sonia L E Brownsett
- School of Health and Rehabilitation Sciences, University of Queensland, Brisbane, QLD 4072, Australia; Centre of Research Excellence in Aphasia Recovery and Rehabilitation, Australia
| | - David A Copland
- School of Health and Rehabilitation Sciences, University of Queensland, Brisbane, QLD 4072, Australia; Centre of Research Excellence in Aphasia Recovery and Rehabilitation, Australia
| | - Kate Drummond
- Royal Melbourne Hospital, Melbourne, VIC 3050, Australia
| | | | - Sarah Olson
- Princess Alexandra Hospital, Brisbane, QLD 4102, Australia
| | - Emma Murton
- Royal Melbourne Hospital, Melbourne, VIC 3050, Australia
| | - Benjamin Ong
- Princess Alexandra Hospital, Brisbane, QLD 4102, Australia
| | - Gail A Robinson
- Queensland Brain Institute and School of Psychology, University of Queensland, Brisbane, QLD 4072, Australia
| | - Valeriya Tolkacheva
- School of Psychology and Counselling, Queensland University of Technology, Brisbane, QLD 4059, Australia
| | - Katie L McMahon
- School of Clinical Sciences, Centre for Biomedical Technologies, Queensland University of Technology, Brisbane, QLD 4059, Australia; Herston Imaging Research Facility, Royal Brisbane & Women's Hospital, Brisbane, QLD 4029, Australia
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24
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Seghier ML. The elusive metric of lesion load. Brain Struct Funct 2023; 228:703-716. [PMID: 36947181 DOI: 10.1007/s00429-023-02630-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/15/2023] [Indexed: 03/23/2023]
Abstract
One of the widely used metrics in lesion-symptom mapping is lesion load that codes the amount of damage to a given brain region of interest. Lesion load aims to reduce the complex 3D lesion information into a feature that can reflect both site of damage, defined by the location of the region of interest, and size of damage within that region of interest. Basically, the process of estimation of lesion load converts a voxel-based lesion map into a region-based lesion map, with regions defined as atlas-based or data-driven spatial patterns. Here, after examining current definitions of lesion load, four methodological issues are discussed: (1) lesion load is agnostic to the location of damage within the region of interest, and it disregards damage outside the region of interest, (2) lesion load estimates are prone to errors introduced by the uncertainty in lesion delineation, spatial warping of the lesion/region, and binarization of the lesion/region, (3) lesion load calculation depends on brain parcellation selection, and (4) lesion load does not necessarily reflect a white matter disconnection. Overall, lesion load, when calculated in a robust way, can serve as a clinically-useful feature for explaining and predicting post-stroke outcome and recovery.
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Affiliation(s)
- Mohamed L Seghier
- Department of Biomedical Engineering, Khalifa University of Science and Technology, Abu Dhabi, UAE.
- Healthcare Engineering Innovation Center (HEIC), Khalifa University of Science and Technology, Abu Dhabi, UAE.
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25
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Sperber C, Gallucci L, Smaczny S, Umarova R. Bayesian lesion-deficit inference with Bayes factor mapping: Key advantages, limitations, and a toolbox. Neuroimage 2023; 271:120008. [PMID: 36914109 DOI: 10.1016/j.neuroimage.2023.120008] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 03/06/2023] [Accepted: 03/07/2023] [Indexed: 03/15/2023] Open
Abstract
Statistical lesion-symptom mapping is largely dominated by frequentist approaches with null hypothesis significance testing. They are popular for mapping functional brain anatomy but are accompanied by some challenges and limitations. The typical analysis design and the structure of clinical lesion data are linked to the multiple comparison problem, an association problem, limitations to statistical power, and a lack of insights into evidence for the null hypothesis. Bayesian lesion deficit inference (BLDI) could be an improvement as it collects evidence for the null hypothesis, i.e. the absence of effects, and does not accumulate α-errors with repeated testing. We implemented BLDI by Bayes factor mapping with Bayesian t-tests and general linear models and evaluated its performance in comparison to frequentist lesion-symptom mapping with a permutation-based family-wise error correction. We mapped the voxel-wise neural correlates of simulated deficits in an in-silico-study with 300 stroke patients, and the voxel-wise and disconnection-wise neural correlates of phonemic verbal fluency and constructive ability in 137 stroke patients. Both the performance of frequentist and Bayesian lesion-deficit inference varied largely across analyses. In general, BLDI could find areas with evidence for the null hypothesis and was statistically more liberal in providing evidence for the alternative hypothesis, i.e. the identification of lesion-deficit associations. BLDI performed better in situations in which the frequentist method is typically strongly limited, for example with on average small lesions and in situations with low power, where BLDI also provided unprecedented transparency in terms of the informative value of the data. On the other hand, BLDI suffered more from the association problem, which led to a pronounced overshoot of lesion-deficit associations in analyses with high statistical power. We further implemented a new approach to lesion size control, adaptive lesion size control, that, in many situations, was able to counter the limitations imposed by the association problem, and increased true evidence both for the null and the alternative hypothesis. In summary, our results suggest that BLDI is a valuable addition to the method portfolio of lesion-deficit inference with some specific and exclusive advantages: it deals better with smaller lesions and low statistical power (i.e. small samples and effect sizes) and identifies regions with absent lesion-deficit associations. However, it is not superior to established frequentist approaches in all respects and therefore not to be seen as a general replacement. To make Bayesian lesion-deficit inference widely accessible, we published an R toolkit for the analysis of voxel-wise and disconnection-wise data.
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Affiliation(s)
- Christoph Sperber
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland.
| | - Laura Gallucci
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | - Stefan Smaczny
- Centre of Neurology, Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Roza Umarova
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
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26
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Smaczny S, Sperber C, Jung S, Moeller K, Karnath HO, Klein E. Disconnection in a left-hemispheric temporo-parietal network impairs multiplication fact retrieval. Neuroimage 2023; 268:119840. [PMID: 36621582 DOI: 10.1016/j.neuroimage.2022.119840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 12/16/2022] [Accepted: 12/25/2022] [Indexed: 01/07/2023] Open
Abstract
Arithmetic fact retrieval has been suggested to recruit a left-lateralized network comprising perisylvian language areas, parietal areas such as the angular gyrus (AG), and non-neocortical structures such as the hippocampus. However, the underlying white matter connectivity of these areas has not been evaluated systematically so far. Using simple multiplication problems, we evaluated how disconnections in parietal brain areas affected arithmetic fact retrieval following stroke. We derived disconnectivity measures by jointly considering data from n = 73 patients with acute unilateral lesions in either hemisphere and a white-matter tractography atlas (HCP-842) using the Lesion Quantification Toolbox (LQT). Whole-brain voxel-based analysis indicated a left-hemispheric cluster of white matter fibers connecting the AG and superior temporal areas to be associated with a fact retrieval deficit. Subsequent analyses of direct gray-to-gray matter disconnections revealed that disconnections of additional left-hemispheric areas (e.g., between the superior temporal gyrus and parietal areas) were significantly associated with the observed fact retrieval deficit. Results imply that disconnections of parietal areas (i.e., the AG) with language-related areas (i.e., superior and middle temporal gyri) seem specifically detrimental to arithmetic fact retrieval. This suggests that arithmetic fact retrieval recruits a widespread left-hemispheric network and emphasizes the relevance of white matter connectivity for number processing.
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Affiliation(s)
- S Smaczny
- Centre of Neurology, Division of Neuropsychology, Hertie-Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany
| | - C Sperber
- Department of Neurology, Inselspital, University Hospital Bern, University of Bern, Bern, Switzerland
| | - S Jung
- Department of Computer Science/Therapy Science, Trier University of Applied Science, Trier, Germany; Leibniz Institut fuer Wissensmedien, Tuebingen, Germany
| | - K Moeller
- Leibniz Institut fuer Wissensmedien, Tuebingen, Germany; Centre for Individual Development and Adaptive Education of Children at Risk (IDeA), Frankfurt, Germany; Centre for Mathematical Cognition, School of Science, Loughborough University, United Kingdom
| | - H O Karnath
- Centre of Neurology, Division of Neuropsychology, Hertie-Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany; Department of Psychology, University of South Carolina, Columbia, SC, USA.
| | - E Klein
- Leibniz Institut fuer Wissensmedien, Tuebingen, Germany; University of Paris, LaPsyDÉ, CNRS, Sorbonne Paris Cité, Paris, France.
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27
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Klein E, Knops A. The two-network framework of number processing: a step towards a better understanding of the neural origins of developmental dyscalculia. J Neural Transm (Vienna) 2023; 130:253-268. [PMID: 36662281 PMCID: PMC10033479 DOI: 10.1007/s00702-022-02580-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 12/23/2022] [Indexed: 01/21/2023]
Abstract
Developmental dyscalculia is a specific learning disorder that persists over lifetime and can have an enormous impact on personal, health-related, and professional aspects of life. Despite its central importance, the origin both at the cognitive and neural level is not yet well understood. Several classification schemas of dyscalculia have been proposed, sometimes together with an associated deficit at the neural level. However, these explanations are (a) not providing an exhaustive framework that is at levels with the observed complexity of developmental dyscalculia at the behavioral level and (b) are largely mono-causal approaches focusing on gray matter deficits. We suggest that number processing is instead the result of context-dependent interaction of two anatomically largely separate, distributed but overlapping networks that function/cooperate in a closely integrated fashion. The proposed two-network framework (TNF) is the result of a series of studies in adults on the neural correlates underlying magnitude processing and arithmetic fact retrieval, which comprised neurofunctional imaging of various numerical tasks, the application of probabilistic fiber tracking to obtain well-defined connections, and the validation and modification of these results using disconnectome mapping in acute stroke patients. Emerged from data in adults, it represents the endpoint of the acquisition and use of mathematical competencies in adults. Yet, we argue that its main characteristics should already emerge earlier during development. Based on this TNF, we develop a classification schema of phenomenological subtypes and their underlying neural origin that we evaluate against existing propositions and the available empirical data.
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Affiliation(s)
- Elise Klein
- LaPsyDÉ, UMR CNRS 8240, Université Paris Cité, La Sorbonne, 46 Rue Saint-Jacques, 75005, Paris, France.
- Leibniz-Institut Fuer Wissensmedien Tuebingen, Tuebingen, Germany.
| | - André Knops
- LaPsyDÉ, UMR CNRS 8240, Université Paris Cité, La Sorbonne, 46 Rue Saint-Jacques, 75005, Paris, France
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28
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Schaechter JD, Kim M, Hightower BG, Ragas T, Loggia ML. Disruptions in Structural and Functional Connectivity Relate to Poststroke Fatigue. Brain Connect 2023; 13:15-27. [PMID: 35570655 PMCID: PMC9942175 DOI: 10.1089/brain.2022.0021] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Introduction: Poststroke fatigue (PSF) is a disabling condition with unclear etiology. The brain lesion is thought to be an important causal factor in PSF, although focal lesion characteristics such as size and location have not proven to be predictive. Given that the stroke lesion results not only in focal tissue death but also in widespread changes in brain networks that are structurally and functionally connected to damaged tissue, we hypothesized that PSF relates to disruptions in structural and functional connectivity. Materials and Methods: Twelve patients who incurred an ischemic stroke in the middle cerebral artery (MCA) territory 1-3 years prior, and currently experiencing a range of fatigue severity, were enrolled. The patients underwent structural and resting-state functional magnetic resonance imaging (MRI). The structural MRI data were used to measure structural disconnection of gray matter resulting from lesion to white matter pathways. The functional MRI data were used to measure network functional connectivity. Results: The patients showed structural disconnection in varying cortical and subcortical regions. Fatigue severity correlated significantly with structural disconnection of several frontal cortex regions in the ipsilesional (IL) and contralesional hemispheres. Fatigue-related structural disconnection was most severe in the IL rostral middle frontal cortex. Greater structural disconnection of a subset of fatigue-related frontal cortex regions, including the IL rostral middle frontal cortex, trended toward correlating significantly with greater loss in functional connectivity. Among identified fatigue-related frontal cortex regions, only the IL rostral middle frontal cortex showed loss in functional connectivity correlating significantly with fatigue severity. Conclusion: Our results provide evidence that loss in structural and functional connectivity of bihemispheric frontal cortex regions plays a role in PSF after MCA stroke, with connectivity disruptions of the IL rostral middle frontal cortex having a central role. Impact statement Poststroke fatigue (PSF) is a common disabling condition with unclear etiology. We hypothesized that PSF relates to disruptions in structural and functional connectivity secondary to the focal lesion. Using structural and resting-state functional connectivity magnetic resonance imaging (MRI) in patients with chronic middle cerebral artery (MCA) stroke, we found frontal cortex regions in the ipsilesional (IL) and contralesional hemispheres with greater structural disconnection correlating with greater fatigue. Among these fatigue-related cortices, the IL rostral middle frontal cortex showed loss in functional connectivity correlating with fatigue. These findings suggest that disruptions in structural and functional connectivity play a role in PSF after MCA stroke.
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Affiliation(s)
- Judith D. Schaechter
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Minhae Kim
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Baileigh G. Hightower
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Trevor Ragas
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Marco L. Loggia
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
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29
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Wittayer M, Weber CE, Krämer J, Platten M, Schirmer L, Gass A, Eisele P. Exploring (peri-) lesional and structural connectivity tissue damage through T1/T2-weighted ratio in iron rim multiple sclerosis lesions. Magn Reson Imaging 2023; 95:12-18. [PMID: 36270415 DOI: 10.1016/j.mri.2022.10.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/11/2022] [Accepted: 10/14/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE In multiple sclerosis (MS), iron rim lesions (IRLs) on magnetic resonance imaging (MRI) are associated with pronounced intralesional tissue damage. The aim of this study was to investigate (peri-)lesional and structural connectivity tissue damage in IRLs compared to non-IRLs. MATERIAL AND METHODS MRI was acquired on a 3 T system. Tissue integrity was assessed using the T1/T2-weighted (T1/T2w) ratio. Furthermore, we assessed the impact on structural network connectivity accounting for differences in lesion volumes and T1/T2w values. RESULTS Seventy-six patients (38 with at least one IRL and 38 age- and sex-matched patients without IRLs) were included. In the IRL-group, T1/T2w ratios of IRLs were significantly lower compared to non-IRLs (p < 0.05). When comparing the T1/T2w ratios in non-IRLs between the IRL-group and non-IRL group, there was no significant difference (p = 0.887). We observed a centrifugal decrease in microstructural damage from lesions to the perilesional white matter. In the IRL-group, T1/T2w ratios in the perilesional white matter 3-8 mm distant to the lesion were significantly lower in IRLs compared to non-IRLs. We found no significant differences in the amount of network disruption between both lesion types (p = 0.122). CONCLUSION T1/T2w represents an interesting candidate to capture a pronounced intra- and perilesional tissue damage of IRLs. However, our preliminary results suggest that a pronounced tissue damage might not result in a higher disruption to structural connectivity networks in IRLs.
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Affiliation(s)
- Matthias Wittayer
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany
| | - Claudia E Weber
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany
| | - Julia Krämer
- Department of Neurology with Institute of Translational Neurology, University Hospital Münster, Albert-Schweitzer-Campus 1; Gebäude A1, Westturm, Ebene 5, 48149 Münster, Germany
| | - Michael Platten
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany; German Consortium of Translational Cancer Research (DKTK), Clinical Cooperation Unit Neuroimmunology and Brain Tumor Immunology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lucas Schirmer
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany; Institute for Innate Immunoscience, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Achim Gass
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany
| | - Philipp Eisele
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, 68167 Mannheim, Germany.
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30
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Zevgolatakou E, Thye M, Mirman D. Behavioural and neural structure of fluent speech production deficits in aphasia. Brain Commun 2022; 5:fcac327. [PMID: 36601623 PMCID: PMC9798301 DOI: 10.1093/braincomms/fcac327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 09/03/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022] Open
Abstract
Deficits in fluent speech production following left hemisphere stroke are a central concern because of their impact on patients' lives and the insight they provide about the neural organization of language processing. Fluent speech production requires the rapid coordination of phonological, semantic, and syntactic processing, so this study examined how deficits in connected speech relate to these language sub-systems. Behavioural data (N = 69 participants with aphasia following left hemisphere stroke) consisted of a diverse and comprehensive set of narrative speech production measures and measures of overall severity, semantic deficits, and phonological deficits. These measures were entered into a principal component analysis with bifactor rotation-a latent structure model where each item loads on a general factor that reflects what is common among the items, and orthogonal factors that explain variance not accounted for by the general factor. Lesion data were available for 58 of the participants, and each factor score was analysed with multivariate lesion-symptom mapping. Effects of connectivity disruption were evaluated using robust regression with tract disconnection or graph theoretic measures of connectivity as predictors. The principal component analysis produced a four-factor solution that accounted for 70.6% of the variance in the data, with a general factor corresponding to the overall severity and length and complexity of speech output (complexity factor), a lexical syntax factor, and independent factors for Semantics and Phonology. Deficits in the complexity of speech output were associated with a large temporo-parietal region, similar to overall aphasia severity. The lexical syntax factor was associated with damage in a relatively small set of fronto-parietal regions which may reflect the recruitment of control systems to support retrieval and correct usage of lexical items that primarily serve a syntactic rather than semantic function. Tract-based measures of connectivity disruption were not statistically associated with the deficit scores after controlling for overall lesion volume. Language network efficiency and average clustering coefficient within the language network were significantly associated with deficit scores after controlling for overall lesion volume. These results highlight overall severity as the critical contributor to fluent speech in post-stroke aphasia, with a dissociable factor corresponding to lexical syntax.
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Affiliation(s)
- Eleni Zevgolatakou
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Melissa Thye
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, UK
| | - Daniel Mirman
- Correspondence to: Daniel Mirman Department of Psychology, 7 George Square Edinburgh EH8 9JZ, UK E-mail:
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31
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Structural disconnection-based prediction of poststroke depression. Transl Psychiatry 2022; 12:461. [PMID: 36329029 PMCID: PMC9633711 DOI: 10.1038/s41398-022-02223-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 10/14/2022] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
Poststroke depression (PSD) is a common complication of stroke. Brain network disruptions caused by stroke are potential biological determinants of PSD but their conclusive roles are unavailable. Our study aimed to identify the strategic structural disconnection (SDC) pattern for PSD at three months poststroke and assess the predictive value of SDC information. Our prospective cohort of 697 first-ever acute ischemic stroke patients were recruited from three hospitals in central China. Sociodemographic, clinical, psychological and neuroimaging data were collected at baseline and depression status was assessed at three months poststroke. Voxel-based disconnection-symptom mapping found that SDCs involving bilateral temporal white matter and posterior corpus callosum, as well as white matter next to bilateral prefrontal cortex and posterior parietal cortex, were associated with PSD. This PSD-specific SDC pattern was used to derive SDC scores for all participants. SDC score was an independent predictor of PSD after adjusting for all imaging and clinical-sociodemographic-psychological covariates (odds ratio, 1.25; 95% confidence interval, 1.07, 1.48; P = 0.006). Split-half replication showed the stability and generalizability of above results. When added to the clinical-sociodemographic-psychological prediction model, SDC score significantly improved the model performance and ranked the highest in terms of predictor importance. In conclusion, a strategic SDC pattern involving multiple lobes bilaterally is identified for PSD at 3 months poststroke. The SDC score is an independent predictor of PSD and may improve the predictive performance of the clinical-sociodemographic-psychological prediction model, providing new evidence for the brain-behavior mechanism and biopsychosocial theory of PSD.
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Idesis S, Favaretto C, Metcalf NV, Griffis JC, Shulman GL, Corbetta M, Deco G. Inferring the dynamical effects of stroke lesions through whole-brain modeling. Neuroimage Clin 2022; 36:103233. [PMID: 36272340 PMCID: PMC9668672 DOI: 10.1016/j.nicl.2022.103233] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/13/2022] [Accepted: 10/14/2022] [Indexed: 11/05/2022]
Abstract
Understanding the effect of focal lesions (stroke) on brain structure-function traditionally relies on behavioral analyses and correlation with neuroimaging data. Here we use structural disconnection maps from individual lesions to derive a causal mechanistic generative whole-brain model able to explain both functional connectivity alterations and behavioral deficits induced by stroke. As compared to other models that use only the local lesion information, the similarity to the empirical fMRI connectivity increases when the widespread structural disconnection information is considered. The presented model classifies behavioral impairment severity with higher accuracy than other types of information (e.g.: functional connectivity). We assessed topological measures that characterize the functional effects of damage. With the obtained results, we were able to understand how network dynamics change emerge, in a nontrivial way, after a stroke injury of the underlying complex brain system. This type of modeling, including structural disconnection information, helps to deepen our understanding of the underlying mechanisms of stroke lesions.
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Affiliation(s)
- Sebastian Idesis
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, Barcelona, Catalonia 08005, Spain,Corresponding author.
| | - Chiara Favaretto
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, Padova 35129, Italy,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, Padova 35128, Italy
| | - Nicholas V. Metcalf
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Joseph C. Griffis
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Gordon L. Shulman
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA,Department of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Maurizio Corbetta
- Padova Neuroscience Center (PNC), University of Padova, via Orus 2/B, Padova 35129, Italy,Department of Neuroscience (DNS), University of Padova, via Giustiniani 2, Padova 35128, Italy,Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA,Department of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA,VIMM, Venetian Institute of Molecular Medicine (VIMM), Biomedical Foundation, via Orus 2, Padova 35129, Italy
| | - Gustavo Deco
- Center for Brain and Cognition (CBC), Department of Information Technologies and Communications (DTIC), Pompeu Fabra University, Edifici Mercè Rodoreda, Carrer Trias i Fargas 25-27, Barcelona, Catalonia 08005, Spain,Institució Catalana de Recerca I Estudis Avançats (ICREA), Passeig Lluis Companys 23, Barcelona, Catalonia 08010, Spain
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Sperber C, Griffis J, Kasties V. Indirect structural disconnection-symptom mapping. Brain Struct Funct 2022; 227:3129-3144. [PMID: 36048282 DOI: 10.1007/s00429-022-02559-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 08/24/2022] [Indexed: 01/01/2023]
Abstract
In vivo tracking of white matter fibres catalysed a modern perspective on the pivotal role of brain connectome disruption in neuropsychological deficits. However, the examination of white matter integrity in neurological patients by diffusion-weighted magnetic resonance imaging bears conceptual limitations and is not widely applicable, as it requires imaging-compatible patients and resources beyond the capabilities of many researchers. The indirect estimation of structural disconnection offers an elegant and economical alternative. For this approach, a patient's structural lesion information and normative connectome data are combined to estimate different measures of lesion-induced structural disconnection. Using one of several toolboxes, this method is relatively easy to implement and is even available to scientists without expertise in fibre tracking analyses. Nevertheless, the anatomo-behavioural statistical mapping of structural brain disconnection requires analysis steps that are not covered by these toolboxes. In this paper, we first review the current state of indirect lesion disconnection estimation, the different existing measures, and the available software. Second, we aim to fill the remaining methodological gap in statistical disconnection-symptom mapping by providing an overview and guide to disconnection data and the statistical mapping of their relationship to behavioural measurements using either univariate or multivariate statistical modelling. To assist in the practical implementation of statistical analyses, we have included software tutorials and analysis scripts.
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Affiliation(s)
- Christoph Sperber
- University of Tubingen: Eberhard Karls Universitat Tubingen, Tubingen, Germany.
| | - Joseph Griffis
- University of Tubingen: Eberhard Karls Universitat Tubingen, Tubingen, Germany
| | - Vanessa Kasties
- Centre of Neurology, Hertie-Institute for Clinical Brain Research, University of Tubingen, Tubingen, Germany
- Child Development Center, University Childrens Hospital Zurich, University of Zurich, Zurich, Switzerland
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Yeh FC. Population-based tract-to-region connectome of the human brain and its hierarchical topology. Nat Commun 2022; 13:4933. [PMID: 35995773 PMCID: PMC9395399 DOI: 10.1038/s41467-022-32595-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 08/05/2022] [Indexed: 12/25/2022] Open
Abstract
Connectome maps region-to-region connectivities but does not inform which white matter pathways form the connections. Here we constructed a population-based tract-to-region connectome to fill this information gap. The constructed connectome quantifies the population probability of a white matter tract innervating a cortical region. The results show that ~85% of the tract-to-region connectome entries are consistent across individuals, whereas the remaining (~15%) have substantial individual differences requiring individualized mapping. Further hierarchical clustering on cortical regions revealed dorsal, ventral, and limbic networks based on the tract-to-region connective patterns. The clustering results on white matter bundles revealed the categorization of fiber bundle systems in the association pathways. This tract-to-region connectome provides insights into the connective topology between cortical regions and white matter bundles. The derived hierarchical relation further offers a categorization of gray and white matter structures. The brain connectome maps region-to-region connections but often ignores the role of the connecting pathways. Here, the authors mapped the tract-to-region relations to reveal the hierarchical relation of fiber bundles and dorsal, ventral, and limbic networks.
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Affiliation(s)
- Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA. .,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
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Mercier MR, Dubarry AS, Tadel F, Avanzini P, Axmacher N, Cellier D, Vecchio MD, Hamilton LS, Hermes D, Kahana MJ, Knight RT, Llorens A, Megevand P, Melloni L, Miller KJ, Piai V, Puce A, Ramsey NF, Schwiedrzik CM, Smith SE, Stolk A, Swann NC, Vansteensel MJ, Voytek B, Wang L, Lachaux JP, Oostenveld R. Advances in human intracranial electroencephalography research, guidelines and good practices. Neuroimage 2022; 260:119438. [PMID: 35792291 DOI: 10.1016/j.neuroimage.2022.119438] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 05/23/2022] [Accepted: 06/30/2022] [Indexed: 12/11/2022] Open
Abstract
Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.
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Wittayer M, Weber CE, Platten M, Schirmer L, Gass A, Eisele P. Spatial distribution of multiple sclerosis iron rim lesions and their impact on disability. Mult Scler Relat Disord 2022; 64:103967. [PMID: 35728430 DOI: 10.1016/j.msard.2022.103967] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 06/07/2022] [Accepted: 06/13/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND In multiple sclerosis (MS), iron rim lesions (IRLs) on magnetic resonance imaging (MRI) have been suggested as an imaging marker of disease progression. However, the exact mechanisms how they contribute to disability are yet not completely known. Strategic lesion location may be an important factor concerning the impact of focal lesions on clinical disability. Therefore, the aim of this study was to investigate the spatial distribution of IRLs compared to non-IRLs and their impact on disability. METHODS We retrospectively identified 67 patients with at least one IRL on MRI and 67 age- and sex-matched patients without IRLs. We compared the spatial distribution of lesions between both groups and between IRLs and non-IRLs in patients with IRLs. Furthermore, we assessed the relationship between lesion localisation and disability on a voxel-by-voxel basis and investigated the impact on structural network disruptions. RESULTS Patients with IRLs had higher disability scores (median Expanded Disability Status Scale score (range): 3.0 (0 - 8.5) versus 1.5 (0 - 6.5); p = 0.001; median pyramidal functional system score (range): 1.0 (0 - 5) versus 0 (0 - 4); p = 0.003), significantly lower brain volumes (mean normal-appearing grey matter volume: 749.66 ± 60.58 versus 785.83 ± 53.71 mL; mean normal-appearing white matter volume: 723.58 ± 60.13 versus 753.25 ± 69.61 mL; mean deep grey matter volume: 33.21 ± 4.19 versus 35.85 ± 4.89 mL; p < 0.05 for all comparisons) and a significantly higher total T2 lesion volume (mean: 9.96 ± 11.6 versus 4.31 ± 8.9 mL; p < 0.001). We found no neuroanatomical regions that were more often affected by IRLs. Furthermore, comparing the overall network disruption in the IRL group, IRLs caused less network disruption/mL lesion size compared to non-IRLs (1.54% / mL versus 2.0% / mL; p < 0.05). CONCLUSION IRLs are associated with higher disability scores. However, our results suggest that a higher disability is not explained by the sheer topography of IRLs or their network disruption.
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Affiliation(s)
- Matthias Wittayer
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, Mannheim 68167, Germany
| | - Claudia E Weber
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, Mannheim 68167, Germany
| | - Michael Platten
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, Mannheim 68167, Germany; DKTK CCU Neuroimmunology and Brain Tumor Immunology, DKFZ, Heidelberg, Germany
| | - Lucas Schirmer
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, Mannheim 68167, Germany; Medical Faculty Mannheim, Institute for Innate Immunoscience, Heidelberg University, Mannheim, Germany
| | - Achim Gass
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, Mannheim 68167, Germany
| | - Philipp Eisele
- Department of Neurology, Medical Faculty Mannheim and Mannheim Center of Translational Neurosciences (MCTN), Heidelberg University, Theodor-Kutzer-Ufer 1 - 3, Mannheim 68167, Germany.
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Bowren M, Bruss J, Manzel K, Edwards D, Liu C, Corbetta M, Tranel D, Boes AD. Post-stroke outcomes predicted from multivariate lesion-behaviour and lesion network mapping. Brain 2022; 145:1338-1353. [PMID: 35025994 PMCID: PMC9630711 DOI: 10.1093/brain/awac010] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 09/10/2021] [Accepted: 12/16/2021] [Indexed: 11/13/2022] Open
Abstract
Clinicians and scientists alike have long sought to predict the course and severity of chronic post-stroke cognitive and motor outcomes, as the ability to do so would inform treatment and rehabilitation strategies. However, it remains difficult to make accurate predictions about chronic post-stroke outcomes due, in large part, to high inter-individual variability in recovery and a reliance on clinical heuristics rather than empirical methods. The neuroanatomical location of a stroke is a key variable associated with long-term outcomes, and because lesion location can be derived from routinely collected clinical neuroimaging data there is an opportunity to use this information to make empirically based predictions about post-stroke deficits. For example, lesion location can be compared to statistically weighted multivariate lesion-behaviour maps of neuroanatomical regions that, when damaged, are associated with specific deficits based on aggregated outcome data from large cohorts. Here, our goal was to evaluate whether we can leverage lesion-behaviour maps based on data from two large cohorts of individuals with focal brain lesions to make predictions of 12-month cognitive and motor outcomes in an independent sample of stroke patients. Further, we evaluated whether we could augment these predictions by estimating the structural and functional networks disrupted in association with each lesion-behaviour map through the use of structural and functional lesion network mapping, which use normative structural and functional connectivity data from neurologically healthy individuals to elucidate lesion-associated networks. We derived these brain network maps using the anatomical regions with the strongest association with impairment for each cognitive and motor outcome based on lesion-behaviour map results. These peak regional findings became the 'seeds' to generate networks, an approach that offers potentially greater precision compared to previously used single-lesion approaches. Next, in an independent sample, we quantified the overlap of each lesion location with the lesion-behaviour maps and structural and functional lesion network mapping and evaluated how much variance each could explain in 12-month behavioural outcomes using a latent growth curve statistical model. We found that each lesion-deficit mapping modality was able to predict a statistically significant amount of variance in cognitive and motor outcomes. Both structural and functional lesion network maps were able to predict variance in 12-month outcomes beyond lesion-behaviour mapping. Functional lesion network mapping performed best for the prediction of language deficits, and structural lesion network mapping performed best for the prediction of motor deficits. Altogether, these results support the notion that lesion location and lesion network mapping can be combined to improve the prediction of post-stroke deficits at 12-months.
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Affiliation(s)
- Mark Bowren
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA 52242, USA
| | - Joel Bruss
- Department of Neurology, Carver College of Medicine, Iowa City, IA 52242, USA
| | - Kenneth Manzel
- Department of Neurology, Carver College of Medicine, Iowa City, IA 52242, USA
| | - Dylan Edwards
- Moss Rehabilitation Research Institute, Elkins Park, PA 19027, USA
- Edith Cowan University, Joondalup, WA 6027, Australia
| | - Charles Liu
- Neurorestoration Center and Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Rancho Los Amigos National Rehabilitation Center, Downey, CA, USA
| | - Maurizio Corbetta
- Department of Neuroscience, Venetian Institute of Molecular Medicine and Padova Neuroscience Center, University of Padua, Padova, PD 32122, Italy
| | - Daniel Tranel
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA 52242, USA
- Department of Neurology, Carver College of Medicine, Iowa City, IA 52242, USA
| | - Aaron D Boes
- Departments of Neurology, Psychiatry, and Pediatrics, Carver College of Medicine, Iowa City, IA 52242, USA
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Pan C, Li G, Sun W, Miao J, Qiu X, Lan Y, Wang Y, Wang H, Zhu Z, Zhu S. Neural Substrates of Poststroke Depression: Current Opinions and Methodology Trends. Front Neurosci 2022; 16:812410. [PMID: 35464322 PMCID: PMC9019549 DOI: 10.3389/fnins.2022.812410] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Accepted: 02/04/2022] [Indexed: 12/21/2022] Open
Abstract
Poststroke depression (PSD), affecting about one-third of stroke survivors, exerts significant impact on patients’ functional outcome and mortality. Great efforts have been made since the 1970s to unravel the neuroanatomical substrate and the brain-behavior mechanism of PSD. Thanks to advances in neuroimaging and computational neuroscience in the past two decades, new techniques for uncovering the neural basis of symptoms or behavioral deficits caused by focal brain damage have been emerging. From the time of lesion analysis to the era of brain networks, our knowledge and understanding of the neural substrates for PSD are increasing. Pooled evidence from traditional lesion analysis, univariate or multivariate lesion-symptom mapping, regional structural and functional analyses, direct or indirect connectome analysis, and neuromodulation clinical trials for PSD, to some extent, echoes the frontal-limbic theory of depression. The neural substrates of PSD may be used for risk stratification and personalized therapeutic target identification in the future. In this review, we provide an update on the recent advances about the neural basis of PSD with the clinical implications and trends of methodology as the main features of interest.
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Kancheva I, Buma F, Kwakkel G, Kancheva A, Ramsey N, Raemaekers M. Investigating secondary white matter degeneration following ischemic stroke by modelling affected fiber tracts. Neuroimage Clin 2022; 33:102945. [PMID: 35124524 PMCID: PMC8829801 DOI: 10.1016/j.nicl.2022.102945] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 12/27/2021] [Accepted: 01/17/2022] [Indexed: 11/27/2022]
Abstract
Secondary white matter degeneration was studied in 11 ischemic stroke patients. We used a custom-developed approach to model damaged fibers associated with a lesion. This approach tackles the inter-subject variability in lesion size and location. Findings suggest that secondary degeneration spreads along an entire fiber’s length.
Secondary white matter degeneration is a common occurrence after ischemic stroke, as identified by Diffusion Tensor Imaging (DTI). However, despite recent advances, the time course of the process is not completely understood. The primary aim of this study was to assess secondary degeneration using an approach whereby we create a patient-specific model of damaged fibers based on the volumetric characteristics of lesions. We also examined the effects of secondary degeneration along the modelled streamlines at different distances from the primary infarction using DTI. Eleven patients who presented with upper limb motor deficits at the time of a first-ever ischemic stroke were included. They underwent scanning at weeks 6 and 29 post-stroke. The fractional anisotropy (FA), mean diffusivity (MD), primary eigenvalue (λ1), and transverse eigenvalue (λ23) were measured. Using regions of interest based on the simulation output, the differences between the modelled fibers and matched contralateral areas were analyzed. The longitudinal change between the two time points and across five distances from the primary lesion was also assessed using the ratios of diffusion quantities (rFA, rMD, rλ1, and rλ23) between the ipsilesional and contralesional hemisphere. At week 6 post-stroke, significantly decreased λ1 was found along the ipsilesional corticospinal tract (CST) with a trend towards lower FA, reduced MD and λ23. At week 29 post-stroke, significantly decreased FA was shown relative to the non-lesioned side, with a trend towards lower λ1, unchanged MD, and higher λ23. Along the ipsilesional tract, the rFA diminished, whereas the rMD, rλ1, and rλ23 significantly increased over time. No significant variations in the time progressive effect with distance were demonstrated. The findings support previously described mechanisms of secondary degeneration and suggest that it spreads along the entire length of a damaged tract. Future investigations using higher-order tractography techniques can further explain the intravoxel alterations caused by ischemic injury.
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Affiliation(s)
- Ivana Kancheva
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, PO Box 85060, 3508AB Utrecht, The Netherlands.
| | - Floor Buma
- Department of Anatomy and Neurosciences, MOVE Research Institute Amsterdam, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands
| | - Gert Kwakkel
- Department of Rehabilitation Medicine, VU University Medical Center, PO Box 7057, 1007MB Amsterdam, The Netherlands
| | - Angelina Kancheva
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, PO Box 85060, 3508AB Utrecht, The Netherlands
| | - Nick Ramsey
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, PO Box 85060, 3508AB Utrecht, The Netherlands
| | - Mathijs Raemaekers
- UMC Utrecht Brain Center, Department of Neurology and Neurosurgery, University Medical Center Utrecht, PO Box 85060, 3508AB Utrecht, The Netherlands
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Ravano V, Andelova M, Fartaria MJ, Mahdi MFAW, Maréchal B, Meuli R, Uher T, Krasensky J, Vaneckova M, Horakova D, Kober T, Richiardi J. Validating atlas-based lesion disconnectomics in multiple sclerosis: A retrospective multi-centric study. Neuroimage Clin 2022; 32:102817. [PMID: 34500427 PMCID: PMC8429972 DOI: 10.1016/j.nicl.2021.102817] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 07/30/2021] [Accepted: 08/30/2021] [Indexed: 12/01/2022]
Abstract
Structural disconnectomes can be modelled without diffusion using tractography atlases. Atlas-based and DTI-derived disconnectome topological metrics correlate strongly. MS patient disconnectomes relate to clinical scores.
The translational potential of MR-based connectivity modelling is limited by the need for advanced diffusion imaging, which is not part of clinical protocols for many diseases. In addition, where diffusion data is available, brain connectivity analyses rely on tractography algorithms which imply two major limitations. First, tracking algorithms are known to be sensitive to the presence of white matter lesions and therefore leading to interpretation pitfalls and poor inter-subject comparability in clinical applications such as multiple sclerosis. Second, tractography quality is highly dependent on the acquisition parameters of diffusion sequences, leading to a trade-off between acquisition time and tractography precision. Here, we propose an atlas-based approach to study the interplay between structural disconnectivity and lesions without requiring individual diffusion imaging. In a multi-centric setting involving three distinct multiple sclerosis datasets (containing both 1.5 T and 3 T data), we compare our atlas-based structural disconnectome computation pipeline to disconnectomes extracted from individual tractography and explore its clinical utility for reducing the gap between radiological findings and clinical symptoms in multiple sclerosis. Results using topological graph properties showed that overall, our atlas-based disconnectomes were suitable approximations of individual disconnectomes from diffusion imaging. Small-worldness was found to decrease for larger total lesion volumes thereby suggesting a loss of efficiency in brain connectivity of MS patients. Finally, the global efficiency of the created brain graph, combined with total lesion volume, allowed to stratify patients into subgroups with different clinical scores in all three cohorts.
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Affiliation(s)
- Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| | - Michaela Andelova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Mário João Fartaria
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | | | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Reto Meuli
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Jan Krasensky
- MR unit, Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Manuela Vaneckova
- MR unit, Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jonas Richiardi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Untapped Neuroimaging Tools for Neuro-Oncology: Connectomics and Spatial Transcriptomics. Cancers (Basel) 2022; 14:cancers14030464. [PMID: 35158732 PMCID: PMC8833690 DOI: 10.3390/cancers14030464] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/13/2022] [Accepted: 01/15/2022] [Indexed: 01/27/2023] Open
Abstract
Simple Summary Brain imaging, specifically magnetic resonance imaging (MRI), plays a key role in the clinical and research aspects of neuro-oncology. Novel neuroimaging techniques enable the transformation of a brain MRI into a so-called average brain. This allows projects using already acquired brain MRIs to perform group analyses and draw conclusions. Once the data are in this average brain, several types of analyses can be performed. For example, determining the most vulnerable locations for certain tumor types or perhaps even the underlying circuitry and gene expression that might cause predisposition to tumor growth. This information may further our understanding of tumor behavior, leading to better patient counseling, surgery timing, and treatment monitoring. Abstract Neuro-oncology research is broad and includes several branches, one of which is neuroimaging. Magnetic resonance imaging (MRI) is instrumental for the diagnosis and treatment monitoring of patients with brain tumors. Most commonly, structural and perfusion MRI sequences are acquired to characterize tumors and understand their behaviors. Thanks to technological advances, structural brain MRI can now be transformed into a so-called average brain accounting for individual morphological differences, which enables retrospective group analysis. These normative analyses are uncommonly used in neuro-oncology research. Once the data have been normalized, voxel-wise analyses and spatial mapping can be performed. Additionally, investigations of underlying connectomics can be performed using functional and structural templates. Additionally, a recently available template of spatial transcriptomics has enabled the assessment of associated gene expression. The few published normative analyses have shown relationships between tumor characteristics and spatial localization, as well as insights into the circuitry associated with epileptogenic tumors and depression after cingulate tumor resection. The wide breadth of possibilities with normative analyses remain largely unexplored, specifically in terms of connectomics and imaging transcriptomics. We provide a framework for performing normative analyses in oncology while also highlighting their limitations. Normative analyses are an opportunity to address neuro-oncology questions from a different perspective.
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Herbet G, Duffau H. Contribution of the medial eye field network to the voluntary deployment of visuospatial attention. Nat Commun 2022; 13:328. [PMID: 35039507 PMCID: PMC8763913 DOI: 10.1038/s41467-022-28030-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 01/02/2022] [Indexed: 11/09/2022] Open
Abstract
Historically, the study of patients with spatial neglect has provided fundamental insights into the neural basis of spatial attention. However, lesion mapping studies have been unsuccessful in establishing the potential role of associative networks spreading on the dorsal-medial axis, mainly because they are uncommonly targeted by vascular injuries. Here we combine machine learning-based lesion-symptom mapping, disconnection analyses and the longitudinal behavioral data of 128 patients with well-delineated surgical resections. The analyses show that surgical resections in a location compatible with both the supplementary and the cingulate eye fields, and disrupting the dorsal-medial fiber network, are specifically associated with severely diminished performance on a visual search task (i.e., visuo-motor exploratory neglect) with intact performance on a task probing the perceptual component of neglect. This general finding provides causal evidence for a role of the frontal-medial network in the voluntary deployment of visuo-spatial attention.
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Affiliation(s)
- Guillaume Herbet
- Institute of Functional Genomics, University of Montpellier, INSERM U1191, CNRS UMR 5203, 141, rue de la Cardonille, 34094, Montpellier, France.
- Department of Neurosurgery, Montpellier University Medical Center, Gui de Chauliac Hospital, 80, Boulevard Augustin Fliche, 34095, Montpellier, France.
| | - Hugues Duffau
- Institute of Functional Genomics, University of Montpellier, INSERM U1191, CNRS UMR 5203, 141, rue de la Cardonille, 34094, Montpellier, France
- Department of Neurosurgery, Montpellier University Medical Center, Gui de Chauliac Hospital, 80, Boulevard Augustin Fliche, 34095, Montpellier, France
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Ng S, Moritz-Gasser S, Lemaitre AL, Duffau H, Herbet G. White matter disconnectivity fingerprints causally linked to dissociated forms of alexia. Commun Biol 2021; 4:1413. [PMID: 34931059 PMCID: PMC8688436 DOI: 10.1038/s42003-021-02943-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 12/01/2021] [Indexed: 11/30/2022] Open
Abstract
For over 150 years, the study of patients with acquired alexia has fueled research aimed at disentangling the neural system critical for reading. An unreached goal, however, relates to the determination of the fiber pathways that root the different visual and linguistic processes needed for accurate word reading. In a unique series of neurosurgical patients with a tumor close to the visual word form area, we combine direct electrostimulation and population-based streamline tractography to map the disconnectivity fingerprints characterizing dissociated forms of alexia. Comprehensive analyses of disconnectivity matrices establish similarities and dissimilarities in the disconnection patterns associated with pure, phonological and lexical-semantic alexia. While disconnections of the inferior longitudinal and posterior arcuate fasciculi are common to all alexia subtypes, disconnections of the long arcuate and vertical occipital fasciculi are specific to phonological and pure alexia, respectively. These findings provide a strong anatomical background for cognitive and neurocomputational models of reading.
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Affiliation(s)
- Sam Ng
- Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France. .,Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France.
| | - Sylvie Moritz-Gasser
- grid.414130.30000 0001 2151 3479Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France ,grid.461890.20000 0004 0383 2080Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France ,grid.121334.60000 0001 2097 0141Department of Speech-Language Pathology, University of Montpellier, Montpellier, France
| | - Anne-Laure Lemaitre
- grid.414130.30000 0001 2151 3479Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France ,grid.461890.20000 0004 0383 2080Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France
| | - Hugues Duffau
- grid.414130.30000 0001 2151 3479Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France ,grid.461890.20000 0004 0383 2080Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France
| | - Guillaume Herbet
- grid.414130.30000 0001 2151 3479Department of Neurosurgery, Gui de Chauliac Hospital, Montpellier University Medical Center, Montpellier, France ,grid.461890.20000 0004 0383 2080Institut de Génomique Fonctionnelle, Université de Montpellier, CNRS, INSERM, Montpellier, France ,grid.121334.60000 0001 2097 0141Department of Speech-Language Pathology, University of Montpellier, Montpellier, France
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Tozlu C, Jamison K, Gu Z, Gauthier SA, Kuceyeski A. Estimated connectivity networks outperform observed connectivity networks when classifying people with multiple sclerosis into disability groups. Neuroimage Clin 2021; 32:102827. [PMID: 34601310 PMCID: PMC8488753 DOI: 10.1016/j.nicl.2021.102827] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 09/09/2021] [Accepted: 09/11/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Multiple Sclerosis (MS), a neurodegenerative and neuroinflammatory disease, causing lesions that disrupt the brain's anatomical and physiological connectivity networks, resulting in cognitive, visual and/or motor disabilities. Advanced imaging techniques like diffusion and functional MRI allow measurement of the brain's structural connectivity (SC) and functional connectivity (FC) networks, and can enable a better understanding of how their disruptions cause disability in people with MS (pwMS). However, advanced MRI techniques are used mainly for research purposes as they are expensive, time-consuming and require high-level expertise to acquire and process. As an alternative, the Network Modification (NeMo) Tool can be used to estimate SC and FC using lesion masks derived from pwMS and a reference set of controls' connectivity networks. OBJECTIVE Here, we test the hypothesis that estimated SC and FC (eSC and eFC) from the NeMo Tool, based only on an individual's lesion masks, can be used to classify pwMS into disability categories just as well as SC and FC extracted from advanced MRI directly in pwMS. We also aim to find the connections most important for differentiating between no disability vs evidence of disability groups. MATERIALS AND METHODS One hundred pwMS (age:45.5 ± 11.4 years, 66% female, disease duration: 12.97 ± 8.07 years) were included in this study. Expanded Disability Status Scale (EDSS) was used to assess disability, 67 pwMS had no disability (EDSS < 2). Observed SC and FC were extracted from diffusion and functional MRI directly in pwMS, respectively. The NeMo Tool was used to estimate the remaining structural connectome (eSC), by removing streamlines in a reference set of tractograms that intersected the lesion mask. The NeMo Tool's eSC was used then as input to a deep neural network to estimate the corresponding FC (eFC). Logistic regression with ridge regularization was used to classify pwMS into disability categories (no disability vs evidence of disability), based on demographics/clinical information (sex, age, race, disease duration, clinical phenotype, and spinal lesion burden) and either pairwise entries or regional summaries from one of the following matrices: SC, FC, eSC, and eFC. The area under the ROC curve (AUC) was used to assess the classification performance. Both univariate statistics and parameter coefficients from the classification models were used to identify features important to differentiating between the groups. RESULTS The regional eSC and eFC models outperformed their observed FC and SC counterparts (p-value < 0.05), while the pairwise eSC and SC performed similarly (p = 0.10). Regional eSC and eFC models had higher AUC (0.66-0.68) than the pairwise models (0.60-0.65), with regional eFC having highest classification accuracy across all models. Ridge regression coefficients for the regional eFC and regional observed FC models were significantly correlated (Pearson's r = 0.52, p-value < 10e-7). Decreased estimated SC node strength in default mode and ventral attention networks and increased eFC node strength in visual networks was associated with evidence of disability. DISCUSSION Here, for the first time, we use clinically acquired lesion masks to estimate both structural and functional connectomes in patient populations to better understand brain lesion-dysfunction mapping in pwMS. Models based on the NeMo Tool's estimates of SC and FC better classified pwMS by disability level than SC and FC observed directly in the individual using advanced MRI. This work provides a viable alternative to performing high-cost, advanced MRI in patient populations, bringing the connectome one step closer to the clinic.
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Affiliation(s)
- Ceren Tozlu
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Keith Jamison
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Zijin Gu
- Electrical and Computer Engineering Department, Cornell University, Ithaca 14850, USA
| | - Susan A Gauthier
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA; Department of Neurology, Weill Cornell Medicine, New York, NY, USA; Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Amy Kuceyeski
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA; Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
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Kasties V, Karnath H, Sperber C. Strategies for feature extraction from structural brain imaging in lesion-deficit modelling. Hum Brain Mapp 2021; 42:5409-5422. [PMID: 34415093 PMCID: PMC8519857 DOI: 10.1002/hbm.25629] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 06/30/2021] [Accepted: 08/07/2021] [Indexed: 12/25/2022] Open
Abstract
High‐dimensional modelling of post‐stroke deficits from structural brain imaging is highly relevant to basic cognitive neuroscience and bears the potential to be translationally used to guide individual rehabilitation measures. One strategy to optimise model performance is well‐informed feature selection and representation. However, different feature representation strategies were so far used, and it is not known what strategy is best for modelling purposes. The present study compared the three common main strategies: voxel‐wise representation, lesion‐anatomical componential feature reduction and region‐wise atlas‐based feature representation. We used multivariate, machine‐learning‐based lesion‐deficit models to predict post‐stroke deficits based on structural lesion data. Support vector regression was tuned by nested cross‐validation techniques and tested on held‐out validation data to estimate model performance. While we consistently found the numerically best models for lower‐dimensional, featurised data and almost always for principal components extracted from lesion maps, our results indicate only minor, non‐significant differences between different feature representation styles. Hence, our findings demonstrate the general suitability of all three commonly applied feature representations in lesion‐deficit modelling. Likewise, model performance between qualitatively different popular brain atlases was not significantly different. Our findings also highlight potential minor benefits in individual fine‐tuning of feature representations and the challenge posed by the high, multifaceted complexity of lesion data, where lesion‐anatomical and functional criteria might suggest opposing solutions to feature reduction.
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Affiliation(s)
- Vanessa Kasties
- Centre of Neurology, Division of NeuropsychologyHertie‐Institute for Clinical Brain Research, University of TübingenTübingenGermany
| | - Hans‐Otto Karnath
- Centre of Neurology, Division of NeuropsychologyHertie‐Institute for Clinical Brain Research, University of TübingenTübingenGermany
| | - Christoph Sperber
- Centre of Neurology, Division of NeuropsychologyHertie‐Institute for Clinical Brain Research, University of TübingenTübingenGermany
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Cohen AL, Fox MD. Reply: Looking beyond indirect lesion network mapping of prosopagnosia: direct measures required. Brain 2021; 144:e76. [PMID: 34273160 DOI: 10.1093/brain/awab277] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Alexander L Cohen
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.,Athinoula A. Martinos Centre for Biomedical Imaging, Department of Neurology and Radiology, Massachusetts General Hospital, Charlestown, MA, USA.,Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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D'Imperio D, Romeo Z, Maistrello L, Durgoni E, Della Pietà C, De Filippo De Grazia M, Meneghello F, Turolla A, Zorzi M. Sensorimotor, Attentional, and Neuroanatomical Predictors of Upper Limb Motor Deficits and Rehabilitation Outcome after Stroke. Neural Plast 2021; 2021:8845685. [PMID: 33868400 PMCID: PMC8035034 DOI: 10.1155/2021/8845685] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 01/28/2021] [Accepted: 03/01/2021] [Indexed: 11/23/2022] Open
Abstract
The rehabilitation of motor deficits following stroke relies on both sensorimotor and cognitive abilities, thereby involving large-scale brain networks. However, few studies have investigated the integration between motor and cognitive domains, as well as its neuroanatomical basis. In this retrospective study, upper limb motor responsiveness to technology-based rehabilitation was examined in a sample of 29 stroke patients (18 with right and 11 with left brain damage). Pretreatment sensorimotor and attentional abilities were found to influence motor recovery. Training responsiveness increased as a function of the severity of motor deficits, whereas spared attentional abilities, especially visuospatial attention, supported motor improvements. Neuroanatomical analysis of structural lesions and white matter disconnections showed that the poststroke motor performance was associated with putamen, insula, corticospinal tract, and frontoparietal connectivity. Motor rehabilitation outcome was mainly associated with the superior longitudinal fasciculus and partial involvement of the corpus callosum. The latter findings support the hypothesis that motor recovery engages large-scale brain networks that involve cognitive abilities and provides insight into stroke rehabilitation strategies.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Marco Zorzi
- IRCCS San Camillo Hospital, Venice, Italy
- Department of General Psychology and Padova Neuroscience Center, University of Padova, Italy
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