1
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Jakabek D, Power BD, Spotorno N, Macfarlane MD, Walterfang M, Velakoulis D, Nilsson C, Waldö ML, Lätt J, Nilsson M, van Westen D, Lindberg O, Looi JCL, Santillo AF. Structural and microstructural thalamocortical network disruption in sporadic behavioural variant frontotemporal dementia. Neuroimage Clin 2023; 39:103471. [PMID: 37473493 PMCID: PMC10371821 DOI: 10.1016/j.nicl.2023.103471] [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: 02/06/2023] [Revised: 06/09/2023] [Accepted: 07/06/2023] [Indexed: 07/22/2023]
Abstract
BACKGROUND Using multi-block methods we combined multimodal neuroimaging metrics of thalamic morphology, thalamic white matter tract diffusion metrics, and cortical thickness to examine changes in behavioural variant frontotemporal dementia. (bvFTD). METHOD Twenty-three patients with sporadic bvFTD and 24 healthy controls underwent structural and diffusion MRI scans. Clinical severity was assessed using the Clinical Dementia Rating scale and behavioural severity using the Frontal Behaviour Inventory by patient caregivers. Thalamic volumes were manually segmented. Anterior and posterior thalamic radiation fractional anisotropy and mean diffusivity were extracted using Tract-Based Spatial Statistics. Finally, cortical thickness was assessed using Freesurfer. We used shape analyses, diffusion measures, and cortical thickness as features in sparse multi-block partial least squares (PLS) discriminatory analyses to classify participants within bvFTD or healthy control groups. Sparsity was tuned with five-fold cross-validation repeated 10 times. Final model fit was assessed using permutation testing. Additionally, sparse multi-block PLS was used to examine associations between imaging features and measures of dementia severity. RESULTS Bilateral anterior-dorsal thalamic atrophy, reduction in mean diffusivity of thalamic projections, and frontotemporal cortical thinning, were the main features predicting bvFTD group membership. The model had a sensitivity of 96%, specificity of 68%, and was statistically significant using permutation testing (p = 0.012). For measures of dementia severity, we found similar involvement of regional thalamic and cortical areas as in discrimination analyses, although more extensive thalamo-cortical white matter metric changes. CONCLUSIONS Using multimodal neuroimaging, we demonstrate combined structural network dysfunction of anterior cortical regions, cortical-thalamic projections, and anterior thalamic regions in sporadic bvFTD.
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Affiliation(s)
| | - Brian D Power
- School of Medicine, The University of Notre Dame Australia, Fremantle, Australia
| | - Nicola Spotorno
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | | | - Mark Walterfang
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne, Australia; Department of Psychiatry, University of Melbourne, Melbourne, Australia
| | - Dennis Velakoulis
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne, Australia; Department of Psychiatry, University of Melbourne, Melbourne, Australia
| | - Christer Nilsson
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Maria Landqvist Waldö
- Clinical Sciences Helsingborg, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Jimmy Lätt
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Markus Nilsson
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Danielle van Westen
- Imaging and Function, Skane University Hospital, Lund, Sweden; Diagnostic Radiology, Institution for Clinical Sciences, Lund University, Lund, Sweden
| | - Olof Lindberg
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden
| | - Jeffrey C L Looi
- Academic Unit of Psychiatry and Addiction Medicine, The Australian National University School of Medicine and Psychology, Canberra Hospital, Canberra, Australian Capital Territory, Australia
| | - Alexander F Santillo
- Department of Clinical Sciences, Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund/Malmö, Sweden.
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2
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Mastej EJ, Leppert MH, Poisson S, Ritchey Z, Barry M, Rundek T, Liebeskind DS, Mirsky D, Bernard TJ, Stence NV. Thalamic Volume Loss Is Greater in Children Than in Adults Following Middle Cerebral Artery Territory Arterial Ischemic Stroke. J Child Neurol 2022; 37:882-888. [PMID: 36069041 PMCID: PMC9560991 DOI: 10.1177/08830738221118807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: Younger stroke patients may suffer worse outcomes than older patients; however, the extent to which age at stroke impacts remote areas of the brain remains unclear. The objective of this study was to determine thalamic volume changes ipsilateral to middle cerebral artery territory strokes based on age at acute ischemic stroke onset. Methods: Acute ischemic stroke patients <9 years, 9-18 years, and >18 years old were retrospectively recruited from a large quaternary care system. Each subject underwent an acute (<72 hours from AIS) and chronic (>90 days) magnetic resonance imaging (MRI) scan. Manual thalamic segmentation was performed. Results: Younger and older children had significantly greater stroke-side thalamic volume loss compared to adults (48.2%, P = .022; 40.7%, P = .044, respectively). Conclusions: Stroke-side thalamic volumes decreased across the age spectrum but to a greater degree in pediatric patients. This observation can affect functional and cognitive outcomes post stroke and warrants further research.
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Affiliation(s)
- Emily J. Mastej
- Computational Bioscience Program, University of Colorado Anschutz, Aurora, CO
| | - Michelle H. Leppert
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO
| | - Sharon Poisson
- Department of Neurology, University of Colorado School of Medicine, Aurora, CO
| | - Zak Ritchey
- Department of Radiology, University of Colorado School of Medicine, Aurora, CO
| | - Megan Barry
- Section of Child Neurology, Children’s Hospital Colorado, University of Colorado School of Medicine, Aurora, CO
| | - Tatjana Rundek
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL
| | - David S. Liebeskind
- Department of Neurology, University of California Los Angeles, Los Angeles, CA
| | - David Mirsky
- Department of Radiology, Children’s Hospital Colorado, Medicine, Aurora, CO
| | - Timothy J. Bernard
- Section of Child Neurology, Children’s Hospital Colorado, University of Colorado School of Medicine, Aurora, CO
| | - Nicholas V. Stence
- Department of Radiology, Children’s Hospital Colorado, Medicine, Aurora, CO
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3
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Thalamic volumetric abnormalities in type 1 diabetes mellitus and 'peripheral' neuropathy. Sci Rep 2022; 12:13053. [PMID: 35906253 PMCID: PMC9338092 DOI: 10.1038/s41598-022-16699-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 07/13/2022] [Indexed: 12/03/2022] Open
Abstract
We hypothesized that thalamic volumes of patients with type 1 diabetes mellitus (DM) and nonpainful diabetic peripheral neuropathy (DPN) would be reduced relative to thalamic volumes of patients with type 1 DM and painful DPN. We calculated the standardized thalamic volumetric difference between these groups in a pilot sample to obtain a statistical power of 80% at a 5% significance level. Hence, we measured thalamic volumes from 15 patients with nonpainful DPN (10 women, mean age = 49 years, standard deviation [SD] = 11.5) and from 13 patients with painful DPN (8 women, mean age = 43 years, SD = 12.5) by using a manual segmentation approach. A volumetric difference of approximately 15% was found between the nonpainful (mean = 5072 mm3, SD = 528.1) and painful (mean = 5976 mm3, SD = 643.1) DPN groups (P < 0.001). Curiously, a volumetric difference between the left (mean = 5198 mm3, SD = 495.0) and the right (mean = 4946 mm3, SD = 590.6) thalamus was also found in patients with nonpainful DPN (P < 0.01), but not in patients with painful DPN (P = 0.97). Patients with nonpainful DPN have lower thalamic volumes than those with painful DPN, especially in the right thalamus.
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4
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Lidauer K, Pulli EP, Copeland A, Silver E, Kumpulainen V, Hashempour N, Merisaari H, Saunavaara J, Parkkola R, Lähdesmäki T, Saukko E, Nolvi S, Kataja EL, Karlsson L, Karlsson H, Tuulari JJ. Subcortical and hippocampal brain segmentation in 5-year-old children: validation of FSL-FIRST and FreeSurfer against manual segmentation. Eur J Neurosci 2022; 56:4619-4641. [PMID: 35799402 PMCID: PMC9543285 DOI: 10.1111/ejn.15761] [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: 08/31/2021] [Revised: 06/06/2022] [Accepted: 06/06/2022] [Indexed: 11/28/2022]
Abstract
Developing accurate subcortical volumetric quantification tools is crucial for neurodevelopmental studies, as they could reduce the need for challenging and time‐consuming manual segmentation. In this study, the accuracy of two automated segmentation tools, FSL‐FIRST (with three different boundary correction settings) and FreeSurfer, were compared against manual segmentation of the hippocampus and subcortical nuclei, including the amygdala, thalamus, putamen, globus pallidus, caudate and nucleus accumbens, using volumetric and correlation analyses in 80 5‐year‐olds. Both FSL‐FIRST and FreeSurfer overestimated the volume on all structures except the caudate, and the accuracy varied depending on the structure. Small structures such as the amygdala and nucleus accumbens, which are visually difficult to distinguish, produced significant overestimations and weaker correlations with all automated methods. Larger and more readily distinguishable structures such as the caudate and putamen produced notably lower overestimations and stronger correlations. Overall, the segmentations performed by FSL‐FIRST's default pipeline were the most accurate, whereas FreeSurfer's results were weaker across the structures. In line with prior studies, the accuracy of automated segmentation tools was imperfect with respect to manually defined structures. However, apart from amygdala and nucleus accumbens, FSL‐FIRST's agreement could be considered satisfactory (Pearson correlation > 0.74, intraclass correlation coefficient (ICC) > 0.68 and Dice score coefficient (DSC) > 0.87) with highest values for the striatal structures (putamen, globus pallidus, caudate) (Pearson correlation > 0.77, ICC > 0.87 and DSC > 0.88, respectively). Overall, automated segmentation tools do not always provide satisfactory results, and careful visual inspection of the automated segmentations is strongly advised.
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Affiliation(s)
- Kristian Lidauer
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland
| | - Elmo P Pulli
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland.,Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Anni Copeland
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland.,Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Eero Silver
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland.,Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland
| | - Venla Kumpulainen
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland
| | - Niloofar Hashempour
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland
| | - Harri Merisaari
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland.,Department of Radiology, University of Turku, Turku, Finland
| | - Jani Saunavaara
- Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Riitta Parkkola
- Department of Radiology, University of Turku, Turku, Finland.,Department of Radiology, Turku University Hospital, Turku, Finland
| | - Tuire Lähdesmäki
- Department of Paediatric Neurology, Turku University Hospital and University of Turku, Turku, Finland
| | - Ekaterina Saukko
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Saara Nolvi
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland.,Turku Institute for Advanced Studies, University of Turku, Turku, Finland.,Department of Psychology and Speech-Language Pathology, University of Turku, Turku, Finland
| | - Eeva-Leena Kataja
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland
| | - Linnea Karlsson
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland.,Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland.,Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Hasse Karlsson
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland.,Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland.,Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Jetro J Tuulari
- The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Finland.,Department of Psychiatry, Turku University Hospital, University of Turku, Turku, Finland.,Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland.,Department of Psychiatry, University of Oxford, UK (Sigrid Juselius Fellowship), United Kingdom
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5
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Yao B, Neggers SFW, Kahn RS, Thakkar KN. Altered thalamocortical structural connectivity in persons with schizophrenia and healthy siblings. NEUROIMAGE-CLINICAL 2020; 28:102370. [PMID: 32798913 PMCID: PMC7451425 DOI: 10.1016/j.nicl.2020.102370] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2019] [Revised: 07/13/2020] [Accepted: 07/29/2020] [Indexed: 12/31/2022]
Abstract
Thalamo-prefrontal structural connectivity reduced in persons with schizophrenia. Similar reduction in thalamo-prefrontal connectivity in healthy siblings. Thalamo-motor structural connectivity increased in persons with schizophrenia. No alterations in thalamo-motor structural connectivity in healthy siblings.
Schizophrenia has long been framed as a disorder of altered brain connectivity, with dysfunction in thalamocortical circuity potentially playing a key role in the development of the illness phenotype, including psychotic symptomatology and cognitive impairments. There is emerging evidence for functional and structural hypoconnectivity between thalamus and prefrontal cortex in persons with schizophrenia spectrum disorders, as well as hyperconnectivity between thalamus and sensory and motor cortices. However, it is unclear whether thalamocortical dysconnectivity is a general marker of vulnerability to schizophrenia or a specific mechanism of schizophrenia pathophysiology. This study aimed to answer this question by using diffusion-weighted imaging to examine thalamocortical structural connectivity in 22 persons with schizophrenia or schizoaffective disorder (SZ), 20 siblings of individuals with a schizophrenia spectrum disorder (SIB), and 44 healthy controls (HC) of either sex. Probabilistic tractography was used to quantify structural connectivity between thalamus and six cortical regions of interest. Thalamocortical structural connectivity was compared among the three groups using cross-thalamic and voxel-wise approaches. Thalamo-prefrontal structural connectivity was reduced in both SZ and SIB relative to HC, while SZ and SIB did not differ from each other. Thalamo-motor structural connectivity was increased in SZ relative to SIB and HC, while SIB and HC did not differ from each other. Hemispheric differences also emerged in thalamic connectivity with motor, posterior parietal, and temporal cortices across all groups. The results support the hypothesis that altered thalamo-prefrontal structural connectivity is a general marker of vulnerability to schizophrenia, whereas altered connectivity between thalamus and motor cortex is related to illness expression or illness-related secondary factors.
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Affiliation(s)
- Beier Yao
- Department of Psychology, Michigan State University, East Lansing, Michigan, USA
| | | | - René S Kahn
- Department of Psychiatry, University Medical Center, Utrecht, the Netherlands; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Katharine N Thakkar
- Department of Psychology, Michigan State University, East Lansing, Michigan, USA; Division of Psychiatry and Behavioral Medicine, Michigan State University, Grand Rapids, MI, USA.
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6
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Oliveira AR, Nunes RG, Figueiredo P, Dias AI, Leal A. Regional White Matter Atrophy Correlates with Spike Activity in Encephalopathy Related to Status Epilepticus During Slow Sleep (ESES) After Early Thalamic Lesions. Brain Topogr 2020; 33:571-585. [PMID: 32653964 DOI: 10.1007/s10548-020-00784-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Accepted: 06/28/2020] [Indexed: 11/24/2022]
Abstract
Encephalopathy related to Status Epilepticus during slow Sleep (ESES) is an age-related, epileptic syndrome, which associates cognitive/behavioral disturbances with a peculiar pattern of spike activity. One promising line of research is the study of ESES in cases of early thalamic lesions. We studied 7 ESES patients with unilateral thalamic lesions using magnetic resonance imaging to assess regional white matter (WM) and thalamic nuclei volume differences, and long-term electroencephalogram recordings to localize the epileptogenic cortex. N170 event-related potentials were used to demonstrate the dysfunctional character of the WM abnormalities. Diffusion-weighted images in a subset of 4 patients were used to parcellate the thalamus and evaluate volume asymmetries, based on cortical connectivity. Large WM regional atrophy in the hemisphere with the thalamic lesion was associated with both cortical dysfunction and epileptic activity. A correlation was demonstrated between lesions in the pulvinar and the mediodorsal thalamic nuclei and WM atrophy of the corresponding cortical projection areas. We propose that these abnormalities are due to the widespread structural disconnection produced by the thalamic lesions associated to a yet unknown age-dependent factor. Further exploration of WM regional atrophy association with the spike activity in other etiologies could lend support to the cortical disconnection role in ESES genesis.
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Affiliation(s)
- Ana R Oliveira
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal.
| | - Rita G Nunes
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- ISR-Lisboa/LARSyS and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Ana I Dias
- Department of Pediatric Neurology, Hospital Dona Estefânia, Lisbon, Portugal
| | - Alberto Leal
- Department of Pediatric Neurology, Hospital Dona Estefânia, Lisbon, Portugal.,Department of Clinical Neurophysiology, Hospital Júlio de Matos, Lisbon, Portugal
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7
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Reduced accuracy of MRI deep grey matter segmentation in multiple sclerosis: an evaluation of four automated methods against manual reference segmentations in a multi-center cohort. J Neurol 2020; 267:3541-3554. [PMID: 32621103 PMCID: PMC7674567 DOI: 10.1007/s00415-020-10023-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/22/2020] [Accepted: 06/23/2020] [Indexed: 12/22/2022]
Abstract
Background Deep grey matter (DGM) atrophy in multiple sclerosis (MS) and its relation to cognitive and clinical decline requires accurate measurements. MS pathology may deteriorate the performance of automated segmentation methods. Accuracy of DGM segmentation methods is compared between MS and controls, and the relation of performance with lesions and atrophy is studied. Methods On images of 21 MS subjects and 11 controls, three raters manually outlined caudate nucleus, putamen and thalamus; outlines were combined by majority voting. FSL-FIRST, FreeSurfer, Geodesic Information Flow and volBrain were evaluated. Performance was evaluated volumetrically (intra-class correlation coefficient (ICC)) and spatially (Dice similarity coefficient (DSC)). Spearman's correlations of DSC with global and local lesion volume, structure of interest volume (ROIV), and normalized brain volume (NBV) were assessed. Results ICC with manual volumes was mostly good and spatial agreement was high. MS exhibited significantly lower DSC than controls for thalamus and putamen. For some combinations of structure and method, DSC correlated negatively with lesion volume or positively with NBV or ROIV. Lesion-filling did not substantially change segmentations. Conclusions Automated methods have impaired performance in patients. Performance generally deteriorated with higher lesion volume and lower NBV and ROIV, suggesting that these may contribute to the impaired performance. Electronic supplementary material The online version of this article (10.1007/s00415-020-10023-1) contains supplementary material, which is available to authorized users.
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8
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Furlong LS, Jakabek D, Power BD, Owens-Walton C, Wilkes FA, Walterfang M, Velakoulis D, Egan G, Looi JC, Georgiou-Karistianis N. Morphometric in vivo evidence of thalamic atrophy correlated with cognitive and motor dysfunction in Huntington's disease: The IMAGE-HD study. Psychiatry Res Neuroimaging 2020; 298:111048. [PMID: 32120305 DOI: 10.1016/j.pscychresns.2020.111048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 02/09/2020] [Accepted: 02/14/2020] [Indexed: 01/18/2023]
Abstract
In Huntington's disease (HD), neurodegeneration causes progressive atrophy to the striatum, cortical areas, and white matter tracts - components of corticostriatal circuitry. Such processes may affect the thalamus, a key circuit node. We investigated whether differences in dorsal thalamic morphology were detectable in HD, and whether thalamic atrophy was associated with neurocognitive, neuropsychiatric and motor dysfunction. Magnetic resonance imaging scans and clinical outcome measures were obtained from 34 presymptomatic HD (pre-HD), 29 early symptomatic HD (symp-HD), and 26 healthy control individuals who participated in the IMAGE-HD study. Manual region of interest (ROI) segmentation was conducted to measure dorsal thalamic volume, and thalamic ROI underwent shape analysis using the spherical harmonic point distribution method. The symp-HD group had significant thalamic volumetric reduction and global shape deflation, indicative of atrophy, compared to pre-HD and control groups. Thalamic atrophy significantly predicted neurocognitive and motor dysfunction within the symp-HD group only. Thalamic morphology differentiates symp-HD from pre-HD and healthy individuals. Thalamic changes may be one of the structural bases (endomorphotypes), of the endophenotypic neurocognitive and motor manifestations of disease. Future research should continue to investigate the thalamus as a potential in vivo biomarker of disease progression in HD.
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Affiliation(s)
- Lisa S Furlong
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University Medical School, Canberra, Australia; John Curtin School of Medical Research, Australian National University, Canberra, Australia.
| | - David Jakabek
- Graduate School of Medicine, University of Wollongong, Wollongong, Australia
| | - Brian D Power
- School of Medicine Fremantle, The University of Notre Dame Australia, Fremantle, Australia; Clinical Research Centre, North Metropolitan Health Service - Mental Health, WA, Australia
| | - Conor Owens-Walton
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University Medical School, Canberra, Australia
| | - Fiona A Wilkes
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University Medical School, Canberra, Australia
| | - Mark Walterfang
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, and University of Melbourne, Melbourne, Australia
| | - Dennis Velakoulis
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, and University of Melbourne, Melbourne, Australia
| | - Gary Egan
- School of Psychological Sciences and The Turner Institute for Brain and Mental Health Monash University, Clayton, Australia; Monash Biomedical Imaging, Monash University, Clayton, Australia; Life Sciences Computation Centre, Victorian Life Sciences Computation Initiative, Melbourne, Australia
| | - Jeffrey Cl Looi
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, School of Clinical Medicine, Australian National University Medical School, Canberra, Australia; Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, and University of Melbourne, Melbourne, Australia
| | - Nellie Georgiou-Karistianis
- School of Psychological Sciences and The Turner Institute for Brain and Mental Health Monash University, Clayton, Australia
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9
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Increased functional connectivity of thalamic subdivisions in patients with Parkinson's disease. PLoS One 2019; 14:e0222002. [PMID: 31483847 PMCID: PMC6726201 DOI: 10.1371/journal.pone.0222002] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Accepted: 08/20/2019] [Indexed: 01/09/2023] Open
Abstract
Parkinson’s disease (PD) affects 2–3% of the population over the age of 65 with loss of dopaminergic neurons in the substantia nigra impacting the functioning of basal ganglia-thalamocortical circuits. The precise role played by the thalamus is unknown, despite its critical role in the functioning of the cerebral cortex, and the abnormal neuronal activity of the structure in PD. Our objective was to more clearly elucidate how functional connectivity and morphology of the thalamus are impacted in PD (n = 32) compared to Controls (n = 20). To investigate functional connectivity of the thalamus we subdivided the structure into two important regions-of-interest, the first with putative connections to the motor cortices and the second with putative connections to prefrontal cortices. We then investigated potential differences in the size and shape of the thalamus in PD, and how morphology and functional connectivity relate to clinical variables. Our data demonstrate that PD is associated with increases in functional connectivity between motor subdivisions of the thalamus and the supplementary motor area, and between prefrontal thalamic subdivisions and nuclei of the basal ganglia, anterior and dorsolateral prefrontal cortices, as well as the anterior and paracingulate gyri. These results suggest that PD is associated with increased functional connectivity of subdivisions of the thalamus which may be indicative alterations to basal ganglia-thalamocortical circuitry.
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10
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Jakabek D, Power BD, Macfarlane MD, Walterfang M, Velakoulis D, van Westen D, Lätt J, Nilsson M, Looi JCL, Santillo AF. Regional structural hypo- and hyperconnectivity of frontal-striatal and frontal-thalamic pathways in behavioral variant frontotemporal dementia. Hum Brain Mapp 2018; 39:4083-4093. [PMID: 29923666 DOI: 10.1002/hbm.24233] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 04/09/2018] [Accepted: 05/15/2018] [Indexed: 12/14/2022] Open
Abstract
Behavioral variant frontotemporal dementia (bvFTD) has been predominantly considered as a frontotemporal cortical disease, with limited direct investigation of frontal-subcortical connections. We aim to characterize the grey and white matter components of frontal-thalamic and frontal-striatal circuits in bvFTD. Twenty-four patients with bvFTD and 24 healthy controls underwent morphological and diffusion imaging. Subcortical structures were manually segmented according to published protocols. Probabilistic pathways were reconstructed separately from the dorsolateral, orbitofrontal and medial prefrontal cortex to the striatum and thalamus. Patients with bvFTD had smaller cortical and subcortical volumes, lower fractional anisotropy, and higher mean diffusivity metrics, which is consistent with disruptions in frontal-striatal-thalamic pathways. Unexpectedly, regional volumes of the striatum and thalamus connected to the medial prefrontal cortex were significantly larger in bvFTD (by 135% in the striatum, p = .032, and 217% in the thalamus, p = .004), despite smaller dorsolateral prefrontal cortex connected regional volumes (by 67% in the striatum, p = .002, and 65% in the thalamus, p = .020), and inconsistent changes in orbitofrontal cortex connected regions. These unanticipated findings may represent compensatory or maladaptive remodeling in bvFTD networks. Comparisons are made to other neuropsychiatric disorders suggesting a common mechanism of changes in frontal-subcortical networks; however, longitudinal studies are necessary to test this hypothesis.
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Affiliation(s)
- David Jakabek
- Graduate School of Medicine, University of Wollongong, Wollongong, Australia
| | - Brian D Power
- School of Medicine, The University of Notre Dame Australia, Fremantle, Australia; Clinical Research Centre, North Metropolitan Health Service - Mental Health, Perth, Australia
| | - Matthew D Macfarlane
- Graduate School of Medicine, University of Wollongong, Wollongong, Australia.,Illawarra Shoalhaven Local Health District, Wollongong, Australia
| | - Mark Walterfang
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, Australia
| | - Dennis Velakoulis
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, Australia
| | - Danielle van Westen
- Centre for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Jimmy Lätt
- Centre for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden.,Department of Radiology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Markus Nilsson
- Department of Radiology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| | - Jeffrey C L Looi
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, Department of Psychiatry, Melbourne Medical School, University of Melbourne, Melbourne, Australia.,Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, Australian National University Medical School, Canberra Hospital, Canberra, Australia
| | - Alexander F Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
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Evaluating accuracy of striatal, pallidal, and thalamic segmentation methods: Comparing automated approaches to manual delineation. Neuroimage 2018; 170:182-198. [DOI: 10.1016/j.neuroimage.2017.02.069] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 02/03/2017] [Accepted: 02/24/2017] [Indexed: 12/16/2022] Open
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12
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Anatomical and physiological basis of continuous spike-wave of sleep syndrome after early thalamic lesions. Epilepsy Behav 2018; 78:243-255. [PMID: 29133062 DOI: 10.1016/j.yebeh.2017.08.027] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2017] [Revised: 08/18/2017] [Accepted: 08/19/2017] [Indexed: 11/24/2022]
Abstract
OBJECTIVE Early neonatal thalamic lesions account for about 14% of continuous spike-wave of sleep (CSWS) syndrome, representing the most common etiology in this epileptic encephalopathy in children, and promise useful insights into the pathophysiology of the disease. METHODS We describe nine patients with unilateral neonatal thalamic lesions which progressed to CSWS. Longitudinal whole-night and high-density electroencephalograms (EEGs) were performed, as well as detailed imaging and clinical evaluation. Visual evoked potentials were used to probe cortical excitability. RESULTS Thalamic volume loss ranged from 19% to 94%, predominantly on medial and dorsal nuclei and sparing the ventral thalamus. Lesions produced white matter loss and ventricle enlargement on the same hemisphere, which in four patients was associated with selective loss of thalamic-cortical fibers. Cortical thickness quantification failed to reveal hemispheric asymmetries. Impact on EEG rhythms was mild, with a volume-loss-related decrease in alpha power and preservation of sleep spindles. The sleep continuous spiking was lateralized to the hemisphere with the lesion. Visual cortex stimulation in five patients with posterior cortex spiking revealed an abnormal frequency-dependent excitability at 10-20Hz on the side of the lesion. SIGNIFICANCE Unilateral selective thalamic-cortical disconnection is a common feature in our patients and is associated with both a focal pattern of CSWS and a pathological type of frequency-dependent excitability (peak: 10-20Hz). We propose that this excitability represents an abnormal synaptic plasticity previously described as the augmenting response. This synaptic plasticity has been described as absent in the corticocortical interactions in healthy experimental animals, emerging after ablation of the thalamus and producing a frequency-dependent potentiation with a peak at 10-20Hz. Because this response is potentiated by sleep states of reduced brainstem activation and by appropriate stimulating rhythms, such as sleep spindles, the simultaneous occurrence of these two factors in nonrapid-eye-movement sleep is proposed as an explanation for CSWS in our patients.
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Glaister J, Carass A, NessAiver T, Stough JV, Saidha S, Calabresi PA, Prince JL. Thalamus segmentation using multi-modal feature classification: Validation and pilot study of an age-matched cohort. Neuroimage 2017; 158:430-440. [PMID: 28669906 PMCID: PMC5614844 DOI: 10.1016/j.neuroimage.2017.06.047] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 05/10/2017] [Accepted: 06/20/2017] [Indexed: 10/19/2022] Open
Abstract
Automatic segmentation of the thalamus can be used to measure differences and track changes in thalamic volume that may occur due to disease, injury or normal aging. An automatic thalamus segmentation algorithm incorporating features from diffusion tensor imaging (DTI) and thalamus priors constructed from multiple atlases is proposed. Multiple atlases with corresponding manual thalamus segmentations are registered to the target image and averaged to generate the thalamus prior. At each voxel in a region of interest around the thalamus, a multidimensional feature vector that includes the thalamus prior as well as a set of DTI features, including fractional anisotropy, mean diffusivity, and fiber orientation is formed. A random forest is trained to classify each voxel as belonging to the thalamus or background within the region of interest. Using a leave-one-out cross-validation on nine subjects, the proposed algorithm achieves a mean Dice score of 0.878 and 0.890 for the left and right thalami, respectively, which are higher Dice scores than the three state-of-art methods we compared to. We demonstrate the utility of the method with a pilot study exploring the difference in the thalamus fraction between 21 multiple sclerosis (MS) patients and 21 age-matched healthy controls. The left and right thalamic volumes (normalized by intracranial volumes) are larger in healthy controls by 7.6% and 7.3% respectively, compared to MS patients (though neither result is statistically significant).
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Affiliation(s)
- Jeffrey Glaister
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA.
| | - Aaron Carass
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA; Department of Computer Science, The Johns Hopkins University, Baltimore, MD 21218, USA
| | - Tziona NessAiver
- Department of Interdisciplinary Studies, University of Maryland, Baltimore County, MD 21250, USA
| | - Joshua V Stough
- Department of Computer Science, Bucknell University, Lewisburg, PA 17837, USA
| | - Shiv Saidha
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA
| | - Peter A Calabresi
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD 21287, USA
| | - Jerry L Prince
- Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD 21218, USA; Department of Computer Science, The Johns Hopkins University, Baltimore, MD 21218, USA
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14
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Power BD, Jakabek D, Hunter-Dickson M, Wilkes FA, van Westen D, Santillo AF, Walterfang M, Velakoulis D, Nilsson C, Looi JCL. Morphometric analysis of thalamic volume in progressive supranuclear palsy: In vivo evidence of regionally specific bilateral thalamic atrophy. Psychiatry Res Neuroimaging 2017; 265:65-71. [PMID: 28550719 DOI: 10.1016/j.pscychresns.2017.05.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Revised: 04/11/2017] [Accepted: 05/11/2017] [Indexed: 11/25/2022]
Abstract
We investigated whether differences were detectable in the volume and shape of the dorsal thalamus on magnetic resonance imaging in patients with progressive supranuclear palsy (PSP). Manual segmentation of the left and right thalami on magnetic resonance imaging scans occurred in 22 patients with clinically diagnosed PSP and 23 healthy controls; thalamic volumes (left, right, total) were calculated. Between group differences were explored by multivariate analysis of co-variance, using age and intracranial volume as covariates. Analysis of the shape of the thalamus was performed using the spherical harmonic point distribution method software package. Patients with PSP were found to have significant bilateral thalamic atrophy on magnetic resonance imaging; there was significant shape deflation over the anterior-lateral and anterior-ventral surfaces bilaterally, and over the right caudal thalamus. Recognizing decreased thalamic morphology in PSP patients in vivo may be an important component of an ensemble of diagnostic biomarkers in the future, particularly given the difficulty of distinguishing PSP from other Parkinsonian conditions early in the disease course.
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Affiliation(s)
- Brian D Power
- School of Medicine Fremantle, The University of Notre Dame Australia, Fremantle, Australia; Clinical Research Centre, North Metropolitan Health Service - Mental Health, Perth, Australia.
| | - David Jakabek
- University of Wollongong, Wollongong, NSW, Australia.
| | - Mitchell Hunter-Dickson
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, Australian National University Medical School, Canberra Hospital, Canberra, Australia.
| | - Fiona A Wilkes
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, Australian National University Medical School, Canberra Hospital, Canberra, Australia.
| | - Danielle van Westen
- Center for Medical Imaging and Physiology, Skåne University Hospital, and Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden; Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden.
| | - Alexander F Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.
| | - Mark Walterfang
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, Melbourne, Australia.
| | - Dennis Velakoulis
- Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, Melbourne, Australia.
| | - Christer Nilsson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden.
| | - Jeffrey C L Looi
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, Australian National University Medical School, Canberra Hospital, Canberra, Australia; Neuropsychiatry Unit, Royal Melbourne Hospital, Melbourne Neuropsychiatry Centre, Melbourne, Australia
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15
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Næss-Schmidt E, Tietze A, Blicher JU, Petersen M, Mikkelsen IK, Coupé P, Manjón JV, Eskildsen SF. Automatic thalamus and hippocampus segmentation from MP2RAGE: comparison of publicly available methods and implications for DTI quantification. Int J Comput Assist Radiol Surg 2016; 11:1979-1991. [PMID: 27325140 DOI: 10.1007/s11548-016-1433-0] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Accepted: 05/27/2016] [Indexed: 01/18/2023]
Abstract
PURPOSE In both structural and functional MRI, there is a need for accurate and reliable automatic segmentation of brain regions. Inconsistent segmentation reduces sensitivity and may bias results in clinical studies. The current study compares the performance of publicly available segmentation tools and their impact on diffusion quantification, emphasizing the importance of using recently developed segmentation algorithms and imaging techniques. METHODS Four publicly available, automatic segmentation methods (volBrain, FSL, FreeSurfer and SPM) are compared to manual segmentation of the thalamus and hippocampus imaged with a recently proposed T1-weighted MRI sequence (MP2RAGE). We evaluate morphometric accuracy on 22 healthy subjects and impact on diffusivity measurements obtained from aligned diffusion-weighted images on a subset of 10 subjects. RESULTS Compared to manual segmentation, the highest Dice similarity index of the thalamus is obtained with volBrain using a local library ([Formula: see text], [Formula: see text]) followed by volBrain using an external library ([Formula: see text], [Formula: see text]), FSL ([Formula: see text], [Formula: see text]), FreeSurfer ([Formula: see text], [Formula: see text]) and SPM ([Formula: see text], [Formula: see text]). The same order is found for hippocampus with volBrain local ([Formula: see text], [Formula: see text]), volBrain external ([Formula: see text], [Formula: see text]), FSL ([Formula: see text], [Formula: see text]), FreeSurfer ([Formula: see text], [Formula: see text]) and SPM ([Formula: see text], [Formula: see text]). For diffusivity measurements, volBrain provides values closest to those obtained from manual segmentations. volBrain is the only method where FA values do not differ significantly from manual segmentation of the thalamus. CONCLUSIONS Overall we find that volBrain is superior in thalamus and hippocampus segmentation compared to FSL, FreeSurfer and SPM. Furthermore, the choice of segmentation technique and training library affects quantitative results from diffusivity measures in thalamus and hippocampus.
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Affiliation(s)
- Erhard Næss-Schmidt
- Hammel Neurorehabilitation Centre and University Research Clinic, Aarhus University, Voldbyvej 15, 8460, Hammel, Denmark. .,Hammel Neurorehabilitation Centre and University Research Clinic, Voldbyvej 15, 8460, Hammel, Denmark.
| | - Anna Tietze
- Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University, Aarhus, Denmark.,Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark
| | - Jakob Udby Blicher
- Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University, Aarhus, Denmark
| | - Mikkel Petersen
- Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University, Aarhus, Denmark
| | - Irene K Mikkelsen
- Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University, Aarhus, Denmark
| | - Pierrick Coupé
- Laboratoire Bordelais de Recherche en Informatique, Unité Mixte de Recherche CNRS (UMR 5800), PICTURA Research Group, 351, cours de la Libération, 33405, Talence cedex, France
| | - José V Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain
| | - Simon Fristed Eskildsen
- Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University, Aarhus, Denmark
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Bartolini E, Falchi M, Zellini F, Parrini E, Grisotto L, Cosottini M, Posar A, Parmeggiani A, Ambrosetto G, Ferrari AR, Santucci M, Salas-Puig J, Barba C, Guerrini R. The syndrome of polymicrogyria, thalamic hypoplasia, and epilepsy with CSWS. Neurology 2016; 86:1250-9. [DOI: 10.1212/wnl.0000000000002526] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2015] [Accepted: 12/14/2015] [Indexed: 11/15/2022] Open
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Abstract
OBJECTIVE This review provides a brief account of the clinically relevant functional neuroanatomy of the thalamus, before considering the utility of various modalities utilized to image the thalamus and technical challenges therein, and going on to provide an overview of studies utilizing structural imaging techniques to map thalamic morphology in the spectrum of neurodegenerative disorders. METHODS A systematic search was conducted for peer-reviewed studies involving structural neuroimaging modalities investigating the morphology (shape and/or size) of the thalamus in the spectrum of neurodegenerative disorders. RESULTS While the precise role of the thalamus in the healthy brain remains unclear, there is a large body of knowledge accumulating which defines more precisely its functional connectivity within the connectome, and a burgeoning literature implicating its involvement in neurodegenerative disorders. It is proposed that correlation of clinical features with thalamic morphology (as a component of a quantifiable subcortical connectome) will provide a better understanding of neuropsychiatric dysfunction in various neurodegenerative disorders, potentially yielding clinically useful endophenotypes and disease biomarkers. CONCLUSION Thalamic biomarkers in the neurodegenerative disorders have great potential to provide clinically meaningful knowledge regarding not only disease onset and progression but may yield targets of and perhaps a way of gauging response to future disease-modifying modalities.
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Affiliation(s)
- Brian D Power
- School of Medicine Fremantle, The University of Notre Dame Australia, Fremantle, WA, Australia Clinical Research Centre, North Metropolitan Health Service - Mental Health, Perth, WA, Australia
| | - Jeffrey C L Looi
- Research Centre for the Neurosciences of Ageing, Academic Unit of Psychiatry and Addiction Medicine, Australian National University Medical School, Canberra Hospital, Canberra, ACT, Australia
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