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Mamah D, Chen S, Shimony JS, Harms MP. Tract-based analyses of white matter in schizophrenia, bipolar disorder, aging, and dementia using high spatial and directional resolution diffusion imaging: a pilot study. Front Psychiatry 2024; 15:1240502. [PMID: 38362028 PMCID: PMC10867155 DOI: 10.3389/fpsyt.2024.1240502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 01/15/2024] [Indexed: 02/17/2024] Open
Abstract
Introduction Structural brain connectivity abnormalities have been associated with several psychiatric disorders. Schizophrenia (SCZ) is a chronic disabling disorder associated with accelerated aging and increased risk of dementia, though brain findings in the disorder have rarely been directly compared to those that occur with aging. Methods We used an automated approach to reconstruct key white matter tracts and assessed tract integrity in five participant groups. We acquired one-hour-long high-directional diffusion MRI data from young control (CON, n =28), bipolar disorder (BPD, n =21), and SCZ (n =22) participants aged 18-30, and healthy elderly (ELD, n =15) and dementia (DEM, n =9) participants. Volume, fractional (FA), radial diffusivity (RD) and axial diffusivity (AD) of seven key white matter tracts (anterior thalamic radiation, ATR; dorsal and ventral cingulum bundle, CBD and CBV; corticospinal tract, CST; and the three superior longitudinal fasciculi: SLF-1, SLF-2 and SLF-3) were analyzed with TRACULA. Group comparisons in tract metrics were performed using multivariate and univariate analyses. Clinical relationships of tract metrics with recent and chronic symptoms were assessed in SCZ and BPD participants. Results A MANOVA showed group differences in FA (λ=0.5; p=0.0002) and RD (λ=0.35; p<0.0001) across the seven tracts, but no significant differences in tract AD and volume. Post-hoc analyses indicated lower tract FA and higher RD in ELD and DEM groups compared to CON, BPD and SCZ groups. Lower FA and higher RD in SCZ compared to CON did not meet statistical significance. In SCZ participants, a significant negative correlation was found between chronic psychosis severity and FA in the SLF-1 (r= -0.45; p=0.035), SLF-2 (r= -0.49; p=0.02) and SLF-3 (r= -0.44; p=0.042). Discussion Our results indicate impaired white matter tract integrity in elderly populations consistent with myelin damage. Impaired tract integrity in SCZ is most prominent in patients with advanced illness.
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Affiliation(s)
- Daniel Mamah
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - ShingShiun Chen
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
| | - Joshua S. Shimony
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Michael P. Harms
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, United States
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Hall GR, Hutchings F, Horsley J, Simpson CM, Wang Y, de Tisi J, Miserocchi A, McEvoy AW, Vos SB, Winston GP, Duncan JS, Taylor PN. Epileptogenic networks in extra temporal lobe epilepsy. Netw Neurosci 2023; 7:1351-1362. [PMID: 38144694 PMCID: PMC10631792 DOI: 10.1162/netn_a_00327] [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: 12/21/2022] [Accepted: 06/22/2023] [Indexed: 12/26/2023] Open
Abstract
Extra temporal lobe epilepsy (eTLE) may involve heterogenous widespread cerebral networks. We investigated the structural network of an eTLE cohort, at the postulated epileptogenic zone later surgically removed, as a network node: the resection zone (RZ). We hypothesized patients with an abnormal connection to/from the RZ to have proportionally increased abnormalities based on topological proximity to the RZ, in addition to poorer post-operative seizure outcome. Structural and diffusion MRI were collected for 22 eTLE patients pre- and post-surgery, and for 29 healthy controls. The structural connectivity of the RZ prior to surgery, measured via generalized fractional anisotropy (gFA), was compared with healthy controls. Abnormal connections were identified as those with substantially reduced gFA (z < -1.96). For patients with one or more abnormal connections to/from the RZ, connections with closer topological distance to the RZ had higher proportion of abnormalities. The minority of the seizure-free patients (3/11) had one or more abnormal connections, while most non-seizure-free patients (8/11) had abnormal connections to the RZ. Our data suggest that eTLE patients with one or more abnormal structural connections to/from the RZ had more proportional abnormal connections based on topological distance to the RZ and associated with reduced chance of seizure freedom post-surgery.
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Affiliation(s)
- Gerard R. Hall
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Frances Hutchings
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Jonathan Horsley
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Callum M. Simpson
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Jane de Tisi
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- UCL/UCLH NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Anna Miserocchi
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Andrew W. McEvoy
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Sjoerd B. Vos
- Centre for Microscopy, Characterisation, and Analysis, University of Western Australia, Nedlands, Australia
| | - Gavin P. Winston
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- Department of Medicine, Division of Neurology, Queen’s University, Kingston, Canada
| | - John S. Duncan
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- UCL/UCLH NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Peter N. Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Department of Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
- Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
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Andica C, Kamagata K, Aoki S. Automated three-dimensional major white matter bundle segmentation using diffusion magnetic resonance imaging. Anat Sci Int 2023:10.1007/s12565-023-00715-9. [PMID: 37017902 DOI: 10.1007/s12565-023-00715-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 03/09/2023] [Indexed: 04/06/2023]
Abstract
White matter bundle segmentation using diffusion magnetic resonance imaging fiber tractography enables detailed evaluation of individual white matter tracts three-dimensionally, and plays a crucial role in studying human brain anatomy, function, development, and diseases. Manual extraction of streamlines utilizing a combination of the inclusion and exclusion of regions of interest can be considered the current gold standard for extracting white matter bundles from whole-brain tractograms. However, this is a time-consuming and operator-dependent process with limited reproducibility. Several automated approaches using different strategies to reconstruct the white matter tracts have been proposed to address the issues of time, labor, and reproducibility. In this review, we discuss few of the most well-validated approaches that automate white matter bundle segmentation with an end-to-end pipeline, including TRActs Constrained by UnderLying Anatomy (TRACULA), Automated Fiber Quantification, and TractSeg.
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Affiliation(s)
- Christina Andica
- Faculty of Health Data Science, Juntendo University, 6-8-1 Hinode, Urayasu, Chiba, 279-0013, Japan.
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan.
| | - Koji Kamagata
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
| | - Shigeki Aoki
- Faculty of Health Data Science, Juntendo University, 6-8-1 Hinode, Urayasu, Chiba, 279-0013, Japan
- Department of Radiology, Juntendo University Graduate School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo, 113-8421, Japan
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Maffei C, Gilmore N, Snider SB, Foulkes AS, Bodien YG, Yendiki A, Edlow BL. Automated detection of axonal damage along white matter tracts in acute severe traumatic brain injury. Neuroimage Clin 2022; 37:103294. [PMID: 36529035 PMCID: PMC9792957 DOI: 10.1016/j.nicl.2022.103294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 12/12/2022] [Accepted: 12/13/2022] [Indexed: 12/15/2022]
Abstract
New techniques for individualized assessment of white matter integrity are needed to detect traumatic axonal injury (TAI) and predict outcomes in critically ill patients with acute severe traumatic brain injury (TBI). Diffusion MRI tractography has the potential to quantify white matter microstructure in vivo and has been used to characterize tract-specific changes following TBI. However, tractography is not routinely used in the clinical setting to assess the extent of TAI, in part because focal lesions reduce the robustness of automated methods. Here, we propose a pipeline that combines automated tractography reconstructions of 40 white matter tracts with multivariate analysis of along-tract diffusion metrics to assess the presence of TAI in individual patients with acute severe TBI. We used the Mahalanobis distance to identify abnormal white matter tracts in each of 18 patients with acute severe TBI as compared to 33 healthy subjects. In all patients for which a FreeSurfer anatomical segmentation could be obtained (17 of 18 patients), including 13 with focal lesions, the automated pipeline successfully reconstructed a mean of 37.5 ± 2.1 white matter tracts without the need for manual intervention. A mean of 2.5 ± 2.1 tracts resulted in partial or failed reconstructions and needed to be reinitialized upon visual inspection. The pipeline detected at least one abnormal tract in all patients (mean: 9.1 ± 7.9) and accurately discriminated between patients and controls (AUC: 0.91). The number and neuroanatomic location of abnormal tracts varied across patients and levels of consciousness. The premotor, temporal, and parietal sections of the corpus callosum were the most commonly damaged tracts (in 10, 9, and 8 patients, respectively), consistent with prior histopathological studies of TAI. TAI measures were not associated with concurrent behavioral measures of consciousness. In summary, we provide proof-of-principle evidence that an automated tractography pipeline has translational potential to detect and quantify TAI in individual patients with acute severe TBI.
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Affiliation(s)
- Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
| | - Natalie Gilmore
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Samuel B Snider
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrea S Foulkes
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Brian L Edlow
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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Adan GH, de Bézenac C, Bonnett L, Pridgeon M, Biswas S, Das K, Richardson MP, Laiou P, Keller SS, Marson T. Protocol for an observational cohort study investigating biomarkers predicting seizure recurrence following a first unprovoked seizure in adults. BMJ Open 2022; 12:e065390. [PMID: 36576179 PMCID: PMC9723849 DOI: 10.1136/bmjopen-2022-065390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 11/16/2022] [Indexed: 12/12/2022] Open
Abstract
INTRODUCTION A first unprovoked seizure is a common presentation, reliably identifying those that will have recurrent seizures is a challenge. This study will be the first to explore the combined utility of serum biomarkers, quantitative electroencephalogram (EEG) and quantitative MRI to predict seizure recurrence. This will inform patient stratification for counselling and the inclusion of high-risk patients in clinical trials of disease-modifying agents in early epilepsy. METHODS AND ANALYSIS 100 patients with first unprovoked seizure will be recruited from a tertiary neuroscience centre and baseline assessments will include structural MRI, EEG and a blood sample. As part of a nested pilot study, a subset of 40 patients will have advanced MRI sequences performed that are usually reserved for patients with refractory chronic epilepsy. The remaining 60 patients will have standard clinical MRI sequences. Patients will be followed up every 6 months for a 24-month period to assess seizure recurrence. Connectivity and network-based analyses of EEG and MRI data will be carried out and examined in relation to seizure recurrence. Patient outcomes will also be investigated with respect to analysis of high-mobility group box-1 from blood serum samples. ETHICS AND DISSEMINATION This study was approved by North East-Tyne & Wear South Research Ethics Committee (20/NE/0078) and funded by an Association of British Neurologists and Guarantors of Brain clinical research training fellowship. Findings will be presented at national and international meetings published in peer-reviewed journals. TRIAL REGISTRATION NUMBER NIHR Clinical Research Network's (CRN) Central Portfolio Management System (CPMS)-44976.
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Affiliation(s)
- Guleed H Adan
- Institute of Systems, Molecular, Integrated Biology, Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
- The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Christophe de Bézenac
- Institute of Systems, Molecular, Integrated Biology, Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
| | - Laura Bonnett
- University of Liverpool Department of Biostatistics, Liverpool, UK
| | | | | | - Kumar Das
- The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Mark P Richardson
- Department of Basic and Clinical Neuroscience, King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK
| | - Petroula Laiou
- Department of Basic and Clinical Neuroscience, King's College London Institute of Psychiatry Psychology and Neuroscience, London, UK
| | - Simon S Keller
- Institute of Systems, Molecular, Integrated Biology, Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
- The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Tony Marson
- Institute of Systems, Molecular, Integrated Biology, Department of Pharmacology and Therapeutics, University of Liverpool, Liverpool, UK
- The Walton Centre NHS Foundation Trust, Liverpool, UK
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Kasa LW, Peters T, Mirsattari SM, Jurkiewicz MT, Khan AR, A M Haast R. The role of the temporal pole in temporal lobe epilepsy: A diffusion kurtosis imaging study. Neuroimage Clin 2022; 36:103201. [PMID: 36126518 PMCID: PMC9486670 DOI: 10.1016/j.nicl.2022.103201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 12/14/2022]
Abstract
This study aimed to evaluate the use of diffusion kurtosis imaging (DKI) to detect microstructural abnormalities within the temporal pole (TP) and its temporopolar cortex in temporal lobe epilepsy (TLE) patients. DKI quantitative maps were obtained from fourteen lesional TLE and ten non-lesional TLE patients, along with twenty-three healthy controls. Data collected included mean (MK); radial (RK) and axial kurtosis (AK); mean diffusivity (MD) and axonal water fraction (AWF). Automated fiber quantification (AFQ) was used to quantify DKI measurements along the inferior longitudinal (ILF) and uncinate fasciculus (Unc). ILF and Unc tract profiles were compared between groups and tested for correlation with disease duration. To characterize temporopolar cortex microstructure, DKI maps were sampled at varying depths from superficial white matter (WM) towards the pial surface. Patients were separated according to the temporal lobe ipsilateral to seizure onset and their AFQ results were used as input for statistical analyses. Significant differences were observed between lesional TLE and controls, towards the most temporopolar segment of ILF and Unc proximal to the TP within the ipsilateral temporal lobe in left TLE patients for MK, RK, AWF and MD. No significant changes were observed with DKI maps in the non-lesional TLE group. DKI measurements correlated with disease duration, mostly towards the temporopolar segments of the WM bundles. Stronger differences in MK, RK and AWF within the temporopolar cortex were observed in the lesional TLE and noticeable differences (except for MD) in non-lesional TLE groups compared to controls. This study demonstrates that DKI has potential to detect subtle microstructural alterations within the temporopolar segments of the ILF and Unc and the connected temporopolar cortex in TLE patients including non-lesional TLE subjects. This could aid our understanding of the extrahippocampal areas, more specifically the temporal pole role in seizure generation in TLE and might inform surgical planning, leading to better seizure outcomes.
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Affiliation(s)
- Loxlan W Kasa
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; School of Biomedical Engineering, Western University, London, Ontario, Canada
| | - Terry Peters
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; School of Biomedical Engineering, Western University, London, Ontario, Canada; Department of Medical Biophysics, Western University, London, Ontario, Canada; Department of Medical Imaging, Western University, London, Ontario, Canada
| | - Seyed M Mirsattari
- Department of Medical Biophysics, Western University, London, Ontario, Canada; Department of Medical Imaging, Western University, London, Ontario, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario, Canada; Department of Psychology, Western University, London, Ontario, Canada
| | - Michael T Jurkiewicz
- Department of Medical Biophysics, Western University, London, Ontario, Canada; Department of Medical Imaging, Western University, London, Ontario, Canada; Department of Clinical Neurological Sciences, Western University, London, Ontario, Canada
| | - Ali R Khan
- Imaging Research Laboratories, Robarts Research Institute, London, Ontario, Canada; School of Biomedical Engineering, Western University, London, Ontario, Canada; Department of Medical Biophysics, Western University, London, Ontario, Canada; Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario, Canada.
| | - Roy A M Haast
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Western University, London, Ontario, Canada
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Lam K, Nguyen PT, Anh LV, Lien T. Blended Motor-Sensory Nerve Bundles on Diffused Tensor Imaging: Evidence of Brain Plasticity in a Patient with 36-year Sequelae from Encephalitis. Open Access Maced J Med Sci 2022. [DOI: 10.3889/oamjms.2022.8643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND: Brain plasticity refers to the extraordinary ability of the brain to modify its structure and function following changes within the body or in the external environment. However, it is not easy to find it on non-invasive imaging modality.
CASE REPORT: In this article, we report the case of a 36-year-old male patient with sequelae of encephalitis. The patient had general epilepsy with multiple hospital admissions. MRI 3.0 Tesla showed his cerebral hemispheres were asymmetrical both morphologically and tractographically; there was a scar at the right temporo-occipital region, and an atrophy of the right temporal lobe, hippocampus and pontine. DTI reconstruction showed asymmetrical cortico-spinal and thalamo-cortical tracts with posterior thalamo-cortical tract was partly damaged by the scar. Blended motor-sensory nerve bundles were observed only on the left side of the patient’s brain but not on the right or healthy subjects. DTI quantification showed the lower line number, lower FA and higher ADC in the patient compared to healthy subjects and within the patient with decreased functionality on the side of the scar.
CONCLUSION: Non-invasive DTI with 3D image reconstruction on the patient showed evidence of brain plasticity appeared on cortico-spinal and thalamo-cortical tracts and can inform diagnosis and treatment strategies.
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Diaz AP, Fernandes BS, Teixeira AL, Mwangi B, Hasan KM, Wu MJ, Selvaraj S, Suen P, Zanao TA, Brunoni AR, Sanches M, Soares JC. White matter microstructure associated with anhedonia among individuals with bipolar disorders and high-risk for bipolar disorders. J Affect Disord 2022; 300:91-98. [PMID: 34936916 PMCID: PMC8828704 DOI: 10.1016/j.jad.2021.12.037] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 12/09/2021] [Accepted: 12/17/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND Anhedonia - a key symptom of depression - is highly associated with poorer outcomes and suicidal behavior. Alterations in the circuitry of reward-related brain regions have been robustly associated with anhedonia in unipolar depression, but not bipolar disorder (BD). We investigated white matter microstructures associated with anhedonia in participants with BD types I and II and first-degree relatives of patients with BD (BD-siblings). METHODS Eighty participants (BD types I and II: 56 [70%], and BD-siblings: 24 [30%]) underwent diffusion tensor imaging (DTI); Fractional anisotropy (FA) of different tracts were computed. Anhedonia was assessed using item 8, ("inability to feel'') of the MADRS scale. General linear models were used to compare the FA of different tracts in participants with and without anhedonia controlling for several clinical and demographic variables. RESULTS The mean age of the sample was 37 (± 11) years old, and 68.8% were female. Participants with anhedonia (32.5%) presented lower mean FA in the left uncinate fasciculus (UF) (p = 0.005), right temporal endings of the superior longitudinal fasciculus (SLFT) (p = 0.04), and in the left and right parietal endings of the superior longitudinal fasciculus (SLFP) (p = 0.003, and p = 0.04, respectively). Similar comparisons between participants with or without current depressive episodes and between participants with or without inner tension according to the MADRS did not show significant differences, specificity of the findings for anhedonia. CONCLUSIONS Lower FA in the left UF and SLF are potential neuroimaging markers of anhedonia in individuals with BD and high-risk for BD.
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Affiliation(s)
- Alexandre Paim Diaz
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, 1941 East Road, Suite 3130, Houston, TX 77054, United States.
| | - Brisa S. Fernandes
- The University of Texas Health Science Center at Houston, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, Houston, Texas
| | - Antonio Lucio Teixeira
- The University of Texas Health Science Center at Houston, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, Houston, Texas
| | - Benson Mwangi
- The University of Texas Health Science Center at Houston, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, Houston, Texas
| | - Khader M. Hasan
- The University of Texas Health Science Center at Houston, Department of Diagnostic and Interventional Imaging, Diffusion MRI Research Lab, Houston, Texas
| | - Mon-Ju Wu
- The University of Texas Health Science Center at Houston, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, Houston, Texas
| | - Sudhakar Selvaraj
- The University of Texas Health Science Center at Houston, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, Houston, Texas
| | - Paulo Suen
- Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Laboratory of Neurosciences (LIM-27), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Tamires Araujo Zanao
- Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Laboratory of Neurosciences (LIM-27), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Andre R. Brunoni
- Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Laboratory of Neurosciences (LIM-27), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Marsal Sanches
- The University of Texas Health Science Center at Houston, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, Houston, Texas
| | - Jair C. Soares
- The University of Texas Health Science Center at Houston, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, Houston, Texas
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Gharaylou Z, Sahraian MA, Hadjighassem M, Kohanpour M, Doosti R, Nahardani S, Moghadasi AN. Widespread Disruptions of White Matter in Familial Multiple Sclerosis: DTI and NODDI Study. Front Neurol 2021; 12:678245. [PMID: 34484098 PMCID: PMC8415561 DOI: 10.3389/fneur.2021.678245] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 06/14/2021] [Indexed: 11/29/2022] Open
Abstract
Diffusion tensor imaging (DTI) is a noninvasive, quantitative MRI technique that measures white matter (WM) integrity. Many brain dimensions are heritable, including white matter integrity measured with DTI. Family studies are valuable to provide insights into the interactive effects of non-environmental factors on multiple sclerosis (MS). To examine the contribution of familial factors to the diffusion signals across WM microstructure, we performed DTI and calculated neurite orientation dispersion plus density imaging (NODDI) diffusion parameters in two patient groups comprising familial and sporadic forms of multiple sclerosis and their unaffected relatives. We divided 111 subjects (49 men and 62 women: age range 19-60) into three groups conforming to their MS history. The familial MS group included 30 participants (patients; n = 16, healthy relatives; n = 14). The sporadic group included 41 participants (patients; n = 10, healthy relatives; n = 31). Forty age-matched subjects with no history of MS in their families were defined as the control group. To study white matter integrity, two methods were employed: one for calculating the mean of DTI, FA, and MD parameters on 18 tracts using Tracts Constrained by Underlying Anatomy (TRACULA) and the other for whole brain voxel-based analysis using tract-based spatial statistics (TBSS) on NDI and ODI parameters derived from NODDI and DTI parameters. Voxel-based analysis showed considerable changes in FA, MD, NDI, and ODI in the familial group when compared with the control group, reflecting widespread impairment of white matter in this group. The analysis of 18 tracts with TRACULA revealed increased MD and FA reduction in more tracts (left and right ILF, UNC, and SLFT, forceps major and minor) in familial MS patients vs. the control group. There were no significant differences between the patient groups. We found no consequential changes in healthy relatives of both patient groups in voxel-based and tract analyses. Considering the multifactorial etiology of MS, familial studies are of great importance to clarify the effects of certain predisposing factors on demyelinating brain pathology.
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Affiliation(s)
- Zeinab Gharaylou
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ali Sahraian
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mahmoudreza Hadjighassem
- Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Kohanpour
- Neuroimaging and Analysis Group (NIAG), Research Center for Molecular and Cellular Imaging, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Rozita Doosti
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shima Nahardani
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Abdorreza Naser Moghadasi
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
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Chen X, Wang Y, Kopetzky SJ, Butz-Ostendorf M, Kaiser M. Connectivity within regions characterizes epilepsy duration and treatment outcome. Hum Brain Mapp 2021; 42:3777-3791. [PMID: 33973688 PMCID: PMC8288103 DOI: 10.1002/hbm.25464] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 04/13/2021] [Accepted: 04/26/2021] [Indexed: 11/11/2022] Open
Abstract
Finding clear connectome biomarkers for temporal lobe epilepsy (TLE) patients, in particular at early disease stages, remains a challenge. Currently, the whole-brain structural connectomes are analyzed based on coarse parcellations (up to 1,000 nodes). However, such global parcellation-based connectomes may be unsuitable for detecting more localized changes in patients. Here, we use a high-resolution network (~50,000-nodes overall) to identify changes at the local level (within brain regions) and test its relation with duration and surgical outcome. Patients with TLE (n = 33) and age-, sex-matched healthy subjects (n = 36) underwent high-resolution (~50,000 nodes) structural network construction based on deterministic tracking of diffusion tensor imaging. Nodes were allocated to 68 cortical regions according to the Desikan-Killany atlas. The connectivity within regions was then used to predict surgical outcome. MRI processing, network reconstruction, and visualization of network changes were integrated into the NICARA (https://nicara.eu). Lower clustering coefficient and higher edge density were found for local connectivity within regions in patients, but were absent for the global network between regions (68 cortical regions). Local connectivity changes, in terms of the number of changed regions and the magnitude of changes, increased with disease duration. Local connectivity yielded a better surgical outcome prediction (Mean value: 95.39% accuracy, 92.76% sensitivity, and 100% specificity) than global connectivity. Connectivity within regions, compared to structural connectivity between brain regions, can be a more efficient biomarker for epilepsy assessment and surgery outcome prediction of medically intractable TLE.
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Affiliation(s)
- Xue Chen
- College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China.,School of Computing, Newcastle University, Newcastle upon Tyne, UK
| | - Yanjiang Wang
- College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China
| | - Sebastian J Kopetzky
- Biomax Informatics AG, Brain Science, Planegg, Germany.,TUM School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany
| | | | - Marcus Kaiser
- School of Computing, Newcastle University, Newcastle upon Tyne, UK.,NIHR Nottingham Biomedical Research Centre, School of Medicine, University of Nottingham, Nottingham, UK.,Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK.,School of Medicine, Shanghai Jiao Tong University, Shanghai, China
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11
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Owen TW, de Tisi J, Vos SB, Winston GP, Duncan JS, Wang Y, Taylor PN. Multivariate white matter alterations are associated with epilepsy duration. Eur J Neurosci 2021; 53:2788-2803. [PMID: 33222308 PMCID: PMC8246988 DOI: 10.1111/ejn.15055] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 11/12/2020] [Accepted: 11/15/2020] [Indexed: 01/08/2023]
Abstract
Previous studies investigating associations between white matter alterations and duration of temporal lobe epilepsy (TLE) have shown differing results, and were typically limited to univariate analyses of tracts in isolation. In this study, we apply a multivariate measure (the Mahalanobis distance), which captures the distinct ways white matter may differ in individual patients, and relate this to epilepsy duration. Diffusion MRI, from a cohort of 94 subjects (28 healthy controls, 33 left-TLE and 33 right-TLE), was used to assess the association between tract fractional anisotropy (FA) and epilepsy duration. Using ten white matter tracts, we analysed associations using the traditional univariate analysis (z-scores) and a complementary multivariate approach (Mahalanobis distance), incorporating multiple white matter tracts into a single unified analysis. For patients with right-TLE, FA was not significantly associated with epilepsy duration for any tract studied in isolation. For patients with left-TLE, the FA of two limbic tracts (ipsilateral fornix, contralateral cingulum gyrus) were significantly negatively associated with epilepsy duration (Bonferonni corrected p < .05). Using a multivariate approach we found significant ipsilateral positive associations with duration in both left, and right-TLE cohorts (left-TLE: Spearman's ρ = 0.487, right-TLE: Spearman's ρ = 0.422). Extrapolating our multivariate results to duration equals zero (i.e., at onset) we found no significant difference between patients and controls. Associations using the multivariate approach were more robust than univariate methods. The multivariate Mahalanobis distance measure provides non-overlapping and more robust results than traditional univariate analyses. Future studies should consider adopting both frameworks into their analysis in order to ascertain a more complete understanding of epilepsy progression, regardless of laterality.
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Affiliation(s)
- Thomas W. Owen
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems GroupSchool of ComputingNewcastle UniversityNewcastle upon TyneUK
| | - Jane de Tisi
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
| | - Sjoerd B. Vos
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- Epilepsy Society MRI UnitChalfont St PeterUK
- Neuroradiological Academic UnitUCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Gavin P. Winston
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
- Epilepsy Society MRI UnitChalfont St PeterUK
- Department of MedicineDivision of NeurologyQueen's UniversityKingstonCanada
| | - John S Duncan
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
- Epilepsy Society MRI UnitChalfont St PeterUK
| | - Yujiang Wang
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems GroupSchool of ComputingNewcastle UniversityNewcastle upon TyneUK
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Peter N. Taylor
- CNNP Lab, Interdisciplinary Computing and Complex BioSystems GroupSchool of ComputingNewcastle UniversityNewcastle upon TyneUK
- NIHR University College London Hospitals Biomedical Research CentreUCL Institute of NeurologyQueen SquareLondonUK
- Faculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
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12
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Bryant L, McKinnon ET, Taylor JA, Jensen JH, Bonilha L, de Bezenac C, Kreilkamp BAK, Adan G, Wieshmann UC, Biswas S, Marson AG, Keller SS. Fiber ball white matter modeling in focal epilepsy. Hum Brain Mapp 2021; 42:2490-2507. [PMID: 33605514 PMCID: PMC8090772 DOI: 10.1002/hbm.25382] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 02/09/2021] [Accepted: 02/10/2021] [Indexed: 12/15/2022] Open
Abstract
Multicompartment diffusion magnetic resonance imaging (MRI) approaches are increasingly being applied to estimate intra‐axonal and extra‐axonal diffusion characteristics in the human brain. Fiber ball imaging (FBI) and its extension fiber ball white matter modeling (FBWM) are such recently described multicompartment approaches. However, these particular approaches have yet to be applied in clinical cohorts. The modeling of several diffusion parameters with interpretable biological meaning may offer the development of new, noninvasive biomarkers of pharmacoresistance in epilepsy. In the present study, we used FBI and FBWM to evaluate intra‐axonal and extra‐axonal diffusion properties of white matter tracts in patients with longstanding focal epilepsy. FBI/FBWM diffusion parameters were calculated along the length of 50 white matter tract bundles and statistically compared between patients with refractory epilepsy, nonrefractory epilepsy and controls. We report that patients with chronic epilepsy had a widespread distribution of extra‐axonal diffusivity relative to controls, particularly in circumscribed regions along white matter tracts projecting to cerebral cortex from thalamic, striatal, brainstem, and peduncular regions. Patients with refractory epilepsy had significantly greater markers of extra‐axonal diffusivity compared to those with nonrefractory epilepsy. The extra‐axonal diffusivity alterations in patients with epilepsy observed in the present study could be markers of neuroinflammatory processes or a reflection of reduced axonal density, both of which have been histologically demonstrated in focal epilepsy. FBI is a clinically feasible MRI approach that provides the basis for more interpretive conclusions about the microstructural environment of the brain and may represent a unique biomarker of pharmacoresistance in epilepsy.
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Affiliation(s)
- Lorna Bryant
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, UK
| | - Emilie T McKinnon
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, USA
| | - James A Taylor
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Jens H Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, South Carolina, USA.,Department of Neuroscience, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Christophe de Bezenac
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, UK
| | - Barbara A K Kreilkamp
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, UK.,Department of Clinical Neurophysiology, University Medicine Göttingen, Göttingen, Germany
| | - Guleed Adan
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, UK.,The Walton Centre NHS Foundation Trust, Liverpool, UK
| | | | | | - Anthony G Marson
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, UK.,The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Simon S Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, UK.,The Walton Centre NHS Foundation Trust, Liverpool, UK
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13
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Sanjari Moghaddam H, Rahmani F, Aarabi MH, Nazem-Zadeh MR, Davoodi-Bojd E, Soltanian-Zadeh H. White matter microstructural differences between right and left mesial temporal lobe epilepsy. Acta Neurol Belg 2020; 120:1323-1331. [PMID: 30635771 DOI: 10.1007/s13760-019-01074-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Accepted: 01/05/2019] [Indexed: 01/20/2023]
Abstract
PURPOSE Mesial temporal lobe epilepsy (mTLE) is a chronic focal epileptic disorder characterized by recalcitrant seizures often necessitating surgical intervention. Identifying the laterality of seizure focus is crucial for pre-surgical planning. We implemented diffusion MRI (DMRI) connectometry to identify differences in white matter connectivity in patients with left and right mTLE relative to healthy control subjects. METHOD We enrolled 12 patients with right mTLE, 12 patients with left mTLE, and 12 age/sex matched healthy controls (HCs). We used DMRI connectometry to identify local connectivity patterns of white matter tracts, based on quantitative anisotropy (QA). We compared QA of white matter to reconstruct tracts with significant difference in connectivity between patients and HCs and then between patients with left and right mTLE. RESULTS Right mTLE patients show higher anisotropy in left inferior longitudinal fasciculus (ILF) and forceps minor and lower QA in genu of corpus callosum (CC), bilateral corticospinal tracts (CSTs), and bilateral middle cerebellar peduncles (MCPs) compared to HCs. Left mTLE patients show higher anisotropy in genu of CC, bilateral CSTs, and right MCP and decreased anisotropy in forceps minor compared to HCs. Compared to patients with right mTLE, left mTLE patients showed increased and decreased connectivity in some major tracts. CONCLUSIONS Our study showed the pattern of microstructural disintegrity in mTLE patients relative to HCs. We demonstrated that left and right mTLE patients have discrepant alternations in their white matter microstructure. These results may indicate that left and right mTLE have different underlying pathologic mechanisms.
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Affiliation(s)
| | - Farzaneh Rahmani
- NeuroImaging Network (NIN), Universal Scientific Education and Research Network (USERN), Tehran, Iran
- Student's Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
| | | | - Mohammad-Reza Nazem-Zadeh
- Research Center for Science and Technology in Medicine (RCSTIM), Tehran University of Medical Sciences, Tehran, Iran
| | - Esmaeil Davoodi-Bojd
- Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, One Ford Place, 2F, Detroit, MI, 48202, USA
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, North Kargar Ave., Tehran, Iran.
- Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, One Ford Place, 2F, Detroit, MI, 48202, USA.
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14
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Zhi D, Wu W, Xiao B, Qi S, Jiang R, Yang X, Yang J, Xiao W, Liu C, Long H, Calhoun VD, Long L, Sui J. NR4A1 Methylation Associated Multimodal Neuroimaging Patterns Impaired in Temporal Lobe Epilepsy. Front Neurosci 2020; 14:727. [PMID: 32760244 PMCID: PMC7372187 DOI: 10.3389/fnins.2020.00727] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Accepted: 06/18/2020] [Indexed: 11/25/2022] Open
Abstract
DNA hypermethylation has been widely observed in temporal lobe epilepsy (TLE), in which NR4A1 knockdown has been reported to be able to alleviate seizure severity in mouse model, while the underlying methylation-imaging pathway modulated by aberrant methylation levels of NR4A1 remains to be clarified in patients with TLE. Here, using multi-site canonical correlation analysis with reference, methylation levels of NR4A1 in blood were used as priori to guide fusion of three MRI features: functional connectivity (FC), fractional anisotropy (FA), and gray matter volume (GMV) for 56 TLE patients and 65 healthy controls. Post-hoc correlations were further evaluated between the identified NR4A1-associated brain components and disease onset. Results suggested that higher NR4A1 methylation levels in TLE were related with impaired temporal-cerebellar and occipital-cerebellar FC strength, lower FA in cingulum (hippocampus), and reduced GMV in putamen, temporal pole, and cerebellum. Moreover, findings were also replicated well in both patient subsets with either right TLE or left TLE only. Particularly, right TLE patients showed poorer cognitive abilities and more severe brain impairment than left TLE patients, especially more reduced GMV in thalamus. In summary, this work revealed a potential imaging-methylation pathway modulated by higher NR4A1 methylation in TLE via data mining, which may impact the above-mentioned multimodal brain circuits and was also associated with earlier disease onset and more cognitive deficits.
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Affiliation(s)
- Dongmei Zhi
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Wenyue Wu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,Department of Neurology, The Second Affiliated Hospital, Nanchang University, Nanchang, China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Shile Qi
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University - Emory University, Atlanta, GA, United States
| | - Rongtao Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Xingdong Yang
- Department of Neurology, Beijing Haidian Hospital, Beijing, China
| | - Jian Yang
- Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, China
| | - Wenbiao Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Chaorong Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Hongyu Long
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University - Emory University, Atlanta, GA, United States
| | - Lili Long
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Jing Sui
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China.,Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University - Emory University, Atlanta, GA, United States.,CAS Centre for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing, China
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15
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Kreilkamp BAK, Lisanti L, Glenn GR, Wieshmann UC, Das K, Marson AG, Keller SS. Comparison of manual and automated fiber quantification tractography in patients with temporal lobe epilepsy. NEUROIMAGE-CLINICAL 2019; 24:102024. [PMID: 31670154 PMCID: PMC6831895 DOI: 10.1016/j.nicl.2019.102024] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Revised: 09/05/2019] [Accepted: 09/27/2019] [Indexed: 11/25/2022]
Abstract
Tractography approaches showed moderate to good agreement for tract morphology. Along- and whole-tract diffusivity was significantly correlated across approaches. Whole-tract AFQ but not manual tract diffusivity correlated with clinical variables. Absence of excellent agreement between approaches warrants caution.
Objective To investigate the agreement between manually and automatically generated tracts from diffusion tensor imaging (DTI) in patients with temporal lobe epilepsy (TLE). Whole and along-the-tract diffusivity metrics and correlations with patient clinical characteristics were analyzed with respect to tractography approach. Methods We recruited 40 healthy controls and 24 patients with TLE who underwent conventional T1-weighted imaging and 60-direction DTI. An automated (Automated Fiber Quantification, AFQ) and manual (TrackVis) deterministic tractography approach was used to identify the uncinate fasciculus (UF) and parahippocampal white matter bundle (PHWM). Tract diffusion scalar metrics were analyzed with respect to agreement across automated and manual approaches (Dice Coefficient and Spearman correlations), to side of onset of epilepsy and patient clinical characteristics, including duration of epilepsy, age of onset and presence of hippocampal sclerosis. Results Across approaches the analysis of tract morphology similarity revealed Dice coefficients at moderate to good agreement (0.54 - 0.6) and significant correlations between diffusion values (Spearman's Rho=0.4–0.9). However, within bilateral PHWM, AFQ yielded significantly lower FA (left: Z = 4.4, p<0.001; right: Z = 5.1, p<0.001) and higher MD values (left: Z=-4.7, p<0.001; right: Z=-3.7, p<0.001) compared to the manual approach. Whole tract DTI metrics determined using AFQ were significantly correlated with patient characteristics, including age of epilepsy onset in FA (R = 0.6, p = 0.02) and MD of the ipsilateral PHWM (R=-0.6, p = 0.02), while duration of epilepsy corrected for age correlated with MD in ipsilateral PHWM (R = 0.7, p<0.01). Correlations between clinical metrics and diffusion values extracted using the manual whole tract technique did not survive correction for multiple comparisons. Both manual and automated along-the-tract analyses demonstrated significant correlations with patient clinical characteristics such as age of onset and epilepsy duration. The strongest and most widespread localized ipsi- and contralateral diffusivity alterations were observed in patients with left TLE and patients with HS compared to controls, while patients with right TLE and patients without HS did not show these strong effects. Conclusions Manual and AFQ tractography approaches revealed significant correlations in the reconstruction of tract morphology and extracted whole and along-tract diffusivity values. However, as non-identical methods they differed in the respective yield of significant results across clinical correlations and group-wise statistics. Given the absence of excellent agreement between manual and AFQ techniques as demonstrated in the present study, caution should be considered when using AFQ particularly when used without reference to benchmark manual measures.
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Affiliation(s)
- Barbara A K Kreilkamp
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom; Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom.
| | - Lucy Lisanti
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom; Royal Society, London, United Kingdom
| | - G Russell Glenn
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States
| | - Udo C Wieshmann
- Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Kumar Das
- Department of Neuroradiology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Anthony G Marson
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom; Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Simon S Keller
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom; Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
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16
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de Bézenac C, Garcia-Finana M, Baker G, Moore P, Leek N, Mohanraj R, Bonilha L, Richardson M, Marson AG, Keller S. Investigating imaging network markers of cognitive dysfunction and pharmacoresistance in newly diagnosed epilepsy: a protocol for an observational cohort study in the UK. BMJ Open 2019; 9:e034347. [PMID: 31619436 PMCID: PMC6797398 DOI: 10.1136/bmjopen-2019-034347] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
INTRODUCTION Epilepsy is one of the most common serious brain disorders, characterised by seizures that severely affect a person's quality of life and, frequently, their cognitive and mental health. Although most existing work has examined chronic epilepsy, newly diagnosed patients present a unique opportunity to understand the underlying biology of epilepsy and predict effective treatment pathways. The objective of this prospective cohort study is to examine whether cognitive dysfunction is associated with measurable brain architectural and connectivity impairments at diagnosis and whether the outcome of antiepileptic drug treatment can be predicted using these measures. METHODS AND ANALYSIS 107 patients with newly diagnosed focal epilepsy from two National Health Service Trusts and 48 healthy controls (aged 16-65 years) will be recruited over a period of 30 months. Baseline assessments will include neuropsychological evaluation, structural and functional Magnetic Resonance Imaging (MRI), Electroencephalography (EEG), and a blood and saliva sample. Patients will be followed up every 6 months for a 24-month period to assess treatment outcomes. Connectivity- and network-based analyses of EEG and MRI data will be carried out and examined in relation to neuropsychological evaluation and patient treatment outcomes. Patient outcomes will also be investigated with respect to analysis of molecular isoforms of high mobility group box-1 from blood and saliva samples. ETHICS AND DISSEMINATION This study was approved by the North West, Liverpool East Research Ethics Committee (19/NW/0384) through the Integrated Research Application System (Project ID 260623). Health Research Authority (HRA) approval was provided on 22 August 2019. The project is sponsored by the UoL (UoL001449) and funded by a UK Medical Research Council (MRC) research grant (MR/S00355X/1). Findings will be presented at national and international meetings and conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER IRAS Project ID 260623.
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Affiliation(s)
- Christophe de Bézenac
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | | | - Gus Baker
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
- Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Perry Moore
- Department of Neurology, Salford Royal NHS Foundation Trust, Salford, UK
| | - Nicola Leek
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Rajiv Mohanraj
- Department of Neurology, Salford Royal NHS Foundation Trust, Salford, UK
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina, USA
| | - Mark Richardson
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Anthony Guy Marson
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
- Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Simon Keller
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, UK
- Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool, UK
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17
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Gharaylou Z, Shafaghi L, Oghabian MA, Yoonessi A, Tafakhori A, Shahsavand Ananloo E, Hadjighassem M. Longitudinal Effects of Bumetanide on Neuro-Cognitive Functioning in Drug-Resistant Epilepsy. Front Neurol 2019; 10:483. [PMID: 31133976 PMCID: PMC6517515 DOI: 10.3389/fneur.2019.00483] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 04/23/2019] [Indexed: 12/25/2022] Open
Abstract
Antiepileptic drugs (AEDs) have repeatedly shown inconsistent and almost contradictory effects on the neurocognitive system, from substantial impairments in processing speed to the noticeable improvement in working memory and executive functioning. Previous studies have provided a novel insight into the cognitive improvement by bumetanide as a potential antiepileptic drug. Through the current investigation, we evaluated the longitudinal effects of bumetanide, an NKCC1 co-transporter antagonist, on the brain microstructural organization as a probable underlying component for cognitive performance. Microstructure assessment was completed using SPM for the whole brain assay and Freesurfer/TRACULA for the automatic probabilistic tractography analysis. Primary cognitive operations including selective attention and processing speed, working memory capacity and spatial memory were evaluated in 12 patients with a confirmed diagnosis of refractory epilepsy. Participants treated with bumetanide (2 mg/ day) in two divided doses as an adjuvant therapy to their regular AEDs for 6 months, which followed by the re-assessment of their cognitive functions and microstructural organizations. Seizure frequency reduced in eight patients which accompanied by white matter reconstruction; fractional anisotropy (FA) increased in the cingulum-cingulate gyrus (CCG), anterior thalamic radiation (ATR), and temporal part of the superior longitudinal fasciculus (SLFt) in correlation with the clinical response. The voxel-based analysis in responder patients revealed increased FA in the left hippocampus, right cerebellum, and right medial temporal lobe, while mean diffusivity (MD) values reduced in the right occipital lobe and cerebellum. Microstructural changes in SLFt and ATR accompanied by a reduction in the error rate in the spatial memory test. These primary results have provided preliminary evidence for the effect of bumetanide on cognitive functioning through microstructural changes in patients with drug-resistant epilepsy.
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Affiliation(s)
- Zeinab Gharaylou
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Lida Shafaghi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Ali Oghabian
- Neuroimaging and Analysis Group, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Yoonessi
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Abbas Tafakhori
- Imam Khomeini Hospital, Iranian Center of Neurological Research, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Mahmoudreza Hadjighassem
- Department of Neuroscience and Addiction Studies, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran.,Brain and Spinal Cord Injury Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
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18
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Chong CD, Peplinski J, Berisha V, Ross K, Schwedt TJ. Differences in fibertract profiles between patients with migraine and those with persistent post-traumatic headache. Cephalalgia 2019; 39:1121-1133. [DOI: 10.1177/0333102418815650] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Objectives Often, persistent post-traumatic headache and migraine are phenotypically similar. However, the similarities and differences in the neuropathological underpinnings of persistent post-traumatic headache and migraine require further understanding. We used diffusion tensor imaging (DTI) and a novel method for detecting subtle changes in fibertract integrity by measuring node-by-node parameters along each tract to compare fibertract profiles between those with migraine and those with persistent post-traumatic headache, and compared both cohorts to a group of controls. Methods Eighteen fibertracts were reconstructed for 131 subjects, including 49 patients with persistent post-traumatic headache attributed to mild traumatic brain injury, 41 with migraine, and 41 controls. Node-by-node diffusion parameters of mean diffusivity and radial diffusivity were calculated along each tract. Mean diffusivity and radial diffusivity measurements were averaged along quartiles of each tract for statistical interpretation and group comparison. Using a post-hoc analysis, correlations between tract quartile measurements and headache frequency were calculated. Results There were significant differences between migraine and persistent post-traumatic headache cohorts for quartile measurements of mean diffusivity or radial diffusivity in the bilateral anterior thalamic radiations, cingulum (angular bundles and cingulate gyri), inferior longitudinal fasciculi, and uncinate fasciculi, the left corticospinal tract, and the right superior longitudinal fasciculi-parietal portion. For migraine patients, there was a significant positive correlation between headache frequency and forceps major mean diffusivity, whereas for persistent post-traumatic headache there was a positive correlation between headache frequency and cingulum angular bundle mean diffusivity and radial diffusivity. Conclusions Quartile measurements of radial diffusivity and mean diffusivity indicate unique differences in fibertract profiles between those with migraine vs. persistent post-traumatic headache. Although for both migraine and persistent post-traumatic headache there was a positive relationship between fibertract alterations and headache frequency, there were disease-specific differences between headache frequency and fibertract injury patterns. These findings might suggest potential differences in the neuropathological mechanisms underlying migraine and persistent post-traumatic headache.
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Affiliation(s)
| | - Jacob Peplinski
- School of Electrical, Computer and Energy Engineering and Department of Speech and Hearing Science, Arizona State University, Phoenix, AZ, USA
| | - Visar Berisha
- School of Electrical, Computer and Energy Engineering and Department of Speech and Hearing Science, Arizona State University, Phoenix, AZ, USA
| | - Katherine Ross
- Phoenix VA Health Care System, Audiology and Speech Pathology Service, Phoenix, AZ, USA
| | - Todd J Schwedt
- Mayo Clinic Department of Neurology, Mayo Clinic, Phoenix, AZ, USA
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White matter correlates of disease duration in patients with temporal lobe epilepsy: updated review of literature. Neurol Sci 2019; 40:1209-1216. [PMID: 30868482 DOI: 10.1007/s10072-019-03818-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Accepted: 02/27/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Medial temporal lobe epilepsy (mTLE) has been associated with widespread white mater (WM) alternations in addition to mesial temporal sclerosis (MTS). Herein, we aimed to investigate the correlation between disease duration and WM structural abnormalities in mTLE using diffusion MRI (DMRI) connectometry approach. METHOD DMRI connectometry was conducted on 24 patients with mTLE. A multiple regression model was used to investigate white matter tracts with microstructural correlates to disease duration, controlling for age and sex. DMRI data were processed in the MNI space using q-space diffeomorphic reconstruction to obtain the spin distribution function (SDF). The SDF values were converted to quantitative anisotropy (QA) and used in further analyses. RESULTS Connectometry analysis identified impaired white matter QA of the following fibers to be correlated with disease duration: bilateral retrosplenial cingulum, bilateral fornix, right inferior longitudinal fasciculus (ILF), and genu of corpus callosum (CC) (FDR = 0.009). CONCLUSION Our results were obtained from DMRI connectometry, which indicates the connectivity and the level of diffusion in nerve fibers rather just the direction of diffusion. Compared to previous studies investigating the correlation between duration of epilepsy and white matter integrity in mTLE patients, we detected broader and somewhat different associations in midline structures and component of limbic system. However, further studies with larger sample sizes are required to elucidate previous and current results.
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Bouwen BLJ, Pieterman KJ, Smits M, Dirven CMF, Gao Z, Vincent AJPE. The Impacts of Tumor and Tumor Associated Epilepsy on Subcortical Brain Structures and Long Distance Connectivity in Patients With Low Grade Glioma. Front Neurol 2018; 9:1004. [PMID: 30538668 PMCID: PMC6277571 DOI: 10.3389/fneur.2018.01004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 11/06/2018] [Indexed: 12/12/2022] Open
Abstract
Low grade gliomas in cerebral cortex often cause symptoms related to higher cerebral functions such as attention, memory and executive function before treatment is initiated. Interestingly, focal tumors residing in one cortical region can lead to a diverse range of symptoms, indicating that the impact of a tumor is extended to multiple brain regions. We hypothesize that the presence of focal glioma in the cerebral cortex leads to alterations of distant subcortical areas and essential white matter tracts. In this study, we analyzed diffusion tensor imaging scans in glioma patients to study the effect of glioma on subcortical gray matter nuclei and long-distance connectivity. We found that the caudate nucleus, putamen and thalamus were affected by cortical glioma, displaying both volumetric and diffusion alterations. The cerebellar cortex contralateral to the tumor side also showed significant volume decrease. Additionally, tractography of the cortico-striatal and cortico-thalamic projections shows similar diffusion alterations. Tumor associated epilepsy might be an important contributing factor to the found alterations. Our findings indeed confirm concurrent structural and connectivity abrasions of brain areas distant from brain tumor, and provide insights into the pathogenesis of diverse neurological symptoms in glioma patients.
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Affiliation(s)
- Bibi L J Bouwen
- Department of Neuroscience, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.,Department of Neurosurgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Kay J Pieterman
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Clemens M F Dirven
- Department of Neurosurgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Zhenyu Gao
- Department of Neuroscience, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Arnaud J P E Vincent
- Department of Neurosurgery, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
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Oishi K, Chang L, Huang H. Baby brain atlases. Neuroimage 2018; 185:865-880. [PMID: 29625234 DOI: 10.1016/j.neuroimage.2018.04.003] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2017] [Revised: 02/27/2018] [Accepted: 04/02/2018] [Indexed: 01/23/2023] Open
Abstract
The baby brain is constantly changing due to its active neurodevelopment, and research into the baby brain is one of the frontiers in neuroscience. To help guide neuroscientists and clinicians in their investigation of this frontier, maps of the baby brain, which contain a priori knowledge about neurodevelopment and anatomy, are essential. "Brain atlas" in this review refers to a 3D-brain image with a set of reference labels, such as a parcellation map, as the anatomical reference that guides the mapping of the brain. Recent advancements in scanners, sequences, and motion control methodologies enable the creation of various types of high-resolution baby brain atlases. What is becoming clear is that one atlas is not sufficient to characterize the existing knowledge about the anatomical variations, disease-related anatomical alterations, and the variations in time-dependent changes. In this review, the types and roles of the human baby brain MRI atlases that are currently available are described and discussed, and future directions in the field of developmental neuroscience and its clinical applications are proposed. The potential use of disease-based atlases to characterize clinically relevant information, such as clinical labels, in addition to conventional anatomical labels, is also discussed.
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Affiliation(s)
- Kenichi Oishi
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Linda Chang
- Departments of Diagnostic Radiology and Nuclear Medicine, and Neurology, University of Maryland School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Medicine, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Hao Huang
- Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
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