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Martins B, Baba MY, Dimateo EM, Costa LF, Camara AS, Lukasova K, Nucci MP. Investigating Dyslexia through Diffusion Tensor Imaging across Ages: A Systematic Review. Brain Sci 2024; 14:349. [PMID: 38672001 PMCID: PMC11047980 DOI: 10.3390/brainsci14040349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 03/17/2024] [Accepted: 03/28/2024] [Indexed: 04/28/2024] Open
Abstract
Dyslexia is a neurodevelopmental disorder that presents a deficit in accuracy and/or fluency while reading or spelling that is not expected given the level of cognitive functioning. Research indicates brain structural changes mainly in the left hemisphere, comprising arcuate fasciculus (AF) and corona radiata (CR). The purpose of this systematic review is to better understand the possible methods for analyzing Diffusion Tensor Imaging (DTI) data while accounting for the characteristics of dyslexia in the last decade of the literature. Among 124 articles screened from PubMed and Scopus, 49 met inclusion criteria, focusing on dyslexia without neurological or psychiatric comorbidities. Article selection involved paired evaluation, with a third reviewer resolving discrepancies. The selected articles were analyzed using two topics: (1) a demographic and cognitive assessment of the sample and (2) DTI acquisition and analysis. Predominantly, studies centered on English-speaking children with reading difficulties, with preserved non-verbal intelligence, attention, and memory, and deficits in reading tests, rapid automatic naming, and phonological awareness. Structural differences were found mainly in the left AF in all ages and in the bilateral superior longitudinal fasciculus for readers-children and adults. A better understanding of structural brain changes of dyslexia and neuroadaptations can be a guide for future interventions.
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Affiliation(s)
- Bruce Martins
- Laboratório de Investigação Médica em Neurorradiologia—LIM44—Hospital das Clínicas da Faculdade Medicina, Universidade de São Paulo, São Paulo 05403-000, Brazil; (B.M.); (M.Y.B.); (E.M.D.)
| | - Mariana Yumi Baba
- Laboratório de Investigação Médica em Neurorradiologia—LIM44—Hospital das Clínicas da Faculdade Medicina, Universidade de São Paulo, São Paulo 05403-000, Brazil; (B.M.); (M.Y.B.); (E.M.D.)
| | - Elisa Monteiro Dimateo
- Laboratório de Investigação Médica em Neurorradiologia—LIM44—Hospital das Clínicas da Faculdade Medicina, Universidade de São Paulo, São Paulo 05403-000, Brazil; (B.M.); (M.Y.B.); (E.M.D.)
| | - Leticia Fruchi Costa
- Centro de Matemática, Computação e Cognição (CMCC), Universidade Federal do ABC, Santo André 09210-580, Brazil; (L.F.C.); (A.S.C.); (K.L.)
| | - Aila Silveira Camara
- Centro de Matemática, Computação e Cognição (CMCC), Universidade Federal do ABC, Santo André 09210-580, Brazil; (L.F.C.); (A.S.C.); (K.L.)
| | - Katerina Lukasova
- Centro de Matemática, Computação e Cognição (CMCC), Universidade Federal do ABC, Santo André 09210-580, Brazil; (L.F.C.); (A.S.C.); (K.L.)
| | - Mariana Penteado Nucci
- Laboratório de Investigação Médica em Neurorradiologia—LIM44—Hospital das Clínicas da Faculdade Medicina, Universidade de São Paulo, São Paulo 05403-000, Brazil; (B.M.); (M.Y.B.); (E.M.D.)
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Zuo L, Tian T, Wang B, Gu H, Wang S. Microstructural white matter abnormalities in overactive bladder syndrome evaluation with diffusion kurtosis imaging tract-based spatial statistics analysis. World J Urol 2024; 42:36. [PMID: 38217714 DOI: 10.1007/s00345-023-04709-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 10/16/2023] [Indexed: 01/15/2024] Open
Abstract
PURPOSE This prospective study aimed to explore the microstructural alterations of the white matter in overactive bladder syndrome (OAB) using the Tract-based Spatial Statistics (TBSS) method of diffusion kurtosis imaging (DKI). METHODS A total of 30 patients were enrolled and compared with 30 controls. White matter (WM) status was assessed using tract-based spatial statistics for DKI. The differences in DKI-derived parameters, including kurtosis fractional anisotropy (KFA), fractional anisotropy (FA), mean kurtosis (MK), mean diffusivity (MD), radial kurtosis (RK), axial kurtosis (AK), axial diffusivity (AD), and radial diffusivity (RD), were compared between the two groups using the TBSS method. The correlation between the altered DKI-derived parameters and the (OABSS) scores was analyzed. A receiver operating characteristic curve (ROC) was used to evaluate the diagnostic performance of different white matter parameters. RESULTS As a result, compared with the HC group, the KFA, and FA values decreased significantly in the OAB group. Compared with the HC group, the MK and MD values increased significantly in the OAB group. The KFA values of the genu of corpus callosum (GCC) were significantly correlated with the OABSS scores (r = - 0.509; p = 0.004). The FA values of anterior corona radiata (ACR) were significantly correlated with OABSS scores (r = - 0.447; p = 0.013). The area under the ROC curve (AUC) for the genu of corpus callosum KFA values was higher than FA for the diagnosis of OAB patients. CONCLUSION DKI is a promising approach to the investigation of the pathophysiology of OAB and a potential biomarker for clinical diagnosis of OAB.
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Affiliation(s)
- Long Zuo
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China
| | - Tian Tian
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China
| | - Biao Wang
- Department of Urology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China
| | - Hua Gu
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China
| | - Shuangkun Wang
- Department of Radiology, Beijing Chao-Yang Hospital, Capital Medical University, 8 Gongren Tiyuchang Nanlu, Chaoyang District, Beijing, 100020, China.
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Rosemann S, Rauschecker JP. Increased fiber density of the fornix in patients with chronic tinnitus revealed by diffusion-weighted MRI. Front Neurosci 2023; 17:1293133. [PMID: 38192511 PMCID: PMC10773749 DOI: 10.3389/fnins.2023.1293133] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 12/05/2023] [Indexed: 01/10/2024] Open
Abstract
Up to 45% of the elderly population suffer from chronic tinnitus - the phantom perception of sound that is often perceived as ringing, whistling, or hissing "in the ear" without external stimulation. Previous research investigated white matter changes in tinnitus patients using diffusion-weighted magnetic resonance imaging (DWI) to assess measures such as fractional anisotropy (a measure of microstructural integrity of fiber tracts) or mean diffusivity (a measure for general water diffusion). However, findings overlap only minimally and are sometimes even contradictory. We here present the first study encompassing higher diffusion data that allow to focus on changes in tissue microstructure, such as number of axons (fiber density) and macroscopic alterations, including axon diameter, and a combination of both. In order to deal with the crossing-fibers problem, we applied a fixel-based analysis using a constrained spherical deconvolution signal modeling approach. We investigated differences between tinnitus patients and control participants as well as how cognitive abilities and tinnitus distress are related to changes in white matter morphology in chronic tinnitus. For that aim, 20 tinnitus patients and 20 control participants, matched in age, sex and whether they had hearing loss or not, underwent DWI, audiometric and cognitive assessments, and filled in questionnaires targeting anxiety and depression. Our results showed increased fiber density in the fornix in tinnitus patients compared to control participants. The observed changes might, reflect compensatory structural alterations related to the processing of negative emotions or maladaptive changes related to the reinforced learning of the chronic tinnitus sensation. Due to the low sample size, the study should be seen as a pilot study that motivates further research to investigate underlying white matter morphology alterations in tinnitus.
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Affiliation(s)
- Stephanie Rosemann
- Laboratory of Integrative Neuroscience and Cognition, Department of Neuroscience, Georgetown University Medical Center, Washington, DC, United States
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Hu R, Tan F, Chen W, Wu Y, Jiang Y, Du W, Zuo Y, Gao B, Song Q, Miao Y. Microstructure abnormalities of the diffusion quantities in children with attention-deficit/hyperactivity disorder: an AFQ and TBSS study. Front Psychiatry 2023; 14:1237113. [PMID: 37674550 PMCID: PMC10477457 DOI: 10.3389/fpsyt.2023.1237113] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/08/2023] [Indexed: 09/08/2023] Open
Abstract
Objective To explore the specific alterations of white matter microstructure in children with attention-deficit/hyperactivity disorder (ADHD) by automated fiber quantification (AFQ) and tract-based spatial statistics (TBSS), and to analyze the correlation between white matter abnormality and impairment of executive function. Methods In this prospective study, a total of twenty-seven patients diagnosed with ADHD (20 males, 7 females; mean age of 8.89 ± 1.67 years) and twenty-two healthy control (HC) individuals (11 males, 11 females, mean age of 9.82 ± 2.13 years) were included. All participants were scanned with diffusion kurtosis imaging (DKI) and assessed for executive functions. AFQ and TBSS analysis methods were used to investigate the white matter fiber impairment of ADHD patients, respectively. Axial diffusivity (AD), radial diffusivity (RD), mean diffusivity (MD) and fractional anisotropy (FA) of 17 fiber properties were calculated using the AFQ. The mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), mean diffusivity (MDDKI), axial diffusivity (ADDKI), radial diffusivity (RDDKI) and fractional anisotropy (FADKI) of DKI and AD, RD, MD, and FA of diffusion tensor imaging (DTI) assessed the integrity of the white matter based on TBSS. Partial correlation analyses were conducted to evaluate the correlation between white matter abnormalities and clinical test scores in ADHD while taking age, gender, and education years into account. The analyses were all family-wise error rate (FWE) corrected. Results ADHD patients performed worse on the Behavior Rating Inventory of Executive Function (BRIEF) test (p < 0.05). Minor variances existed in gender and age between ADHD and HC, but these variances did not yield statistically significant distinctions. There were no significant differences in TBSS for DKI and DTI parameters (p > 0.05, TFCE-corrected). Compared to HC volunteers, the mean AD value of right cingulum bundle (CB_R) fiber tract showed a significantly higher level in ADHD patients following the correction of FWE. As a result of the point-wise comparison between groups, significant alterations (FWE correction, p < 0.05) were mainly located in AD (nodes 36-38, nodes 83-97) and MD (nodes 92-95) of CB_R. There was no significant correlation between white matter diffusion parameters and clinical test scores in ADHD while taking age, gender, and education years into account. Conclusion The AFQ method can detect ADHD white matter abnormalities in a specific location with greater sensitivity, and the CB_R played a critical role. Our findings may be helpful in further studying the relationship between focal white matter abnormalities and ADHD.
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Affiliation(s)
- Rui Hu
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Fan Tan
- Department of Nuclear Medicine, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Wen Chen
- Department of Radiology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Yong Wu
- Department of Paediatrics, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Yuhan Jiang
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Wei Du
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yuchen Zuo
- Department of Paediatrics, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Bingbing Gao
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Qingwei Song
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Yanwei Miao
- Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, China
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Grant M, Liu J, Wintermark M, Bagci U, Douglas D. Current State of Diffusion-Weighted Imaging and Diffusion Tensor Imaging for Traumatic Brain Injury Prognostication. Neuroimaging Clin N Am 2023; 33:279-297. [PMID: 36965946 DOI: 10.1016/j.nic.2023.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2023]
Abstract
Advanced imaging techniques are needed to assist in providing a prognosis for patients with traumatic brain injury (TBI), particularly mild TBI (mTBI). Diffusion tensor imaging (DTI) is one promising advanced imaging technique, but has shown variable results in patients with TBI and is not without limitations, especially when considering individual patients. Efforts to resolve these limitations are being explored and include developing advanced diffusion techniques, creating a normative database, improving study design, and testing machine learning algorithms. This article will review the fundamentals of DTI, providing an overview of the current state of its utility in evaluating and providing prognosis in patients with TBI.
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Affiliation(s)
- Matthew Grant
- Department of Radiology, Stanford University, 453 Quarry Road, Palo Alto, CA 94304, USA; Department of Radiology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Rd, Bethesda, MD 20814, USA; Department of Radiology, Landstuhl Regional Medical Center, Dr Hitzelberger Straße, 66849 Landstuhl, Germany.
| | - JiaJing Liu
- Department of Radiology, Stanford University, 453 Quarry Road, Palo Alto, CA 94304, USA
| | - Max Wintermark
- Department of Radiology, Stanford University, 453 Quarry Road, Palo Alto, CA 94304, USA; Neuroradiology Department, The University of Texas Anderson Cancer Center, 1400 Pressler Street, Unit 1482, Houston, TX 77030, USA
| | - Ulas Bagci
- Radiology and Biomedical Engineering Department, Northwestern University, 737 North Michigan Drive, Suite 1600, Chicago, IL 60611, USA; Department of Computer Science, University of Central Florida, 4328 Scorpius Street, Orlando, Florida, 32816
| | - David Douglas
- Department of Radiology, Stanford University, 453 Quarry Road, Palo Alto, CA 94304, USA; Department of Radiology, 96th Medical Group, Eglin Air Force Base, 307 Boatner Road, Eglin Air Force Base, Florida 32542, USA
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Li Y, Wen H, Li H, Peng Y, Tai J, Bai J, Mei L, Ji T, Li X, Liu Y, Ni X. Characterisation of brain microstructural alterations in children with obstructive sleep apnea syndrome using diffusion kurtosis imaging. J Sleep Res 2023; 32:e13710. [PMID: 36377256 DOI: 10.1111/jsr.13710] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 07/10/2022] [Accepted: 07/20/2022] [Indexed: 11/16/2022]
Abstract
Obstructive sleep apnea (OSA) is a common chronic sleep-related breathing disorder in children. Previous studies showed widespread alterations in white matter (WM) in children with OSA mainly by using diffusion tensor imaging (DTI), while diffusional kurtosis imaging (DKI) extended DTI and exhibited improved sensitivity in detecting developmental and pathological changes in neural tissues. Therefore, we conducted whole-brain DTI and DKI analyses and compared the differences in kurtosis and diffusion parameters within the skeleton between 41 children with OSA and 32 healthy children. Between-group differences were evaluated by tract-based spatial statistics (TBSS) analysis (p < 0.05, TFCE corrected), and partial correlations between DKI metrics and sleep parameters were assessed considering age and gender as covariates. Compared with the controls, children with OSA showed significantly decreased kurtosis fractional anisotropy (KFA) mainly in white matter regions with a complex fibre arrangement including the posterior corona radiate (PCR), superior longitudinal fasciculus (SLF), and inferior fronto-occipital fasciculus (IFOF), while decreased FA in white matter regions with a coherent fibre arrangement including the posterior limb of internal capsule (PLIC), anterior thalamic radiation (ATR), and corpus callosum (CC). Notably, the receiver operating characteristic (ROC) curve analysis demonstrated the KFA value in complex tissue regions significantly (p < 0.001) differentiated children with OSA from the controls. In addition, the KFA value in the left PCR, SLF, and IFOF showed significant partial correlations to the sleep parameters for children with OSA. Combining DKI derived kurtosis and diffusion parameters can provide complementary neuroimaging biomarkers for assessing white matter alterations, and reveal pathological changes and monitor disease progression in paediatric OSA.
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Affiliation(s)
- Yanhua Li
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Hongwei Wen
- Faculty of Psychology, Southwest University, Chongqing, China.,Key Laboratory of Cognition and Personality (Ministry of Education), Chongqing, China
| | - Hongbin Li
- Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Yun Peng
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Jun Tai
- Department of Otolaryngology, Head and Neck Surgery, Capital Institute of Pediatrics, Beijing, China
| | - Jie Bai
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Lin Mei
- Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Tingting Ji
- Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Xiaodan Li
- Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Yue Liu
- Department of Radiology, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
| | - Xin Ni
- Department of Otolaryngology, Head and Neck Surgery, Beijing Children's Hospital, Capital Medical University, National Centre for Children's Health, Beijing, China
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Subramanyam Rallabandi V, Seetharaman K. Classification of cognitively normal controls, mild cognitive impairment and Alzheimer’s disease using transfer learning approach. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
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Afzali M, Pieciak T, Jones DK, Schneider JE, Özarslan E. Cumulant expansion with localization: A new representation of the diffusion MRI signal. FRONTIERS IN NEUROIMAGING 2022; 1:958680. [PMID: 37555138 PMCID: PMC10406302 DOI: 10.3389/fnimg.2022.958680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 07/19/2022] [Indexed: 08/10/2023]
Abstract
Diffusion MR is sensitive to the microstructural features of a sample. Fine-scale characteristics can be probed by employing strong diffusion gradients while the low b-value regime is determined by the cumulants of the distribution of particle displacements. A signal representation based on the cumulants, however, suffers from a finite convergence radius and cannot represent the 'localization regime' characterized by a stretched exponential decay that emerges at large gradient strengths. Here, we propose a new representation for the diffusion MR signal. Our method provides not only a robust estimate of the first three cumulants but also a meaningful extrapolation of the entire signal decay.
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Affiliation(s)
- Maryam Afzali
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Tomasz Pieciak
- LPI, ETSI Telecomunicación, Universidad de Valladolid, Valladolid, Spain
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Jürgen E. Schneider
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom
| | - Evren Özarslan
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
- Center for Medical Image Science and Visualization, Linköping University, Linköping, Sweden
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Bouchard HC, Sun D, Dennis EL, Newsome MR, Disner SG, Elman J, Silva A, Velez C, Irimia A, Davenport ND, Sponheim SR, Franz CE, Kremen WS, Coleman MJ, Williams MW, Geuze E, Koerte IK, Shenton ME, Adamson MM, Coimbra R, Grant G, Shutter L, George MS, Zafonte RD, McAllister TW, Stein MB, Thompson PM, Wilde EA, Tate DF, Sotiras A, Morey RA. Age-dependent white matter disruptions after military traumatic brain injury: Multivariate analysis results from ENIGMA brain injury. Hum Brain Mapp 2022; 43:2653-2667. [PMID: 35289463 PMCID: PMC9057089 DOI: 10.1002/hbm.25811] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 12/18/2021] [Accepted: 02/10/2022] [Indexed: 01/27/2023] Open
Abstract
Mild Traumatic brain injury (mTBI) is a signature wound in military personnel, and repetitive mTBI has been linked to age-related neurogenerative disorders that affect white matter (WM) in the brain. However, findings of injury to specific WM tracts have been variable and inconsistent. This may be due to the heterogeneity of mechanisms, etiology, and comorbid disorders related to mTBI. Non-negative matrix factorization (NMF) is a data-driven approach that detects covarying patterns (components) within high-dimensional data. We applied NMF to diffusion imaging data from military Veterans with and without a self-reported TBI history. NMF identified 12 independent components derived from fractional anisotropy (FA) in a large dataset (n = 1,475) gathered through the ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) Military Brain Injury working group. Regressions were used to examine TBI- and mTBI-related associations in NMF-derived components while adjusting for age, sex, post-traumatic stress disorder, depression, and data acquisition site/scanner. We found significantly stronger age-dependent effects of lower FA in Veterans with TBI than Veterans without in four components (q < 0.05), which are spatially unconstrained by traditionally defined WM tracts. One component, occupying the most peripheral location, exhibited significantly stronger age-dependent differences in Veterans with mTBI. We found NMF to be powerful and effective in detecting covarying patterns of FA associated with mTBI by applying standard parametric regression modeling. Our results highlight patterns of WM alteration that are differentially affected by TBI and mTBI in younger compared to older military Veterans.
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Affiliation(s)
- Heather C. Bouchard
- Duke‐UNC Brain Imaging and Analysis CenterDuke UniversityDurhamNorth CarolinaUSA
- Mid‐Atlantic Mental Illness Research Education and Clinical CenterDurham VA Medical CenterDurhamNorth CarolinaUSA
- Center for Brain, Biology & BehaviorUniversity of Nebraska‐LincolnLincolnNebraskaUSA
| | - Delin Sun
- Duke‐UNC Brain Imaging and Analysis CenterDuke UniversityDurhamNorth CarolinaUSA
- Mid‐Atlantic Mental Illness Research Education and Clinical CenterDurham VA Medical CenterDurhamNorth CarolinaUSA
| | - Emily L. Dennis
- Department of NeurologyUniversity of UtahSalt Lake CityUtahUSA
- Department of RadiologyStanford UniversityStanfordCaliforniaUSA
| | - Mary R. Newsome
- Michael E. DeBakey VA Medical CenterHoustonTexasUSA
- H. Ben Taub Department of Physical Medicine and RehabilitationBaylor College of MedicineHoustonTexasUSA
| | - Seth G. Disner
- Minneapolis VA Health Care SystemMinneapolisMinnesotaUSA
- Department of PsychiatryUniversity of Minnesota Medical SchoolMinneapolisMinnesotaUSA
| | - Jeremy Elman
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoSan DiegoCaliforniaUSA
| | - Annelise Silva
- Psychiatry Neuroimaging LaboratoryBrigham & Women's HospitalBostonMassachusettsUSA
| | - Carmen Velez
- Department of NeurologyUniversity of UtahSalt Lake CityUtahUSA
- George E. Wahlen Veterans Affairs Medical CenterSalt Lake CityUtahUSA
| | - Andrei Irimia
- Leonard Davis School of GerontologyUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
- Department of Biomedical Engineering, Viterbi School of EngineeringUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Nicholas D. Davenport
- Minneapolis VA Health Care SystemMinneapolisMinnesotaUSA
- Department of PsychiatryUniversity of Minnesota Medical SchoolMinneapolisMinnesotaUSA
| | - Scott R. Sponheim
- Minneapolis VA Health Care SystemMinneapolisMinnesotaUSA
- Department of PsychiatryUniversity of Minnesota Medical SchoolMinneapolisMinnesotaUSA
| | - Carol E. Franz
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoSan DiegoCaliforniaUSA
| | - William S. Kremen
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
- Center for Behavior Genetics of AgingUniversity of California, San DiegoSan DiegoCaliforniaUSA
- Center of Excellence for Stress and Mental HealthVA San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Michael J. Coleman
- Psychiatry Neuroimaging LaboratoryBrigham & Women's HospitalBostonMassachusettsUSA
| | - M. Wright Williams
- Michael E. DeBakey VA Medical CenterHoustonTexasUSA
- Menninger Department of Psychiatry and Behavioral SciencesBaylor College of MedicineHoustonTexasUSA
| | - Elbert Geuze
- Department of PsychiatryUniversity Medical CenterUtrechtNetherlands
- Brain Research & Innovation CentreMinistry of DefenceUtrechtNetherlands
| | - Inga K. Koerte
- Psychiatry Neuroimaging LaboratoryBrigham & Women's HospitalBostonMassachusettsUSA
| | - Martha E. Shenton
- Psychiatry Neuroimaging LaboratoryBrigham & Women's HospitalBostonMassachusettsUSA
| | - Maheen M. Adamson
- Rehabilitation ServiceVA Palo AltoPalo AltoCaliforniaUSA
- NeurosurgeryStanford School of MedicineStanfordCaliforniaUSA
| | - Raul Coimbra
- Department of SurgeryUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Gerald Grant
- Department of NeurosurgeryStanford University Medical CenterPalo AltoCaliforniaUSA
| | - Lori Shutter
- Department of Critical Care MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Mark S. George
- Department of PsychiatryMedical University of South CarolinaCharlestonSouth CarolinaUSA
| | - Ross D. Zafonte
- Spaulding Rehabilitation HospitalMassachusetts General Hospital, Brigham and Women's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | | | - Murray B. Stein
- Department of PsychiatryUniversity of California San DiegoLa JollaCaliforniaUSA
- Herbert Wertheim School of Public Health and Human Longevity ScienceUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics InstituteKeck School of Medicine of USCMarina del ReyCaliforniaUSA
- Department of Neurology, Pediatrics, Psychiatry, Radiology, Engineering, and OphthalmologyUniversity of Southern California (USC), Los AngelesCaliforniaUSA
- Department of PediatricsUSCLos AngelesCaliforniaUSA
- Department of PsychiatryUSCLos AngelesCaliforniaUSA
- Department of RadiologyUSCLos AngelesCaliforniaUSA
- Department of EngineeringUSCLos AngelesCaliforniaUSA
- Department of OphthalmologyUSCLos AngelesCaliforniaUSA
- Department of Radiology and Institute for Informatics, School of MedicineWashington University St. LouisSt. LouisMissouriUSA
| | - Elisabeth A. Wilde
- Department of NeurologyUniversity of UtahSalt Lake CityUtahUSA
- Michael E. DeBakey VA Medical CenterHoustonTexasUSA
- George E. Wahlen Veterans Affairs Medical CenterSalt Lake CityUtahUSA
| | - David F. Tate
- Department of NeurologyUniversity of UtahSalt Lake CityUtahUSA
- George E. Wahlen Veterans Affairs Medical CenterSalt Lake CityUtahUSA
| | - Aristeidis Sotiras
- Department of Radiology and Institute for Informatics, School of MedicineWashington University St. LouisSt. LouisMissouriUSA
| | - Rajendra A. Morey
- Duke‐UNC Brain Imaging and Analysis CenterDuke UniversityDurhamNorth CarolinaUSA
- Mid‐Atlantic Mental Illness Research Education and Clinical CenterDurham VA Medical CenterDurhamNorth CarolinaUSA
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Gerritsen JKW, Broekman MLD, De Vleeschouwer S, Schucht P, Nahed BV, Berger MS, Vincent AJPE. Safe Surgery for Glioblastoma: Recent Advances and Modern Challenges. Neurooncol Pract 2022; 9:364-379. [PMID: 36127890 PMCID: PMC9476986 DOI: 10.1093/nop/npac019] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
One of the major challenges during glioblastoma surgery is balancing between maximizing extent of resection and preventing neurological deficits. Several surgical techniques and adjuncts have been developed to help identify eloquent areas both preoperatively (fMRI, nTMS, MEG, DTI) and intraoperatively (imaging (ultrasound, iMRI), electrostimulation (mapping), cerebral perfusion measurements (fUS)), and visualization (5-ALA, fluoresceine)). In this review, we give an update of the state-of-the-art management of both primary and recurrent glioblastomas. We will review the latest surgical advances, challenges, and approaches that define the onco-neurosurgical practice in a contemporary setting and give an overview of the current prospective scientific efforts.
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Affiliation(s)
| | | | | | - Philippe Schucht
- Department of Neurosurgery, University Hospital Bern, Switzerland
| | - Brian Vala Nahed
- Department of Neurosurgery, Massachusetts General Hospital/Harvard Medical School, Boston MA, USA
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11
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Figley CR, Uddin MN, Wong K, Kornelsen J, Puig J, Figley TD. Potential Pitfalls of Using Fractional Anisotropy, Axial Diffusivity, and Radial Diffusivity as Biomarkers of Cerebral White Matter Microstructure. Front Neurosci 2022; 15:799576. [PMID: 35095400 PMCID: PMC8795606 DOI: 10.3389/fnins.2021.799576] [Citation(s) in RCA: 68] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 12/17/2021] [Indexed: 01/31/2023] Open
Abstract
Fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD) are commonly used as MRI biomarkers of white matter microstructure in diffusion MRI studies of neurodevelopment, brain aging, and neurologic injury/disease. Some of the more frequent practices include performing voxel-wise or region-based analyses of these measures to cross-sectionally compare individuals or groups, longitudinally assess individuals or groups, and/or correlate with demographic, behavioral or clinical variables. However, it is now widely recognized that the majority of cerebral white matter voxels contain multiple fiber populations with different trajectories, which renders these metrics highly sensitive to the relative volume fractions of the various fiber populations, the microstructural integrity of each constituent fiber population, and the interaction between these factors. Many diffusion imaging experts are aware of these limitations and now generally avoid using FA, AD or RD (at least in isolation) to draw strong reverse inferences about white matter microstructure, but based on the continued application and interpretation of these metrics in the broader biomedical/neuroscience literature, it appears that this has perhaps not yet become common knowledge among diffusion imaging end-users. Therefore, this paper will briefly discuss the complex biophysical underpinnings of these measures in the context of crossing fibers, provide some intuitive “thought experiments” to highlight how conventional interpretations can lead to incorrect conclusions, and suggest that future studies refrain from using (over-interpreting) FA, AD, and RD values as standalone biomarkers of cerebral white matter microstructure.
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Affiliation(s)
- Chase R. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
- *Correspondence: Chase R. Figley,
| | - Md Nasir Uddin
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Department of Neurology, University of Rochester, Rochester, NY, United States
| | - Kaihim Wong
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
| | - Jennifer Kornelsen
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
| | - Josep Puig
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Girona Biomedical Research Institute (IDIBGI), Hospital Universitari de Girona Dr. Josep Trueta, Girona, Spain
| | - Teresa D. Figley
- Department of Radiology, University of Manitoba, Winnipeg, MB, Canada
- Division of Diagnostic Imaging, Health Sciences Centre, Winnipeg, MB, Canada
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB, Canada
- Department of Physiology & Pathophysiology, University of Manitoba, Winnipeg, MB, Canada
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12
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Suo X, Guo L, Fu D, Ding H, Li Y, Qin W. A Comparative Study of Diffusion Fiber Reconstruction Models for Pyramidal Tract Branches. Front Neurosci 2021; 15:777377. [PMID: 34955727 PMCID: PMC8698251 DOI: 10.3389/fnins.2021.777377] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 11/02/2021] [Indexed: 11/13/2022] Open
Abstract
Currently, comparative studies evaluating the quantification accuracy of pyramidal tracts (PT) and PT branches that were tracked based on four mainstream diffusion models are deficient. The present study aims to evaluate four mainstream models using the high-quality Human Connectome Project (HCP) dataset. Diffusion tensor imaging (DTI), diffusion spectral imaging (DSI), generalized Q-space sampling imaging (GQI), and Q-ball imaging (QBI) were used to construct the PT and PT branches in 50 healthy volunteers from the HCP. False and true PT fibers were identified based on anatomic information. One-way repeated measure analysis of variance and post hoc paired-sample t-test were performed to identify the best PT and PT branch quantification model. The number, percentage, and density of true fibers of PT obtained based on GQI and QBI were significantly larger than those based on DTI and DSI (all p < 0.0005, Bonferroni corrected), whereas false fibers yielded the opposite results (all p < 0.0005, Bonferroni corrected). More trunk branches (PTtrunk) were present in the four diffusion models compared with the upper limb (PTUlimb), lower limb (PTLlimb), and cranial (PTcranial) branches. In addition, significantly more true fibers were obtained in PTtrunk, PTUlimb, and PTLlimb based on the GQI and QBI compared with DTI and DSI (all p < 0.0005, Bonferroni corrected). Finally, GQI-based group probabilistic maps showed that the four PT branches exhibited relatively unique spatial distributions. Therefore, the GQI and QBI represent better diffusion models for the PT and PT branches. The group probabilistic maps of PT branches have been shared with the public to facilitate more precise studies on the plasticity of and the damage to the motor pathway.
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Affiliation(s)
- Xinjun Suo
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Lining Guo
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Dianxun Fu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Hao Ding
- Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Yihong Li
- School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Wen Qin
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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13
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Morales H. Current and Future Challenges of Functional MRI and Diffusion Tractography in the Surgical Setting: From Eloquent Brain Mapping to Neural Plasticity. Semin Ultrasound CT MR 2021; 42:474-489. [PMID: 34537116 DOI: 10.1053/j.sult.2021.07.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Decades ago, Spetzler (1986) and Sawaya (1998) provided a rough brain segmentation of the eloquent areas of the brain, aimed to help surgical decisions in cases of vascular malformations and tumors, respectively. Currently in clinical use, their criteria are in need of revision. Defining functions (eg, sensorimotor, language and visual) that should be preserved during surgery seems a straightforward task. In practice, locating the specific areas that could cause a permanent vs transient deficit is not an easy task. This is particularly true for the associative cortex and cognitive domains such as language. The old model, with Broca's and Wernicke's areas at the forefront, has been superseded by a dual-stream model of parallel language processing; named ventral and dorsal pathways. This complicated network of cortical hubs and subcortical white matter pathways needing preservation during surgery is a work in progress. Preserving not only cortical regions but most importantly preserving the connections, or white matter fiber bundles, of core regions in the brain is the new paradigm. For instance, the arcuate fascicululs and inferior fronto-occipital fasciculus are key components of the dorsal and ventral language pathways, respectively; and their damage result in permanent language deficits. Interestedly, the damage of the temporal portions of these bundles -where there is a crossroad with other multiple bundles-, appears to be more important (permanent) than the damage of the frontal portions - where plasticity and contralateral activation could help. Although intraoperative direct cortical and subcortical stimulation have contributed largely, advanced MR techniques such as functional MRI (fMRI) and diffusion tractography (DT), are at the epi-center of our current understanding. Nevertheless, these techniques posse important challenges: such as neurovascular uncoupling or venous bias on fMRI; and appropriate anatomical validation or accurate representation of crossing fibers on DT. These limitations should be well understood and taken into account in clinical practice. Unifying multidisciplinary research and clinical efforts is desirable, so these techniques could contribute more efficiently not only to locate eloquent areas but to improve outcomes and our understanding of neural plasticity. Finally, although there are constant anatomical and functional regions at the individual level, there is a known variability at the inter-individual level. This concept should strengthen the importance of a personalized approach when evaluating these regions on fMRI and DT. It should strengthen the importance of personalized treatments as well, aimed to meet tailored needs and expectations.
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Affiliation(s)
- Humberto Morales
- Section of Neuroradiology, University of Cincinnati Medical Center, Cincinnati, OH.
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14
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Henriques RN, Correia MM, Marrale M, Huber E, Kruper J, Koudoro S, Yeatman JD, Garyfallidis E, Rokem A. Diffusional Kurtosis Imaging in the Diffusion Imaging in Python Project. Front Hum Neurosci 2021; 15:675433. [PMID: 34349631 PMCID: PMC8327208 DOI: 10.3389/fnhum.2021.675433] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Accepted: 06/17/2021] [Indexed: 12/28/2022] Open
Abstract
Diffusion-weighted magnetic resonance imaging (dMRI) measurements and models provide information about brain connectivity and are sensitive to the physical properties of tissue microstructure. Diffusional Kurtosis Imaging (DKI) quantifies the degree of non-Gaussian diffusion in biological tissue from dMRI. These estimates are of interest because they were shown to be more sensitive to microstructural alterations in health and diseases than measures based on the total anisotropy of diffusion which are highly confounded by tissue dispersion and fiber crossings. In this work, we implemented DKI in the Diffusion in Python (DIPY) project-a large collaborative open-source project which aims to provide well-tested, well-documented and comprehensive implementation of different dMRI techniques. We demonstrate the functionality of our methods in numerical simulations with known ground truth parameters and in openly available datasets. A particular strength of our DKI implementations is that it pursues several extensions of the model that connect it explicitly with microstructural models and the reconstruction of 3D white matter fiber bundles (tractography). For instance, our implementations include DKI-based microstructural models that allow the estimation of biophysical parameters, such as axonal water fraction. Moreover, we illustrate how DKI provides more general characterization of non-Gaussian diffusion compatible with complex white matter fiber architectures and gray matter, and we include a novel mean kurtosis index that is invariant to the confounding effects due to tissue dispersion. In summary, DKI in DIPY provides a well-tested, well-documented and comprehensive reference implementation for DKI. It provides a platform for wider use of DKI in research on brain disorders and in cognitive neuroscience.
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Affiliation(s)
| | - Marta M. Correia
- Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Maurizio Marrale
- Department of Physics and Chemistry “Emilio Segrè”, University of Palermo, Palermo, Italy
- National Institute for Nuclear Physics (INFN), Catania Division, Catania, Italy
| | - Elizabeth Huber
- Department of Speech and Hearing, Institute for Learning and Brain Science, University of Washington, Seattle, WA, United States
| | - John Kruper
- Department of Psychology and eScience Institute, The University of Washington, Seattle, WA, United States
| | - Serge Koudoro
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computer Science and Engineering, Indiana University, Bloomington, IN, United States
| | - Jason D. Yeatman
- Department of Speech and Hearing, Institute for Learning and Brain Science, University of Washington, Seattle, WA, United States
- Department of Pediatrics, Graduate School of Education, Stanford University, Stanford, CA, United States
| | - Eleftherios Garyfallidis
- Department of Intelligent Systems Engineering, Luddy School of Informatics, Computer Science and Engineering, Indiana University, Bloomington, IN, United States
| | - Ariel Rokem
- Department of Psychology and eScience Institute, The University of Washington, Seattle, WA, United States
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15
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Mendez Colmenares A, Voss MW, Fanning J, Salerno EA, Gothe NP, Thomas ML, McAuley E, Kramer AF, Burzynska AZ. White matter plasticity in healthy older adults: The effects of aerobic exercise. Neuroimage 2021; 239:118305. [PMID: 34174392 DOI: 10.1016/j.neuroimage.2021.118305] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Revised: 06/22/2021] [Accepted: 06/23/2021] [Indexed: 12/15/2022] Open
Abstract
White matter deterioration is associated with cognitive impairment in healthy aging and Alzheimer's disease. It is critical to identify interventions that can slow down white matter deterioration. So far, clinical trials have failed to demonstrate the benefits of aerobic exercise on the adult white matter using diffusion Magnetic Resonance Imaging. Here, we report the effects of a 6-month aerobic walking and dance interventions (clinical trial NCT01472744) on white matter integrity in healthy older adults (n = 180, 60-79 years) measured by changes in the ratio of calibrated T1- to T2-weighted images (T1w/T2w). Specifically, the aerobic walking and social dance interventions resulted in positive changes in the T1w/T2w signal in late-myelinating regions, as compared to widespread decreases in the T1w/T2w signal in the active control. Notably, in the aerobic walking group, positive change in the T1w/T2w signal correlated with improved episodic memory performance. Lastly, intervention-induced increases in cardiorespiratory fitness did not correlate with change in the T1w/T2w signal. Together, our findings suggest that white matter regions that are vulnerable to aging retain some degree of plasticity that can be induced by aerobic exercise training. In addition, we provided evidence that the T1w/T2w signal may be a useful and broadly accessible measure for studying short-term within-person plasticity and deterioration in the adult human white matter.
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Affiliation(s)
- Andrea Mendez Colmenares
- Department of Human Development and Family Studies/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, CO, 80523, United States; Department of Psychology/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, CO, 80523, United States
| | - Michelle W Voss
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, 52242, United States
| | - Jason Fanning
- Department of Health and Exercise Sciences, Wake Forest University, Winston-Salem, NC, 27109, United States
| | - Elizabeth A Salerno
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine in St. Louis, St. Louis, MO, 63130, United States
| | - Neha P Gothe
- Department of Kinesiology and Community Health, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, United States
| | - Michael L Thomas
- Department of Psychology/Molecular, Cellular and Integrative Neurosciences, Colorado State University, Fort Collins, CO, 80523, United States
| | - Edward McAuley
- Department of Kinesiology and Community Health, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, United States
| | - Arthur F Kramer
- Department of Kinesiology and Community Health, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, United States; Department of Psychology, Northeastern University, Boston, MA, 02115, United States
| | - Agnieszka Z Burzynska
- Department of Psychology, Northeastern University, Boston, MA, 02115, United States.
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16
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Bopp MHA, Emde J, Carl B, Nimsky C, Saß B. Diffusion Kurtosis Imaging Fiber Tractography of Major White Matter Tracts in Neurosurgery. Brain Sci 2021; 11:brainsci11030381. [PMID: 33802710 PMCID: PMC8002557 DOI: 10.3390/brainsci11030381] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 03/08/2021] [Accepted: 03/14/2021] [Indexed: 01/31/2023] Open
Abstract
Diffusion tensor imaging (DTI)-based fiber tractography is routinely used in clinical applications to visualize major white matter tracts, such as the corticospinal tract (CST), optic radiation (OR), and arcuate fascicle (AF). Nevertheless, DTI is limited due to its capability of resolving intra-voxel multi-fiber populations. Sophisticated models often require long acquisition times not applicable in clinical practice. Diffusion kurtosis imaging (DKI), as an extension of DTI, combines sophisticated modeling of the diffusion process with short acquisition times but has rarely been investigated in fiber tractography. In this study, DTI- and DKI-based fiber tractography of the CST, OR, and AF was investigated in healthy volunteers and glioma patients. For the CST, significantly larger tract volumes were seen in DKI-based fiber tractography. Similar results were obtained for the OR, except for the right OR in patients. In the case of the AF, results of both models were comparable with DTI-based fiber tractography showing even significantly larger tract volumes in patients. In the case of the CST and OR, DKI-based fiber tractography contributes to advanced visualization under clinical time constraints, whereas for the AF, other models should be considered.
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Affiliation(s)
- Miriam H. A. Bopp
- Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany; (J.E.); (B.C.); (C.N.); (B.S.)
- Center for Mind, Brain and Behavior (CMBB), 35043 Marburg, Germany
- Correspondence:
| | - Julia Emde
- Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany; (J.E.); (B.C.); (C.N.); (B.S.)
| | - Barbara Carl
- Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany; (J.E.); (B.C.); (C.N.); (B.S.)
- Department of Neurosurgery, Helios Dr. Horst Schmidt Kliniken, Ludwig-Erhard-Strasse 100, 65199 Wiesbaden, Germany
| | - Christopher Nimsky
- Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany; (J.E.); (B.C.); (C.N.); (B.S.)
- Center for Mind, Brain and Behavior (CMBB), 35043 Marburg, Germany
| | - Benjamin Saß
- Department of Neurosurgery, University of Marburg, Baldingerstrasse, 35043 Marburg, Germany; (J.E.); (B.C.); (C.N.); (B.S.)
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17
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Nägele FL, Pasternak O, Bitzan LV, Mußmann M, Rauh J, Kubicki M, Leicht G, Shenton ME, Lyall AE, Mulert C. Cellular and extracellular white matter alterations indicate conversion to psychosis among individuals at clinical high-risk for psychosis. World J Biol Psychiatry 2021; 22:214-227. [PMID: 32643526 PMCID: PMC7798359 DOI: 10.1080/15622975.2020.1775890] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
OBJECTIVES It is important to find biomarkers associated with transition to illness in individuals at clinical high-risk for psychosis (CHR). Here, we use free-water imaging, an advanced diffusion MRI technique, to identify white matter alterations in the brains of CHR subjects who subsequently develop psychosis (CHR-P) compared to those who do not (CHR-NP). METHODS Twenty-four healthy controls (HC) and 30 CHR individuals, 8 of whom converted to schizophrenia after a mean follow-up of 15.16 months, received baseline MRI scans. Maps of fractional anisotropy (FA), FA of cellular tissue (FAT), and extracellular free-water (FW) were extracted using tract-based spatial statistics after which voxel-wise non-parametric group statistics and correlations with symptom severity were performed. RESULTS There were no significant differences between HCs and the combined CHR group. However, prior to conversion, CHR-P showed widespread lower FA compared to CHR-NP (pFWE < 0.05). FA changes in CHR-P were associated with significantly lower FAT and higher FW, compared to CHR-NP. Positive symptoms correlated significantly with diffusion parameters in similar regions as those discriminating CHR-P from CHR-NP. CONCLUSIONS Our study suggests that cellular (FAT) and extracellular (FW) white matter alterations are associated with positive symptom severity and indicate an elevated illness risk among CHR individuals.
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Affiliation(s)
- Felix L. Nägele
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany;,Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA;,Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Lisa V. Bitzan
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany;,Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Marius Mußmann
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Jonas Rauh
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Marek Kubicki
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA;,Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA;,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Gregor Leicht
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Martha E. Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA;,Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA;,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA;,VA Boston Healthcare System, Brockton Division, Brockton, MA, USA
| | - Amanda E. Lyall
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA;,Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Christoph Mulert
- Psychiatry Neuroimaging Branch, Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany;,Centre for Psychiatry and Psychotherapy, Justus-Liebig-University, Giessen, Germany
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18
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Zhang Y, Zhang Z, Jia X, Guan X, Lyu Y, Yang J, Jiang T. Imaging Parameters of the Ipsilateral Medial Geniculate Body May Predict Prognosis of Patients with Idiopathic Unilateral Sudden Sensorineural Hearing Loss on the Basis of Diffusion Spectrum Imaging. AJNR Am J Neuroradiol 2021; 42:152-159. [PMID: 33214182 DOI: 10.3174/ajnr.a6874] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 08/29/2020] [Indexed: 01/17/2023]
Abstract
BACKGROUND AND PURPOSE Idiopathic sudden sensorineural hearing loss is an acute unexplained onset of hearing loss. We examined the central auditory pathway abnormalities in patients with unilateral idiopathic sudden sensorineural hearing loss using diffusion spectrum imaging and the relationships between hearing recovery and diffusion spectrum imaging parameters. MATERIALS AND METHODS Forty-eight patients with unilateral idiopathic sudden sensorineural hearing loss with a duration of ≤2 weeks (range, 8.9 ± 4.3 days) and 20 healthy subjects underwent diffusion spectrum imaging tractography. Hearing levels were evaluated using a pure-tone average at initial presentation and 3-month follow-up. Clinical characteristics and MR imaging findings were assessed. RESULTS Compared with healthy control subjects, the generalized fractional anisotropy values of patients decreased significantly in the bilateral posterior limbs of the internal capsule, with no differences between the ipsilateral and contralateral sides. The quantitative anisotropy values decreased in the Brodmann area 41, contralateral medial geniculate body, bilateral lateral lemniscus, anterior limb of internal capsule, middle temporal gyrus, and anterior corona radiata. Furthermore, at 3-month follow-up, 14 patients had <15 dB of hearing gain. Receiver operating characteristic curve analysis demonstrated that generalized fractional anisotropy in the ipsilateral medial geniculate body was related to prognosis (sensitivity = 64.7%; specificity = 85.7%; area under the curve = 0.796, 95% CI, 0.661-0.931; P < .01). CONCLUSIONS Diffusion spectrum imaging can detect abnormalities of white matter microstructure along the central auditory pathway in patients with unilateral idiopathic sudden sensorineural hearing loss. The generalized fractional anisotropy value of the ipsilateral medial geniculate body may help to predict recovery outcomes.
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Affiliation(s)
- Y Zhang
- From the Departments of Hyperbaric Oxygen (Y.Z., J.Y.)
| | - Z Zhang
- Radiology (Z.Z., X.J., Y.L., T.J.), Beijing Chaoyang Hospital
| | - X Jia
- Radiology (Z.Z., X.J., Y.L., T.J.), Beijing Chaoyang Hospital
| | - X Guan
- Department of Radiology (X.G.), Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Y Lyu
- Radiology (Z.Z., X.J., Y.L., T.J.), Beijing Chaoyang Hospital
| | - J Yang
- From the Departments of Hyperbaric Oxygen (Y.Z., J.Y.)
| | - T Jiang
- Radiology (Z.Z., X.J., Y.L., T.J.), Beijing Chaoyang Hospital
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19
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Ye Z, Gary SE, Sun P, Mustafi SM, Glenn GR, Yeh FC, Merisaari H, Song C, Yang R, Huang GS, Kao HW, Lin CY, Wu YC, Jensen JH, Song SK. The impact of edema and fiber crossing on diffusion MRI metrics assessed in an ex vivo nerve phantom: Multi-tensor model vs. diffusion orientation distribution function. NMR IN BIOMEDICINE 2021; 34:e4414. [PMID: 33015890 PMCID: PMC9743958 DOI: 10.1002/nbm.4414] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 08/23/2020] [Accepted: 09/06/2020] [Indexed: 05/30/2023]
Abstract
Diffusion tensor imaging (DTI) has been employed for over 2 decades to noninvasively quantify central nervous system diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of coexisting inflammation, edema and crossing nerve fibers. We employed a tissue phantom using fixed mouse trigeminal nerves coated with various amounts of agarose gel to mimic crossing fibers in the presence of vasogenic edema. Diffusivity measures derived by DTI and diffusion basis spectrum imaging (DBSI) were compared at increasing levels of simulated edema and degrees of fiber crossing. Furthermore, we assessed the ability of DBSI, diffusion kurtosis imaging (DKI), generalized q-sampling imaging (GQI), q-ball imaging (QBI) and neurite orientation dispersion and density imaging to resolve fiber crossing, in reference to the gold standard angles measured from structural images. DTI-computed diffusivities and fractional anisotropy were significantly confounded by gel-mimicked edema and crossing fibers. Conversely, DBSI calculated accurate diffusivities of individual fibers regardless of the extent of simulated edema and degrees of fiber crossing angles. Additionally, DBSI accurately and consistently estimated crossing angles in various conditions of gel-mimicked edema when compared with the gold standard (r2 = 0.92, P = 1.9 × 10-9 , bias = 3.9°). Small crossing angles and edema significantly impact the diffusion orientation distribution function, making DKI, GQI and QBI less accurate in detecting and estimating fiber crossing angles. Lastly, we used diffusion tensor ellipsoids to demonstrate that DBSI resolves the confounds of edema and crossing fibers in the peritumoral edema region from a patient with lung cancer metastasis, while DTI failed. In summary, DBSI is able to separate two crossing fibers and accurately recover their diffusivities in a complex environment characterized by increasing crossing angles and amounts of gel-mimicked edema. DBSI also indicated better angular resolution compared with DKI, QBI and GQI.
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Affiliation(s)
- Zezhong Ye
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Sam E. Gary
- Medical Scientist Training Program, University of Alabama at Birmingham, Birmingham, AL 35294
| | - Peng Sun
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
| | - Sourajit Mitra Mustafi
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202
| | - George Russell Glenn
- Department of Radiology and Imaging Science, Emory University School of Medicine, Atlanta, GA 30322
| | - Fang-Cheng Yeh
- Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213
| | - Harri Merisaari
- Department of Diagnostic Radiology, University of Turku, Turku, Finland 20014
| | - Chunyu Song
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63130
| | - Ruimeng Yang
- Department of Radiology, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong 510180, China
| | - Guo-Shu Huang
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan 114
| | - Hung-Wen Kao
- Department of Radiology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan 114
| | | | - Yu-Chien Wu
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN 46202
| | - Jens H. Jensen
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC 29425
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC 29425
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC 29425
| | - Sheng-Kwei Song
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110
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Ly M, Foley L, Manivannan A, Hitchens TK, Richardson RM, Modo M. Mesoscale diffusion magnetic resonance imaging of the ex vivo human hippocampus. Hum Brain Mapp 2020; 41:4200-4218. [PMID: 32621364 PMCID: PMC7502840 DOI: 10.1002/hbm.25119] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/01/2020] [Accepted: 06/16/2020] [Indexed: 12/21/2022] Open
Abstract
Mesoscale diffusion magnetic resonance imaging (MRI) endeavors to bridge the gap between macroscopic white matter tractography and microscopic studies investigating the cytoarchitecture of human brain tissue. To ensure a robust measurement of diffusion at the mesoscale, acquisition parameters were arrayed to investigate their effects on scalar indices (mean, radial, axial diffusivity, and fractional anisotropy) and streamlines (i.e., graphical representation of axonal tracts) in hippocampal layers. A mesoscale resolution afforded segementation of the pyramidal cell layer (CA1-4), the dentate gyrus, as well as stratum moleculare, radiatum, and oriens. Using ex vivo samples, surgically excised from patients with intractable epilepsy (n = 3), we found that shorter diffusion times (23.7 ms) with a b-value of 4,000 s/mm2 were advantageous at the mesoscale, providing a compromise between mean diffusivity and fractional anisotropy measurements. Spatial resolution and sample orientation exerted a major effect on tractography, whereas the number of diffusion gradient encoding directions minimally affected scalar indices and streamline density. A sample temperature of 15°C provided a compromise between increasing signal-to-noise ratio and increasing the diffusion properties of the tissue. Optimization of the acquisition afforded a system's view of intra- and extra-hippocampal connections. Tractography reflected histological boundaries of hippocampal layers. Individual layer connectivity was visualized, as well as streamlines emanating from individual sub-fields. The perforant path, subiculum and angular bundle demonstrated extra-hippocampal connections. Histology of the samples confirmed individual cell layers corresponding to ROIs defined on MR images. We anticipate that this ex vivo mesoscale imaging will yield novel insights into human hippocampal connectivity.
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Affiliation(s)
- Maria Ly
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Lesley Foley
- Department of NeurobiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | | | - T. Kevin Hitchens
- Department of NeurobiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - R. Mark Richardson
- Department of Neurological SurgeryUniversity of PittsburghPittsburghPennsylvaniaUSA
- McGowan Institute for Regenerative MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Brain InstituteUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Michel Modo
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- McGowan Institute for Regenerative MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of BioengineeringUniversity of PittsburghPittsburghPennsylvaniaUSA
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21
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Liu Z, Bian B, Wang G, Tian C, Lv Z, Shao Z, Li D. Evaluation of microstructural changes in spinal cord of patients with degenerative cervical myelopathy by diffusion kurtosis imaging and investigate the correlation with JOA score. BMC Neurol 2020; 20:185. [PMID: 32404188 PMCID: PMC7218841 DOI: 10.1186/s12883-020-01752-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2020] [Accepted: 04/28/2020] [Indexed: 12/13/2022] Open
Abstract
Background To explore the feasibility of the metrics of diffusion kurtosis imaging (DKI) for investigations of the microstructural changes of spinal cord injury in patients with degenerative cervical myelopathy (DCM) and the correlation between Japan Orthopaedic Association (JOA) scores and DKI metrics. Methods Fifty-seven patients with DCM and 38 healthy volunteers underwent 3.0 T magnetic resonance (MR) imaging with routine MRI sequences and DKI from echo-planar imaging sequence. Based on the JOA score, DCM patients were divided into four subgroups. DKI metrics of the DCM group and control group were obtained and compared, separately for the white matter (WM) and the gray matter (GM). Results The FA values in WM were significantly lower (P = 0.020) in the DCM group than in the control group. The MK values in GM were lower (P = 0.011) in the DCM group than in the control group. The MD values in WM were significantly higher (P = 0.010) in the DCM group than in the control group. In GM, the JOA score was positively correlated with the MK values (r = 0.768, P < 0.05). In the WM, the JOA score was positively correlated with the FA values (r = 0.612, P < 0.05). Conclusion DKI provides quantitive evaluation to the characters of microstructure of the spinal cord damage in patients with DCM compared to conventional MR. MK values can reflect microstructural abnormalities of gray matter of the cervical spinal cord and provide more information beyond that obtained with routine diffusion metrics. In addition, MK values of GM and FA values of WM may as a be highly sensitive biomarker for the degree of cervical spinal cord damage.
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Affiliation(s)
- Zhuohang Liu
- Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, 130021, People's Republic of China
| | - Bingyang Bian
- Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, 130021, People's Republic of China
| | - Gang Wang
- Department of Orthopedics, The Third Hospital of Jilin University, Changchun, Jilin, 130021, People's Republic of China
| | - Cheukying Tian
- Icahn School of Medicine at Mount Sinai, New York, 10001, USA
| | - Zhenshan Lv
- Department of Spine Surgery, The First Hospital of Jilin University, Changchun, Jilin, 130021, People's Republic of China
| | - Zhiqing Shao
- Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, 130021, People's Republic of China
| | - Dan Li
- Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, 130021, People's Republic of China.
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22
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Zhong Y, Huang Y, Ding H. Re-understanding of edema zone from the nerve fiber bundles: A narrative review. GLIOMA 2020. [DOI: 10.4103/glioma.glioma_28_20] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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23
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Jennings JE, Kassam AB, Fukui MB, Monroy-Sosa A, Chakravarthi S, Kojis N, Rovin RA. The Surgical White Matter Chassis: A Practical 3-Dimensional Atlas for Planning Subcortical Surgical Trajectories. Oper Neurosurg (Hagerstown) 2019; 14:469-482. [PMID: 28961936 DOI: 10.1093/ons/opx177] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2016] [Accepted: 07/13/2017] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND The imperative role of white matter preservation in improving surgical functional outcomes is now recognized. Understanding the fundamental white matter framework is essential for translating the anatomic and functional literature into practical strategies for surgical planning and neuronavigation. OBJECTIVE To present a 3-dimensional (3-D) atlas of the structural and functional scaffolding of human white matter-ie, a "Surgical White Matter Chassis (SWMC)"-that can be used as an organizational tool in designing precise and individualized trajectory-based neurosurgical corridors. METHODS Preoperative diffusion tensor imaging magnetic resonance images were obtained prior to each of our last 100 awake subcortical resections, using a clinically available 3.0 Tesla system. Tractography was generated using a semiautomated deterministic global seeding algorithm. Tract data were conceptualized as a 3-D modular chassis based on the 3 major fiber types, organized along median and paramedian planes, with special attention to limbic and neocortical association tracts and their interconnections. RESULTS We discuss practical implementation of the SWMC concept, and highlight its use in planning select illustrative cases. Emphasis has been given to developing practical understanding of the arcuate fasciculus, uncinate fasciculus, and vertical rami of the superior longitudinal fasciculus, which are often-neglected fibers in surgical planning. CONCLUSION A working knowledge of white matter anatomy, as embodied in the SWMC, is of paramount importance to the planning of parafascicular surgical trajectories, and can serve as a basis for developing reliable safe corridors, or modules, toward the goal of "zero-footprint" transsulcal access to the subcortical space.
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Affiliation(s)
- Jonathan E Jennings
- Aurora Neuroscience Innovation Insti-tute, Aurora St. Luke's Medical Center, Milwaukee, Wisconsin
| | - Amin B Kassam
- Aurora Neuroscience Innovation Insti-tute, Aurora St. Luke's Medical Center, Milwaukee, Wisconsin
| | - Melanie B Fukui
- Aurora Neuroscience Innovation Insti-tute, Aurora St. Luke's Medical Center, Milwaukee, Wisconsin
| | - Alejandro Monroy-Sosa
- Aurora Neuroscience Innovation Insti-tute, Aurora St. Luke's Medical Center, Milwaukee, Wisconsin
| | - Srikant Chakravarthi
- Aurora Neuroscience Innovation Insti-tute, Aurora St. Luke's Medical Center, Milwaukee, Wisconsin
| | - Nathan Kojis
- Aurora Neuroscience Innovation Insti-tute, Aurora St. Luke's Medical Center, Milwaukee, Wisconsin
| | - Richard A Rovin
- Aurora Neuroscience Innovation Insti-tute, Aurora St. Luke's Medical Center, Milwaukee, Wisconsin
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24
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Crosson B, Rodriguez AD, Copland D, Fridriksson J, Krishnamurthy LC, Meinzer M, Raymer AM, Krishnamurthy V, Leff AP. Neuroplasticity and aphasia treatments: new approaches for an old problem. J Neurol Neurosurg Psychiatry 2019; 90:1147-1155. [PMID: 31055282 PMCID: PMC8014302 DOI: 10.1136/jnnp-2018-319649] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 04/05/2019] [Accepted: 04/10/2019] [Indexed: 12/11/2022]
Abstract
Given the profound impact of language impairment after stroke (aphasia), neuroplasticity research is garnering considerable attention as means for eventually improving aphasia treatments and how they are delivered. Functional and structural neuroimaging studies indicate that aphasia treatments can recruit both residual and new neural mechanisms to improve language function and that neuroimaging modalities may hold promise in predicting treatment outcome. In relatively small clinical trials, both non-invasive brain stimulation and behavioural manipulations targeting activation or suppression of specific cortices can improve aphasia treatment outcomes. Recent language interventions that employ principles consistent with inducing neuroplasticity also are showing improved performance for both trained and novel items and contexts. While knowledge is rapidly accumulating, larger trials emphasising how to select optimal paradigms for individualised aphasia treatment are needed. Finally, a model of how to incorporate the growing knowledge into clinical practice could help to focus future research.
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Affiliation(s)
- Bruce Crosson
- Center for Visual and Neurocognitive Rehabilitation, Atlanta VA Medical Center, Decatur, Georgia, USA .,Department of Neurology, Emory University, Atlanta, Georgia, USA
| | - Amy D Rodriguez
- Center for Visual and Neurocognitive Rehabilitation, Atlanta VA Medical Center, Decatur, Georgia, USA.,Department of Neurology, Emory University, Atlanta, Georgia, USA
| | - David Copland
- School of Health and Rehabilitation Sciences, University of Queensland, Brisbane, Queensland, Australia.,Centre for Clinical Research, University of Queensland, Brisbane, Queensland, Australia
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, South Carolina, USA
| | - Lisa C Krishnamurthy
- Center for Visual and Neurocognitive Rehabilitation, Atlanta VA Medical Center, Decatur, Georgia, USA.,Department of Physics and Astronomy, Georgia State University, Atlanta, Georgia, USA
| | - Marcus Meinzer
- Department of Neurology, University of Greifswald, Greifswald, Germany
| | - Anastasia M Raymer
- Department of Communication Disorders and Special Education, Old Dominion University, Norfolk, Virginia, USA
| | - Venkatagiri Krishnamurthy
- Center for Visual and Neurocognitive Rehabilitation, Atlanta VA Medical Center, Decatur, Georgia, USA.,Department of Neurology, Emory University, Atlanta, Georgia, USA
| | - Alexander P Leff
- Department of Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
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25
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Revuelta G, McGill C, Jensen JH, Bonilha L. Characterizing Thalamo-Cortical Structural Connectivity in Essential Tremor with Diffusional Kurtosis Imaging Tractography. TREMOR AND OTHER HYPERKINETIC MOVEMENTS (NEW YORK, N.Y.) 2019; 9:tre-09-690. [PMID: 31534829 PMCID: PMC6727860 DOI: 10.7916/tohm.v0.690] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Accepted: 07/31/2019] [Indexed: 12/26/2022]
Abstract
Background Neuromodulation of the cerebello-thalamo-cortical (CTC) circuit via thalamic stimulation is an effective therapy for essential tremor (ET). In order to develop non-invasive neuromodulation approaches, clinically relevant thalamo-cortical connections must be elucidated. Methods Twenty-eight subjects (18 ET patients and 10 controls) underwent MRI diffusional kurtosis imaging (DKI). A deterministic fiber-tracking algorithm based on DKI was used, with a seeding region placed at the ventral intermediate nucleus (Vim—located based on intraoperative physiology) to the ending regions at the supplementary motor area (SMA), pre-SMA, or primary motor cortex. One-tailed t-tests were performed to compare groups, and associations with tremor severity were determined by Pearson correlations. All p-values were adjusted for multiple comparisons using Bonferroni correction. Results There was a decrease in the mean diffusivity (MD) in patients compared to controls in all three tracts: Vim-M1 (ET 0.87, control 0.96, p < 0.01), Vim-SMA (ET 0.86, control 0.96, p < 0.05), and Vim-pre-SMA (ET 0.87, control 0.95, p < 0.05). There was a significant positive correlation between Tremor Rating Scale score and MK (r = 0.471, p = 0.033) and mean FA (r = 0.438, p = 0.045) for the Vim-SMA tract, and no significant correlation for the Vim-pre-SMA or Vim-M1 tracts was found. Discussion Patients with ET demonstrated a reinforcement of Vim-cortical connectivity, with higher Vim-SMA connectivity being associated with greater tremor severity. This finding suggests that the Vim-SMA connection is relevant to the underlying pathophysiology of ET, and inhibition of the SMA may be an effective therapeutic approach.
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Affiliation(s)
- Gonzalo Revuelta
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Corinne McGill
- Department of Neuroscience, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Jens H Jensen
- Department of Neuroscience, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Leonardo Bonilha
- Department of Neurology, College of Medicine, Medical University of South Carolina, Charleston, SC, USA
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26
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Graziano RC, Bruce SE, Paul RH, Korgaonkar MS, Williams LM. The effects of bullying in depression on white matter integrity. Behav Brain Res 2019; 363:149-154. [PMID: 30710613 DOI: 10.1016/j.bbr.2019.01.054] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2018] [Revised: 12/21/2018] [Accepted: 01/29/2019] [Indexed: 11/19/2022]
Abstract
Individuals with elevated symptoms of depression exhibit alterations in white matter integrity, including lower fractional anisotropy (FA) evident on diffusion tensor imaging (DTI). Similarly, individuals with a history of early life stress (ELS) exhibit lower FA in the white matter independent of concurrent depression. Prior studies have not determined whether the neuroimaging signature of comorbid ELS and adult depression differs from the pattern of brain white matter changes associated with depression in the absence of self-reported ELS. The current study examined FA in multiple white matter tracts in 186 adults (93 males; 93 females) with a current diagnosis of major depressive disorder, including 88 who reported a history of bullying before the age of 18 (43 males; 45 females). All patients were antidepressant medication free at the time of testing. After adjusting for demographics and other ELS subtypes, participants with a history of bullying exhibited increased FA in the right medial lemniscus (p =.039) and left posterior corona radiata (p =.008) compared to participants with depression but no self-reported history of bullying. Both groups endorsed similar levels of depression. Group differences were most pronounced among individuals who endorsed bullying in late adolescence (14-17 years of age). Results suggest bullying in late adolescence is uniquely related to abnormal brain microstructure among individuals with current diagnoses of depression, possibly due to an overactive fear response. Further work is needed to differentiate why ELS within bullying is associated with higher FA.
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Affiliation(s)
| | | | | | - Mayuresh S Korgaonkar
- Discipline of Psychiatry, Sydney Medical School, The University of Sydney, NSW, Australia; Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Westmead, NSW, Australia
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27
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McKinnon ET, Fridriksson J, Basilakos A, Hickok G, Hillis AE, Spampinato MV, Gleichgerrcht E, Rorden C, Jensen JH, Helpern JA, Bonilha L. Types of naming errors in chronic post-stroke aphasia are dissociated by dual stream axonal loss. Sci Rep 2018; 8:14352. [PMID: 30254222 PMCID: PMC6156587 DOI: 10.1038/s41598-018-32457-4] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 09/03/2018] [Indexed: 11/09/2022] Open
Abstract
The types of errors during speech production can vary across individuals with chronic post-stroke aphasia, possibly due to the location and extent of brain damage. In this study, we evaluated the relationship between semantic vs. phonemic errors during confrontational naming, and their relationship with the degree of damage to ventral and dorsal white matter pathways extending beyond the necrotic stroke lesion. Based on the dual stream model of language processing, we tested the hypothesis that semantic errors would be associated with ventral stream damage, whereas phonemic errors would be associated with dorsal stream damage, but not vice-versa. Multi-shell diffusion MRI was used to obtain kurtosis-based white matter tractography from 32 chronic stroke survivors. Using diffusion microstructural tissue modeling, we estimated axonal loss along the length of the inferior and superior longitudinal fasciculi (ILF and SLF), representing the main pathways in the ventral and dorsal streams, respectively. The frequency of semantic paraphasias was strongly associated with ILF axonal loss, whereas phonemic paraphasias were strongly associated with SLF axonal loss, but not vice versa. This dissociation between semantic and phonological processing is in agreement with the dual stream model of language processing and corroborates the concept that, during speech production, knowledge association (semantics) depends on the integrity of ventral, whereas form encoding (phonological encoding) is more localized to dorsal pathways. These findings also demonstrate the importance of the residual integrity of specific white matter pathways beyond regional gray matter damage for speech production.
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Affiliation(s)
- Emilie T McKinnon
- Department of Neurology, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA
- Center for Biomedical Imaging, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA
- Department of Neuroscience, Medical University of South Carolina, 173 Ashley Avenue, Charleston, SC, 29425, USA
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, 921 Assembly Street, Columbia, SC, 29208, USA
| | - Alexandra Basilakos
- Department of Communication Sciences and Disorders, University of South Carolina, 921 Assembly Street, Columbia, SC, 29208, USA
| | - Gregory Hickok
- Department of Cognitive Sciences, Center for Language Science and Center for Cognitive Neuroscience, University of California, 2201 Social & Behavioral Sciences Gateway Building, Irvine, CA, 92697, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins University, 725 N Wolfe St, Baltimore, MD, 21205, USA
| | - M Vittoria Spampinato
- Department of Radiology and Radiological Science, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA
| | - Ezequiel Gleichgerrcht
- Department of Neurology, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA
| | - Chris Rorden
- Department of Psychology, University of South Carolina, 1512 Pendelton Street, Columbia, SC, 29208, USA
| | - Jens H Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA
- Department of Neuroscience, Medical University of South Carolina, 173 Ashley Avenue, Charleston, SC, 29425, USA
- Department of Radiology and Radiological Science, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA
| | - Joseph A Helpern
- Department of Neurology, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA
- Center for Biomedical Imaging, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA
- Department of Neuroscience, Medical University of South Carolina, 173 Ashley Avenue, Charleston, SC, 29425, USA
- Department of Radiology and Radiological Science, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA.
- Center for Biomedical Imaging, Medical University of South Carolina, 96 Jonathan Lucas St, Charleston, SC, 29425, USA.
- Department of Neuroscience, Medical University of South Carolina, 173 Ashley Avenue, Charleston, SC, 29425, USA.
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Diffusion kurtosis imaging as a neuroimaging biomarker in patients with carbon monoxide intoxication. Neurotoxicology 2018; 68:38-46. [PMID: 30017424 DOI: 10.1016/j.neuro.2018.07.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 06/10/2018] [Accepted: 07/02/2018] [Indexed: 11/23/2022]
Abstract
Attempting suicide by burning charcoal can lead to carbon monoxide (CO) intoxication and cognitive deficits. Changes in white matter (WM) quantified by diffusion tensor imaging (DTI)-derived parameters have been validated to reflect cognitive test scores. As diffusion kurtosis imaging (DKI) measures biological microstructures using non-Gaussian diffusivity, we assessed the added-information of DKI with neuropsychological test scores as the major outcome measure. A total of 45 patients were enrolled and compared with 30 age-matched controls. The patients were stratified into acute or chronic phase according to the intervals of intoxication and assessments. WM status was assessed using tract-based spatial statistics for DKI and DTI topographies, and the sensitivity/specificity of either model was tested using area under the curve (AUC) analysis. To evaluate their clinical significance, values of DKI- and DTI-derived parameters were extracted from seven regions of interest (ROI) and correlated with neuropsychiatric scores. The kurtosis parameters were lower in the patients than in the controls but none of the parameters provided differentiations between the acute or chronic phase. Kurtosis fractional anisotropy (KFA) had a higher AUC than fractional anisotropy while the other 3 DTI parameters had higher AUC than the corresponding DKI ones. In clinical correlations, KFA value of right posterior WM correlated with visual memory (r = 0.326, p = 0.029), and KFA values of bilateral posterior WM correlated with the digit forward score (right: r = 0.302, p = 0.043; left: r = 0.314, p = 0.036). Although DTI was more sensitive in reflecting disease status, KFA may be more sensitive and specific than fractional anisotropy in cognitive test score predictions.
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Münnich T, Klein J, Hattingen E, Noack A, Herrmann E, Seifert V, Senft C, Forster MT. Tractography Verified by Intraoperative Magnetic Resonance Imaging and Subcortical Stimulation During Tumor Resection Near the Corticospinal Tract. Oper Neurosurg (Hagerstown) 2018; 16:197-210. [DOI: 10.1093/ons/opy062] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2017] [Accepted: 03/08/2018] [Indexed: 02/07/2023] Open
Abstract
Abstract
BACKGROUND
Tractography is a popular tool for visualizing the corticospinal tract (CST). However, results may be influenced by numerous variables, eg, the selection of seeding regions of interests (ROIs) or the chosen tracking algorithm.
OBJECTIVE
To compare different variable sets by correlating tractography results with intraoperative subcortical stimulation of the CST, correcting intraoperative brain shift by the use of intraoperative MRI.
METHODS
Seeding ROIs were created by means of motor cortex segmentation, functional MRI (fMRI), and navigated transcranial magnetic stimulation (nTMS). Based on these ROIs, tractography was run for each patient using a deterministic and a probabilistic algorithm. Tractographies were processed on pre- and postoperatively acquired data.
RESULTS
Using a linear mixed effects statistical model, best correlation between subcortical stimulation intensity and the distance between tractography and stimulation sites was achieved by using the segmented motor cortex as seeding ROI and applying the probabilistic algorithm on preoperatively acquired imaging sequences. Tractographies based on fMRI or nTMS results differed very little, but with enlargement of positive nTMS sites the stimulation-distance correlation of nTMS-based tractography improved.
CONCLUSION
Our results underline that the use of tractography demands for careful interpretation of its virtual results by considering all influencing variables.
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Affiliation(s)
- Timo Münnich
- Department of Neurosurgery, Goet-he University Hospital, Frankfurt am Main, Germany
| | - Jan Klein
- Fraunhofer MEVIS, Institute for Medical Image Computing, Bremen, Germany
| | - Elke Hattingen
- Department of Neuroradiology, Goethe University Hospital, Frankfurt am Main, Germa-ny
| | - Anika Noack
- Department of Neurosurgery, Goet-he University Hospital, Frankfurt am Main, Germany
| | - Eva Herrmann
- Institute for Biostatistics and Math-ematical Modelling, Goethe-University Hospital, Frankfurt am Main, Germany
| | - Volker Seifert
- Department of Neurosurgery, Goet-he University Hospital, Frankfurt am Main, Germany
| | - Christian Senft
- Department of Neurosurgery, Goet-he University Hospital, Frankfurt am Main, Germany
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30
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Leote J, Nunes RG, Cerqueira L, Loução R, Ferreira HA. Reconstruction of white matter fibre tracts using diffusion kurtosis tensor imaging at 1.5T: Pre-surgical planning in patients with gliomas. Eur J Radiol Open 2018; 5:20-23. [PMID: 29719853 PMCID: PMC5926250 DOI: 10.1016/j.ejro.2018.01.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2017] [Accepted: 01/18/2018] [Indexed: 12/04/2022] Open
Abstract
Tractography studies for pre-surgical planning of primary brain tumors is typically done using diffusion tensor imaging (DTI), which cannot resolve crossing, kissing or highly angulated fibres. Tractography based on the estimation of the diffusion kurtosis (DK) tensor was recently demonstrated to enable tackling these limitations. However, its use in the clinical context at low 1.5T field has not yet been reported. PURPOSE To evaluate if the estimation of whole-brain tractography using the DK tensor is feasible for pre-surgical investigation of patients with brain tumors at 1.5T. METHODS Eight healthy subjects and 3 patients with brain tumors were scanned at 1.5T using a 12-channel head coil. Diffusion-weighted images were acquired with repetition/echo times of 5800/107 ms, 82 × 82 resolution, 3 × 3 × 3 mm3 voxel size, b-values of 0, 1000, 2000 s/mm2 and 64 gradient sensitising directions. Whole-brain tractography was estimated using the DK tensor and corticospinal tracts (CST) were isolated using regions-of-interest placed at the cerebral peduncles and motor gyrus. Tract size, DK metrics and CST deviation index (highest curvature point) were compared between healthy subjects and patients. RESULTS Tract sizes did not differ between groups. The CST deviation index was significantly higher in patients compared to healthy subjects. Fractional anisotropy was significantly lower in patients, with higher mean kurtosis asymmetry index at the highest curvature point in patients. CONCLUSIONS Corticospinal fibre bundles estimated using DK tensor in a 1.5T scanner presented similar properties in patients with brain gliomas as those reported in the literature using DTI-based tractography.
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Affiliation(s)
- Joao Leote
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal
- Neurosurgery Department, Hospital Garcia de Orta, Almada, Portugal
| | - Rita G. Nunes
- Institute for Systems and Robotics (LARSyS) and Department of Bioengineering, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal
| | - Luis Cerqueira
- Neuroradiology Department, Centro Hospitalar Lisboa Central, Lisbon, Portugal
| | - Ricardo Loução
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal
| | - Hugo A. Ferreira
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, Lisbon, Portugal
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31
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Salama GR, Heier LA, Patel P, Ramakrishna R, Magge R, Tsiouris AJ. Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma-Foundations and Future. Front Neurol 2018; 8:660. [PMID: 29403420 PMCID: PMC5786563 DOI: 10.3389/fneur.2017.00660] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 11/22/2017] [Indexed: 01/20/2023] Open
Abstract
In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes.
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Affiliation(s)
- Gayle R Salama
- Department of Neuroradiology, Weill Cornell Medical College, New York, NY, United States
| | - Linda A Heier
- Department of Neuroradiology, Weill Cornell Medical College, New York, NY, United States
| | - Praneil Patel
- Department of Neuroradiology, Weill Cornell Medical College, New York, NY, United States
| | - Rohan Ramakrishna
- Department of Neurological Surgery, Weill Cornell Medical College, New York, NY, United States
| | - Rajiv Magge
- Department of Neurology, Weill Cornell Medical College, New York, NY, United States
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32
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Mohanty V, McKinnon ET, Helpern JA, Jensen JH. Comparison of cumulant expansion and q-space imaging estimates for diffusional kurtosis in brain. Magn Reson Imaging 2018; 48:80-88. [PMID: 29306048 DOI: 10.1016/j.mri.2017.12.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Accepted: 12/29/2017] [Indexed: 12/31/2022]
Abstract
PURPOSE To compare estimates for the diffusional kurtosis in brain as obtained from a cumulant expansion (CE) of the diffusion MRI (dMRI) signal and from q-space (QS) imaging. THEORY AND METHODS For the CE estimates of the kurtosis, the CE was truncated to quadratic order in the b-value and fit to the dMRI signal for b-values from 0 up to 2000s/mm2. For the QS estimates, b-values ranging from 0 up to 10,000s/mm2 were used to determine the diffusion displacement probability density function (dPDF) via Stejskal's formula. The kurtosis was then calculated directly from the second and fourth order moments of the dPDF. These two approximations were studied for in vivo human data obtained on a 3T MRI scanner using three orthogonal diffusion encoding directions. RESULTS The whole brain mean values for the CE and QS kurtosis estimates differed by 16% or less in each of the considered diffusion encoding directions, and the Pearson correlation coefficients all exceeded 0.85. Nonetheless, there were large discrepancies in many voxels, particularly those with either very high or very low kurtoses relative to the mean values. CONCLUSION Estimates of the diffusional kurtosis in brain obtained using CE and QS approximations are strongly correlated, suggesting that they encode similar information. However, for the choice of b-values employed here, there may be substantial differences, depending on the properties of the diffusion microenvironment in each voxel.
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Affiliation(s)
- Vaibhav Mohanty
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
| | - Emilie T McKinnon
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Joseph A Helpern
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | - Jens H Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA.
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33
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Olson DV, Arpinar VE, Muftuler LT. Assessing diffusion kurtosis tensor estimation methods using a digital brain phantom derived from human connectome project data. Magn Reson Imaging 2018; 48:122-128. [PMID: 29305126 DOI: 10.1016/j.mri.2017.12.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Accepted: 12/29/2017] [Indexed: 11/19/2022]
Abstract
PURPOSE Diffusion kurtosis imaging (DKI) has gained popularity in recent years as an advanced diffusion-weighted MRI technique. This work aims to quantitatively compare the performance and accuracy of four DKI processing algorithms. For this purpose, a digital DKI brain phantom is developed. METHODS Data from the Human Connectome Project database were used to generate a DKI digital phantom. In a Monte Carlo Rician noise simulation, four DKI processing algorithms were compared based on their mean squared error, squared bias, and variance. RESULTS Algorithm performance was region-dependent and differed for each diffusion metric and noise level. Crossover between variance and squared bias error occurred between signal-to-noise ratios of 30 and 40. CONCLUSION Through the framework presented here, DKI algorithms can be quantitatively compared via a ground truth data set. Error maps are critical as algorithm performance varies spatially. Bias-plus-variance decomposition provides a more complete picture than MSE alone. In combination with refinements in acquisition in future studies, the accuracy and efficiency of DKI will continue to improve promoting clinical adoption.
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Affiliation(s)
- Daniel V Olson
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, USA.
| | - Volkan E Arpinar
- Department of Radiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - L Tugan Muftuler
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
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34
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McKinnon ET, Fridriksson J, Glenn GR, Jensen JH, Helpern JA, Basilakos A, Rorden C, Shih AY, Spampinato MV, Bonilha L. Structural plasticity of the ventral stream and aphasia recovery. Ann Neurol 2017. [PMID: 28628946 DOI: 10.1002/ana.24983] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Restrengthening of the residual language network is likely to be crucial for speech recovery in poststroke aphasia. Eight participants with chronic aphasia received intensive speech therapy for 3 weeks, with standardized naming tests and brain magnetic resonance imaging before and after therapy. Kurtosis-based diffusion tensor tractography was used to measure mean kurtosis (MK) along a segment of the inferior longitudinal fasciculus (ILF). Therapy-related reduction in the number of semantic but not phonemic errors was associated with strengthening (renormalization) of ILF MK (r = -0.90, p < 0.05 corrected), suggesting that speech recovery is related to structural plasticity of language-specific components of the residual language network. Ann Neurol 2017;82:147-151.
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Affiliation(s)
- Emilie T McKinnon
- Department of Neurology, Medical University of South Carolina, Charleston, SC.,Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC.,Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC
| | - Julius Fridriksson
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | - G Russell Glenn
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC.,Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC.,Department of Neuroscience, Medical University of South Carolina, Charleston, SC
| | - Jens H Jensen
- Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC.,Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC
| | - Joseph A Helpern
- Department of Neurology, Medical University of South Carolina, Charleston, SC.,Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC.,Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC.,Department of Neuroscience, Medical University of South Carolina, Charleston, SC
| | - Alexandra Basilakos
- Department of Communication Sciences and Disorders, University of South Carolina, Columbia, SC
| | - Chris Rorden
- Department of Psychology, University of South Carolina, Columbia, SC
| | - Andy Y Shih
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC
| | - M Vittoria Spampinato
- Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, SC
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35
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Li D, Wang X. Application value of diffusional kurtosis imaging (DKI) in evaluating microstructural changes in the spinal cord of patients with early cervical spondylotic myelopathy. Clin Neurol Neurosurg 2017; 156:71-76. [DOI: 10.1016/j.clineuro.2017.03.015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2016] [Revised: 02/13/2017] [Accepted: 03/17/2017] [Indexed: 11/29/2022]
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36
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Liu W, Gu R, Zhu Q, Xiao C, Huang L, Zhuang X, Zhang J, Liu L, Ma B, Yang H, Ma J, Hu Z, Tang C, Zhao S, Chen X. Rapid fluorescence imaging of spinal cord following epidural administration of a nerve-highlighting fluorophore. Am J Cancer Res 2017. [PMID: 28638473 PMCID: PMC5479274 DOI: 10.7150/thno.18962] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Iatrogenic spinal cord injury (SCI) is the most devastating complication of spine surgery, which usually results in permanent and serious disabilities of patients. Improvement of the visualization and discrimination of the spinal cord is critical for accuracy and safety during surgery; however, to date, there is no suitable technology to fulfill this clinical need. Here, we first show an efficient and rapid fluorescence imaging of the spinal cord in rabbit by epidural administration of a nerve-highlighting fluorophore, i.e. (E, E)-1,4-bis(p-aminostryl)-2-methoxy benzene (BMB). The BMB is firstly encapsulated into polymeric micelles to form a BMB-micelle (BMB-m) formulation with well-dispersion in normal saline solution. After epidural administration of BMB-m, BMB is transported by the flow of cerebrospinal fluid (CSF) and binds to the peripheral region of the white matter thus facilitating rapid staining of the spinal cord. Furthermore, this BMB imaging technology also holds great potential for visually monitoring the integrity of the spinal cord in real time and promptly identifying acute SCI during spine surgery.
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37
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Leh SE, Schroeder C, Chen JK, Mallar Chakravarty M, Park MTM, Cheung B, Huntgeburth SC, Gosselin N, Hock C, Ptito A, Petrides M. Microstructural Integrity of Hippocampal Subregions Is Impaired after Mild Traumatic Brain Injury. J Neurotrauma 2017; 34:1402-1411. [DOI: 10.1089/neu.2016.4591] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Affiliation(s)
- Sandra E. Leh
- Institute for Regenerative Medicine, University of Zurich, Switzerland
| | - Clemens Schroeder
- Institute for Regenerative Medicine, University of Zurich, Switzerland
| | - Jen-Kai Chen
- Cognitive Neuroscience Unit, Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Psychology, McGill University Health Centre, Montreal, Quebec, Canada
| | - M. Mallar Chakravarty
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- Departments of Psychiatry and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Min Tae M. Park
- Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Bob Cheung
- Defense Research and Development Canada (DRDC) Toronto, Ontario, Canada
| | - Sonja C. Huntgeburth
- Cognitive Neuroscience Unit, Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Psychology, McGill University, Montreal, Quebec, Canada
| | - Nadia Gosselin
- Research Center, Hôpital du Sacré-Coeur de Montréal, Montreal, Quebec, Canada
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Switzerland
| | - Alain Ptito
- Cognitive Neuroscience Unit, Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Psychology, McGill University Health Centre, Montreal, Quebec, Canada
| | - Michael Petrides
- Cognitive Neuroscience Unit, Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Psychology, McGill University, Montreal, Quebec, Canada
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38
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Yu F, Shukla DK, Armstrong RC, Marion CM, Radomski KL, Selwyn RG, Dardzinski BJ. Repetitive Model of Mild Traumatic Brain Injury Produces Cortical Abnormalities Detectable by Magnetic Resonance Diffusion Imaging, Histopathology, and Behavior. J Neurotrauma 2016; 34:1364-1381. [PMID: 27784203 PMCID: PMC5385606 DOI: 10.1089/neu.2016.4569] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Noninvasive detection of mild traumatic brain injury (mTBI) is important for evaluating acute through chronic effects of head injuries, particularly after repetitive impacts. To better detect abnormalities from mTBI, we performed longitudinal studies (baseline, 3, 6, and 42 days) using magnetic resonance diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) in adult mice after repetitive mTBI (r-mTBI; daily × 5) or sham procedure. This r-mTBI produced righting reflex delay and was first characterized in the corpus callosum to demonstrate low levels of axon damage, astrogliosis, and microglial activation, without microhemorrhages. High-resolution DTI-DKI was then combined with post-imaging pathological validation along with behavioral assessments targeted for the impact regions. In the corpus callosum, only DTI fractional anisotropy at 42 days showed significant change post-injury. Conversely, cortical regions under the impact site (M1–M2, anterior cingulate) had reduced axial diffusivity (AD) at all time points with a corresponding increase in axial kurtosis (Ka) at 6 days. Post-imaging neuropathology showed microglial activation in both the corpus callosum and cortex at 42 days after r-mTBI. Increased cortical microglial activation correlated with decreased cortical AD after r-mTBI (r = −0.853; n = 5). Using Thy1-YFP-16 mice to fluorescently label neuronal cell bodies and processes revealed low levels of axon damage in the cortex after r-mTBI. Finally, r-mTBI produced social deficits consistent with the function of this anterior cingulate region of cortex. Overall, vulnerability of cortical regions is demonstrated after mild repetitive injury, with underlying differences of DTI and DKI, microglial activation, and behavioral deficits.
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Affiliation(s)
- Fengshan Yu
- 1 Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences , Bethesda, Maryland.,2 Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences , Bethesda, Maryland
| | - Dinesh K Shukla
- 1 Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences , Bethesda, Maryland.,5 Department of Psychiatry, University of Maryland School of Medicine , Baltimore, Maryland
| | - Regina C Armstrong
- 1 Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences , Bethesda, Maryland.,2 Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences , Bethesda, Maryland.,3 Program in Neuroscience, Uniformed Services University of the Health Sciences , Bethesda, Maryland
| | - Christina M Marion
- 1 Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences , Bethesda, Maryland.,3 Program in Neuroscience, Uniformed Services University of the Health Sciences , Bethesda, Maryland
| | - Kryslaine L Radomski
- 1 Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences , Bethesda, Maryland.,2 Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences , Bethesda, Maryland
| | - Reed G Selwyn
- 1 Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences , Bethesda, Maryland.,6 Department of Radiology, University of New Mexico , Albuquerque, New Mexico
| | - Bernard J Dardzinski
- 1 Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences , Bethesda, Maryland.,4 Department of Radiology and Radiological Sciences, Uniformed Services University of the Health Sciences , Bethesda, Maryland
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