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Madzime J, Jankiewicz M, Meintjes EM, Torre P, Laughton B, van der Kouwe AJW, Holmes M. Reduced white matter maturation in the central auditory system of children living with HIV. FRONTIERS IN NEUROIMAGING 2024; 3:1341607. [PMID: 38510428 PMCID: PMC10951401 DOI: 10.3389/fnimg.2024.1341607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 02/15/2024] [Indexed: 03/22/2024]
Abstract
Introduction School-aged children experience crucial developmental changes in white matter (WM) in adolescence. The human immunodeficiency virus (HIV) affects neurodevelopment. Children living with perinatally acquired HIV (CPHIVs) demonstrate hearing and neurocognitive impairments when compared to their uninfected peers (CHUUs), but investigations into the central auditory system (CAS) WM integrity are lacking. The integration of the CAS and other brain areas is facilitated by WM fibers whose integrity may be affected in the presence of HIV, contributing to neurocognitive impairments. Methods We used diffusion tensor imaging (DTI) tractography to map the microstructural integrity of WM between CAS regions, including the lateral lemniscus and acoustic radiation, as well as between CAS regions and non-auditory regions of 11-year-old CPHIVs. We further employed a DTI-based graph theoretical framework to investigate the nodal strength and efficiency of the CAS and other brain regions in the structural brain network of the same population. Finally, we investigated associations between WM microstructural integrity outcomes and neurocognitive outcomes related to auditory and language processing. We hypothesized that compared to the CHUU group, the CPHIV group would have lower microstructural in the CAS and related regions. Results Our analyses showed higher mean diffusivity (MD), a marker of axonal maturation, in the lateral lemniscus and acoustic radiations, as well as WM between the CAS and non-auditory regions predominantly in frontotemporal areas. Most affected WM connections also showed higher axial and radial diffusivity (AD and RD, respectively). There were no differences in the nodal properties of the CAS regions between groups. The MD of frontotemporal and subcortical WM-connected CAS regions, including the inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, and internal capsule showed negative associations with sequential processing in the CPHIV group but not in the CHUU group. Discussion The current results point to reduced axonal maturation in WM, marked by higher MD, AD, and RD, within and from the CAS. Furthermore, alterations in WM integrity were associated with sequential processing, a neurocognitive marker of auditory working memory. Our results provide insights into the microstructural integrity of the CAS and related WM in the presence of HIV and link these alterations to auditory working memory.
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Affiliation(s)
- Joanah Madzime
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Marcin Jankiewicz
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
| | - Ernesta M. Meintjes
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
| | - Peter Torre
- School of Speech, Language, and Hearing Sciences, College of Health and Human Services, San Diego, CA, United States
| | - Barbara Laughton
- Family Centre for Research with Ubuntu, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, South Africa
| | - Andre J. W. van der Kouwe
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
| | - Martha Holmes
- Biomedical Engineering Research Centre, Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
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López-Ornelas A, Escobedo-Avila I, Ramírez-García G, Lara-Rodarte R, Meléndez-Ramírez C, Urrieta-Chávez B, Barrios-García T, Cáceres-Chávez VA, Flores-Ponce X, Carmona F, Reynoso CA, Aguilar C, Kerik NE, Rocha L, Verdugo-Díaz L, Treviño V, Bargas J, Ramos-Mejía V, Fernández-Ruiz J, Campos-Romo A, Velasco I. Human Embryonic Stem Cell-Derived Immature Midbrain Dopaminergic Neurons Transplanted in Parkinsonian Monkeys. Cells 2023; 12:2738. [PMID: 38067166 PMCID: PMC10706241 DOI: 10.3390/cells12232738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 11/20/2023] [Accepted: 11/23/2023] [Indexed: 12/18/2023] Open
Abstract
Human embryonic stem cells (hESCs) differentiate into specialized cells, including midbrain dopaminergic neurons (DANs), and Non-human primates (NHPs) injected with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine develop some alterations observed in Parkinson's disease (PD) patients. Here, we obtained well-characterized DANs from hESCs and transplanted them into two parkinsonian monkeys to assess their behavioral and imaging changes. DANs from hESCs expressed dopaminergic markers, generated action potentials, and released dopamine (DA) in vitro. These neurons were transplanted bilaterally into the putamen of parkinsonian NHPs, and using magnetic resonance imaging techniques, we calculated the fractional anisotropy (FA) and mean diffusivity (MD), both employed for the first time for these purposes, to detect in vivo axonal and cellular density changes in the brain. Likewise, positron-emission tomography scans were performed to evaluate grafted DANs. Histological analyses identified grafted DANs, which were quantified stereologically. After grafting, animals showed signs of partially improved motor behavior in some of the HALLWAY motor tasks. Improvement in motor evaluations was inversely correlated with increases in bilateral FA. MD did not correlate with behavior but presented a negative correlation with FA. We also found higher 11C-DTBZ binding in positron-emission tomography scans associated with grafts. Higher DA levels measured by microdialysis after stimulation with a high-potassium solution or amphetamine were present in grafted animals after ten months, which has not been previously reported. Postmortem analysis of NHP brains showed that transplanted DANs survived in the putamen long-term, without developing tumors, in immunosuppressed animals. Although these results need to be confirmed with larger groups of NHPs, our molecular, behavioral, biochemical, and imaging findings support the integration and survival of human DANs in this pre-clinical PD model.
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Affiliation(s)
- Adolfo López-Ornelas
- Instituto de Fisiología Celular—Neurociencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (A.L.-O.); (I.E.-A.); (R.L.-R.); (C.M.-R.); (B.U.-C.); (V.A.C.-C.); (X.F.-P.); (J.B.)
- Laboratorio de Reprogramación Celular, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico
- División de Investigación, Hospital Juárez de México, Mexico City 07760, Mexico
| | - Itzel Escobedo-Avila
- Instituto de Fisiología Celular—Neurociencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (A.L.-O.); (I.E.-A.); (R.L.-R.); (C.M.-R.); (B.U.-C.); (V.A.C.-C.); (X.F.-P.); (J.B.)
- Laboratorio de Reprogramación Celular, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (L.V.-D.); (J.F.-R.)
- Unidad Periférica de Neurociencias, Facultad de Medicina, Universidad Nacional Autónoma de México, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico;
| | - Gabriel Ramírez-García
- Unidad Periférica de Neurociencias, Facultad de Medicina, Universidad Nacional Autónoma de México, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico;
| | - Rolando Lara-Rodarte
- Instituto de Fisiología Celular—Neurociencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (A.L.-O.); (I.E.-A.); (R.L.-R.); (C.M.-R.); (B.U.-C.); (V.A.C.-C.); (X.F.-P.); (J.B.)
- Laboratorio de Reprogramación Celular, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico
| | - César Meléndez-Ramírez
- Instituto de Fisiología Celular—Neurociencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (A.L.-O.); (I.E.-A.); (R.L.-R.); (C.M.-R.); (B.U.-C.); (V.A.C.-C.); (X.F.-P.); (J.B.)
- Laboratorio de Reprogramación Celular, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico
| | - Beetsi Urrieta-Chávez
- Instituto de Fisiología Celular—Neurociencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (A.L.-O.); (I.E.-A.); (R.L.-R.); (C.M.-R.); (B.U.-C.); (V.A.C.-C.); (X.F.-P.); (J.B.)
- Laboratorio de Reprogramación Celular, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico
| | - Tonatiuh Barrios-García
- Escuela de Medicina y Ciencias de la Salud, Tecnológico de Monterrey, Monterrey 64710, Mexico; (T.B.-G.); (V.T.)
| | - Verónica A. Cáceres-Chávez
- Instituto de Fisiología Celular—Neurociencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (A.L.-O.); (I.E.-A.); (R.L.-R.); (C.M.-R.); (B.U.-C.); (V.A.C.-C.); (X.F.-P.); (J.B.)
| | - Xóchitl Flores-Ponce
- Instituto de Fisiología Celular—Neurociencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (A.L.-O.); (I.E.-A.); (R.L.-R.); (C.M.-R.); (B.U.-C.); (V.A.C.-C.); (X.F.-P.); (J.B.)
- Laboratorio de Reprogramación Celular, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico
| | - Francia Carmona
- Departamento de Farmacobiología, Centro de Investigación y de Estudios Avanzados del IPN (Cinvestav), Mexico City 07360, Mexico; (F.C.); (L.R.)
| | - Carlos Alberto Reynoso
- Molecular Imaging PET-CT Unit, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico; (C.A.R.); (C.A.); (N.E.K.)
| | - Carlos Aguilar
- Molecular Imaging PET-CT Unit, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico; (C.A.R.); (C.A.); (N.E.K.)
| | - Nora E. Kerik
- Molecular Imaging PET-CT Unit, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico; (C.A.R.); (C.A.); (N.E.K.)
| | - Luisa Rocha
- Departamento de Farmacobiología, Centro de Investigación y de Estudios Avanzados del IPN (Cinvestav), Mexico City 07360, Mexico; (F.C.); (L.R.)
| | - Leticia Verdugo-Díaz
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (L.V.-D.); (J.F.-R.)
| | - Víctor Treviño
- Escuela de Medicina y Ciencias de la Salud, Tecnológico de Monterrey, Monterrey 64710, Mexico; (T.B.-G.); (V.T.)
| | - José Bargas
- Instituto de Fisiología Celular—Neurociencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (A.L.-O.); (I.E.-A.); (R.L.-R.); (C.M.-R.); (B.U.-C.); (V.A.C.-C.); (X.F.-P.); (J.B.)
| | - Verónica Ramos-Mejía
- Gene Regulation, Stem Cells, and Development Group, GENYO-Centre for Genomics and Oncological Research Pfizer, University of Granada, Andalusian Regional Government, PTS, 18016 Granada, Spain;
| | - Juan Fernández-Ruiz
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (L.V.-D.); (J.F.-R.)
| | - Aurelio Campos-Romo
- Departamento de Fisiología, Facultad de Medicina, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (L.V.-D.); (J.F.-R.)
- Unidad Periférica de Neurociencias, Facultad de Medicina, Universidad Nacional Autónoma de México, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico;
| | - Iván Velasco
- Instituto de Fisiología Celular—Neurociencias, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico; (A.L.-O.); (I.E.-A.); (R.L.-R.); (C.M.-R.); (B.U.-C.); (V.A.C.-C.); (X.F.-P.); (J.B.)
- Laboratorio de Reprogramación Celular, Instituto Nacional de Neurología y Neurocirugía Manuel Velasco Suárez, Mexico City 14269, Mexico
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Murray KD, Tivarus ME, Schifitto G, Uddin MN, Zhong J. Brain iron imaging markers in the presence of white matter hyperintensities. Magn Reson Imaging 2023; 98:115-123. [PMID: 36682396 PMCID: PMC9968496 DOI: 10.1016/j.mri.2023.01.021] [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: 06/06/2022] [Revised: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 01/21/2023]
Abstract
PURPOSE To investigate the relationship between pathological brain iron deposition and white matter hyperintensities (WMHs) in cerebral small vessel disease (CSVD), via Monte Carlo simulations of magnetic susceptibility imaging and the development of a novel imaging marker called the Expected Iron Coefficient (EIC). METHODS A synthetic pathological model of a different number of impenetrable spheres at random locations was employed to represent pathological iron deposition. The diffusion process was simulated with a Monte Carlo method with adjustable parameters to manipulate sphere size, distribution, and extracellular properties. Quantitative susceptibility mapping (QSM) was performed in a clinical dataset to study CSVD to derive and evaluate QSM, R2*, the iron microenvironment coefficient (IMC), and the EIC in the presence of WMHs. RESULTS The simulations show that QSM signals increase in the presence of increased tissue iron, confirming that the EIC increases with pathology. Clinical results demonstrate that while QSM, R2*, and the IMC do not show significant differences in brain iron, the EIC does in the context of CSVD. CONCLUSION The EIC is more sensitive to subtle changes in brain iron deposition caused by pathology, even when QSM, R2*, and the IMC fail.
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Affiliation(s)
- Kyle D Murray
- Department of Physics and Astronomy, University of Rochester, Rochester, NY, USA
| | - Madalina E Tivarus
- Department of Imaging Sciences, University of Rochester, Rochester, NY, USA; Department of Neuroscience, University of Rochester, Rochester, NY, USA
| | - Giovanni Schifitto
- Department of Imaging Sciences, University of Rochester, Rochester, NY, USA; Department of Neurology, University of Rochester, Rochester, NY, USA; Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA
| | - Md Nasir Uddin
- Department of Neurology, University of Rochester, Rochester, NY, USA
| | - Jianhui Zhong
- Department of Physics and Astronomy, University of Rochester, Rochester, NY, USA; Department of Imaging Sciences, University of Rochester, Rochester, NY, USA; Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA.
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Foesleitner O, Knop KC, Lindenau M, Preisner F, Bäumer P, Heiland S, Bendszus M, Kronlage M. Quantitative MR Neurography in Multifocal Motor Neuropathy and Amyotrophic Lateral Sclerosis. Diagnostics (Basel) 2023; 13:diagnostics13071237. [PMID: 37046455 PMCID: PMC10093201 DOI: 10.3390/diagnostics13071237] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 03/19/2023] [Indexed: 03/29/2023] Open
Abstract
Background: The aim of this study was to assess the phenotype of multifocal motor neuropathy (MMN) and amyotrophic lateral sclerosis (ALS) in quantitative MR neurography. Methods: In this prospective study, 22 patients with ALS, 8 patients with MMN, and 10 healthy volunteers were examined with 3T MR neurography, using a high-resolution fat-saturated T2-weighted sequence, diffusion-tensor imaging (DTI), and a multi-echo T2-relaxometry sequence. The quantitative biomarkers fractional anisotropy (FA), radial and axial diffusivity (RD, AD), mean diffusivity (MD), cross-sectional area (CSA), T2-relaxation time, and proton spin density (PSD) were measured in the tibial nerve at the thigh and calf, and in the median, radial, and ulnar nerves at the mid-upper arm. Results: MMN showed a characteristic imaging pattern of decreased FA (p = 0.018), increased RD (p = 0.014), increased CSA (p < 0.001), increased T2-relaxation time (p < 0.001), and increased PSD (p = 0.025) in the upper arm nerves compared to ALS and controls. ALS patients did not differ from controls in any imaging marker, nor were there any group differences in the tibial nerve (p > 0.05). Conclusions: MMN shows a characteristic pattern of quantitative DTI and T2-relaxometry parameters in the upper-arm nerves, primarily indicating demyelination. Peripheral nerve changes in ALS seem to be below the detection level of current state-of-the-art quantitative MR neurography.
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Huang P, Zhang M. Magnetic Resonance Imaging Studies of Neurodegenerative Disease: From Methods to Translational Research. Neurosci Bull 2023; 39:99-112. [PMID: 35771383 PMCID: PMC9849544 DOI: 10.1007/s12264-022-00905-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 05/07/2022] [Indexed: 01/22/2023] Open
Abstract
Neurodegenerative diseases (NDs) have become a significant threat to an aging human society. Numerous studies have been conducted in the past decades to clarify their pathologic mechanisms and search for reliable biomarkers. Magnetic resonance imaging (MRI) is a powerful tool for investigating structural and functional brain alterations in NDs. With the advantages of being non-invasive and non-radioactive, it has been frequently used in both animal research and large-scale clinical investigations. MRI may serve as a bridge connecting micro- and macro-level analysis and promoting bench-to-bed translational research. Nevertheless, due to the abundance and complexity of MRI techniques, exploiting their potential is not always straightforward. This review aims to briefly introduce research progress in clinical imaging studies and discuss possible strategies for applying MRI in translational ND research.
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Affiliation(s)
- Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009 China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009 China
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Tallus J, Mohammadian M, Kurki T, Roine T, Posti JP, Tenovuo O. A comparison of diffusion tensor imaging tractography and constrained spherical deconvolution with automatic segmentation in traumatic brain injury. Neuroimage Clin 2023; 37:103284. [PMID: 36502725 PMCID: PMC9758569 DOI: 10.1016/j.nicl.2022.103284] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 10/20/2022] [Accepted: 12/05/2022] [Indexed: 12/12/2022]
Abstract
Detection of microstructural white matter injury in traumatic brain injury (TBI) requires specialised imaging methods, of which diffusion tensor imaging (DTI) has been extensively studied. Newer fibre alignment estimation methods, such as constrained spherical deconvolution (CSD), are better than DTI in resolving crossing fibres that are ubiquitous in the brain and may improve the ability to detect microstructural injuries. Furthermore, automatic tract segmentation has the potential to improve tractography reliability and accelerate workflow compared to the manual segmentation commonly used. In this study, we compared the results of deterministic DTI based tractography and manual tract segmentation with CSD based probabilistic tractography and automatic tract segmentation using TractSeg. 37 participants with a history of TBI (with Glasgow Coma Scale 13-15) and persistent symptoms, and 41 healthy controls underwent deterministic DTI-based tractography with manual tract segmentation and probabilistic CSD-based tractography with TractSeg automatic segmentation.Fractional anisotropy (FA) and mean diffusivity of corpus callosum and three bilateral association tracts were measured. FA and MD values derived from both tractography methods were generally moderately to strongly correlated. CSD with TractSeg differentiated the groups based on FA, while DTI did not. CSD and TractSeg-based tractography may be more sensitive in detecting microstructural changes associated with TBI than deterministic DTI tractography. Additionally, CSD with TractSeg was found to be applicable at lower b-value and number of diffusion-encoding gradients data than previously reported.
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Affiliation(s)
- Jussi Tallus
- Turku Brain Injury Center, Department of Clinical Neurosciences, University of Turku and Turku University Hospital, Hämeentie 11, Turku FI-20521, Finland; Department of Radiology, University of Turku and Turku University Hospital, Hämeentie 11, Turku FI-20521, Finland.
| | - Mehrbod Mohammadian
- Turku Brain Injury Center, Department of Clinical Neurosciences, University of Turku and Turku University Hospital, Hämeentie 11, Turku FI-20521, Finland
| | - Timo Kurki
- Turku Brain Injury Center, Department of Clinical Neurosciences, University of Turku and Turku University Hospital, Hämeentie 11, Turku FI-20521, Finland; Department of Radiology, University of Turku and Turku University Hospital, Hämeentie 11, Turku FI-20521, Finland
| | - Timo Roine
- Turku Brain and Mind Center, University of Turku, Turku FI-20014, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Rakentajanaukio 2 C, Espoo 02150, Finland
| | - Jussi P Posti
- Turku Brain Injury Center, Department of Clinical Neurosciences, University of Turku and Turku University Hospital, Hämeentie 11, Turku FI-20521, Finland; Neurocenter, Department of Neurosurgery, Turku University Hospital, University of Turku, Hämeentie 11, Turku FI-20521, Finland
| | - Olli Tenovuo
- Turku Brain Injury Center, Department of Clinical Neurosciences, University of Turku and Turku University Hospital, Hämeentie 11, Turku FI-20521, Finland
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Ridehalgh C, Fundaun J, Bremner S, Cercignani M, Young R, Trivedy C, Novak A, Greening J, Schmid A, Dilley A. Does peripheral neuroinflammation predict chronicity following whiplash injury? Protocol for a prospective cohort study. BMJ Open 2022; 12:e066021. [PMID: 36521884 PMCID: PMC9756191 DOI: 10.1136/bmjopen-2022-066021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 11/21/2022] [Indexed: 12/23/2022] Open
Abstract
INTRODUCTION Whiplash-associated disorder grade 2 (WAD2) is characterised by musculoskeletal pain/tenderness but no apparent nerve injury. However, studies have found clinical features indicative of neuropathy and neuropathic pain. These studies may indicate peripheral nerve inflammation, since preclinical neuritis models found mechanical sensitivity in inflamed, intact nociceptors. The primary aim of this study is to establish the contribution of peripheral neuroinflammation to WAD2 and its role in prognosis. Participants will be invited to participate in a sub-study investigating the contribution of cutaneous small fibre pathology to WAD2. METHODS AND ANALYSIS 115 participants within 1 month following whiplash injury and 34 healthy control participants will be recruited and complete validated questionnaires for pain, function and psychological factors. Data collection will take place at the Universities of Sussex and Oxford, UK. Clinical examination, quantitative sensory testing and blood samples will be undertaken. MRI scans using T2-weighted and diffusion tensor images of the brachial plexus and wrist will determine nerve inflammation and nerve structural changes. Skin biopsies from a substudy will determine structural integrity of dermal and intraepidermal nerve fibres. At 6 months, we will evaluate recovery using Neck Disability Index and a self-rated global recovery question and repeat the outcome measures. Regression analysis will identify differences in MRI parameters, clinical tests and skin biopsies between participants with WAD2 and age/gender-matched controls. Linear and logistic regression analyses will assess if nerve inflammation (MRI parameters) predicts poor outcome. Mixed effects modelling will compare MRI and clinical measures between recovered and non-recovered participants over time. ETHICS AND DISSEMINATION Ethical approval was received from London-Brighton and Sussex Research Ethics Committee (20/PR/0625) and South Central-Oxford C Ethics Committee (18/SC/0263). Written informed consent will be obtained from participants prior to participation in the study. Results will be disseminated through publications in peer-reviewed journals, presentations at national/international conferences and social media. TRIAL REGISTRATION NUMBER NCT04940923.
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Affiliation(s)
- Colette Ridehalgh
- Department of Neuroscience, Brighton and Sussex Medical School, Brighton, UK
- School of Sport and Health Sciences, University of Brighton, Eastbourne, UK
| | - Joel Fundaun
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stephen Bremner
- Department of Primary Care and Public Health, Brighton and Sussex Medical School, Brighton, UK
| | - Mara Cercignani
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
| | - Rupert Young
- School of engineering and informatics, University of Sussex, Brighton, UK
| | - Chetan Trivedy
- Emergency Departments, University Hospitals Sussex NHS Foundation Trust, Brighton, UK
- Queen Mary University of London, London, UK
| | - Alex Novak
- Emergency Medicine Research Oxford, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Jane Greening
- Department of Neuroscience, Brighton and Sussex Medical School, Brighton, UK
| | - Annina Schmid
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Andrew Dilley
- Department of Neuroscience, Brighton and Sussex Medical School, Brighton, UK
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Shinn R, Riffe A, Edwards M, Rossmeisl J. MRI diffusion tensor imaging scalar values in dogs with intervertebral disc herniation: A comparison between manual and semiautomated region of interest methods. Vet Radiol Ultrasound 2022; 63:753-762. [PMID: 35789512 DOI: 10.1111/vru.13126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 04/13/2022] [Accepted: 04/14/2022] [Indexed: 11/29/2022] Open
Abstract
Magnetic resonance imaging (MRI) diffusion tensor imaging (DTI) measures have been described as methods for quantifying spinal cord injury and predicting outcome in dogs with intervertebral disc herniation (IVDH); however, studies comparing methods for selecting regions of interest (ROIs) are currently lacking. The aims of this retrospective, methods comparison, observational study were to compare DTI measurements acquired using manual (mROI) versus semiautomated ROI (sROI) methods and to compare DTI measurements with patient outcomes. Magnetic resonance imaging scans that included DTI pulse sequences were retrieved for 65 dogs with confirmed IVDH. Regions of interest were placed at one vertebral length cranial and caudal to the region of spinal cord compression (RSCC) using the mROI and sROI methods. Scalar values based on the mROI and sROI methods were compared. There was a significant difference for all DTI measures (P < 0.0001), where fractional anisotropy was higher (95% confidence interval [CI]: 0.15, 0.19) and mean diffusivity (MD; CI: -0.41, -0.35), axial diffusivity (AD; CI: -0.47, -0.36) and radial diffusivity (RD; CI: -0.36, -0.27) were lower for the mROI than for the sROI. For both the mROI and sROI, MD, AD, and RD were significantly lower (p < 0.05) at the RSCC in paraplegic dogs that did not regain motor function. The findings indicated that DTI methods for quantifying SCI using open source software and ROI were feasible for use in dogs with IVDH; however, values based on sROI methods differed from values based on mROI methods. Some DTI measures based on both the mROI and sROI methods were predictive of poor patient outcome.
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Affiliation(s)
- Richard Shinn
- Department of Small Animal Clinical Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Ashley Riffe
- VCA Alameda East Veterinary Hospital, Denver, Colorado, USA
| | - Michael Edwards
- Department of Small Animal Clinical Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - John Rossmeisl
- Department of Small Animal Clinical Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
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Shao S, Guo T, Li F, Zhao Z, Li J, Wang X. Experimental study on the therapeutic effect of BDNF gene-carrying nanoparticles on traumatic brain injury. APPLIED NANOSCIENCE 2022. [DOI: 10.1007/s13204-022-02405-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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10
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Wu F, Ren Y, Wang W, Li C, Wang Y, Yang Y, Shen Y, Wang J, Yang J, Liu H. Microstructural Alteration of Lumbosacral Nerve Roots in Chronic Inflammatory Demyelinating Polyradiculoneuropathy: Insights From DTI and Correlations with Electrophysiological Parameters. Acad Radiol 2022; 29 Suppl 3:S175-S182. [PMID: 34642113 DOI: 10.1016/j.acra.2021.08.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 08/12/2021] [Accepted: 08/18/2021] [Indexed: 11/30/2022]
Abstract
RATIONALE AND OBJECTIVES To detect the diffusion characteristics of lumbosacral nerve roots in patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) and further to explore their correlations with electrophysiological parameters of lower extremity nerves. MATERIALS AND METHODS Eighteen CIDP patients and 18 age and sex-matched healthy volunteers were enrolled in this study from August 2019 to August 2020. Axial diffusion tensor imaging (DTI) of lumbosacral plexus was performed in all subjects and fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) of lumbosacral nerve roots were measured. Two-sample t test or Mann-Whitney U test was used to compare the difference of DTI parameters between two groups. Receiver operating characteristic curves were plotted to determine the diagnostic accuracy. All patients also underwent nerve conduction studies. Correlations between DTI parameters of lumbosacral nerve roots and electrophysiological parameters were analyzed with Pearson or Spearman coefficients. RESULTS CIDP patients showed significantly lower FA as well as higher AD, RD, and MD values of lumbosacral nerve roots (FA:0.24±0.054, 0.32±0.044; AD:2.31±0.256, 2.11±0.230 (×10-3mm2/s); RD:1.28±0.189, 1.13±0.106 (×10-3mm2/s); MD:1.68±0.268, 1.45±0.186 (×10-3mm2/s) in CIDP and control group, respectively, all p < 0.05). Receiver operating characteristic analysis showed among all DTI parameters, FA had the best diagnostic accuracy with an area under the curve of 0.914 and optimal cut-off value of 0.27. FA showed a positive correlation while RD showed a negative correlation with a conduction velocity of tibial and common peroneal nerves. RD also correlated positively with F-wave minimal latency of tibial nerves. CONCLUSION DTI can be used to assess the microstructure alterations of lumbosacral nerve roots in CIDP patients. FA and RD may serve as potential markers reflecting the conduction function of tibial and common peroneal nerves.
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Affiliation(s)
- Fei Wu
- Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai 20040, China
| | - Yan Ren
- Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai 20040, China
| | - Weiwei Wang
- Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai 20040, China
| | - Chong Li
- Department of Radiology, Shijiazhuang People's Hospital, Fangbei Rd, Shijiazhuang, 050000, China
| | - Yin Wang
- Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai 20040, China
| | - Yang Yang
- Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai 20040, China
| | - Yiyuan Shen
- Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai 20040, China
| | - Junlong Wang
- Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai 20040, China
| | - Jinming Yang
- Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai 20040, China
| | - Hanqiu Liu
- Department of Radiology, Huashan Hospital, Fudan University, 12 Middle Wulumuqi Rd, Shanghai 20040, China.
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11
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Liu Y, Liu C, Qin C, Zhang X, Feng H, Wang Z, Li J. Evaluation of the effect of myelotomy on nerve function in rats with spinal cord injury by diffusion tensor imaging. Acta Radiol 2021; 62:1666-1673. [PMID: 33287549 DOI: 10.1177/0284185120975182] [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: 11/17/2022]
Abstract
BACKGROUND Spinal cord injury (SCI) is a severe central nervous system injury that can generally induce different degrees of sensory and motor dysfunction. PURPOSE To clarify the changes of diffusion tensor imaging (DTI) parameters after spinal cord myelotomy in rats with SCI. MATERIAL AND METHODS Eighteen Sprague Dawley (SD) rats were randomly divided into the Sham group (n=6), SCI group (n=6), and Mye group (n=6), respectively. The DTI values at 1, 3, 7, and 21 days after modeling were collected by magnetic resonance imaging (MRI). The spinal specimen at the injury site was collected on the 21st day for Nissl's staining to assess the changes in neurons. RESULTS The fractional anisotropy (FA) values in both the SCI group and Mye group significantly decreased. In addition, the FA values between the two groups were statistically significant (P < 0.001). The apparent diffusion coefficient (ADC), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values all decreased and then increased (P < 0.001). Pearson correlation test showed that the ADC, MD, and AD values were positively correlated with the Basso Beattie Bresnahan (BBB) score. Nissl's staining showed a higher number of Nissl's bodies, and deep staining of Nissl's bodies in the Mye group, while the morphology of neurons was relatively good. The number of neurons in the Mye group was significantly higher after myelotomy compared to the SCI group (P < 0.001). CONCLUSION The DTI parameters, especially ADC values, could non-invasively and quantifiably evaluate the efficacy of myelotomy for rats with SCI.
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Affiliation(s)
- Yi Liu
- School of Rehabilitation Medicine, Capital Medical University, Beijing, PR China
- China Rehabilitation Science Institute, Beijing, PR China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, PR China
- Department of Spinal and Neural Functional Reconstruction, China Rehabilitation Research Center, Beijing, PR China
- Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, PR China
| | - Changbin Liu
- Department of Rehabilitation Medicine, Beijing Tiantan Hospital, Beijing, PR China
| | - Chuan Qin
- School of Rehabilitation Medicine, Capital Medical University, Beijing, PR China
- China Rehabilitation Science Institute, Beijing, PR China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, PR China
- Department of Spinal and Neural Functional Reconstruction, China Rehabilitation Research Center, Beijing, PR China
- Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, PR China
| | - Xin Zhang
- School of Rehabilitation Medicine, Capital Medical University, Beijing, PR China
- China Rehabilitation Science Institute, Beijing, PR China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, PR China
- Department of Spinal and Neural Functional Reconstruction, China Rehabilitation Research Center, Beijing, PR China
- Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, PR China
| | - Hao Feng
- School of Rehabilitation Medicine, Capital Medical University, Beijing, PR China
- China Rehabilitation Science Institute, Beijing, PR China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, PR China
- Department of Spinal and Neural Functional Reconstruction, China Rehabilitation Research Center, Beijing, PR China
- Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, PR China
| | - Zhanjing Wang
- Medical Experiment and Test Center, Capital Medical University, Beijing, PR China
| | - Jianjun Li
- School of Rehabilitation Medicine, Capital Medical University, Beijing, PR China
- China Rehabilitation Science Institute, Beijing, PR China
- Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, PR China
- Department of Spinal and Neural Functional Reconstruction, China Rehabilitation Research Center, Beijing, PR China
- Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, PR China
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12
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Xia X, Dai L, Zhou H, Chen P, Liu S, Yang W, Zuo Z, Xu X. Assessment of peripheral neuropathy in type 2 diabetes by diffusion tensor imaging: A case-control study. Eur J Radiol 2021; 145:110007. [PMID: 34758418 DOI: 10.1016/j.ejrad.2021.110007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Revised: 09/16/2021] [Accepted: 10/21/2021] [Indexed: 10/19/2022]
Abstract
OBJECTIVES This study aimed to evaluate diabetes peripheral neuropathy (DPN) by diffusion tensor imaging (DTI) and explore the correlation between DTI parameters and electrophysiological parameters. METHODS We examined tibial nerve (TN) and common peroneal nerve (CPN) of 32 DPN patients and 23 healthy controls using T1-weighted magnetic resonance imaging and DTI. Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) of TN and CPN were measured and compared between groups. Spearman correlation coefficient was used to explore the relationship between DTI parameters and electrophysiology parameters in the DPN group. Diagnostic value was assessed by receiver operating characteristic (ROC) analysis. RESULTS In the DPN group, FA was decreased (p < 0.0001) and MD and RD were increased (p < 0.05, p < 0.001) in the TN and CPN compared with the values of healthy control group. Moreover, in the DPN group, FA was positively correlated with motor nerve conduction velocity (MCV) (p < 0.0001), and both MD and RD were negatively correlated with MCV (p < 0.05, p < 0.001). However, there was no correlation between AD and any electrophysiological parameters. Among all DTI parameters, FA displayed the best diagnostic accuracy, with an area under the ROC curve of 0.882 in TN and 0.917 in CPN. CONCLUSION FA and RD demonstrate appreciable diagnostic accuracy. Furthermore, they both have a moderate correlation with MCV.
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Affiliation(s)
- Xinyue Xia
- Department of Radiology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China; Department of Radiology, Maternal and Child Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China
| | - Lisong Dai
- Department of Radiology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China
| | - Hongmei Zhou
- Department of Radiology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China
| | - Panpan Chen
- Department of Radiology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China
| | - Shuhua Liu
- Burn Department, Department of Burns, Tongren Hospital of Wuhan University and Wuhan Third Hospital, Wuhan 430060, China
| | - Wenzhong Yang
- Department of Radiology, Maternal and Child Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China
| | - Zhentao Zuo
- State Key Laboratory of Brain and Cognitive Science, Beijing MRI Center for Brain Research, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Chaoyang District, Beijing 100101, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Brain and Science and Intelligence Technology, Chinese Academy of Sciences, Beijing 100049, China.
| | - Xiangyang Xu
- Department of Radiology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430077, China.
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Shinn RL, Pancotto TE, Stadler KL, Werre SR, Rossmeisl JH. Magnetization transfer and diffusion tensor imaging in dogs with intervertebral disk herniation. J Vet Intern Med 2020; 34:2536-2544. [PMID: 33006411 PMCID: PMC7694818 DOI: 10.1111/jvim.15899] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 08/20/2020] [Accepted: 08/20/2020] [Indexed: 12/22/2022] Open
Abstract
Background Quantitative magnetic resonance imaging (QMRI) techniques of magnetization transfer ratio (MTR) and diffusion tensor imaging (DTI) provide microstructural information about the spinal cord. Objective Compare neurologic grades using the modified Frankel scale with MTR and DTI measurements in dogs with thoracolumbar intervertebral disk herniation (IVDH). Animals Fifty‐one dogs with thoracolumbar IVDH. Methods Prospective cohort study. Quantitative MRI measurements of the spinal cord were obtained at the region of compression. A linear regression generalized estimating equations model was used to compare QMRI measurements between different neurological grades after adjusting for age, weight, duration of clinical signs, and lesion location. Results Grade 5 (.79 × 10−3 mm2/s [median], .43−.91 [range]) and axial (1.47 × 10−3 mm2/s, .58−1.8) diffusivity were lower compared to grades 2 (1.003, .68−1.36; P = .02 and 1.81 × 10−3 mm2/s, 1.36−2.12; P < .001, respectively) and 3 (1.07 × 10−3 mm2/s, .77−1.5; P = .04 and 1.92 × 10−3 mm2/s, 1.83−2.37;P < .001, respectively). Compared to dogs with acute myelopathy, chronic myelopathy was associated with higher mean (1.02 × 10−3 mm2/s, .77−1.36 vs. .83 × 10−3 mm2/s, .64−1.5; P = .03) and radial diffusivity (.75 × 10−3 mm2/s, .38−1.04 vs. .44 × 10−3 mm2/s, .22−1.01; P = .008) and lower MTR (46.76, 31.8−56.43 vs. 54.4, 45.2−62.27; P = .004) and fractional anisotropy (.58, .4−0.75 vs. .7, .46−.85; P = .02). Fractional anisotropy was lower in dogs with a T2‐weighted intramedullary hyperintensity compared to those without (.7, .45−.85 vs. .54, .4−.8; P = .01). Conclusion and Clinical Relevance Mean diffusivity and AD could serve as surrogates of severity of spinal cord injury and are complementary to the clinical exam in dogs with thoracolumbar IVDH.
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Affiliation(s)
- Richard L Shinn
- Department of Small Animal Clinical Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - Theresa E Pancotto
- Department of Small Animal Clinical Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | | | - Stephen R Werre
- Laboratory for Study Design and Statistical Analysis, Virginia-Maryland Regional College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
| | - John H Rossmeisl
- Department of Small Animal Clinical Sciences, Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA
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14
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Zhou Z, Tong Q, Zhang L, Ding Q, Lu H, Jonkman LE, Yao J, He H, Zhu K, Zhong J. Evaluation of the diffusion MRI white matter tract integrity model using myelin histology and Monte-Carlo simulations. Neuroimage 2020; 223:117313. [PMID: 32882384 DOI: 10.1016/j.neuroimage.2020.117313] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Revised: 08/21/2020] [Accepted: 08/24/2020] [Indexed: 12/13/2022] Open
Abstract
Quantitative evaluation of brain myelination has drawn considerable attention. Conventional diffusion-based magnetic resonance imaging models, including diffusion tensor imaging and diffusion kurtosis imaging (DKI),1 have been used to infer the microstructure and its changes in neurological diseases. White matter tract integrity (WMTI) was proposed as a biophysical model to relate the DKI-derived metrics to the underlying microstructure. Although the model has been validated on ex vivo animal brains, it was not well evaluated with ex vivo human brains. In this study, histological samples (namely corpus callosum) from postmortem human brains have been investigated based on WMTI analyses on a clinical 3T scanner and comparisons with gold standard myelin staining in proteolipid protein and Luxol fast blue. In addition, Monte Carlo simulations were conducted to link changes from ex vivo to in vivo conditions based on the microscale parameters of water diffusivity and permeability. The results show that WMTI metrics, including axonal water fraction AWF, radial extra-axonal diffusivity De⊥, and intra-axonal diffusivity Dawere needed to characterize myelin content alterations. Thus, WMTI model metrics are shown to be promising candidates as sensitive biomarkers of demyelination.
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Affiliation(s)
- Zihan Zhou
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
| | - Qiqi Tong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
| | - Lei Zhang
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou 310058, China; Department of Pathology, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Qiuping Ding
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
| | - Hui Lu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands
| | - Junye Yao
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China.
| | - Keqing Zhu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou 310058, China; Department of Pathology, Zhejiang University School of Medicine, Hangzhou 310058, China.
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China; Department of Imaging Sciences, University of Rochester, United States
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Venkatasubramanian PN, Keni P, Gastfield R, Li L, Aksenov D, Sherman SA, Bailes J, Sindelar B, Finan JD, Lee J, Bailes JE, Wyrwicz AM. Diffusion Tensor Imaging Detects Acute and Subacute Changes in Corpus Callosum in Blast-Induced Traumatic Brain Injury. ASN Neuro 2020; 12:1759091420922929. [PMID: 32403948 PMCID: PMC7238783 DOI: 10.1177/1759091420922929] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
There is a critical need for understanding the progression of neuropathology in blast-induced traumatic brain injury using valid animal models to develop diagnostic approaches. In the present study, we used diffusion imaging and magnetic resonance (MR) morphometry to characterize axonal injury in white matter structures of the rat brain following a blast applied via blast tube to one side of the brain. Diffusion tensor imaging was performed on acute and subacute phases of pathology from which fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were calculated for corpus callosum (CC), cingulum bundle, and fimbria. Ventricular volume and CC thickness were measured. Blast-injured rats showed temporally varying bilateral changes in diffusion metrics indicating persistent axonal pathology. Diffusion changes in the CC suggested vasogenic edema secondary to axonal injury in the acute phase. Axonal pathology persisted in the subacute phase marked by cytotoxic edema and demyelination which was confirmed by ultrastructural analysis. The evolution of pathology followed a different pattern in the cingulum bundle: axonal injury and demyelination in the acute phase followed by cytotoxic edema in the subacute phase. Spatially, structures close to midline were most affected. Changes in the genu were greater than in the body and splenium; the caudal cingulum bundle was more affected than the rostral cingulum. Thinning of CC and ventriculomegaly were greater only in the acute phase. Our results reveal the persistent nature of blast-induced axonal pathology and suggest that diffusion imaging may have potential for detecting the temporal evolution of blast injury.
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Affiliation(s)
- Palamadai N Venkatasubramanian
- Center for Basic M.R. Research, Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - Prachi Keni
- Department of Neurosurgery, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - Roland Gastfield
- Center for Basic M.R. Research, Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - Limin Li
- Center for Basic M.R. Research, Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - Daniil Aksenov
- Center for Basic M.R. Research, Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - Sydney A Sherman
- Department of Neurosurgery, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - Julian Bailes
- Department of Neurosurgery, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - Brian Sindelar
- Department of Neurosurgery, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - John D Finan
- Department of Neurosurgery, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - John Lee
- Department of Pathology, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - Julian E Bailes
- Department of Neurosurgery, NorthShore University HealthSystem, Evanston, Illinois, United States
| | - Alice M Wyrwicz
- Center for Basic M.R. Research, Department of Radiology, NorthShore University HealthSystem, Evanston, Illinois, United States
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Rafael-Patino J, Romascano D, Ramirez-Manzanares A, Canales-Rodríguez EJ, Girard G, Thiran JP. Robust Monte-Carlo Simulations in Diffusion-MRI: Effect of the Substrate Complexity and Parameter Choice on the Reproducibility of Results. Front Neuroinform 2020; 14:8. [PMID: 32210781 PMCID: PMC7076166 DOI: 10.3389/fninf.2020.00008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 02/20/2020] [Indexed: 12/13/2022] Open
Abstract
Monte-Carlo Diffusion Simulations (MCDS) have been used extensively as a ground truth tool for the validation of microstructure models for Diffusion-Weighted MRI. However, methodological pitfalls in the design of the biomimicking geometrical configurations and the simulation parameters can lead to approximation biases. Such pitfalls affect the reliability of the estimated signal, as well as its validity and reproducibility as ground truth data. In this work, we first present a set of experiments in order to study three critical pitfalls encountered in the design of MCDS in the literature, namely, the number of simulated particles and time steps, simplifications in the intra-axonal substrate representation, and the impact of the substrate's size on the signal stemming from the extra-axonal space. The results obtained show important changes in the simulated signals and the recovered microstructure features when changes in those parameters are introduced. Thereupon, driven by our findings from the first studies, we outline a general framework able to generate complex substrates. We show the framework's capability to overcome the aforementioned simplifications by generating a complex crossing substrate, which preserves the volume in the crossing area and achieves a high packing density. The results presented in this work, along with the simulator developed, pave the way toward more realistic and reproducible Monte-Carlo simulations for Diffusion-Weighted MRI.
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Affiliation(s)
- Jonathan Rafael-Patino
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - David Romascano
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | | | - Erick Jorge Canales-Rodríguez
- Radiology Department, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.,FIDMAG Germanes Hospitalàries, Sant Boi de Llobregat, Barcelona, Spain.,Mental Health Research Networking Center (CIBERSAM), Madrid, Spain
| | - Gabriel Girard
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Radiology Department, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.,Centre d'Imagerie Biomédicale (CIBM), Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Lab (LTS5), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Radiology Department, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.,Centre d'Imagerie Biomédicale (CIBM), Lausanne, Switzerland.,University of Lausanne, Lausanne, Switzerland
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17
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Ginsburger K, Matuschke F, Poupon F, Mangin JF, Axer M, Poupon C. MEDUSA: A GPU-based tool to create realistic phantoms of the brain microstructure using tiny spheres. Neuroimage 2019; 193:10-24. [DOI: 10.1016/j.neuroimage.2019.02.055] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 02/18/2019] [Accepted: 02/21/2019] [Indexed: 12/16/2022] Open
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18
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Dawes BH, Lloyd RA, Rogers JM, Magnussen JS, Bilston LE, Stoodley MA. Cerebellar Tissue Strain in Chiari Malformation with Headache. World Neurosurg 2019; 130:e74-e81. [PMID: 31158545 DOI: 10.1016/j.wneu.2019.05.211] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2018] [Revised: 05/23/2019] [Accepted: 05/24/2019] [Indexed: 11/25/2022]
Abstract
OBJECTIVE The pathogenesis of Chiari malformation type 1 (CM-1)-associated Valsalva headache is unknown, but it may be caused by abnormal cerebellar tonsil tissue strain. Advances in cardiac-gated magnetic resonance imaging (MRI) techniques such as balanced fast-field echo (bFFE) allow quantification of the motion of anatomic structures and can be used to measure tissue strain. The current study investigated the relationship between Valsalva heachache and tonsillar motion in patients with CM-1. METHODS A retrospective review of patients with CM-1 who had undergone cardiac-gated bFFE MRI was performed. Headache symptoms were retrieved from the medical records. Anatomic landmarks were manually selected on the cine bFFE, and a validated motion-tracking software was used to assess motion over the cardiac cycle in patients at rest. For each patient, displacement, strain, and strain rate were calculated for 3 anatomic segments. Patients undergoing surgery were examined before and after surgery. RESULTS From 88 patients, a total of 108 bFFE sequences were analyzed. Valsalva headache was present in 50% of patients. Cerebellar tonsil displacement (P = 0.003), strain (P = 0.012), and maximum strain rate (P = 0.04) were reduced after surgery (n = 20). There was no statistically significant association between tissue motion and headache symptoms. CONCLUSION The results of this study do not support a relationship between cardiac cycle cerebellar strain and Valsalva headache in patients with CM-1. It is possible that cerebellar strain related to respiratory maneuvers is associated with headache in Chiari patients. Further investigation of tissue strain is warranted because it represents a potential biomarker for outcomes after surgery.
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Affiliation(s)
- Bryden H Dawes
- Department of Clinical Medicine, Macquarie University, Sydney, New South Wales, Australia
| | - Robert A Lloyd
- Neuroscience Research Australia and Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Jeffrey M Rogers
- Department of Clinical Medicine, Macquarie University, Sydney, New South Wales, Australia; Faculty of Health Sciences, University of Sydney, Sydney, New South Wales, Australia
| | - John S Magnussen
- Department of Clinical Medicine, Macquarie University, Sydney, New South Wales, Australia
| | - Lynne E Bilston
- Neuroscience Research Australia and Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Marcus A Stoodley
- Department of Clinical Medicine, Macquarie University, Sydney, New South Wales, Australia.
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19
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Harris NG, Paydar A, Smith GS, Lepore S. Diffusion MR imaging acquisition and analytics for microstructural delineation in preclinical models of TBI. J Neurosci Res 2019; 100:1128-1139. [PMID: 31044457 PMCID: PMC6824967 DOI: 10.1002/jnr.24416] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Revised: 02/13/2019] [Accepted: 03/04/2019] [Indexed: 12/31/2022]
Abstract
Significant progress has been made toward improving both the acquisition of clinical diffusion-weighted imaging (DWI) data and its analysis in the uninjured brain, through various techniques including a large number of model-based solutions that have been proposed to fit for multiple tissue compartments, and multiple fibers per voxel. While some of these techniques have been applied to clinical traumatic brain injury (TBI) research, the majority of these technological enhancements have yet to be fully implemented in the preclinical arena of TBI animal model-based research. In this review, we describe the requirement for preclinical, MRI-based efforts to provide systematic confirmation of the applicability of some of these models as indicators of tissue pathology within the injured brain. We review how current DWI techniques are currently being used in animal TBI models, and describe how both acquisition and analytic techniques could be extended to leverage the progress made in clinical work. Finally, we highlight remaining gaps in the preclinical pipeline from data acquisition to final analysis that currently have no real, preclinical-based correlate.
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Affiliation(s)
- N G Harris
- Department of Neurosurgery, UCLA Brain Injury Research Centre, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California.,UCLA Intellectual Development and Disabilities Research Center, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
| | - A Paydar
- Department of Neurosurgery, UCLA Brain Injury Research Centre, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
| | - G S Smith
- Department of Neurosurgery, UCLA Brain Injury Research Centre, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
| | - S Lepore
- Department of Neurosurgery, UCLA Brain Injury Research Centre, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
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20
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Zhang C, Ding Q, He H, Peng Y, Li C, Mai J, Li JS, Zhong J, Chang MW. Nanoporous hollow fibers as a phantom material for the validation of diffusion magnetic resonance imaging. J Appl Polym Sci 2019. [DOI: 10.1002/app.47617] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Affiliation(s)
- Chunchen Zhang
- Key Laboratory for Biomedical Engineering of Education Ministry of China; Zhejiang University; Hangzhou 310027 People's Republic of China
- Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal; Zhejiang University; Hangzhou 310027 People's Republic of China
| | - Qiuping Ding
- Key Laboratory for Biomedical Engineering of Education Ministry of China; Zhejiang University; Hangzhou 310027 People's Republic of China
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science; Zhejiang University; Hangzhou 310027 People's Republic of China
| | - Hongjian He
- Key Laboratory for Biomedical Engineering of Education Ministry of China; Zhejiang University; Hangzhou 310027 People's Republic of China
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science; Zhejiang University; Hangzhou 310027 People's Republic of China
| | - Yu Peng
- College of Civil Engineering and Architecture; Zhejiang University; Hangzhou 310027 People's Republic of China
| | - Chen Li
- Key Laboratory for Biomedical Engineering of Education Ministry of China; Zhejiang University; Hangzhou 310027 People's Republic of China
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science; Zhejiang University; Hangzhou 310027 People's Republic of China
| | - John Mai
- Alfred E. Mann Institute for Biomedical Engineering; University of Southern California; California Los Angeles 90089
| | - Jing-Song Li
- Key Laboratory for Biomedical Engineering of Education Ministry of China; Zhejiang University; Hangzhou 310027 People's Republic of China
| | - Jianhui Zhong
- Key Laboratory for Biomedical Engineering of Education Ministry of China; Zhejiang University; Hangzhou 310027 People's Republic of China
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science; Zhejiang University; Hangzhou 310027 People's Republic of China
| | - Ming-Wei Chang
- Key Laboratory for Biomedical Engineering of Education Ministry of China; Zhejiang University; Hangzhou 310027 People's Republic of China
- Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal; Zhejiang University; Hangzhou 310027 People's Republic of China
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21
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Godel T, Pham M, Kele H, Kronlage M, Schwarz D, Brunée M, Heiland S, Bendszus M, Bäumer P. Diffusion tensor imaging in anterior interosseous nerve syndrome - functional MR Neurography on a fascicular level. NEUROIMAGE-CLINICAL 2019; 21:101659. [PMID: 30642759 PMCID: PMC6412076 DOI: 10.1016/j.nicl.2019.101659] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 12/21/2018] [Accepted: 01/04/2019] [Indexed: 12/31/2022]
Abstract
Purpose By applying diffusor tensor imaging (DTI) in patients with anterior interosseous nerve syndrome (AINS), this proof of principle study aims to quantify the extent of structural damage of a peripheral nerve at the anatomical level of individual fascicles. Methods In this institutional review board approved prospective study 13 patients with spontaneous AINS were examined at 3 Tesla including a transversal T2-weighted turbo-spin-echo and a spin-echo echo-planar-imaging pulse sequence of the upper arm level. Calculations of quantitative DTI parameters including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) for median nerve lesion and non-lesion fascicles as well as ulnar and radial nerve were obtained. DTI values were compared to each other and to a previously published dataset of 58 healthy controls using one-way Analysis of Variance with Bonferroni correction and p-values <.05 were considered significant. Receiver operating characteristic (ROC) curves were performed to assess diagnostic accuracy. Results FA of median nerve lesion fascicles was decreased compared to median nerve non-lesion fascicles, ulnar nerve and radial nerve while MD, RD, and AD was increased (p < .001 for all parameters). Compared to median nerve values of healthy controls, lesion fascicles showed a significant decrease in FA while MD, RD, and AD was increased (p < .001 for all parameters). FA of median nerve non-lesion fascicles showed a weak significant decrease compared to healthy controls (p < .01) while there was no difference in MD, RD, and AD. ROC analyses revealed an excellent diagnostic accuracy of FA, MD and RD in the discrimination of median nerve lesion and non-lesion fascicles in AINS patients as well as in the discrimination of lesion fascicles and normative median nerve values of healthy controls. Conclusion By applying this functional MR Neurography technique in patients with AINS, this proof of principle study demonstrates that diffusion tensor imaging is feasible to quantify structural nerve injury at the anatomical level of individual fascicles. DTI is capable to quantify structural nerve injury on a fascicular level. Lesion- and non-lesion fascicles can be discriminated at high diagnostic accuracy. FA seems to be to most sensitive parameter in quantitative DTI.
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Affiliation(s)
- Tim Godel
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
| | - Mirko Pham
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Department of Neuroradiology, Würzburg University Hospital, Josef-Schneider-Str. 11, 97080 Würzburg, Germany.
| | - Henrich Kele
- Center for Neurology and Clinical Neurophysiology, Neuer Wall 19, 20354 Hamburg, Germany.
| | - Moritz Kronlage
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
| | - Daniel Schwarz
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
| | - Merle Brunée
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
| | - Sabine Heiland
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
| | - Philipp Bäumer
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany; Center for Radiology Dia.log, Vinzenz-von-Paul Str. 8, 84503 Altötting, Germany.
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22
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Fieremans E, Lee HH. Physical and numerical phantoms for the validation of brain microstructural MRI: A cookbook. Neuroimage 2018; 182:39-61. [PMID: 29920376 PMCID: PMC6175674 DOI: 10.1016/j.neuroimage.2018.06.046] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2017] [Revised: 06/08/2018] [Accepted: 06/13/2018] [Indexed: 12/24/2022] Open
Abstract
Phantoms, both numerical (software) and physical (hardware), can serve as a gold standard for the validation of MRI methods probing the brain microstructure. This review aims to provide guidelines on how to build, implement, or choose the right phantom for a particular application, along with an overview of the current state-of-the-art of phantoms dedicated to study brain microstructure with MRI. For physical phantoms, we discuss the essential requirements and relevant characteristics of both the (NMR visible) liquid and (NMR invisible) phantom materials that induce relevant microstructural features detectable via MRI, based on diffusion, intra-voxel incoherent motion, magnetization transfer or magnetic susceptibility weighted contrast. In particular, for diffusion MRI, many useful phantoms have been proposed, ranging from simple liquids to advanced biomimetic phantoms consisting of hollow or plain microfibers and capillaries. For numerical phantoms, the focus is on Monte Carlo simulations of random walk, for which the basic principles, along with useful criteria to check and potential pitfalls are reviewed, in addition to a literature overview highlighting recent advances. While many phantoms exist already, the current review aims to stimulate further research in the field and to address remaining needs.
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Affiliation(s)
- Els Fieremans
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA.
| | - Hong-Hsi Lee
- Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA
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23
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Budde MD, Skinner NP. Diffusion MRI in acute nervous system injury. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2018; 292:137-148. [PMID: 29773299 DOI: 10.1016/j.jmr.2018.04.016] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2017] [Revised: 04/06/2018] [Accepted: 04/27/2018] [Indexed: 06/08/2023]
Abstract
Diffusion weighted magnetic resonance imaging (DWI) and related techniques such as diffusion tensor imaging (DTI) are uniquely sensitive to the microstructure of the brain and spinal cord. In the acute aftermath of nervous system injury, for example, DWI reveals changes caused by injury that remains invisible on other MRI contrasts such as T2-weighted imaging. This ability has led to a demonstrated clinical utility in cerebral ischemia. However, despite strong promise in preclinical models and research settings, DWI has not been as readily adopted for other acute injuries such as traumatic spinal cord, brain, or peripheral nerve injury. Furthermore, the precise biophysical mechanisms that underlie DWI and DTI changes are not fully understood. In this report, we review the DWI and DTI changes that occur in acute neurological injury of cerebral ischemia, spinal cord injury, traumatic brain injury, and peripheral nerve injury. Their associations with the underlying biology are examined with an emphasis on the role of acute axon and dendrite beading. Lastly, emerging DWI techniques to overcome the limitations of DTI are discussed as these may offer the needed improvements to translate to clinical settings.
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Affiliation(s)
- Matthew D Budde
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States.
| | - Nathan P Skinner
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States; Medical Scientist Training Program, Medical College of Wisconsin, Milwaukee, WI, United States
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24
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Liu C, Yang D, Li J, Li D, Yang M, Sun W, Meng Q, Zhang W, Cai C, Du L, Li J, Gao F, Gu R, Feng Y, Dong X, Miao Q, Yang X, Zuo Z. Dynamic diffusion tensor imaging of spinal cord contusion: A canine model. J Neurosci Res 2018; 96:1093-1103. [PMID: 29485189 DOI: 10.1002/jnr.24222] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 12/29/2017] [Accepted: 01/12/2018] [Indexed: 11/08/2022]
Abstract
This study aimed to explore the dynamic diffusion tensor imaging (DTI) of changes in spinal cord contusion using a canine model of injury involving rostral and caudal levels. In this study, a spinal cord contusion model was established in female dogs using a custom-made weight-drop lesion device. DTI was performed on dogs with injured spinal cords (n=7) using a Siemens 3.0T MRI scanner at pre-contusion and at 3 h, 24 h, 6 weeks and 12 weeks post-injury. The tissue sections were stained for immunohistochemical analysis. Canine models of spinal cord contusion were created successfully using the weight-drop lesion device. The fractional anisotropy (FA) value of lesion epicenter decreased, while the apparent diffusion coefficient (ADC), mean diffusivity (MD), and radial diffusivity (RD) values increased, and the extent of the curve was apparent gradually. The site and time affected the DTI parameters significantly in the whole spinal cord, ADC (site, P < 0.001 and time, P = 0.077, respectively); FA (site, P < 0.001 and time, P = 0.002, respectively). Immunohistological analysis of GFAP and NF revealed the pathologic changes of reactive astrocytes and axons, as well as the cavity and glial scars occurring during chronic SCI. DTI is a sensitive and noninvasive imaging tool useful to assess edema, hemorrhage, cavity formation, structural damage and reconstruction of axon, and myelin in dogs. The DTI parameters after contusion vary. However, the curves of ADC, MD, and RD were nearly similar and the FA curve was distinct. All the DTI parameters were affected by distance and time.
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Affiliation(s)
- Changbin Liu
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Degang Yang
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Jianjun Li
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Dapeng Li
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Mingliang Yang
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Wei Sun
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Qianru Meng
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Wenhao Zhang
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Chang Cai
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Liangjie Du
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Jun Li
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Feng Gao
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Rui Gu
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Yutong Feng
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Xuechao Dong
- School of Rehabilitation Medicine, Capital Medical University, Beijing, 100068, China.,Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center, Beijing, 100068, China.,Center of Neural Injury and Repair, Beijing Institute for Brain Disorders, Beijing, 100068, China.,China Rehabilitation Science Institute, Beijing, 100068, China.,Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, 100068, China
| | - Qi Miao
- Zibo Shanhang Medical Engineering Co., ltd, Zibo, Shandong, 255000, China
| | - Xinghua Yang
- School of Public Health, Capital Medical University, 10 Xitoutiao, Youanmen, Beijing, 100069, China
| | - Zhentao Zuo
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.,The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences, Beijing, 100049, China.,Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100049, China
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25
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Liu CB, Yang DG, Meng QR, Li DP, Yang ML, Sun W, Zhang WH, Cai C, Du LJ, Li J, Gao F, Yu Y, Zhang X, Zuo ZT, Li JJ. Dynamic correlation of diffusion tensor imaging and neurological function scores in beagles with spinal cord injury. Neural Regen Res 2018; 13:877-886. [PMID: 29863019 PMCID: PMC5998642 DOI: 10.4103/1673-5374.232485] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Exploring the relationship between different structure of the spinal cord and functional assessment after spinal cord injury is important. Quantitative diffusion tensor imaging can provide information about the microstructure of nerve tissue and can quantify the pathological damage of spinal cord white matter and gray matter. In this study, a custom-designed spinal cord contusion-impactor was used to damage the T10 spinal cord of beagles. Diffusion tensor imaging was used to observe changes in the whole spinal cord, white matter, and gray matter, and the Texas Spinal Cord Injury Score was used to assess changes in neurological function at 3 hours, 24 hours, 6 weeks, and 12 weeks after injury. With time, fractional anisotropy values after spinal cord injury showed a downward trend, and the apparent diffusion coefficient, mean diffusivity, and radial diffusivity first decreased and then increased. The apparent diffusion-coefficient value was highly associated with the Texas Spinal Cord Injury Score for the whole spinal cord (R = 0.919, P = 0.027), white matter (R = 0.932, P = 0.021), and gray matter (R = 0.882, P = 0.048). Additionally, the other parameters had almost no correlation with the score (P > 0.05). In conclusion, the highest and most significant correlation between diffusion parameters and neurological function was the apparent diffusion-coefficient value for white matter, indicating that it could be used to predict the recovery of neurological function accurately after spinal cord injury.
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Affiliation(s)
- Chang-Bin Liu
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - De-Gang Yang
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Qian-Ru Meng
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Da-Peng Li
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Ming-Liang Yang
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Wei Sun
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Wen-Hao Zhang
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Chang Cai
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Liang-Jie Du
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Jun Li
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Feng Gao
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Yan Yu
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Xin Zhang
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
| | - Zhen-Tao Zuo
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences; The Innovation Center of Excellence on Brain Science, Chinese Academy of Sciences; Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China
| | - Jian-Jun Li
- School of Rehabilitation Medicine, Capital Medical University; Department of Spinal and Neural Function Reconstruction, China Rehabilitation Research Center; Center of Neural Injury and Repair, Beijing Institute for Brain Disorders; China Rehabilitation Science Institute; Beijing Key Laboratory of Neural Injury and Rehabilitation, Beijing, China
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26
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Kronlage M, Schwehr V, Schwarz D, Godel T, Uhlmann L, Heiland S, Bendszus M, Bäumer P. Peripheral nerve diffusion tensor imaging (DTI): normal values and demographic determinants in a cohort of 60 healthy individuals. Eur Radiol 2017; 28:1801-1808. [PMID: 29230526 DOI: 10.1007/s00330-017-5134-z] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Revised: 09/14/2017] [Accepted: 10/12/2017] [Indexed: 12/14/2022]
Abstract
OBJECTIVE To identify demographic determinants of peripheral nerve diffusion tensor imaging (DTI) and to establish normal values for fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). METHODS Sixty subjects were examined at 3 Tesla by single-shot DTI. FA, AD, RD, and MD were collected for the sciatic, tibial, median, ulnar, and radial nerve and were correlated with demographic variables. RESULTS Mean FA of all nerves declined with increasing age (r = -0.77), which could be explained by RD increasing (r = 0.56) and AD declining (r = -0.40) with age. Moreover, FA was inversely associated with height (r = -0.28), weight (r = -0.38) and BMI (r = -0.35). Although FA tended to be lower in men than women (p = 0.052), this difference became completely negligible after adjustment to body weight. A multiple linear regression model for FA was calculated with age and weight as predictors (defined by backward variable selection), yielding an R 2 = 0.71 and providing a correction formula to adjust FA for age and weight. CONCLUSION Peripheral nerve DTI parameters depend on demographic variables. The most important determinants age and weight should be considered in all studies employing peripheral nerve DTI. KEY POINTS • Peripheral nerve diffusion tensor imaging (DTI) parameters depend on demographic variables. • Fractional anisotropy (FA) declines with increasing age and weight. • Gender does not systematically affect peripheral nerve DTI. • The formula presented here allows adjustment of FA for demographic variables.
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Affiliation(s)
- Moritz Kronlage
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany.
| | - Véronique Schwehr
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Daniel Schwarz
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Tim Godel
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Lorenz Uhlmann
- Institute for medical biometry and informatics, Heidelberg University, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
| | - Philipp Bäumer
- Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120, Heidelberg, Germany
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany
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Bates J, Teh I, McClymont D, Kohl P, Schneider JE, Grau V. Monte Carlo Simulations of Diffusion Weighted MRI in Myocardium: Validation and Sensitivity Analysis. IEEE TRANSACTIONS ON MEDICAL IMAGING 2017; 36:1316-1325. [PMID: 28328501 DOI: 10.1109/tmi.2017.2679809] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
A model of cardiac microstructure and diffusion MRI is presented, and compared with experimental data from ex vivo rat hearts. The model includes a simplified representation of individual cells, with physiologically correct cell size and orientation, as well as intra- to extracellular volume ratio. Diffusion MRI is simulated using a Monte Carlo model and realistic MRI sequences. The results show good correspondence between the simulated and experimental MRI signals. Similar patterns are observed in the eigenvalues of the diffusion tensor, the mean diffusivity (MD), and the fractional anisotropy (FA). A sensitivity analysis shows that the diffusivity is the dominant influence on all three eigenvalues of the diffusion tensor, the MD, and the FA. The area and aspect ratio of the cell cross-section affect the secondary and tertiary eigenvalues, and hence the FA. Within biological norms, the cell length, volume fraction of cells, and rate of change of helix angle play a relatively small role in influencing tissue diffusion. Results suggest that the model could be used to improve understanding of the relationship between cardiac microstructure and diffusion MRI measurements, as well as in testing and refinement of cardiac diffusion MRI protocols.
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Kruggel F, Masaki F, Solodkin A. Analysis of longitudinal diffusion-weighted images in healthy and pathological aging: An ADNI study. J Neurosci Methods 2017; 278:101-115. [DOI: 10.1016/j.jneumeth.2016.12.020] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2016] [Revised: 10/28/2016] [Accepted: 12/30/2016] [Indexed: 12/13/2022]
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Mohammadian M, Roine T, Hirvonen J, Kurki T, Ala-Seppälä H, Frantzén J, Katila A, Kyllönen A, Maanpää HR, Posti J, Takala R, Tallus J, Tenovuo O. High angular resolution diffusion-weighted imaging in mild traumatic brain injury. Neuroimage Clin 2016; 13:174-180. [PMID: 27981032 PMCID: PMC5144744 DOI: 10.1016/j.nicl.2016.11.016] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2016] [Revised: 10/24/2016] [Accepted: 11/16/2016] [Indexed: 01/19/2023]
Abstract
We sought to investigate white matter abnormalities in mild traumatic brain injury (mTBI) using diffusion-weighted magnetic resonance imaging (DW-MRI). We applied a global approach based on tract-based spatial statistics skeleton as well as constrained spherical deconvolution tractography. DW-MRI was performed on 102 patients with mTBI within two months post-injury and 30 control subjects. A robust global approach considering only the voxels with a single-fiber configuration was used in addition to global analysis of the tract skeleton and probabilistic whole-brain tractography. In addition, we assessed whether the microstructural parameters correlated with age, time from injury, patient's outcome and white matter MRI hyperintensities. We found that whole-brain global approach restricted to single-fiber voxels showed significantly decreased fractional anisotropy (FA) (p = 0.002) and increased radial diffusivity (p = 0.011) in patients with mTBI compared with controls. The results restricted to single-fiber voxels were more significant and reproducible than those with the complete tract skeleton or the whole-brain tractography. FA correlated with patient outcomes, white matter hyperintensities and age. No correlation was observed between FA and time of scan post-injury. In conclusion, the global approach could be a promising imaging biomarker to detect white matter abnormalities following traumatic brain injury.
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Key Words
- AD, axial diffusivity
- CSD, constrained-spherical deconvolution
- DAI, diffuse axonal injury
- DTI, diffusion tensor imaging
- DW-MRI, diffusion-weighted magnetic resonance imaging
- Diffusion-weighted magnetic resonance imaging
- FA, fractional anisotropy
- GCS, Glasgow Coma Scale
- GOSe, Glasgow Outcome Scale extended
- Global approach
- HARDI, high angular resolution diffusion imaging
- MD, mean diffusivity
- Magnetic resonance imaging
- PTA, post-traumatic amnesia
- Probabilistic tractography
- RD, radial diffusivity
- TBI, traumatic brain injury
- TBSS, tract-based spatial statistics
- Traumatic brain injury
- mTBI, mild traumatic brain injury
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Affiliation(s)
- Mehrbod Mohammadian
- Department of Neurology, University of Turku, Turku, Finland
- Division of Clinical Neurosciences, Department of Rehabilitation and Brain Trauma, Turku University Hospital, Turku, Finland
| | - Timo Roine
- iMinds-Vision lab, Department of Physics, University of Antwerp, Antwerp, Belgium
| | - Jussi Hirvonen
- Department of Neurology, University of Turku, Turku, Finland
- Division of Clinical Neurosciences, Department of Rehabilitation and Brain Trauma, Turku University Hospital, Turku, Finland
- Department of Radiology, Turku University Hospital, Turku, Finland
| | - Timo Kurki
- Department of Neurology, University of Turku, Turku, Finland
- Division of Clinical Neurosciences, Department of Rehabilitation and Brain Trauma, Turku University Hospital, Turku, Finland
- Department of Radiology, Turku University Hospital, Turku, Finland
| | | | - Janek Frantzén
- Department of Neurology, University of Turku, Turku, Finland
- Division of Clinical Neurosciences, Department of Neurosurgery, Turku University Hospital, Turku, Finland
| | - Ari Katila
- Perioperative Services, Intensive Care Medicine and Pain Management, Turku University Hospital and University of Turku, Turku, Finland
| | - Anna Kyllönen
- Department of Neurology, University of Turku, Turku, Finland
| | | | - Jussi Posti
- Department of Neurology, University of Turku, Turku, Finland
- Division of Clinical Neurosciences, Department of Rehabilitation and Brain Trauma, Turku University Hospital, Turku, Finland
- Division of Clinical Neurosciences, Department of Neurosurgery, Turku University Hospital, Turku, Finland
| | - Riikka Takala
- Perioperative Services, Intensive Care Medicine and Pain Management, Turku University Hospital and University of Turku, Turku, Finland
| | - Jussi Tallus
- Department of Neurology, University of Turku, Turku, Finland
| | - Olli Tenovuo
- Department of Neurology, University of Turku, Turku, Finland
- Division of Clinical Neurosciences, Department of Rehabilitation and Brain Trauma, Turku University Hospital, Turku, Finland
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In-vivo Dynamics of the Human Hippocampus across the Menstrual Cycle. Sci Rep 2016; 6:32833. [PMID: 27713470 PMCID: PMC5054394 DOI: 10.1038/srep32833] [Citation(s) in RCA: 81] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2016] [Accepted: 08/11/2016] [Indexed: 12/31/2022] Open
Abstract
Sex hormones fluctuate during the menstrual cycle. Evidence from animal studies suggests similar subtle fluctuations in hippocampal structure, predominantly linked to estrogen. Hippocampal abnormalities have been observed in several neuropsychiatric pathologies with prominent sexual dimorphism. Yet, the potential impact of subtle sex-hormonal fluctuations on human hippocampal structure in health is unclear. We tested the feasibility of longitudinal neuroimaging in conjunction with rigorous menstrual cycle monitoring to evaluate potential changes in hippocampal microstructure associated with physiological sex-hormonal changes. Thirty longitudinal diffusion weighted imaging scans of a single healthy female subject were acquired across two full menstrual cycles. We calculated hippocampal fractional anisotropy (FA), a measure sensitive to changes in microstructural integrity, and investigated potential correlations with estrogen. We observed a significant positive correlation between FA values and estrogen in the hippocampus bilaterally, revealing a peak in FA closely paralleling ovulation. This exploratory, single-subject study demonstrates the feasibility of a longitudinal DWI scanning protocol across the menstrual cycle and is the first to link subtle endogenous hormonal fluctuations to changes in FA in vivo. In light of recent attempts to neurally phenotype single humans, our findings highlight menstrual cycle monitoring in parallel with highly sampled individual neuroimaging data to address fundamental questions about the dynamics of plasticity in the adult brain.
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Gogliettino AR, Potenza MN, Yip SW. White matter development and tobacco smoking in young adults: A systematic review with recommendations for future research. Drug Alcohol Depend 2016; 162:26-33. [PMID: 26948756 PMCID: PMC4833590 DOI: 10.1016/j.drugalcdep.2016.02.015] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2015] [Revised: 02/09/2016] [Accepted: 02/10/2016] [Indexed: 12/21/2022]
Abstract
BACKGROUND Adolescence and young adulthood are critical vulnerability periods for initiation of tobacco smoking. White matter development is ongoing during this time and may be influenced by exposure to nicotine. Synthesis of findings from diffusion tensor imaging (DTI) studies of adolescent and young adult smokers may be helpful in understanding the relationship between neurodevelopment and initiation and progression of tobacco-use behaviors and in guiding further research. METHODS A systematic literature review was conducted to identify DTI studies comparing adolescent and young adult (mean age <30 years) smokers versus nonsmokers. A total of 5 studies meeting inclusion criteria were identified. Primary study findings are reviewed and discussed within the context of neurodevelopment and in relation to findings from adult studies. Directions for further research are also discussed. RESULTS All identified studies reported increases in fractional anisotropy (FA) among adolescent/young adult smokers in comparison to non-smokers. Increased FA was most frequently reported in regions of the corpus callosum (genu, body and spenium), internal capsule and superior longitudinal fasciculus. CONCLUSIONS Findings of increased FA among adolescent/young adult smokers are contrary to those from most adult studies and thus raise the possibility of differential effects of nicotine on white matter across the lifespan. Further research including multiple time points is needed to test this hypothesis. Other areas warranting further research include DTI studies of e-cigarette use and studies incorporating measures of pubertal stage.
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Affiliation(s)
| | - Marc N. Potenza
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States, CASAColumbia, Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States, Connecticut Mental Health Center, New Haven, CT, United States, Department of Neurobiology, Yale University School of Medicine, New Haven, CT, United States, Yale Child Study Center, Yale University School of Medicine, New Haven, CT, United States
| | - Sarah W. Yip
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States, CASAColumbia, Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States, Corresponding author at: 1 Church Street, 7th Floor, Room 730, New Haven, CT 06510-3330, United States. Fax: +1 203 737 3591. (S.W. Yip)
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Tu TW, Williams RA, Lescher JD, Jikaria N, Turtzo LC, Frank JA. Radiological-pathological correlation of diffusion tensor and magnetization transfer imaging in a closed head traumatic brain injury model. Ann Neurol 2016; 79:907-20. [PMID: 27230970 DOI: 10.1002/ana.24641] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2015] [Revised: 03/13/2016] [Accepted: 03/14/2016] [Indexed: 12/27/2022]
Abstract
OBJECTIVE Metrics of diffusion tensor imaging (DTI) and magnetization transfer imaging (MTI) can detect diffuse axonal injury in traumatic brain injury (TBI). The relationship between the changes in these imaging measures and the underlying pathologies is still relatively unknown. This study investigated the radiological-pathological correlation between these imaging techniques and immunohistochemistry using a closed head rat model of TBI. METHODS TBI was performed on female rats followed longitudinally by magnetic resonance imaging (MRI) out to 30 days postinjury, with a subset of animals selected for histopathological analyses. A MRI-based finite element analysis was generated to characterize the pattern of the mechanical insult and estimate the extent of brain injury to direct the pathological correlation with imaging findings. RESULTS DTI axial diffusivity and fractional anisotropy (FA) were sensitive to axonal integrity, whereas radial diffusivity showed significant correlation to the myelin compactness. FA was correlated with astrogliosis in the gray matter, whereas mean diffusivity was correlated with increased cellularity. Secondary inflammatory responses also partly affected the changes of these DTI metrics. The magnetization transfer ratio (MTR) at 3.5ppm demonstrated a strong correlation with both axon and myelin integrity. Decrease in MTR at 20ppm correlated with the extent of astrogliosis in both gray and white matter. INTERPRETATION Although conventional T2-weighted MRI did not detect abnormalities following TBI, DTI and MTI afforded complementary insight into the underlying pathologies reflecting varying injury states over time, and thus may substitute for histology to reveal diffusive axonal injury pathologies in vivo. This correlation of MRI and histology furthers understanding of the microscopic pathology underlying DTI and MTI changes in TBI. Ann Neurol 2016;79:907-920.
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Affiliation(s)
- Tsang-Wei Tu
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD
| | - Rashida A Williams
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD
| | - Jacob D Lescher
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD
| | - Neekita Jikaria
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD
| | - L Christine Turtzo
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.,Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD
| | - Joseph A Frank
- Frank Laboratory, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD.,National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD
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