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Yin JH, Liu YO, Li HL, Burgunder JM, Huang Y. White Matter Microstructure Changes Revealed by Diffusion Kurtosis and Diffusion Tensor Imaging in Mutant Huntingtin Gene Carriers. J Huntingtons Dis 2024:JHD240018. [PMID: 38905054 DOI: 10.3233/jhd-240018] [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: 06/23/2024]
Abstract
Background Diffusion magnetic resonance imaging (dMRI) has revealed microstructural changes in white matter (WM) in Huntington's disease (HD). Objective To compare the validities of different dMRI, i.e., diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) in HD. Methods 22 mutant huntingtin (mHTT) carriers and 14 controls were enrolled. Clinical assessments and dMRI were conducted. Based on CAG-Age Product (CAP) score, mHTT carriers were categorized into high CAP (hCAP) and medium and low CAP (m& lCAP) groups. Spearman analyses were used to explore correlations between imaging parameters in brain regions and clinical assessments. Receiver operating characteristic (ROC) was used to distinguish mHTT carriers from control, and define the HD patients at advanced stage. Results Compared to controls, mHTT carriers exhibited WM changes in DKI and DTI. There were 22 more regions showing significant differences in HD detected by MK than FA. Only MK in five brain regions showed significantly difference between any two group, and negatively correlated with the disease burden (r = -0.80 to -0.71). ROC analysis revealed that MK was more sensitive and FA was more specific, while Youden index showed that the integration of FA and MK gave rise to higher authenticities, in distinguishing m& lCAP from controls (Youden Index = 0.786), and discerning different phase of HD (Youden Index = 0.804). Conclusions Microstructural changes in WM occur at early stage of HD and deteriorate over the disease progression. Integrating DKI and DTI would provide the best accuracies for differentiating early HD from control and identifying advanced HD.
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Affiliation(s)
- Jin-Hui Yin
- Human Brain & Tissue Bank, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ya-Ou Liu
- Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Hong-Liang Li
- Department of Neurology, Aviation General Hospital, Beijing, China
| | - Jean Marc Burgunder
- Department of Neurology, Swiss Huntington's Disease Centre, Siloah, and Department of Neurology, University Hospital, Gümligen (Muri bei Bern), Switzerland
| | - Yue Huang
- Human Brain & Tissue Bank, China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Pharmacology Department, School of Biomedical Sciences, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
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Hu B, Younes L, Bu X, Liu CF, Ratnanather JT, Paulsen J, Georgiou-Karistianis N, Miller MI, Ross C, Faria AV. Mixed longitudinal and cross-sectional analyses of deep gray matter and white matter using diffusion weighted images in premanifest and manifest Huntington's disease. Neuroimage Clin 2023; 39:103493. [PMID: 37582307 PMCID: PMC10448214 DOI: 10.1016/j.nicl.2023.103493] [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: 12/01/2022] [Revised: 04/29/2023] [Accepted: 08/07/2023] [Indexed: 08/17/2023]
Abstract
Changes in the brain of patients with Huntington's disease (HD) begin years before clinical onset, so it remains critical to identify biomarkers to track these early changes. Metrics derived from tensor modeling of diffusion-weighted MRIs (DTI), that indicate the microscopic brain structure, can add important information to regional volumetric measurements. This study uses two large-scale longitudinal, multicenter datasets, PREDICT-HD and IMAGE-HD, to trace changes in DTI of HD participants with a broad range of CAP scores (a product of CAG repeat expansion and age), including those with pre-manifest disease (i.e., prior to clinical onset). Utilizing a fully automated data-driven approach to study the whole brain divided in regions of interest, we traced changes in DTI metrics (diffusivity and fractional anisotropy) versus CAP scores, using sigmoidal and linear regression models. We identified points of inflection in the sigmoidal regression using change-point analysis. The deep gray matter showed more evident and earlier changes in DTI metrics over CAP scores, compared to the deep white matter. In the deep white matter, these changes were more evident and occurred earlier in superior and posterior areas, compared to anterior and inferior areas. The curves of mean diffusivity vs. age of HD participants within a fixed CAP score were different from those of controls, indicating that the disease has an additional effect to age on the microscopic brain structure. These results show the regional and temporal vulnerability of the white matter and deep gray matter in HD, with potential implications for experimental therapeutics.
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Affiliation(s)
- Beini Hu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Laurent Younes
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Xuan Bu
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Chin-Fu Liu
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - J Tilak Ratnanather
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Jane Paulsen
- Department of Psychiatry, Neurology, Psychological Brain Sciences, University of Iowa, USA; Department Neurology, University of Wisconsin-Madison, USA
| | - Nellie Georgiou-Karistianis
- School of Psychological Sciences and Turner Institute of Brain and Mental Health, Monash University, Australia
| | - Michael I Miller
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Christopher Ross
- Department of Psychiatry, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Andreia V Faria
- Department of Radiology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
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3
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Estevez-Fraga C, Scahill R, Rees G, Tabrizi SJ, Gregory S. Diffusion imaging in Huntington's disease: comprehensive review. J Neurol Neurosurg Psychiatry 2020; 92:jnnp-2020-324377. [PMID: 33033167 PMCID: PMC7803908 DOI: 10.1136/jnnp-2020-324377] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 09/07/2020] [Accepted: 09/07/2020] [Indexed: 12/31/2022]
Abstract
Huntington's disease (HD) is a monogenic disorder with 100% penetrance. With the advent of genetic testing in adults, disease-related, structural brain changes can be investigated from the earliest, premorbid stages of HD. While examining macrostructural change characterises global neuronal damage, investigating microstructural alterations provides information regarding brain organisation and its underlying biological properties. Diffusion MRI can be used to track the progression of microstructural anomalies in HD decades prior to clinical disease onset, providing a greater understanding of neurodegeneration. Multiple approaches, including voxelwise, region of interest and tractography, have been used in HD cohorts, showing a centrifugal pattern of white matter (WM) degeneration starting from deep brain areas, which is consistent with neuropathological studies. The corpus callosum, longer WM tracts and areas that are more densely connected, in particular the sensorimotor network, also tend to be affected early during premanifest stages. Recent evidence supports the routine inclusion of diffusion analyses within clinical trials principally as an additional measure to improve understanding of treatment effects, while the advent of novel techniques such as multitissue compartment models and connectomics can help characterise the underpinnings of progressive functional decline in HD.
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Affiliation(s)
- Carlos Estevez-Fraga
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Rachael Scahill
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Geraint Rees
- Wellcome Centre for Neuroimaging, University College London, London, UK
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Sarah J Tabrizi
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah Gregory
- Huntington's Disease Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
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4
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Steventon JJ, Trueman RC, Rosser AE, Jones DK. Robust MR-based approaches to quantifying white matter structure and structure/function alterations in Huntington's disease. J Neurosci Methods 2016; 265:2-12. [PMID: 26335798 PMCID: PMC4863525 DOI: 10.1016/j.jneumeth.2015.08.027] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2015] [Revised: 08/17/2015] [Accepted: 08/20/2015] [Indexed: 12/02/2022]
Abstract
BACKGROUND Huge advances have been made in understanding and addressing confounds in diffusion MRI data to quantify white matter microstructure. However, there has been a lag in applying these advances in clinical research. Some confounds are more pronounced in HD which impedes data quality and interpretability of patient-control differences. This study presents an optimised analysis pipeline and addresses specific confounds in a HD patient cohort. METHOD 15 HD gene-positive and 13 matched control participants were scanned on a 3T MRI system with two diffusion MRI sequences. An optimised post processing pipeline included motion, eddy current and EPI correction, rotation of the B matrix, free water elimination (FWE) and tractography analysis using an algorithm capable of reconstructing crossing fibres. The corpus callosum was examined using both a region-of-interest and a deterministic tractography approach, using both conventional diffusion tensor imaging (DTI)-based and spherical deconvolution analyses. RESULTS Correcting for CSF contamination significantly altered microstructural metrics and the detection of group differences. Reconstructing the corpus callosum using spherical deconvolution produced a more complete reconstruction with greater sensitivity to group differences, compared to DTI-based tractography. Tissue volume fraction (TVF) was reduced in HD participants and was more sensitive to disease burden compared to DTI metrics. CONCLUSION Addressing confounds in diffusion MR data results in more valid, anatomically faithful white matter tract reconstructions with reduced within-group variance. TVF is recommended as a complementary metric, providing insight into the relationship with clinical symptoms in HD not fully captured by conventional DTI metrics.
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Affiliation(s)
- Jessica J Steventon
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Park Place, Cardiff CF10 3AT, UK; Brain Repair Group, Life Science Building, 3rd Floor, School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, UK; Neuroscience and Mental Health Research Institute, Cardiff University, Hadyn Ellis Building, Cathays, Cardiff CF24 4HQ, UK.
| | - Rebecca C Trueman
- Brain Repair Group, Life Science Building, 3rd Floor, School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, UK; School of Biomedical Sciences, Queen's Medical Centre, Nottingham University, Nottingham NG7 2UH, UK
| | - Anne E Rosser
- Brain Repair Group, Life Science Building, 3rd Floor, School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, UK; Neuroscience and Mental Health Research Institute, Cardiff University, Hadyn Ellis Building, Cathays, Cardiff CF24 4HQ, UK; Institute of Psychological Medicine and Neurology, School of Medicine, Hadyn Ellis Building, Maindy Road, Cathays, Cardiff CF24 4HQ, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Park Place, Cardiff CF10 3AT, UK; Neuroscience and Mental Health Research Institute, Cardiff University, Hadyn Ellis Building, Cathays, Cardiff CF24 4HQ, UK
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5
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Gregory S, Cole JH, Farmer RE, Rees EM, Roos RA, Sprengelmeyer R, Durr A, Landwehrmeyer B, Zhang H, Scahill RI, Tabrizi SJ, Frost C, Hobbs NZ. Longitudinal Diffusion Tensor Imaging Shows Progressive Changes in White Matter in Huntington’s Disease. J Huntingtons Dis 2015; 4:333-46. [DOI: 10.3233/jhd-150173] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Sarah Gregory
- Wellcome Trust Centre for Neuroimaging, UCL, London, WC1N 3BG, UK
| | - James H. Cole
- UCL Institute of Neurology, University College London, UK
- Computational, Cognitive & Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, UK
| | - Ruth E. Farmer
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine London, UK
| | - Elin M. Rees
- UCL Institute of Neurology, University College London, UK
| | - Raymund A.C. Roos
- Department of Neurology, Leiden University Medical Centre, 2300RC Leiden, The Netherlands
| | | | - Alexandra Durr
- Department of Genetics and Cytogenetics, INSERM UMR S679, APHP Hôpital de la Salpêtrière, Paris, France
| | | | - Hui Zhang
- Centre for Medical Image Computing, University College London, UK
| | | | | | - Chris Frost
- Department of Medical Statistics, London School of Hygiene & Tropical Medicine London, UK
| | - Nicola Z. Hobbs
- UCL Institute of Neurology, University College London, UK
- IXICO Plc., London, UK
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6
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Chang R, Liu X, Li S, Li XJ. Transgenic animal models for study of the pathogenesis of Huntington's disease and therapy. DRUG DESIGN DEVELOPMENT AND THERAPY 2015; 9:2179-88. [PMID: 25931812 PMCID: PMC4404937 DOI: 10.2147/dddt.s58470] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Huntington’s disease (HD) is caused by a genetic mutation that results in polyglutamine expansion in the N-terminal regions of huntingtin. As a result, this polyQ expansion leads to the misfolding and aggregation of mutant huntingtin as well as age-dependent neurodegeneration. The genetic mutation in HD allows for generating a variety of animal models that express different forms of mutant huntingtin and show differential pathology. Studies of these animal models have provided an important insight into the pathogenesis of HD. Mouse models of HD include transgenic mice, which express N-terminal or full-length mutant huntingtin ubiquitously or selectively in different cell types, and knock-in mice that express full-length mutant Htt at the endogenous level. Large animals, such as pig, sheep, and monkeys, have also been used to generate animal HD models. This review focuses on the different features of commonly used transgenic HD mouse models as well as transgenic large animal models of HD, and also discusses how to use them to identify potential therapeutics. Since HD shares many pathological features with other neurodegenerative diseases, identification of therapies for HD would also help to develop effective treatment for different neurodegenerative diseases that are also caused by protein misfolding and occur in an age-dependent manner.
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Affiliation(s)
- Renbao Chang
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Xudong Liu
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, People's Republic of China
| | - Shihua Li
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Xiao-Jiang Li
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, People's Republic of China ; Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
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7
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Poudel GR, Stout JC, Domínguez D JF, Salmon L, Churchyard A, Chua P, Georgiou-Karistianis N, Egan GF. White matter connectivity reflects clinical and cognitive status in Huntington's disease. Neurobiol Dis 2014; 65:180-7. [PMID: 24480090 DOI: 10.1016/j.nbd.2014.01.013] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2013] [Revised: 12/18/2013] [Accepted: 01/19/2014] [Indexed: 10/25/2022] Open
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8
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Phillips O, Squitieri F, Sanchez-Castaneda C, Elifani F, Griguoli A, Maglione V, Caltagirone C, Sabatini U, Di Paola M. The Corticospinal Tract in Huntington's Disease. Cereb Cortex 2014; 25:2670-82. [PMID: 24706734 DOI: 10.1093/cercor/bhu065] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Huntington's disease (HD) is characterized by progressive motor impairment. Therefore, the connectivity of the corticospinal tract (CST), which is the main white matter (WM) pathway that conducts motor impulses from the primary motor cortex to the spinal cord, merits particular attention. WM abnormalities have already been shown in presymptomatic (Pre-HD) and symptomatic HD subjects using magnetic resonance imaging (MRI). In the present study, we examined CST microstructure using diffusion tensor imaging (DTI)-based tractography in 30-direction DTI data collected from 100 subjects: Pre-HD subjects (n = 25), HD patients (n = 25) and control subjects (n = 50), and T2*-weighted (iron sensitive) imaging. Results show decreased fractional anisotropy (FA) and increased axial (AD), and radial diffusivity (RD) in the bilateral CST of HD patients. Pre-HD subjects had elevated iron in the left CST, regionally localized between the brainstem and thalamus. CAG repeat length in conjunction with age, as well as motor (UHDRS) assessment were correlated with CST FA, AD, and RD both in Pre-HD and HD. In the presymptomatic phase, increased iron in the inferior portion supports the "dying back" hypothesis that axonal damage advances in a retrograde fashion. Furthermore, early iron alteration may cause a high level of toxicity, which may contribute to further damage.
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Affiliation(s)
- O Phillips
- Clinical and Behavioral Neurology Department, Rome, Italy
| | | | | | - F Elifani
- IRCCS Neuromed (Pozzilli), Pozzilli, Italy
| | - A Griguoli
- IRCCS Neuromed (Pozzilli), Pozzilli, Italy
| | - V Maglione
- IRCCS Neuromed (Pozzilli), Pozzilli, Italy
| | - C Caltagirone
- Clinical and Behavioral Neurology Department, Rome, Italy Neuroscience Department, University of Rome 'Tor Vergata', Rome, Italy
| | - U Sabatini
- Radiology Department, IRCCS Santa Lucia Foundation, Rome, Italy
| | - M Di Paola
- Clinical and Behavioral Neurology Department, Rome, Italy Department of Internal Medicine and Public Health, University of L'Aquila, Rome, Italy
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9
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Wolf RC, Sambataro F, Vasic N, Baldas EM, Ratheiser I, Bernhard Landwehrmeyer G, Depping MS, Thomann PA, Sprengelmeyer R, Süssmuth SD, Orth M. Visual system integrity and cognition in early Huntington's disease. Eur J Neurosci 2014; 40:2417-26. [PMID: 24698429 DOI: 10.1111/ejn.12575] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2013] [Revised: 02/17/2014] [Accepted: 02/27/2014] [Indexed: 10/25/2022]
Abstract
Posterior cortical volume changes and abnormal visuomotor performance are present in patients with Huntington's disease (HD). However, it is unclear whether posterior cortical volume loss contributes to abnormal neural activity, and whether activity changes predict cognitive dysfunction. Using magnetic resonance imaging (MRI), we investigated brain structure and visual network activity at rest in patients with early HD (n = 20) and healthy controls (n = 20). The symbol digit modalities test (SDMT) and subtests of the Visual Object and Space Perception Battery were completed offline. For functional MRI data, a group independent component analysis was used. Voxel-based morphometry was employed to assess regional brain atrophy, and 'biological parametric mapping' analyses were included to investigate the impact of atrophy on neural activity. Patients showed significantly worse visuomotor and visual object performance than controls. Structural analyses confirmed occipitotemporal atrophy. In patients and controls, two spatiotemporally distinct visual systems were identified. Patients showed decreased activity in the left fusiform cortex, and increased left cerebellar activity. These findings remained stable after correction for brain atrophy. Lower fusiform cortex activity was associated with lower SDMT performance and with higher disease burden scores. These associations were absent when cerebellar function was related to task performance and disease burden. The results of this study suggest that regionally specific functional abnormalities of the visual system can account for the worse visuomotor cognition in HD patients. However, occipital volume changes cannot sufficiently explain abnormal neural function in these patients.
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Affiliation(s)
- Robert C Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, University of Heidelberg, Voßstraße 4, Heidelberg, 69115, Germany
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10
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Novak MJ, Seunarine KK, Gibbard CR, Hobbs NZ, Scahill RI, Clark CA, Tabrizi SJ. White matter integrity in premanifest and early Huntington's disease is related to caudate loss and disease progression. Cortex 2014; 52:98-112. [DOI: 10.1016/j.cortex.2013.11.009] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2013] [Revised: 08/26/2013] [Accepted: 11/25/2013] [Indexed: 11/26/2022]
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11
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Hess CW, Ofori E, Akbar U, Okun MS, Vaillancourt DE. The evolving role of diffusion magnetic resonance imaging in movement disorders. Curr Neurol Neurosci Rep 2013; 13:400. [PMID: 24046183 PMCID: PMC3824956 DOI: 10.1007/s11910-013-0400-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Significant advances have allowed diffusion magnetic resonance imaging (MRI) to evolve into a powerful tool in the field of movement disorders that can be used to study disease states and connectivity between brain regions. Diffusion MRI is a promising potential biomarker for Parkinson's disease and other forms of parkinsonism, and may allow the distinction of different forms of parkinsonism. Techniques such as tractography have contributed to our current thinking regarding the pathophysiology of dystonia and possible mechanisms of penetrance. Diffusion MRI measures could potentially assist in monitoring disease progression in Huntington's disease, and in uncovering the nature of the processes and structures involved the development of essential tremor. The ability to represent structural connectivity in vivo also makes diffusion MRI an ideal adjunctive tool for the surgical treatment of movement disorders. We review recent studies using diffusion MRI in movement disorders research and present the current state of the science as well as future directions.
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Affiliation(s)
- Christopher W. Hess
- Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
- University of Florida Center for Movement Disorders & Neurorestoration, Gainesville, FL, USA
- Neurology Service, Malcom Randall VA Medical Center, Gainesville, FL, USA
| | - Edward Ofori
- Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
| | - Umer Akbar
- University of Florida Center for Movement Disorders & Neurorestoration, Gainesville, FL, USA
| | - Michael S. Okun
- University of Florida Center for Movement Disorders & Neurorestoration, Gainesville, FL, USA
| | - David E. Vaillancourt
- Laboratory for Rehabilitation Neuroscience, University of Florida, Gainesville, FL, USA
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12
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Phillips O, Sanchez-Castaneda C, Elifani F, Maglione V, Di Pardo A, Caltagirone C, Squitieri F, Sabatini U, Di Paola M. Tractography of the corpus callosum in Huntington's disease. PLoS One 2013; 8:e73280. [PMID: 24019913 PMCID: PMC3760905 DOI: 10.1371/journal.pone.0073280] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2013] [Accepted: 07/18/2013] [Indexed: 12/22/2022] Open
Abstract
White matter abnormalities have been shown in presymptomatic and symptomatic Huntington's disease (HD) subjects using Magnetic Resonance Imaging (MRI) and Diffusion Tensor Imaging (DTI) methods. The largest white matter tract, the corpus callosum (CC), has been shown to be particularly vulnerable; however, little work has been done to investigate the regional specificity of tract abnormalities in the CC. Thus, this study examined the major callosal tracts by applying DTI-based tractography. Using TrackVis, a previously defined region of interest tractography method parcellating CC into seven major tracts based on target region was applied to 30 direction DTI data collected from 100 subjects: presymptomatic HD (Pre-HD) subjects (n=25), HD patients (n=25) and healthy control subjects (n=50). Tractography results showed decreased fractional anisotropy (FA) and increased radial diffusivity (RD) across broad regions of the CC in Pre-HD subjects. Similar though more severe deficits were seen in HD patients. In Pre-HD and HD, callosal FA and RD were correlated with Disease Burden/CAG repeat length as well as motor (UHDRSI) and cognitive (URDRS2) assessments. These results add evidence that CC pathways are compromised prior to disease onset with possible demyelination occurring early in the disease and suggest that CAG repeat length is a contributing factor to connectivity deficits. Furthermore, disruption of these callosal pathways potentially contributes to the disturbances of motor and cognitive processing that characterize HD.
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Affiliation(s)
- Owen Phillips
- Clinical and Behavioural Neurology Department, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
| | - Cristina Sanchez-Castaneda
- Radiology Department, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
| | - Francesca Elifani
- Centre for Neurogenetics and Rare Diseases, Istituto di Ricovero e Cura a Carattere Scientifico Neuromed, Pozzilli, Italy
| | - Vittorio Maglione
- Centre for Neurogenetics and Rare Diseases, Istituto di Ricovero e Cura a Carattere Scientifico Neuromed, Pozzilli, Italy
| | - Alba Di Pardo
- Centre for Neurogenetics and Rare Diseases, Istituto di Ricovero e Cura a Carattere Scientifico Neuromed, Pozzilli, Italy
| | - Carlo Caltagirone
- Clinical and Behavioural Neurology Department, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
- Neuroscience Department, University of Rome “Tor Vergata,” Rome, Italy
| | - Ferdinando Squitieri
- Centre for Neurogenetics and Rare Diseases, Istituto di Ricovero e Cura a Carattere Scientifico Neuromed, Pozzilli, Italy
| | - Umberto Sabatini
- Radiology Department, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
| | - Margherita Di Paola
- Clinical and Behavioural Neurology Department, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia Foundation, Rome, Italy
- Department of Internal Medicine and Public Health, University of L’Aquila, L’Aquila, Italy
- * E-mail:
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13
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Müller HP, Kassubek J. Diffusion tensor magnetic resonance imaging in the analysis of neurodegenerative diseases. J Vis Exp 2013. [PMID: 23928996 DOI: 10.3791/50427] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Diffusion tensor imaging (DTI) techniques provide information on the microstructural processes of the cerebral white matter (WM) in vivo. The present applications are designed to investigate differences of WM involvement patterns in different brain diseases, especially neurodegenerative disorders, by use of different DTI analyses in comparison with matched controls. DTI data analysis is performed in a variate fashion, i.e. voxelwise comparison of regional diffusion direction-based metrics such as fractional anisotropy (FA), together with fiber tracking (FT) accompanied by tractwise fractional anisotropy statistics (TFAS) at the group level in order to identify differences in FA along WM structures, aiming at the definition of regional patterns of WM alterations at the group level. Transformation into a stereotaxic standard space is a prerequisite for group studies and requires thorough data processing to preserve directional inter-dependencies. The present applications show optimized technical approaches for this preservation of quantitative and directional information during spatial normalization in data analyses at the group level. On this basis, FT techniques can be applied to group averaged data in order to quantify metrics information as defined by FT. Additionally, application of DTI methods, i.e. differences in FA-maps after stereotaxic alignment, in a longitudinal analysis at an individual subject basis reveal information about the progression of neurological disorders. Further quality improvement of DTI based results can be obtained during preprocessing by application of a controlled elimination of gradient directions with high noise levels. In summary, DTI is used to define a distinct WM pathoanatomy of different brain diseases by the combination of whole brain-based and tract-based DTI analysis.
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14
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Diffusion imaging quality control via entropy of principal direction distribution. Neuroimage 2013; 82:1-12. [PMID: 23684874 DOI: 10.1016/j.neuroimage.2013.05.022] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2012] [Revised: 04/25/2013] [Accepted: 05/03/2013] [Indexed: 12/11/2022] Open
Abstract
Diffusion MR imaging has received increasing attention in the neuroimaging community, as it yields new insights into the microstructural organization of white matter that are not available with conventional MRI techniques. While the technology has enormous potential, diffusion MRI suffers from a unique and complex set of image quality problems, limiting the sensitivity of studies and reducing the accuracy of findings. Furthermore, the acquisition time for diffusion MRI is longer than conventional MRI due to the need for multiple acquisitions to obtain directionally encoded Diffusion Weighted Images (DWI). This leads to increased motion artifacts, reduced signal-to-noise ratio (SNR), and increased proneness to a wide variety of artifacts, including eddy-current and motion artifacts, "venetian blind" artifacts, as well as slice-wise and gradient-wise inconsistencies. Such artifacts mandate stringent Quality Control (QC) schemes in the processing of diffusion MRI data. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts, often only visible when investigating groups of DWI's or a derived diffusion model, such as the most-employed diffusion tensor imaging (DTI). Here, we propose a novel regional QC measure in the DTI domain that employs the entropy of the regional distribution of the principal directions (PD). The PD entropy quantifies the scattering and spread of the principal diffusion directions and is invariant to the patient's position in the scanner. High entropy value indicates that the PDs are distributed relatively uniformly, while low entropy value indicates the presence of clusters in the PD distribution. The novel QC measure is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Such residual artifacts cause directional bias in the measured PD and here called dominant direction artifacts. Experiments show that our automatic method can reliably detect and potentially correct such artifacts, especially the ones caused by the vibrations of the scanner table during the scan. The results further indicate the usefulness of this method for general quality assessment in DTI studies.
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Matsui JT, Vaidya JG, Johnson HJ, Magnotta VA, Long JD, Mills JA, Lowe MJ, Sakaie KE, Rao SM, Smith MM, Paulsen JS. Diffusion weighted imaging of prefrontal cortex in prodromal Huntington's disease. Hum Brain Mapp 2013; 35:1562-73. [PMID: 23568433 DOI: 10.1002/hbm.22273] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2012] [Revised: 11/09/2012] [Accepted: 01/28/2013] [Indexed: 11/07/2022] Open
Abstract
Huntington's disease (HD) is a devastating neurodegenerative disease with no effective disease-modifying treatments. There is considerable interest in finding reliable indicators of disease progression to judge the efficacy of novel treatments that slow or stop disease onset before debilitating signs appear. Diffusion-weighted imaging (DWI) may provide a reliable marker of disease progression by characterizing diffusivity changes in white matter (WM) in individuals with prodromal HD. The prefrontal cortex (PFC) may play a role in HD progression due to its prominent striatal connections and documented role in executive function. This study uses DWI to characterize diffusivity in specific regions of PFC WM defined by FreeSurfer in 53 prodromal HD participants and 34 controls. Prodromal HD individuals were separated into three CAG-Age Product (CAP) groups (16 low, 22 medium, 15 high) that indexed baseline progression. Statistically significant increases in mean diffusivity (MD) and radial diffusivity (RD) among CAP groups relative to controls were seen in inferior and lateral PFC regions. For MD and RD, differences among controls and HD participants tracked with baseline disease progression. The smallest difference was for the low group and the largest for the high group. Significant correlations between Trail Making Test B (TMTB) and mean fractional anisotropy (FA) and/or RD paralleled group differences in mean MD and/or RD in several right hemisphere regions. The gradient of effects that tracked with CAP group suggests DWI may provide markers of disease progression in future longitudinal studies as increasing diffusivity abnormalities in the lateral PFC of prodromal HD individuals.
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Affiliation(s)
- Joy T Matsui
- Department of Psychiatry, The University of Iowa, Iowa City, Iowa; John A. Burns School of Medicine, The University of Hawaii, Honolulu, Hawaii
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Mohammadi S, Hutton C, Nagy Z, Josephs O, Weiskopf N. Retrospective correction of physiological noise in DTI using an extended tensor model and peripheral measurements. Magn Reson Med 2012; 70:358-69. [PMID: 22936599 PMCID: PMC3792745 DOI: 10.1002/mrm.24467] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2012] [Revised: 07/23/2012] [Accepted: 08/01/2012] [Indexed: 11/07/2022]
Abstract
Diffusion tensor imaging is widely used in research and clinical applications, but this modality is highly sensitive to artefacts. We developed an easy-to-implement extension of the original diffusion tensor model to account for physiological noise in diffusion tensor imaging using measures of peripheral physiology (pulse and respiration), the so-called extended tensor model. Within the framework of the extended tensor model two types of regressors, which respectively modeled small (linear) and strong (nonlinear) variations in the diffusion signal, were derived from peripheral measures. We tested the performance of four extended tensor models with different physiological noise regressors on nongated and gated diffusion tensor imaging data, and compared it to an established data-driven robust fitting method. In the brainstem and cerebellum the extended tensor models reduced the noise in the tensor-fit by up to 23% in accordance with previous studies on physiological noise. The extended tensor model addresses both large-amplitude outliers and small-amplitude signal-changes. The framework of the extended tensor model also facilitates further investigation into physiological noise in diffusion tensor imaging. The proposed extended tensor model can be readily combined with other artefact correction methods such as robust fitting and eddy current correction.
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Affiliation(s)
- Siawoosh Mohammadi
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London, UK.
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Mohammadi S, Nagy Z, Hutton C, Josephs O, Weiskopf N. Correction of vibration artifacts in DTI using phase-encoding reversal (COVIPER). Magn Reson Med 2011; 68:882-9. [PMID: 22213396 PMCID: PMC3569871 DOI: 10.1002/mrm.23308] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2011] [Revised: 10/07/2011] [Accepted: 11/07/2011] [Indexed: 11/11/2022]
Abstract
Diffusion tensor imaging is widely used in research and clinical applications, but still suffers from substantial artifacts. Here, we focus on vibrations induced by strong diffusion gradients in diffusion tensor imaging, causing an echo shift in k-space and consequential signal-loss. We refined the model of vibration-induced echo shifts, showing that asymmetric k-space coverage in widely used Partial Fourier acquisitions results in locally differing signal loss in images acquired with reversed phase encoding direction (blip-up/blip-down). We implemented a correction of vibration artifacts in diffusion tensor imaging using phase-encoding reversal (COVIPER) by combining blip-up and blip-down images, each weighted by a function of its local tensor-fit error. COVIPER was validated against low vibration reference data, resulting in an error reduction of about 72% in fractional anisotropy maps. COVIPER can be combined with other corrections based on phase encoding reversal, providing a comprehensive correction for eddy currents, susceptibility-related distortions and vibration artifact reduction.
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Affiliation(s)
- Siawoosh Mohammadi
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, United Kingdom.
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Müller HP, Süssmuth SD, Landwehrmeyer GB, Ludolph A, Tabrizi SJ, Kloppel S, Kassubek J. Stability effects on results of diffusion tensor imaging analysis by reduction of the number of gradient directions due to motion artifacts: an application to presymptomatic Huntington's disease. PLOS CURRENTS 2011; 3:RRN1292. [PMID: 22307262 PMCID: PMC3269342 DOI: 10.1371/currents.rrn1292] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 12/12/2011] [Indexed: 12/11/2022]
Abstract
In diffusion tensor imaging (DTI), an improvement in the signal-to-noise ratio (SNR) of the fractional anisotropy (FA) maps can be obtained when the number of recorded gradient directions (GD) is increased. Vice versa, elimination of motion-corrupted or noisy GD leads to a more accurate characterization of the diffusion tensor. We previously suggest a slice-wise method for artifact detection in FA maps. This current study applies this approach to a cohort of 18 premanifest Huntington's disease (pHD) subjects and 23 controls. By 2-D voxelwise statistical comparison of original FA-maps and FA-maps with a reduced number of GD, the effect of eliminating GD that were affected by motion was demonstrated.We present an evaluation metric that allows to test if the computed FA-maps (with a reduced number of GD) still reflect a "true" FA-map, as defined by simulations in the control sample. Furthermore, we investigated if omitting data volumes affected by motion in the pHD cohort could lead to an increased SNR in the resulting FA-maps.A high agreement between original FA maps (with all GD) and corrected FA maps (i.e. without GD corrupted by motion) were observed even for numbers of eliminated GD up to 13. Even in one data set in which 46 GD had to be eliminated, the results showed a moderate agreement.
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Affiliation(s)
- Hans-Peter Müller
- Dept. of Neurology, University of Ulm, Ulm, Germany; Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK and Freiburg Brain Imaging, Department of Psychiatry and Psychotherapy. University of Freiburg
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