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Barrett RLC, Cash D, Simmons C, Kim E, Wood TC, Stones R, Vernon AC, Catani M, Dell'Acqua F. Tissue optimization strategies for high-quality ex vivo diffusion imaging. NMR IN BIOMEDICINE 2023; 36:e4866. [PMID: 36321360 PMCID: PMC10078604 DOI: 10.1002/nbm.4866] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 09/09/2022] [Accepted: 10/03/2022] [Indexed: 06/16/2023]
Abstract
Ex vivo diffusion imaging can be used to study healthy and pathological tissue microstructure in the rodent brain with high resolution, providing a link between in vivo MRI and ex vivo microscopy techniques. Major challenges for the successful acquisition of ex vivo diffusion imaging data however are changes in the relaxivity and diffusivity of brain tissue following perfusion fixation. In this study we address this question by examining the combined effects of tissue preparation factors that influence signal-to-noise ratio (SNR) and consequently image quality, including fixative concentration, contrast agent concentration and tissue rehydration time. We present an optimization strategy combining these factors to manipulate theT 1 andT 2 of fixed tissue and maximize SNR efficiency. We apply this strategy in the rat brain, for a diffusion-weighted spin echo protocol with TE = 27 ms on a 9.4 T scanner with a 39 mm volume coil and 660 mT/m 114 mm gradient insert. We used a reduced fixative concentration of 2% paraformaldehyde (PFA), rehydration time more than 20 days, 15 mM Gd-DTPA in perfusate and TR 250 ms. This resulted in a doubling of SNR and an increase in SNR per unit time of 135% in cortical grey matter and 88% in white matter compared with 4% PFA and no contrast agent. This improved SNR efficiency enabled the acquisition of excellent-quality high-resolution (78 μ m isotropic voxel size) diffusion data with b = 4000 s/mm2 , 30 diffusion directions and a field of view of 40 × 13 × 18 mm3 in less than 4 days. It was also possible to achieve comparable data quality for a standard resolution (150 μ m) diffusion dataset in 2 1 4 h. In conclusion, the tissue optimization strategy presented here may be used to improve SNR, increase spatial resolution and/or allow faster acquisitions in preclinical ex vivo diffusion MRI experiments.
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Affiliation(s)
- Rachel L. C. Barrett
- NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
- Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
| | - Diana Cash
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
| | - Camilla Simmons
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
| | - Eugene Kim
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
| | - Tobias C. Wood
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
| | - Richard Stones
- NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
- Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
| | - Anthony C. Vernon
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology, and Neuroscience, King's College LondonUK
| | - Marco Catani
- NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
- Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
| | - Flavio Dell'Acqua
- NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
- Sackler Institute for Translational Neurodevelopment, Department of Forensic and Neurodevelopmental Science, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonUK
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2
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Zeng C, Chen Z, Yang H, Fan Y, Fei L, Chen X, Zhang M. Advanced high resolution three-dimensional imaging to visualize the cerebral neurovascular network in stroke. Int J Biol Sci 2022; 18:552-571. [PMID: 35002509 PMCID: PMC8741851 DOI: 10.7150/ijbs.64373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 10/28/2021] [Indexed: 11/05/2022] Open
Abstract
As an important method to accurately and timely diagnose stroke and study physiological characteristics and pathological mechanism in it, imaging technology has gone through more than a century of iteration. The interaction of cells densely packed in the brain is three-dimensional (3D), but the flat images brought by traditional visualization methods show only a few cells and ignore connections outside the slices. The increased resolution allows for a more microscopic and underlying view. Today's intuitive 3D imagings of micron or even nanometer scale are showing its essentiality in stroke. In recent years, 3D imaging technology has gained rapid development. With the overhaul of imaging mediums and the innovation of imaging mode, the resolution has been significantly improved, endowing researchers with the capability of holistic observation of a large volume, real-time monitoring of tiny voxels, and quantitative measurement of spatial parameters. In this review, we will summarize the current methods of high-resolution 3D imaging applied in stroke.
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Affiliation(s)
- Chudai Zeng
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Zhuohui Chen
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Haojun Yang
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Yishu Fan
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Lujing Fei
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Xinghang Chen
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
| | - Mengqi Zhang
- Department of Neurology, Xiangya Hospital of Central South University, Changsha, Hunan, China, 410008.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China, 410008
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3
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Preparation of Ex Vivo Rodent Phantoms for Developing, Testing, and Training MR Imaging of the Kidney and Other Organs. Methods Mol Biol 2021; 2216:75-85. [PMID: 33475995 DOI: 10.1007/978-1-0716-0978-1_5] [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] [Indexed: 03/28/2023]
Abstract
Here we describe a simple and inexpensive protocol for preparing ex vivo rodent phantoms for use in MR imaging studies. The experimental animals are perfused and fixed with formaldehyde, and then wrapped with gauze and sealed with liquid latex. This yields a phantom that preserves all organs in situ, and which avoids the need to keep fixed animals and organs in containers that have dimensions very different from living animals. This is especially important for loading in MR detectors, and specifically the RF coils, they are usually used with. The phantom can be safely stored and conveniently reused, and can provide MR scientists with a realistic phantom with which to establish protocols in preparation for preclinical in vivo studies-for renal, brain, and body imaging. The phantom also serves as an ideal teaching tool, for trainees learning how to perform preclinical MRI investigations of the kidney and other target organs, while avoiding the need for handling living animals, and reducing the total number of animals required.This protocol chapter is part of the PARENCHIMA initiative "MRI Biomarkers for CKD " (CA16103), a community-driven Action of the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers.
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4
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Ly M, Foley L, Manivannan A, Hitchens TK, Richardson RM, Modo M. Mesoscale diffusion magnetic resonance imaging of the ex vivo human hippocampus. Hum Brain Mapp 2020; 41:4200-4218. [PMID: 32621364 PMCID: PMC7502840 DOI: 10.1002/hbm.25119] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/01/2020] [Accepted: 06/16/2020] [Indexed: 12/21/2022] Open
Abstract
Mesoscale diffusion magnetic resonance imaging (MRI) endeavors to bridge the gap between macroscopic white matter tractography and microscopic studies investigating the cytoarchitecture of human brain tissue. To ensure a robust measurement of diffusion at the mesoscale, acquisition parameters were arrayed to investigate their effects on scalar indices (mean, radial, axial diffusivity, and fractional anisotropy) and streamlines (i.e., graphical representation of axonal tracts) in hippocampal layers. A mesoscale resolution afforded segementation of the pyramidal cell layer (CA1-4), the dentate gyrus, as well as stratum moleculare, radiatum, and oriens. Using ex vivo samples, surgically excised from patients with intractable epilepsy (n = 3), we found that shorter diffusion times (23.7 ms) with a b-value of 4,000 s/mm2 were advantageous at the mesoscale, providing a compromise between mean diffusivity and fractional anisotropy measurements. Spatial resolution and sample orientation exerted a major effect on tractography, whereas the number of diffusion gradient encoding directions minimally affected scalar indices and streamline density. A sample temperature of 15°C provided a compromise between increasing signal-to-noise ratio and increasing the diffusion properties of the tissue. Optimization of the acquisition afforded a system's view of intra- and extra-hippocampal connections. Tractography reflected histological boundaries of hippocampal layers. Individual layer connectivity was visualized, as well as streamlines emanating from individual sub-fields. The perforant path, subiculum and angular bundle demonstrated extra-hippocampal connections. Histology of the samples confirmed individual cell layers corresponding to ROIs defined on MR images. We anticipate that this ex vivo mesoscale imaging will yield novel insights into human hippocampal connectivity.
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Affiliation(s)
- Maria Ly
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Lesley Foley
- Department of NeurobiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | | | - T. Kevin Hitchens
- Department of NeurobiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - R. Mark Richardson
- Department of Neurological SurgeryUniversity of PittsburghPittsburghPennsylvaniaUSA
- McGowan Institute for Regenerative MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Brain InstituteUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Michel Modo
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- McGowan Institute for Regenerative MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of BioengineeringUniversity of PittsburghPittsburghPennsylvaniaUSA
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5
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Ma D, Cardoso MJ, Zuluaga MA, Modat M, Powell NM, Wiseman FK, Cleary JO, Sinclair B, Harrison IF, Siow B, Popuri K, Lee S, Matsubara JA, Sarunic MV, Beg MF, Tybulewicz VLJ, Fisher EMC, Lythgoe MF, Ourselin S. Substantially thinner internal granular layer and reduced molecular layer surface in the cerebellar cortex of the Tc1 mouse model of down syndrome - a comprehensive morphometric analysis with active staining contrast-enhanced MRI. Neuroimage 2020; 223:117271. [PMID: 32835824 PMCID: PMC8417772 DOI: 10.1016/j.neuroimage.2020.117271] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 08/03/2020] [Accepted: 08/10/2020] [Indexed: 12/18/2022] Open
Abstract
Down Syndrome is a chromosomal disorder that affects the development of cerebellar cortical lobules. Impaired neurogenesis in the cerebellum varies among different types of neuronal cells and neuronal layers. In this study, we developed an imaging analysis framework that utilizes gadolinium-enhanced ex vivo mouse brain MRI. We extracted the middle Purkinje layer of the mouse cerebellar cortex, enabling the estimation of the volume, thickness, and surface area of the entire cerebellar cortex, the internal granular layer, and the molecular layer in the Tc1 mouse model of Down Syndrome. The morphometric analysis of our method revealed that a larger proportion of the cerebellar thinning in this model of Down Syndrome resided in the inner granule cell layer, while a larger proportion of the surface area shrinkage was in the molecular layer.
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Affiliation(s)
- Da Ma
- Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom; Centre for Advanced Biomedical Imaging, University College London, United Kingdom; School of Engineering Science, Simon Fraser University, Burnaby, Canada.
| | - Manuel J Cardoso
- Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom; School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom
| | - Maria A Zuluaga
- Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom; Data Science Department, EURECOM, France
| | - Marc Modat
- Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom; School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom
| | - Nick M Powell
- Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom; Centre for Advanced Biomedical Imaging, University College London, United Kingdom
| | - Frances K Wiseman
- UK Dementia Research Institute at University College London, UK London; Down Syndrome Consortium (LonDownS), London, United Kingdom
| | - Jon O Cleary
- Centre for Advanced Biomedical Imaging, University College London, United Kingdom; Department of Radiology, Guy´s and St Thomas' NHS Foundation Trust, United Kingdom; Melbourne Brain Centre Imaging Unit, Department of Medicine and Radiology, University of Melbourne, Melbourne, Australia
| | - Benjamin Sinclair
- Centre for Advanced Biomedical Imaging, University College London, United Kingdom
| | - Ian F Harrison
- Centre for Advanced Biomedical Imaging, University College London, United Kingdom
| | - Bernard Siow
- Centre for Advanced Biomedical Imaging, University College London, United Kingdom; The Francis Crick Institute, London, United Kingdom
| | - Karteek Popuri
- School of Engineering Science, Simon Fraser University, Burnaby, Canada
| | - Sieun Lee
- School of Engineering Science, Simon Fraser University, Burnaby, Canada
| | - Joanne A Matsubara
- Department of Ophthalmology & Visual Science, University of British Columbia, Vancouver, Canada
| | - Marinko V Sarunic
- School of Engineering Science, Simon Fraser University, Burnaby, Canada
| | - Mirza Faisal Beg
- School of Engineering Science, Simon Fraser University, Burnaby, Canada
| | - Victor L J Tybulewicz
- The Francis Crick Institute, London, United Kingdom; Department of Immunology and Inflammation, Imperial College, London, United Kingdom
| | | | - Mark F Lythgoe
- Centre for Advanced Biomedical Imaging, University College London, United Kingdom
| | - Sebastien Ourselin
- Department of Medical Physics and Biomedical Engineering, University College London, United Kingdom; School of Biomedical Engineering & Imaging Sciences, King's College London, United Kingdom
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6
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Badea A, Ng KL, Anderson RJ, Zhang J, Miller MI, O’Brien RJ. Magnetic resonance imaging of mouse brain networks plasticity following motor learning. PLoS One 2019; 14:e0216596. [PMID: 31067263 PMCID: PMC6505950 DOI: 10.1371/journal.pone.0216596] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Accepted: 04/24/2019] [Indexed: 12/12/2022] Open
Abstract
We do not have a full understanding of the mechanisms underlying plasticity in the human brain. Mouse models have well controlled environments and genetics, and provide tools to help dissect the mechanisms underlying the observed responses to therapies devised for humans recovering from injury of ischemic nature or trauma. We aimed to detect plasticity following learning of a unilateral reaching movement, and relied on MRI performed with a rapid structural protocol suitable for in vivo brain imaging, and a longer diffusion tensor imaging (DTI) protocol executed ex vivo. In vivo MRI detected contralateral volume increases in trained animals (reachers), in circuits involved in motor control, sensory processing, and importantly, learning and memory. The temporal association area, parafascicular and mediodorsal thalamic nuclei were also enlarged. In vivo MRI allowed us to detect longitudinal effects over the ~25 days training period. The interaction between time and group (trained versus not trained) supported a role for the contralateral, but also the ipsilateral hemisphere. While ex vivo imaging was affected by shrinkage due to the fixation, it allowed for superior resolution and improved contrast to noise ratios, especially for subcortical structures. We examined microstructural changes based on DTI, and identified increased fractional anisotropy and decreased apparent diffusion coefficient, predominantly in the cerebellum and its connections. Cortical thickness differences did not survive multiple corrections, but uncorrected statistics supported the contralateral effects seen with voxel based volumetric analysis, showing thickening in the somatosensory, motor and visual cortices. In vivo and ex vivo analyses identified plasticity in circuits relevant to selecting actions in a sensory-motor context, through exploitation of learned association and decision making. By mapping a connectivity atlas into our ex vivo template we revealed that changes due to skilled motor learning occurred in a network of 35 regions, including the primary and secondary motor (M1, M2) and sensory cortices (S1, S2), the caudate putamen (CPu), visual (V1) and temporal association cortex. The significant clusters intersected tractography based networks seeded in M1, M2, S1, V1 and CPu at levels > 80%. We found that 89% of the significant cluster belonged to a network seeded in the contralateral M1, and 85% to one seeded in the contralateral M2. Moreover, 40% of the M1 and S1 cluster by network intersections were in the top 80th percentile of the tract densities for their respective networks. Our investigation may be relevant to studies of rehabilitation and recovery, and points to widespread network changes that accompany motor learning that may have potential applications to designing recovery strategies following brain injury.
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Affiliation(s)
- Alexandra Badea
- Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America
- Department of Neurology, Duke University Medical Center, Durham, NC, United States of America
- Brain Imaging and Analysis Center, Duke University, Durham, NC, United States of America
- * E-mail:
| | - Kwan L. Ng
- Department of Neurology, UC Davis School of Medicine, Davis, CA, United States of America
| | - Robert J. Anderson
- Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America
| | - Jiangyang Zhang
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States of America
| | - Michael I. Miller
- Center for Imaging Science, Johns Hopkins University; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States of America
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
| | - Richard J. O’Brien
- Department of Neurology, Duke University Medical Center, Durham, NC, United States of America
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7
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Ma D, Holmes HE, Cardoso MJ, Modat M, Harrison IF, Powell NM, O'Callaghan JM, Ismail O, Johnson RA, O'Neill MJ, Collins EC, Beg MF, Popuri K, Lythgoe MF, Ourselin S. Study the Longitudinal in vivo and Cross-Sectional ex vivo Brain Volume Difference for Disease Progression and Treatment Effect on Mouse Model of Tauopathy Using Automated MRI Structural Parcellation. Front Neurosci 2019; 13:11. [PMID: 30733665 PMCID: PMC6354066 DOI: 10.3389/fnins.2019.00011] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Accepted: 01/08/2019] [Indexed: 11/29/2022] Open
Abstract
Brain volume measurements extracted from structural MRI data sets are a widely accepted neuroimaging biomarker to study mouse models of neurodegeneration. Whether to acquire and analyze data in vivo or ex vivo is a crucial decision during the phase of experimental designs, as well as data analysis. In this work, we extracted the brain structures for both longitudinal in vivo and single-time-point ex vivo MRI acquired from the same animals using accurate automatic multi-atlas structural parcellation, and compared the corresponding statistical and classification analysis. We found that most gray matter structures volumes decrease from in vivo to ex vivo, while most white matter structures volume increase. The level of structural volume change also varies between different genetic strains and treatment. In addition, we showed superior statistical and classification power of ex vivo data compared to the in vivo data, even after resampled to the same level of resolution. We further demonstrated that the classification power of the in vivo data can be improved by incorporating longitudinal information, which is not possible for ex vivo data. In conclusion, this paper demonstrates the tissue-specific changes, as well as the difference in statistical and classification power, between the volumetric analysis based on the in vivo and ex vivo structural MRI data. Our results emphasize the importance of longitudinal analysis for in vivo data analysis.
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Affiliation(s)
- Da Ma
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom.,Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom.,School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada
| | - Holly E Holmes
- Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom
| | - Manuel J Cardoso
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Marc Modat
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Ian F Harrison
- Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom
| | - Nick M Powell
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom.,Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom
| | - James M O'Callaghan
- Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom
| | - Ozama Ismail
- Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom
| | - Ross A Johnson
- Tailored Therapeutics, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, United States
| | | | - Emily C Collins
- Tailored Therapeutics, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, United States
| | - Mirza F Beg
- Tailored Therapeutics, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, United States
| | - Karteek Popuri
- Tailored Therapeutics, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, United States
| | - Mark F Lythgoe
- Centre for Advanced Biomedical Imaging, University College London, London, United Kingdom
| | - Sebastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, United Kingdom.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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8
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Sato C, Sawada K, Wright D, Higashi T, Aoki I. Isotropic 25-Micron 3D Neuroimaging Using ex vivo Microstructural Manganese-Enhanced MRI (MEMRI). Front Neural Circuits 2018; 12:110. [PMID: 30574072 PMCID: PMC6291442 DOI: 10.3389/fncir.2018.00110] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Accepted: 11/23/2018] [Indexed: 12/27/2022] Open
Abstract
MRI observations following in vivo administration of Mn2+ [manganese (Mn)-enhanced MRI, MEMRI] have been used as an excellent morphological and functional MRI tool for in vivo preclinical studies. To detect brain three-dimensional (3D) microstructures, we improved the ex vivo MEMRI method for mouse brains after in vivo Mn administration and obtained high-resolution MRIs using a cryogenic radiofrequency (RF) coil. Male C57BL/6 mice (n = 8) were injected with 50 mM MnCl2 intravenously and MEMRIs of the brain were acquired in vivo after 24 h, followed by perfusion fixation with a 4% paraformaldehyde (PFA) solution. High-resolution 25-μm isotropic MRIs were successfully acquired from the extracted brain tissue and could identify the brain microstructures, especially in the hippocampus [the pyramidal cell layer through CA1–3 and the dentate gyrus (DG) granular layers (GLs)], cell layers of cerebellum, three sub-regions of the deep cerebellar nucleus, and white matter (WM) structures [e.g., the fasciculus retroflexus (fr) and optic tract in the thalamus]. The following technical conditions were also examined: (i) the longitudinal stability of Mn-enhanced ex vivo tissue after in vivo administration; and (ii) the effects of mixing glutaraldehyde (GA) with the fixative solution for the preservation of in vivo MEMRI contrast. Our results indicate that ex vivo MEMRI observations made shortly after fixation maintain the contrast observed in vivo. This research will be useful for non-destructive whole-brain pathological analysis.
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Affiliation(s)
- Chika Sato
- Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology (QST), Chiba, Japan.,Group of Quantum-State Controlled MRI, QST, Chiba, Japan
| | - Kazuhiko Sawada
- Department of Nutrition, Faculty of Medical and Health Sciences, Tsukuba International University, Ibaraki, Japan
| | - David Wright
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia.,Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Tatsuya Higashi
- Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology (QST), Chiba, Japan.,Group of Quantum-State Controlled MRI, QST, Chiba, Japan
| | - Ichio Aoki
- Department of Molecular Imaging and Theranostics, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology (QST), Chiba, Japan.,Group of Quantum-State Controlled MRI, QST, Chiba, Japan
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9
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Clayton EL, Mancuso R, Nielsen TT, Mizielinska S, Holmes H, Powell N, Norona F, Larsen JO, Milioto C, Wilson KM, Lythgoe MF, Ourselin S, Nielsen JE, Johannsen P, Holm I, Collinge J, Oliver PL, Gomez-Nicola D, Isaacs AM. Early microgliosis precedes neuronal loss and behavioural impairment in mice with a frontotemporal dementia-causing CHMP2B mutation. Hum Mol Genet 2017; 26:873-887. [PMID: 28093491 PMCID: PMC5409096 DOI: 10.1093/hmg/ddx003] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2016] [Accepted: 01/03/2017] [Indexed: 01/13/2023] Open
Abstract
Frontotemporal dementia (FTD)-causing mutations in the CHMP2B gene lead to the generation of mutant C-terminally truncated CHMP2B. We report that transgenic mice expressing endogenous levels of mutant CHMP2B developed late-onset brain volume loss associated with frank neuronal loss and FTD-like changes in social behaviour. These data are the first to show neurodegeneration in mice expressing mutant CHMP2B and indicate that our mouse model is able to recapitulate neurodegenerative changes observed in FTD. Neuroinflammation has been increasingly implicated in neurodegeneration, including FTD. Therefore, we investigated neuroinflammation in our CHMP2B mutant mice. We observed very early microglial proliferation that develops into a clear pro-inflammatory phenotype at late stages. Importantly, we also observed a similar inflammatory profile in CHMP2B patient frontal cortex. Aberrant microglial function has also been implicated in FTD caused by GRN, MAPT and C9orf72 mutations. The presence of early microglial changes in our CHMP2B mutant mice indicates neuroinflammation may be a contributing factor to the neurodegeneration observed in FTD.
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Affiliation(s)
- Emma L Clayton
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Renzo Mancuso
- Biological Sciences, University of Southampton, Southampton General Hospital, South Laboratory and Pathology Block, Tremona Road, Southampton SO166YD, UK
| | - Troels Tolstrup Nielsen
- Department of Neurology, Danish Dementia Research Centre, Rigshospitalet, University of Copenhagen, Denmark
| | - Sarah Mizielinska
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Holly Holmes
- Centre for Advanced Biomedical Imaging, Division of Medicine and Institute of Child Health, University College London, 72 Huntley Street, London WC1E 6DD, UK
| | - Nicholas Powell
- Centre for Advanced Biomedical Imaging, Division of Medicine and Institute of Child Health, University College London, 72 Huntley Street, London WC1E 6DD, UK.,Faculty of Health and Medical Sciences, Department of Neuroscience and Pharmacology, Panum Institute, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Frances Norona
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Jytte Overgaard Larsen
- Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, UK
| | - Carmelo Milioto
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Katherine M Wilson
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Mark F Lythgoe
- Centre for Advanced Biomedical Imaging, Division of Medicine and Institute of Child Health, University College London, 72 Huntley Street, London WC1E 6DD, UK
| | - Sebastian Ourselin
- Faculty of Health and Medical Sciences, Department of Neuroscience and Pharmacology, Panum Institute, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Jörgen E Nielsen
- Department of Neurology, Danish Dementia Research Centre, Rigshospitalet, University of Copenhagen, Denmark.,Section of Neurogenetics, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Peter Johannsen
- Department of Neurology, Danish Dementia Research Centre, Rigshospitalet, University of Copenhagen, Denmark
| | - Ida Holm
- Laboratory for Experimental Neuropathology, Department of Pathology, Randers Hospital, DK-8930 Randers NØ, Denmark.,Institute of Clinical Medicine, Aarhus University, DK-8000 Aarhus C, Denmark
| | - John Collinge
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK.,MRC Prion Unit, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | | | - Peter L Oliver
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford OX1 3PT, UK
| | - Diego Gomez-Nicola
- Biological Sciences, University of Southampton, Southampton General Hospital, South Laboratory and Pathology Block, Tremona Road, Southampton SO166YD, UK
| | - Adrian M Isaacs
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London WC1N 3BG, UK
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10
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Holmes HE, Powell NM, Ma D, Ismail O, Harrison IF, Wells JA, Colgan N, O'Callaghan JM, Johnson RA, Murray TK, Ahmed Z, Heggenes M, Fisher A, Cardoso MJ, Modat M, O'Neill MJ, Collins EC, Fisher EMC, Ourselin S, Lythgoe MF. Comparison of In Vivo and Ex Vivo MRI for the Detection of Structural Abnormalities in a Mouse Model of Tauopathy. Front Neuroinform 2017; 11:20. [PMID: 28408879 PMCID: PMC5374887 DOI: 10.3389/fninf.2017.00020] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 02/27/2017] [Indexed: 11/15/2022] Open
Abstract
With increasingly large numbers of mouse models of human disease dedicated to MRI studies, compromises between in vivo and ex vivo MRI must be fully understood in order to inform the choice of imaging methodology. We investigate the application of high resolution in vivo and ex vivo MRI, in combination with tensor-based morphometry (TBM), to uncover morphological differences in the rTg4510 mouse model of tauopathy. The rTg4510 mouse also offers a novel paradigm by which the overexpression of mutant tau can be regulated by the administration of doxycycline, providing us with a platform on which to investigate more subtle alterations in morphology with morphometry. Both in vivo and ex vivo MRI allowed the detection of widespread bilateral patterns of atrophy in the rTg4510 mouse brain relative to wild-type controls. Regions of volume loss aligned with neuronal loss and pathological tau accumulation demonstrated by immunohistochemistry. When we sought to investigate more subtle structural alterations in the rTg4510 mice relative to a subset of doxycycline-treated rTg4510 mice, ex vivo imaging enabled the detection of more regions of morphological brain changes. The disadvantages of ex vivo MRI may however mitigate this increase in sensitivity: we observed a 10% global shrinkage in brain volume of the post-mortem tissues due to formalin fixation, which was most notable in the cerebellum and olfactory bulbs. However, many central brain regions were not adversely affected by the fixation protocol, perhaps due to our “in-skull” preparation. The disparity between our TBM findings from in vivo and ex vivo MRI underlines the importance of appropriate study design, given the trade-off between these two imaging approaches. We support the utility of in vivo MRI for morphological phenotyping of mouse models of disease; however, for subtler phenotypes, ex vivo offers enhanced sensitivity to discrete morphological changes.
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Affiliation(s)
- Holly E Holmes
- Division of Medicine, UCL Centre for Advanced Biomedical Imaging, University College LondonLondon, UK
| | - Nick M Powell
- Division of Medicine, UCL Centre for Advanced Biomedical Imaging, University College LondonLondon, UK.,Centre for Medical Image Computing, University College LondonLondon, UK
| | - Da Ma
- Division of Medicine, UCL Centre for Advanced Biomedical Imaging, University College LondonLondon, UK.,Centre for Medical Image Computing, University College LondonLondon, UK
| | - Ozama Ismail
- Division of Medicine, UCL Centre for Advanced Biomedical Imaging, University College LondonLondon, UK
| | - Ian F Harrison
- Division of Medicine, UCL Centre for Advanced Biomedical Imaging, University College LondonLondon, UK
| | - Jack A Wells
- Division of Medicine, UCL Centre for Advanced Biomedical Imaging, University College LondonLondon, UK
| | - Niall Colgan
- Division of Medicine, UCL Centre for Advanced Biomedical Imaging, University College LondonLondon, UK
| | - James M O'Callaghan
- Division of Medicine, UCL Centre for Advanced Biomedical Imaging, University College LondonLondon, UK
| | - Ross A Johnson
- Tailored Therapeutics, Eli Lilly and Company, Lilly Corporate CenterIndianapolis, IN, USA
| | | | - Zeshan Ahmed
- Molecular Pathology, Eli Lilly & Co. LtdWindlesham, UK
| | | | - Alice Fisher
- Molecular Pathology, Eli Lilly & Co. LtdWindlesham, UK
| | - M Jorge Cardoso
- Centre for Medical Image Computing, University College LondonLondon, UK
| | - Marc Modat
- Centre for Medical Image Computing, University College LondonLondon, UK
| | | | - Emily C Collins
- Tailored Therapeutics, Eli Lilly and Company, Lilly Corporate CenterIndianapolis, IN, USA
| | - Elizabeth M C Fisher
- Department of Neurodegenerative Disease, Institute of Neurology, University College LondonLondon, UK
| | | | - Mark F Lythgoe
- Division of Medicine, UCL Centre for Advanced Biomedical Imaging, University College LondonLondon, UK
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11
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Busato A, Fumene Feruglio P, Parnigotto PP, Marzola P, Sbarbati A. In vivo imaging techniques: a new era for histochemical analysis. Eur J Histochem 2016; 60:2725. [PMID: 28076937 PMCID: PMC5159782 DOI: 10.4081/ejh.2016.2725] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Revised: 11/16/2016] [Accepted: 11/17/2016] [Indexed: 01/15/2023] Open
Abstract
In vivo imaging techniques can be integrated with classical histochemistry to create an actual histochemistry of water. In particular, Magnetic Resonance Imaging (MRI), an imaging technique primarily used as diagnostic tool in clinical/preclinical research, has excellent anatomical resolution, unlimited penetration depth and intrinsic soft tissue contrast. Thanks to the technological development, MRI is not only capable to provide morphological information but also and more interestingly functional, biophysical and molecular. In this paper we describe the main features of several advanced imaging techniques, such as MRI microscopy, Magnetic Resonance Spectroscopy, functional MRI, Diffusion Tensor Imaging and MRI with contrast agent as a useful support to classical histochemistry.
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Affiliation(s)
- A Busato
- University of Verona, Department of Computer Science.
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12
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Powell NM, Modat M, Cardoso MJ, Ma D, Holmes HE, Yu Y, O’Callaghan J, Cleary JO, Sinclair B, Wiseman FK, Tybulewicz VLJ, Fisher EMC, Lythgoe MF, Ourselin S. Fully-Automated μMRI Morphometric Phenotyping of the Tc1 Mouse Model of Down Syndrome. PLoS One 2016; 11:e0162974. [PMID: 27658297 PMCID: PMC5033246 DOI: 10.1371/journal.pone.0162974] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Accepted: 08/31/2016] [Indexed: 01/07/2023] Open
Abstract
We describe a fully automated pipeline for the morphometric phenotyping of mouse brains from μMRI data, and show its application to the Tc1 mouse model of Down syndrome, to identify new morphological phenotypes in the brain of this first transchromosomic animal carrying human chromosome 21. We incorporate an accessible approach for simultaneously scanning multiple ex vivo brains, requiring only a 3D-printed brain holder, and novel image processing steps for their separation and orientation. We employ clinically established multi-atlas techniques–superior to single-atlas methods–together with publicly-available atlas databases for automatic skull-stripping and tissue segmentation, providing high-quality, subject-specific tissue maps. We follow these steps with group-wise registration, structural parcellation and both Voxel- and Tensor-Based Morphometry–advantageous for their ability to highlight morphological differences without the laborious delineation of regions of interest. We show the application of freely available open-source software developed for clinical MRI analysis to mouse brain data: NiftySeg for segmentation and NiftyReg for registration, and discuss atlases and parameters suitable for the preclinical paradigm. We used this pipeline to compare 29 Tc1 brains with 26 wild-type littermate controls, imaged ex vivo at 9.4T. We show an unexpected increase in Tc1 total intracranial volume and, controlling for this, local volume and grey matter density reductions in the Tc1 brain compared to the wild-types, most prominently in the cerebellum, in agreement with human DS and previous histological findings.
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Affiliation(s)
- Nick M. Powell
- Translational Imaging Group, Centre for Medical Image Computing, University College London, 3rd Floor, Wolfson House, 4 Stephenson Way, London NW1 2HE, United Kingdom
- Centre for Advanced Biomedical Imaging, Division of Medicine, University College London, Paul O’Gorman Building, 72 Huntley Street, London WC1E 6DD, United Kingdom
- * E-mail:
| | - Marc Modat
- Translational Imaging Group, Centre for Medical Image Computing, University College London, 3rd Floor, Wolfson House, 4 Stephenson Way, London NW1 2HE, United Kingdom
| | - M. Jorge Cardoso
- Translational Imaging Group, Centre for Medical Image Computing, University College London, 3rd Floor, Wolfson House, 4 Stephenson Way, London NW1 2HE, United Kingdom
| | - Da Ma
- Translational Imaging Group, Centre for Medical Image Computing, University College London, 3rd Floor, Wolfson House, 4 Stephenson Way, London NW1 2HE, United Kingdom
- Centre for Advanced Biomedical Imaging, Division of Medicine, University College London, Paul O’Gorman Building, 72 Huntley Street, London WC1E 6DD, United Kingdom
| | - Holly E. Holmes
- Centre for Advanced Biomedical Imaging, Division of Medicine, University College London, Paul O’Gorman Building, 72 Huntley Street, London WC1E 6DD, United Kingdom
| | - Yichao Yu
- Centre for Advanced Biomedical Imaging, Division of Medicine, University College London, Paul O’Gorman Building, 72 Huntley Street, London WC1E 6DD, United Kingdom
| | - James O’Callaghan
- Centre for Advanced Biomedical Imaging, Division of Medicine, University College London, Paul O’Gorman Building, 72 Huntley Street, London WC1E 6DD, United Kingdom
| | - Jon O. Cleary
- Centre for Advanced Biomedical Imaging, Division of Medicine, University College London, Paul O’Gorman Building, 72 Huntley Street, London WC1E 6DD, United Kingdom
- Melbourne Brain Centre Imaging Unit, Department of Anatomy and Neuroscience, University of Melbourne, Parkville, Victoria 3052, Australia
| | - Ben Sinclair
- Centre for Advanced Biomedical Imaging, Division of Medicine, University College London, Paul O’Gorman Building, 72 Huntley Street, London WC1E 6DD, United Kingdom
| | - Frances K. Wiseman
- Department of Neurodegenerative Disease, Institute of Neurology, University College, London WC1N 3BG, United Kingdom
| | - Victor L. J. Tybulewicz
- The Francis Crick Institute, Mill Hill Laboratory, London NW7 1AA, United Kingdom
- Imperial College, London W12 0NN, United Kingdom
| | - Elizabeth M. C. Fisher
- Department of Neurodegenerative Disease, Institute of Neurology, University College, London WC1N 3BG, United Kingdom
| | - Mark F. Lythgoe
- Centre for Advanced Biomedical Imaging, Division of Medicine, University College London, Paul O’Gorman Building, 72 Huntley Street, London WC1E 6DD, United Kingdom
| | - Sébastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing, University College London, 3rd Floor, Wolfson House, 4 Stephenson Way, London NW1 2HE, United Kingdom
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13
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Wu D, Zhang J. Recent Progress in Magnetic Resonance Imaging of the Embryonic and Neonatal Mouse Brain. Front Neuroanat 2016; 10:18. [PMID: 26973471 PMCID: PMC4776397 DOI: 10.3389/fnana.2016.00018] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2015] [Accepted: 02/15/2016] [Indexed: 01/21/2023] Open
Abstract
The laboratory mouse has been widely used as a model system to investigate the genetic control mechanisms of mammalian brain development. Magnetic resonance imaging (MRI) is an important tool to characterize changes in brain anatomy in mutant mouse strains and injury progression in mouse models of fetal and neonatal brain injury. Progress in the last decade has enabled us to acquire MRI data with increasing anatomical details from the embryonic and neonatal mouse brain. High-resolution ex vivo MRI, especially with advanced diffusion MRI methods, can visualize complex microstructural organizations in the developing mouse brain. In vivo MRI of the embryonic mouse brain, which is critical for tracking anatomical changes longitudinally, has become available. Applications of these techniques may lead to further insights into the complex and dynamic processes of brain development.
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Affiliation(s)
- Dan Wu
- Department of Radiology, Johns Hopkins University School of Medicine Baltimore, MD, USA
| | - Jiangyang Zhang
- Department of Radiology, Johns Hopkins University School of MedicineBaltimore, MD, USA; Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of MedicineNew York, NY, USA
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14
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Abstract
In order to understand the consequences of the mutation on behavioral and biological phenotypes relevant to autism, mutations in many of the risk genes for autism spectrum disorder have been experimentally generated in mice. Here, we summarize behavioral outcomes and neuroanatomical abnormalities, with a focus on high-resolution magnetic resonance imaging of postmortem mouse brains. Results are described from multiple mouse models of autism spectrum disorder and comorbid syndromes, including the 15q11-13, 16p11.2, 22q11.2, Cntnap2, Engrailed2, Fragile X, Integrinβ3, MET, Neurexin1a, Neuroligin3, Reelin, Rett, Shank3, Slc6a4, tuberous sclerosis, and Williams syndrome models, and inbred strains with strong autism-relevant behavioral phenotypes, including BTBR and BALB. Concomitant behavioral and neuroanatomical abnormalities can strengthen the interpretation of results from a mouse model, and may elevate the usefulness of the model system for therapeutic discovery.
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Affiliation(s)
- Jacob Ellegood
- />Mouse Imaging Centre (MICe), Hospital for Sick Children, 25 Orde Street, Toronto, ON M5T 3H7 Canada
| | - Jacqueline N. Crawley
- />MIND Institute and Department of Psychiatry and Behavioral Sciences, University of California Davis School of Medicine, 4625 2nd Avenue, Sacramento, CA 95817 USA
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15
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Foxley S, Domowicz M, Karczmar GS, Schwartz N. 3D high spectral and spatial resolution imaging of ex vivo mouse brain. Med Phys 2015; 42:1463-72. [PMID: 25735299 PMCID: PMC5148176 DOI: 10.1118/1.4908203] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Widely used MRI methods show brain morphology both in vivo and ex vivo at very high resolution. Many of these methods (e.g., T2*-weighted imaging, phase-sensitive imaging, or susceptibility-weighted imaging) are sensitive to local magnetic susceptibility gradients produced by subtle variations in tissue composition. However, the spectral resolution of commonly used methods is limited to maintain reasonable run-time combined with very high spatial resolution. Here, the authors report on data acquisition at increased spectral resolution, with 3-dimensional high spectral and spatial resolution MRI, in order to analyze subtle variations in water proton resonance frequency and lineshape that reflect local anatomy. The resulting information compliments previous studies based on T2* and resonance frequency. METHODS The proton free induction decay was sampled at high resolution and Fourier transformed to produce a high-resolution water spectrum for each image voxel in a 3D volume. Data were acquired using a multigradient echo pulse sequence (i.e., echo-planar spectroscopic imaging) with a spatial resolution of 50 × 50 × 70 μm(3) and spectral resolution of 3.5 Hz. Data were analyzed in the spectral domain, and images were produced from the various Fourier components of the water resonance. This allowed precise measurement of local variations in water resonance frequency and lineshape, at the expense of significantly increased run time (16-24 h). RESULTS High contrast T2*-weighted images were produced from the peak of the water resonance (peak height image), revealing a high degree of anatomical detail, specifically in the hippocampus and cerebellum. In images produced from Fourier components of the water resonance at -7.0 Hz from the peak, the contrast between deep white matter tracts and the surrounding tissue is the reverse of the contrast in water peak height images. This indicates the presence of a shoulder in the water resonance that is not present at +7.0 Hz and may be specific to white matter anatomy. Moreover, a frequency shift of 6.76 ± 0.55 Hz was measured between the molecular and granular layers of the cerebellum. This shift is demonstrated in corresponding spectra; water peaks from voxels in the molecular and granular layers are consistently 2 bins apart (7.0 Hz, as dictated by the spectral resolution) from one another. CONCLUSIONS High spectral and spatial resolution MR imaging has the potential to accurately measure the changes in the water resonance in small voxels. This information can guide optimization and interpretation of more commonly used, more rapid imaging methods that depend on image contrast produced by local susceptibility gradients. In addition, with improved sampling methods, high spectral and spatial resolution data could be acquired in reasonable run times, and used for in vivo scans to increase sensitivity to variations in local susceptibility.
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Affiliation(s)
| | - Miriam Domowicz
- Department of Pediatrics, University of Chicago, Chicago, Illinois 60637
| | | | - Nancy Schwartz
- Department of Pediatrics, Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637
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16
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Phenotyping the central nervous system of the embryonic mouse by magnetic resonance microscopy. Neuroimage 2014; 97:95-106. [PMID: 24769183 DOI: 10.1016/j.neuroimage.2014.04.043] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2013] [Revised: 04/07/2014] [Accepted: 04/13/2014] [Indexed: 11/20/2022] Open
Abstract
Genetic mouse models of neurodevelopmental disorders are being massively generated, but technologies for their high-throughput phenotyping are missing. The potential of high-resolution magnetic resonance imaging (MRI) for structural phenotyping has been demonstrated before. However, application to the embryonic mouse central nervous system has been limited by the insufficient anatomical detail. Here we present a method that combines staining of live embryos with a contrast agent together with MR microscopy after fixation, to provide unprecedented anatomical detail at relevant embryonic stages. By using this method we have phenotyped the embryonic forebrain of Robo1/2(-/-) double mutant mice enabling us to identify most of the well-known anatomical defects in these mutants, as well as novel more subtle alterations. We thus demonstrate the potential of this methodology for a fast and reliable screening of subtle structural abnormalities in the developing mouse brain, as those associated to defects in disease-susceptibility genes of neurologic and psychiatric relevance.
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17
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von Bohlen Und Halbach O, Lotze M, Pfannmöller JP. Post-mortem magnetic resonance microscopy (MRM) of the murine brain at 7 Tesla results in a gain of resolution as compared to in vivo MRM. Front Neuroanat 2014; 8:47. [PMID: 24982617 PMCID: PMC4056281 DOI: 10.3389/fnana.2014.00047] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2014] [Accepted: 05/28/2014] [Indexed: 11/21/2022] Open
Abstract
Small-animal MRI with high field strength allows imaging of the living animal. However, spatial resolution in in vivo brain imaging is limited by the scanning time. Measurements of fixated mouse brains allow longer measurement time, but fixation procedures are time consuming, since the process of fixation may take several weeks. We here present a quick and simple post-mortem approach without fixation that allows high-resolution MRI even at 7 Tesla (T2-weighted MRI). This method was compared to in vivo scans with optimized spatial resolution for the investigation of anesthetized mice (T1-weighted MRI) as well as to ex situ scans of fixed brains (T1- and T2-weighted scans) by using standard MRI-sequences, along with anatomic descriptions of areas observable in the MRI, analysis of tissue shrinkage and post-processing procedures (intensity inhomogeneity correction, PCNN3D brain extract, SPMMouse segmentation, and volumetric measurement). Post-mortem imaging quality was sufficient to determine small brain substructures on the morphological level, provided fast possibilities for volumetric acquisition and for automatized processing without manual correction. Moreover, since no fixation was used, tissue shrinkage due to fixation does not occur as it is, e.g., the case by using ex vivo brains that have been kept in fixatives for several days. Thus, the introduced method is well suited for comparative investigations, since it allows determining small structural alterations in the murine brain at a reasonable high resolution even by MRI performed at 7 Tesla.
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Affiliation(s)
| | - Martin Lotze
- Functional Imaging Unit, Center for Diagnostic Radiology, University of Greifswald Germany
| | - Jörg P Pfannmöller
- Functional Imaging Unit, Center for Diagnostic Radiology, University of Greifswald Germany
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18
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O’Callaghan J, Wells J, Richardson S, Holmes H, Yu Y, Walker-Samuel S, Siow B, Lythgoe MF. Is your system calibrated? MRI gradient system calibration for pre-clinical, high-resolution imaging. PLoS One 2014; 9:e96568. [PMID: 24804737 PMCID: PMC4013024 DOI: 10.1371/journal.pone.0096568] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2014] [Accepted: 04/08/2014] [Indexed: 11/27/2022] Open
Abstract
High-field, pre-clinical MRI systems are widely used to characterise tissue structure and volume in small animals, using high resolution imaging. Both applications rely heavily on the consistent, accurate calibration of imaging gradients, yet such calibrations are typically only performed during maintenance sessions by equipment manufacturers, and potentially with acceptance limits that are inadequate for phenotyping. To overcome this difficulty, we present a protocol for gradient calibration quality assurance testing, based on a 3D-printed, open source, structural phantom that can be customised to the dimensions of individual scanners and RF coils. In trials on a 9.4 T system, the gradient scaling errors were reduced by an order of magnitude, and displacements of greater than 100 µm, caused by gradient non-linearity, were corrected using a post-processing technique. The step-by-step protocol can be integrated into routine pre-clinical MRI quality assurance to measure and correct for these errors. We suggest that this type of quality assurance is essential for robust pre-clinical MRI experiments that rely on accurate imaging gradients, including small animal phenotyping and diffusion MR.
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Affiliation(s)
- James O’Callaghan
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom
| | - Jack Wells
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom
| | - Simon Richardson
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom
- UCL Centre for Medical Image Computing, London, United Kingdom
| | - Holly Holmes
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom
| | - Yichao Yu
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom
| | - Simon Walker-Samuel
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom
| | - Bernard Siow
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom
- UCL Centre for Medical Image Computing, London, United Kingdom
| | - Mark F. Lythgoe
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, London, United Kingdom
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19
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Kurniawan ND, Richards KL, Yang Z, She D, Ullmann JFP, Moldrich RX, Liu S, Yaksic JU, Leanage G, Kharatishvili I, Wimmer V, Calamante F, Galloway GJ, Petrou S, Reutens DC. Visualization of mouse barrel cortex using ex-vivo track density imaging. Neuroimage 2013; 87:465-75. [PMID: 24060319 DOI: 10.1016/j.neuroimage.2013.09.030] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2013] [Revised: 09/06/2013] [Accepted: 09/13/2013] [Indexed: 02/04/2023] Open
Abstract
We describe the visualization of the barrel cortex of the primary somatosensory area (S1) of ex vivo adult mouse brain with short-tracks track density imaging (stTDI). stTDI produced much higher definition of barrel structures than conventional fractional anisotropy (FA), directionally-encoded color FA maps, spin-echo T1- and T2-weighted imaging and gradient echo T1/T2*-weighted imaging. 3D high angular resolution diffusion imaging (HARDI) data were acquired at 48 micron isotropic resolution for a (3mm)(3) block of cortex containing the barrel field and reconstructed using stTDI at 10 micron isotropic resolution. HARDI data were also acquired at 100 micron isotropic resolution to image the whole brain and reconstructed using stTDI at 20 micron isotropic resolution. The 10 micron resolution stTDI maps showed exceptionally clear delineation of barrel structures. Individual barrels could also be distinguished in the 20 micron stTDI maps but the septa separating the individual barrels appeared thicker compared to the 10 micron maps, indicating that the ability of stTDI to produce high quality structural delineation is dependent upon acquisition resolution. Close homology was observed between the barrel structure delineated using stTDI and reconstructed histological data from the same samples. stTDI also detects barrel deletions in the posterior medial barrel sub-field in mice with infraorbital nerve cuts. The results demonstrate that stTDI is a novel imaging technique that enables three-dimensional characterization of complex structures such as the barrels in S1 and provides an important complementary non-invasive imaging tool for studying synaptic connectivity, development and plasticity of the sensory system.
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Affiliation(s)
- Nyoman D Kurniawan
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia.
| | - Kay L Richards
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
| | - Zhengyi Yang
- ITEE, University of Queensland, Brisbane, Queensland, Australia
| | - David She
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Jeremy F P Ullmann
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Randal X Moldrich
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Sha Liu
- Queensland Brain Institute, Brisbane, Queensland, Australia
| | - Javier Urriola Yaksic
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Gayeshika Leanage
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Irina Kharatishvili
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Verena Wimmer
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
| | - Fernando Calamante
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia; Department of Medicine, Austin Health and Northern Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Graham J Galloway
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
| | - Steven Petrou
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
| | - David C Reutens
- Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia
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20
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Norris FC, Betts-Henderson J, Wells JA, Cleary JO, Siow BM, Walker-Samuel S, McCue K, Salomoni P, Scambler PJ, Lythgoe MF. Enhanced tissue differentiation in the developing mouse brain using magnetic resonance micro-histology. Magn Reson Med 2012; 70:1380-8. [DOI: 10.1002/mrm.24573] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2012] [Revised: 10/29/2012] [Accepted: 10/30/2012] [Indexed: 12/15/2022]
Affiliation(s)
- Francesca C. Norris
- Department of Medicine and UCL Institute of Child Health; Centre for Advanced Biomedical Imaging; University College London; UK
- Centre for Mathematics and Physics in the Life Sciences and EXperimental Biology (CoMPLEX); University College London; UK
| | | | - Jack A. Wells
- Department of Medicine and UCL Institute of Child Health; Centre for Advanced Biomedical Imaging; University College London; UK
| | - Jon O. Cleary
- Department of Medicine and UCL Institute of Child Health; Centre for Advanced Biomedical Imaging; University College London; UK
- Department of Medical Physics and Bioengineering; University College London; UK
| | - Bernard M. Siow
- Department of Medicine and UCL Institute of Child Health; Centre for Advanced Biomedical Imaging; University College London; UK
- Departments of Medical Physics and Bioengineering and Computer Science; Centre for Medical Image Computing; University College London; UK
| | - Simon Walker-Samuel
- Department of Medicine and UCL Institute of Child Health; Centre for Advanced Biomedical Imaging; University College London; UK
| | - Karen McCue
- Molecular Medicine Unit; UCL Institute of Child Health; University College London; UK
| | - Paolo Salomoni
- Samantha Dickson Brain Cancer Unit; UCL Cancer Institute; London UK
| | - Peter J. Scambler
- Molecular Medicine Unit; UCL Institute of Child Health; University College London; UK
| | - Mark F. Lythgoe
- Department of Medicine and UCL Institute of Child Health; Centre for Advanced Biomedical Imaging; University College London; UK
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21
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Artuso L, Zoccolella S, Favia P, Amati A, Capozzo R, Logroscino G, Serlenga L, Simone I, Gasparre G, Petruzzella V. Mitochondrial genome aberrations in skeletal muscle of patients with motor neuron disease. Amyotroph Lateral Scler Frontotemporal Degener 2012; 14:261-6. [DOI: 10.3109/21678421.2012.735239] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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22
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Waiczies H, Millward JM, Lepore S, Infante-Duarte C, Pohlmann A, Niendorf T, Waiczies S. Identification of cellular infiltrates during early stages of brain inflammation with magnetic resonance microscopy. PLoS One 2012; 7:e32796. [PMID: 22427887 PMCID: PMC3299701 DOI: 10.1371/journal.pone.0032796] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2011] [Accepted: 01/31/2012] [Indexed: 11/18/2022] Open
Abstract
A comprehensive view of brain inflammation during the pathogenesis of autoimmune encephalomyelitis can be achieved with the aid of high resolution non-invasive imaging techniques such as microscopic magnetic resonance imaging (μMRI). In this study we demonstrate the benefits of cryogenically-cooled RF coils to produce μMRI in vivo, with sufficient detail to reveal brain pathology in the experimental autoimmune encephalomyelitis (EAE) model. We could visualize inflammatory infiltrates in detail within various regions of the brain, already at an early phase of EAE. Importantly, this pathology could be seen clearly even without the use of contrast agents, and showed excellent correspondence with conventional histology. The cryogenically-cooled coil enabled the acquisition of high resolution images within short scan times: an important practical consideration in conducting animal experiments. The detail of the cellular infiltrates visualized by in vivo μMRI allows the opportunity to follow neuroinflammatory processes even during the early stages of disease progression. Thus μMRI will not only complement conventional histological examination but will also enable longitudinal studies on the kinetics and dynamics of immune cell infiltration.
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Affiliation(s)
- Helmar Waiczies
- Experimental and Clinical Research Center, a joint cooperation between the Charité Medical Faculty and the Max-Delbrück Center for Molecular Medicine, Berlin, Germany.
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23
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Gonzalez-Segura A, Morales JM, Gonzalez-Darder JM, Cardona-Marsal R, Lopez-Gines C, Cerda-Nicolas M, Monleon D. Magnetic resonance microscopy at 14 Tesla and correlative histopathology of human brain tumor tissue. PLoS One 2011; 6:e27442. [PMID: 22110653 PMCID: PMC3216972 DOI: 10.1371/journal.pone.0027442] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2011] [Accepted: 10/17/2011] [Indexed: 01/18/2023] Open
Abstract
Magnetic Resonance Microscopy (MRM) can provide high microstructural detail in excised human lesions. Previous MRM images on some experimental models and a few human samples suggest the large potential of the technique. The aim of this study was the characterization of specific morphological features of human brain tumor samples by MRM and correlative histopathology. We performed MRM imaging and correlative histopathology in 19 meningioma and 11 glioma human brain tumor samples obtained at surgery. To our knowledge, this is the first MRM direct structural characterization of human brain tumor samples. MRM of brain tumor tissue provided images with 35 to 40 µm spatial resolution. The use of MRM to study human brain tumor samples provides new microstructural information on brain tumors for better classification and characterization. The correlation between MRM and histopathology images allowed the determination of image parameters for critical microstructures of the tumor, like collagen patterns, necrotic foci, calcifications and/or psammoma bodies, vascular distribution and hemorrhage among others. Therefore, MRM may help in interpreting the Clinical Magnetic Resonance images in terms of cell biology processes and tissue patterns. Finally, and most importantly for clinical diagnosis purposes, it provides three-dimensional information in intact samples which may help in selecting a preferential orientation for the histopathology slicing which contains most of the informative elements of the biopsy. Overall, the findings reported here provide a new and unique microstructural view of intact human brain tumor tissue. At this point, our approach and results allow the identification of specific tissue types and pathological features in unprocessed tumor samples.
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Affiliation(s)
- Ana Gonzalez-Segura
- Fundación de Investigación del Hospital Clínico Universitario de Valencia/Instituto de Investigación Sanitaria INCLIVA, Valencia, Spain
| | - Jose Manuel Morales
- Unidad Central de Investigación en Medicina, Universitat de Valéncia, Valencia, Spain
| | | | - Ramon Cardona-Marsal
- Fundación de Investigación del Hospital Clínico Universitario de Valencia/Instituto de Investigación Sanitaria INCLIVA, Valencia, Spain
| | | | - Miguel Cerda-Nicolas
- Departamento de Patología, Universitat de Valencia, Valencia, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-RES), Valencia, Spain
- * E-mail: (DM); (MCN)
| | - Daniel Monleon
- Fundación de Investigación del Hospital Clínico Universitario de Valencia/Instituto de Investigación Sanitaria INCLIVA, Valencia, Spain
- * E-mail: (DM); (MCN)
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Nieman BJ, Wong MD, Henkelman RM. Genes into geometry: imaging for mouse development in 3D. Curr Opin Genet Dev 2011; 21:638-46. [PMID: 21907568 DOI: 10.1016/j.gde.2011.08.009] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2011] [Revised: 08/19/2011] [Accepted: 08/23/2011] [Indexed: 02/07/2023]
Abstract
Mammalian development is a sophisticated program coordinated by a complex set of genetic and physiological factors. Alterations in anatomy or morphology provide intrinsic measures of progress in or deviations from this program. Emerging three-dimensional imaging methods now allow for more sophisticated morphological assessment than ever before, enabling comprehensive phenotyping, visualization of anatomical context and patterns, automated and quantitative morphological analysis, as well as improved understanding of the developmental time course. Furthermore, these imaging tools are becoming increasingly available and will consequently play a prominent role in elucidating the factors that direct and influence mammalian development.
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Affiliation(s)
- Brian J Nieman
- Mouse Imaging Centre, Hospital for Sick Children, and Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
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