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Schilling KG, Grussu F, Ianus A, Hansen B, Howard AFD, Barrett RLC, Aggarwal M, Michielse S, Nasrallah F, Syeda W, Wang N, Veraart J, Roebroeck A, Bagdasarian AF, Eichner C, Sepehrband F, Zimmermann J, Soustelle L, Bowman C, Tendler BC, Hertanu A, Jeurissen B, Verhoye M, Frydman L, van de Looij Y, Hike D, Dunn JF, Miller K, Landman BA, Shemesh N, Anderson A, McKinnon E, Farquharson S, Dell'Acqua F, Pierpaoli C, Drobnjak I, Leemans A, Harkins KD, Descoteaux M, Xu D, Huang H, Santin MD, Grant SC, Obenaus A, Kim GS, Wu D, Le Bihan D, Blackband SJ, Ciobanu L, Fieremans E, Bai R, Leergaard TB, Zhang J, Dyrby TB, Johnson GA, Cohen‐Adad J, Budde MD, Jelescu IO. Considerations and recommendations from the ISMRM diffusion study group for preclinical diffusion MRI: Part 2-Ex vivo imaging: Added value and acquisition. Magn Reson Med 2025; 93:2535-2560. [PMID: 40035293 PMCID: PMC11971501 DOI: 10.1002/mrm.30435] [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: 10/09/2024] [Revised: 12/10/2024] [Accepted: 12/26/2024] [Indexed: 03/05/2025]
Abstract
The value of preclinical diffusion MRI (dMRI) is substantial. While dMRI enables in vivo non-invasive characterization of tissue, ex vivo dMRI is increasingly being used to probe tissue microstructure and brain connectivity. Ex vivo dMRI has several experimental advantages including higher SNR and spatial resolution compared to in vivo studies, and enabling more advanced diffusion contrasts for improved microstructure and connectivity characterization. Another major advantage of ex vivo dMRI is the direct comparison with histological data, as a crucial methodological validation. However, there are a number of considerations that must be made when performing ex vivo experiments. The steps from tissue preparation, image acquisition and processing, and interpretation of results are complex, with many decisions that not only differ dramatically from in vivo imaging of small animals, but ultimately affect what questions can be answered using the data. This work represents "Part 2" of a three-part series of recommendations and considerations for preclinical dMRI. We describe best practices for dMRI of ex vivo tissue, with a focus on the value that ex vivo imaging adds to the field of dMRI and considerations in ex vivo image acquisition. We first give general considerations and foundational knowledge that must be considered when designing experiments. We briefly describe differences in specimens and models and discuss why some may be more or less appropriate for different studies. We then give guidelines for ex vivo protocols, including tissue fixation, sample preparation, and MR scanning. In each section, we attempt to provide guidelines and recommendations, but also highlight areas for which no guidelines exist (and why), and where future work should lie. An overarching goal herein is to enhance the rigor and reproducibility of ex vivo dMRI acquisitions and analyses, and thereby advance biomedical knowledge.
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Affiliation(s)
- Kurt G. Schilling
- Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt University Institute of Imaging ScienceVanderbilt UniversityNashvilleTennesseeUSA
| | - Francesco Grussu
- Radiomics Group, Vall d'Hebron Institute of OncologyVall d'Hebron Barcelona Hospital CampusBarcelonaSpain
- Queen Square MS Centre, Queen Square Institute of Neurology, Faculty of Brain SciencesUniversity College LondonLondonUK
| | - Andrada Ianus
- Champalimaud ResearchChampalimaud FoundationLisbonPortugal
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondon
| | - Brian Hansen
- Center of Functionally Integrative NeuroscienceAarhus UniversityAarhusDenmark
| | - Amy F. D. Howard
- Department of BioengineeringImperial College LondonLondonUK
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Rachel L. C. Barrett
- Department of Neuroimaging, Institute of Psychiatry, Psychology and NeuroscienceKing's College LondonLondonUK
- NatBrainLab, Department of Forensics and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and NeuroscienceKing's College London|LondonUK
| | - Manisha Aggarwal
- Russell H. Morgan Department of Radiology and Radiological ScienceJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Stijn Michielse
- Department of Neurosurgery, School for Mental Health and Neuroscience (MHeNS)Maastricht University Medical CenterMaastrichtThe Netherlands
| | - Fatima Nasrallah
- The Queensland Brain InstituteThe University of QueenslandQueenslandAustralia
| | - Warda Syeda
- Melbourne Neuropsychiatry CentreThe University of MelbourneParkvilleAustralia
| | - Nian Wang
- Department of Radiology and Imaging SciencesIndiana UniversityBloomingtonIndianaUSA
- Stark Neurosciences Research InstituteIndiana University School of MedicineIndianapolisIndianaUSA
| | - Jelle Veraart
- Center for Biomedical ImagingNYU Grossman School of MedicineNew YorkNew YorkUSA
| | - Alard Roebroeck
- Faculty of psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Andrew F. Bagdasarian
- Department of Chemical & Biomedical Engineering, FAMU‐FSU College of EngineeringFlorida State UniversityTallahasseeFloridaUSA
- Center for Interdisciplinary Magnetic ResonanceNational HIgh Magnetic Field LaboratoryTallahasseeFloridaUSA
| | - Cornelius Eichner
- Department of NeuropsychologyMax Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Farshid Sepehrband
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USCUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Jan Zimmermann
- Department of Neuroscience, Center for Magnetic Resonance ResearchUniversity of MinnesotaMinneapolisMinnesotaUSA
| | | | - Christien Bowman
- Bio‐Imaging Lab, Faculty of Pharmaceutical, Biomedical and Veterinary SciencesUniversity of AntwerpAntwerpBelgium
- μNEURO Research Centre of ExcellenceUniversity of AntwerpAntwerpBelgium
| | - Benjamin C. Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | - Andreea Hertanu
- Department of RadiologyLausanne University Hospital and University of LausanneLausanneSwitzerland
| | - Ben Jeurissen
- imec Vision Lab, Dept. of PhysicsUniversity of AntwerpAntwerpBelgium
- Lab for Equilibrium Investigations and Aerospace, Dept. of PhysicsUniversity of AntwerpAntwerpBelgium
| | - Marleen Verhoye
- Bio‐Imaging Lab, Faculty of Pharmaceutical, Biomedical and Veterinary SciencesUniversity of AntwerpAntwerpBelgium
- μNEURO Research Centre of ExcellenceUniversity of AntwerpAntwerpBelgium
| | - Lucio Frydman
- Department of Chemical and Biological PhysicsWeizmann Institute of ScienceRehovotIsrael
| | - Yohan van de Looij
- Division of Child Development & Growth, Department of Pediatrics, Gynaecology & Obstetrics, School of MedicineUniversité de GenèveGenèveSwitzerland
| | - David Hike
- Department of Chemical & Biomedical Engineering, FAMU‐FSU College of EngineeringFlorida State UniversityTallahasseeFloridaUSA
- Center for Interdisciplinary Magnetic ResonanceNational HIgh Magnetic Field LaboratoryTallahasseeFloridaUSA
| | - Jeff F. Dunn
- Department of Radiology, Cumming School of MedicineUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain Institute, Cumming School of MedicineUniversity of CalgaryCalgaryAlbertaCanada
- Alberta Children's Hospital Research Institute, Cumming School of MedicineUniversity of CalgaryCalgaryAlbertaCanada
| | - Karla Miller
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUK
| | | | - Noam Shemesh
- Champalimaud ResearchChampalimaud FoundationLisbonPortugal
| | - Adam Anderson
- Vanderbilt University Institute of Imaging ScienceVanderbilt UniversityNashvilleTennesseeUSA
- Department of Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Emilie McKinnon
- Medical University of South CarolinaCharlestonSouth CarolinaUSA
| | | | - Flavio Dell'Acqua
- Department of Forensic and Neurodevelopmental SciencesKing's College LondonLondonUK
| | - Carlo Pierpaoli
- Laboratory on Quantitative Medical imaging, NIBIBNational Institutes of HealthBethesdaMarylandUSA
| | - Ivana Drobnjak
- Department of Computer ScienceUniversity College LondonLondonUK
| | - Alexander Leemans
- PROVIDI Lab, Image Sciences InstituteUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Kevin D. Harkins
- Radiology and Radiological SciencesVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt University Institute of Imaging ScienceVanderbilt UniversityNashvilleTennesseeUSA
- Biomedical EngineeringVanderbilt UniversityNashvilleTennesseeUSA
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaing Lab (SCIL), Computer Science departmentUniversité de SherbrookeSherbrookeQuebecCanada
- Imeka SolutionsSherbrookeQuebecCanada
| | - Duan Xu
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Hao Huang
- Department of Radiology, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
- Department of RadiologyChildren's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Mathieu D. Santin
- Centre for NeuroImaging Research (CENIR)Inserm U 1127, CNRS UMR 7225, Sorbonne UniversitéParisFrance
- Paris Brain InstituteParisFrance
| | - Samuel C. Grant
- Department of Chemical & Biomedical Engineering, FAMU‐FSU College of EngineeringFlorida State UniversityTallahasseeFloridaUSA
- Center for Interdisciplinary Magnetic ResonanceNational HIgh Magnetic Field LaboratoryTallahasseeFloridaUSA
| | - Andre Obenaus
- Department of PediatricsUniversity of California IrvineIrvineCaliforniaUSA
- Preclinical and Translational Imaging CenterUniversity of California IrvineIrvineCaliforniaUSA
| | - Gene S. Kim
- Department of RadiologyWeill Cornell Medical CollegeNew YorkNew YorkUSA
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument ScienceZhejiang UniversityHangzhouChina
| | - Denis Le Bihan
- CEA, DRF, JOLIOT, NeuroSpinGif‐sur‐YvetteFrance
- Université Paris‐SaclayGif‐sur‐YvetteFrance
| | - Stephen J. Blackband
- Department of NeuroscienceUniversity of FloridaGainesvilleFloridaUSA
- McKnight Brain InstituteUniversity of FloridaGainesvilleFloridaUSA
- National High Magnetic Field LaboratoryTallahasseeFloridaUSA
| | - Luisa Ciobanu
- NeuroSpin, UMR CEA/CNRS 9027Paris‐Saclay UniversityGif‐sur‐YvetteFrance
| | - Els Fieremans
- Department of RadiologyNew York University Grossman School of MedicineNew YorkNew YorkUSA
| | - Ruiliang Bai
- Interdisciplinary Institute of Neuroscience and Technology, School of MedicineZhejiang UniversityHangzhouChina
- Frontier Center of Brain Science and Brain‐machine IntegrationZhejiang UniversityHangzhouChina
| | - Trygve B. Leergaard
- Department of Molecular Biology, Institute of Basic Medical SciencesUniversity of OsloOsloNorway
| | - Jiangyang Zhang
- Department of RadiologyNew York University School of MedicineNew YorkNew YorkUSA
| | - Tim B. Dyrby
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and ResearchCopenhagen University Hospital Amager & HvidovreHvidovreDenmark
- Department of Applied Mathematics and Computer ScienceTechnical University of DenmarkKongens LyngbyDenmark
| | - G. Allan Johnson
- Duke Center for In Vivo Microscopy, Department of RadiologyDuke UniversityDurhamNorth CarolinaUSA
- Department of Biomedical EngineeringDuke UniversityDurhamNorth CarolinaUSA
| | - Julien Cohen‐Adad
- NeuroPoly Lab, Institute of Biomedical EngineeringPolytechnique MontrealMontrealQuebecCanada
- Functional Neuroimaging Unit, CRIUGMUniversity of MontrealMontrealQuebecCanada
- Mila – Quebec AI InstituteMontrealQuebecCanada
| | - Matthew D. Budde
- Department of NeurosurgeryMedical College of WisconsinMilwaukeeWisconsinUSA
- Clement J Zablocki VA Medical CenterMilwaukeeWisconsinUSA
| | - Ileana O. Jelescu
- Department of RadiologyLausanne University Hospital and University of LausanneLausanneSwitzerland
- CIBM Center for Biomedical ImagingEcole Polytechnique Fédérale de LausanneLausanneSwitzerland
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Flint JJ, Menon K, Hansen B, Forder J, Blackband SJ. Visualization of live, mammalian neurons during Kainate-infusion using magnetic resonance microscopy. Neuroimage 2020; 219:116997. [PMID: 32492508 PMCID: PMC7510773 DOI: 10.1016/j.neuroimage.2020.116997] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 05/25/2020] [Accepted: 05/26/2020] [Indexed: 01/30/2023] Open
Abstract
Since its first description and development in the late 20th century, diffusion magnetic resonance imaging (dMRI) has proven useful in describing the microstructural details of biological tissues. Signal generated from the protons of water molecules undergoing Brownian motion produces contrast based on the varied diffusivity of tissue types. Images employing diffusion contrast were first used to describe the diffusion characteristics of tissues, later used to describe the fiber orientations of white matter through tractography, and most recently proposed as a functional contrast method capable of delineating neuronal firing in the active brain. Thanks to the molecular origins of its signal source, diffusion contrast is inherently useful at describing features of the microenvironment; however, limitations in achievable resolution in magnetic resonance imaging (MRI) scans precluded direct visualization of tissue microstructure for decades following MRI's inception as an imaging modality. Even after advancements in MRI hardware had permitted the visualization of mammalian cells, these specialized systems could only accommodate fixed specimens that prohibited the observation and characterization of physiological processes. The goal of the current study was to visualize cellular structure and investigate the subcellular origins of the functional diffusion contrast mechanism (DfMRI) in living, mammalian tissue explants. Using a combination of ultra-high field spectrometers, micro radio frequency (RF) coils, and an MRI-compatible superfusion device, we are able to report the first live, mammalian cells-α-motor neurons-visualized with magnetic resonance microscopy (MRM). We are also able to report changes in the apparent diffusion of the stratum oriens within the hippocampus-a layer comprised primarily of pyramidal cell axons and basal dendrites-and the spinal cord's ventral horn following exposure to kainate.
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Affiliation(s)
- Jeremy J Flint
- Department of Neuroscience, University of Florida, Gainesville, FL, USA; McKnight Brain Institute, University of Florida, Gainesville, FL, USA.
| | - Kannan Menon
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA; McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Brian Hansen
- Center of Functionally Integrative Neuroscience, Aarhus University, Denmark
| | - John Forder
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA; Department of Radiology, University of Florida, Gainesville, FL, USA; McKnight Brain Institute, University of Florida, Gainesville, FL, USA; National High Magnetic Field Laboratory, Tallahassee, FL, USA
| | - Stephen J Blackband
- Department of Neuroscience, University of Florida, Gainesville, FL, USA; McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Structural Biology, University of Florida, Gainesville, FL, USA; National High Magnetic Field Laboratory, Tallahassee, FL, USA
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Eremeev AV, Volovikov EA, Shuvalova LD, Davidenko AV, Khomyakova EA, Bogomiakova ME, Lebedeva OS, Zubkova OA, Lagarkova MA. "Necessity Is the Mother of Invention" or Inexpensive, Reliable, and Reproducible Protocol for Generating Organoids. BIOCHEMISTRY (MOSCOW) 2019; 84:321-328. [PMID: 31221070 DOI: 10.1134/s0006297919030143] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Organoids are three-dimensional (3D) cell cultures that replicate some of the key features of morphology, spatial architecture, and functions of a particular organ. Organoids can be generated from both adult and pluripotent stem cells (PSCs), and complex organoids can also be obtained by combining different types of cells, including differentiated cells. The ability of pluripotent cells to self-organize into organotypic structures containing several cell subtypes specific for a particular organ was used for creating organoids of the brain, eye, kidney, intestine, and other organs. Despite the advantages of using PSCs for obtaining organoids, an essential shortcoming that prevents their widespread use has been a low yield when they are obtained from a PSC monolayer culture and a large variation in size. This leads to great heterogeneity on further differentiation. In this article, we describe our own protocol for generating standardized organoids, with emphasis on a method for generating brain organoids, which allows scaling-up experiments and makes their cultivation less expensive and easier.
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Affiliation(s)
- A V Eremeev
- Federal Research and Clinical Center of Physical-Chemical Medicine (FRCC PCM), Federal Medical Biological Agency of Russia (FMBA), Moscow, 119435, Russia.
| | - E A Volovikov
- Federal Research and Clinical Center of Physical-Chemical Medicine (FRCC PCM), Federal Medical Biological Agency of Russia (FMBA), Moscow, 119435, Russia
| | - L D Shuvalova
- Federal Research and Clinical Center of Physical-Chemical Medicine (FRCC PCM), Federal Medical Biological Agency of Russia (FMBA), Moscow, 119435, Russia
| | - A V Davidenko
- Federal Research and Clinical Center of Physical-Chemical Medicine (FRCC PCM), Federal Medical Biological Agency of Russia (FMBA), Moscow, 119435, Russia
| | - E A Khomyakova
- Federal Research and Clinical Center of Physical-Chemical Medicine (FRCC PCM), Federal Medical Biological Agency of Russia (FMBA), Moscow, 119435, Russia
| | - M E Bogomiakova
- Federal Research and Clinical Center of Physical-Chemical Medicine (FRCC PCM), Federal Medical Biological Agency of Russia (FMBA), Moscow, 119435, Russia
| | - O S Lebedeva
- Federal Research and Clinical Center of Physical-Chemical Medicine (FRCC PCM), Federal Medical Biological Agency of Russia (FMBA), Moscow, 119435, Russia
| | - O A Zubkova
- Federal Research and Clinical Center of Physical-Chemical Medicine (FRCC PCM), Federal Medical Biological Agency of Russia (FMBA), Moscow, 119435, Russia
| | - M A Lagarkova
- Federal Research and Clinical Center of Physical-Chemical Medicine (FRCC PCM), Federal Medical Biological Agency of Russia (FMBA), Moscow, 119435, Russia.
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Kamberger R, Göbel-Guéniot K, Gerlach J, Gruschke OG, Hennig J, LeVan P, Haas C, Korvink JG. Improved method for MR microscopy of brain tissue cultured with the interface method combined with Lenz lenses. Magn Reson Imaging 2018; 52:24-32. [PMID: 29857037 DOI: 10.1016/j.mri.2018.05.010] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Revised: 05/21/2018] [Accepted: 05/21/2018] [Indexed: 12/17/2022]
Abstract
MR in microscopy can non-invasively image the morphology of living tissue, which is of particular interest in studying the mammalian brain. Many studies use live animals for basic research on brain functions, disease pathogenesis, and drug development. However, in vitro systems are on the rise, due to advantages such as the absence of a blood-brain barrier, predictable pharmacokinetics, and reduced ethical restrictions. Hence, they present an inexpensive and adequate technique to answer scientific questions and to perform drug screenings. Some publications report the use of acute brain slices for MR microscopy studies, but these only permit single measurements over several hours. Repetitive MR measurements in longitudinal studies demand an MR-compatible setup which allows cultivation for several days or weeks, and hence properly functioning in vitro systems. Organotypic hippocampal slice cultures (OHSC) are a well-established and robust in vitro system which still exhibits most histological hallmarks of the hippocampal network in vivo. An MR compatible incubation platform is introduced in which OHSC are cultivated according to the interface method following Stoppini et al. In this cultivation method a tissue slice is placed onto a membrane with nutrition medium underneath and a gas atmosphere above, where the air-tissue interface perpendicular to the B0 field induces strong artefacts. We introduce a handling protocol that suppresses these artefacts and increases signal quality significantly to acquire high resolution images of tissue slices. An additional challenge is the lack of available of MR microscopy equipment suitable for small animal scanners. A Lenz lens with an attached capacitor can dramatically increase the SNR in these cases, and wirelessly bring the detection system in close proximity to the sample without compromising the OHSC system through the introduction of wired detectors. The resultant signal gain is demonstrated by imaging a PFA-fixed brain slice with a 72 mm diameter volume coil without a Lenz lens, and with a broadband and a self-resonant Lenz lens. In our setting, the self-resonant Lenz lens increases the SNR 10-fold over using the volume coil only.
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Affiliation(s)
- R Kamberger
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany
| | - K Göbel-Guéniot
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Medical Physics, Department of Radiology, Medical Center - University of Freiburg, Germany
| | - J Gerlach
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Experimental Epilepsy Laboratory, Department of Neurosurgery, Medical Center - University of Freiburg, Germany
| | - O G Gruschke
- Institute of Microstructure Technology, Karlsruhe Institute of Technology, Germany
| | - J Hennig
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Medical Physics, Department of Radiology, Medical Center - University of Freiburg, Germany
| | - P LeVan
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Medical Physics, Department of Radiology, Medical Center - University of Freiburg, Germany
| | - C Haas
- BrainLinks-BrainTools Cluster of Excellence, University of Freiburg, Germany; Experimental Epilepsy Laboratory, Department of Neurosurgery, Medical Center - University of Freiburg, Germany
| | - J G Korvink
- Institute of Microstructure Technology, Karlsruhe Institute of Technology, Germany.
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Flint JJ, Menon K, Hansen B, Forder J, Blackband SJ. Metabolic Support of Excised, Living Brain Tissues During Magnetic Resonance Microscopy Acquisition. J Vis Exp 2017. [PMID: 29155793 PMCID: PMC5752427 DOI: 10.3791/56282] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
This protocol describes the procedures necessary to support normal metabolic functions of acute brain slice preparations during the collection of magnetic resonance (MR) microscopy data. While it is possible to perform MR collections on living, excised mammalian tissue, such experiments have traditionally been constrained by resolution limits and are thus incapable of visualizing tissue microstructure. Conversely, MR protocols that did achieve microscopic image resolution required the use of fixed samples to accommodate the need for static, unchanging conditions over lengthy scan times. The current protocol describes the first available MR technique that enables imaging of living, mammalian tissue samples at microscopic resolutions. Such data is of great importance to the understanding of how pathology-based contrast changes occurring at the microscopic level influence the content of macroscopic MR scans such as those used in the clinic. Once such an understanding is realized, diagnostic methods with greater sensitivity and accuracy can be developed, which will translate directly to earlier disease treatment, more accurate therapy monitoring and improved patient outcomes. While the described methodology focuses on brain slice preparations, the protocol is adaptable to any excised tissue slice given that changes are made to the gas and perfusate preparations to accommodate the tissue's specific metabolic needs. Successful execution of the protocol should result in living, acute slice preparations that exhibit MR diffusion signal stability for periods up to 15.5 h. The primary advantages of the current system over other MR compatible perfusion apparatuses are its compatibility with the MR microscopy hardware required to attain higher resolution images and ability to provide constant, uninterrupted flow with carefully regulated perfusate conditions. Reduced sample throughput is a consideration with this design as only one tissue slice may be imaged at a time.
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Affiliation(s)
- Jeremy J Flint
- Department of Neuroscience, University of Florida; McKnight Brain Institute, University of Florida;
| | - Kannan Menon
- McKnight Brain Institute, University of Florida; Department of Biomedical Engineering, University of Florida
| | - Brian Hansen
- Center for Functionally Integrative Neuroscience, Aarhus University
| | - John Forder
- McKnight Brain Institute, University of Florida; Department of Biomedical Engineering, University of Florida; Department of Radiology, University of Florida
| | - Stephen J Blackband
- Department of Neuroscience, University of Florida; McKnight Brain Institute, University of Florida; National High Magnetic Field Laboratory, Florida State University
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Hansen B, Khan AR, Shemesh N, Lund TE, Sangill R, Eskildsen SF, Østergaard L, Jespersen SN. White matter biomarkers from fast protocols using axially symmetric diffusion kurtosis imaging. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3741. [PMID: 28543843 PMCID: PMC5557696 DOI: 10.1002/nbm.3741] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2016] [Revised: 03/27/2017] [Accepted: 04/03/2017] [Indexed: 05/12/2023]
Abstract
White matter tract integrity (WMTI) can characterize brain microstructure in areas with highly aligned fiber bundles. Several WMTI biomarkers have now been validated against microscopy and provided promising results in studies of brain development and aging, as well as in a number of brain disorders. Currently, WMTI is mostly used in dedicated animal studies and clinical studies of slowly progressing diseases, and has not yet emerged as a routine clinical tool. To this end, a less data intensive experimental method would be beneficial by enabling high resolution validation studies, and ease clinical applications by speeding up data acquisition compared with typical diffusion kurtosis imaging (DKI) protocols utilized as part of WMTI imaging. Here, we evaluate WMTI based on recently introduced axially symmetric DKI, which has lower data demand than conventional DKI. We compare WMTI parameters derived from conventional DKI with those calculated analytically from axially symmetric DKI. We employ numerical simulations, as well as data from fixed rat spinal cord (one sample) and in vivo human (three subjects) and rat brain (four animals). Our analysis shows that analytical WMTI based on axially symmetric DKI with sparse data sets (19 images) produces WMTI metrics that correlate strongly with estimates based on traditional DKI data sets (60 images or more). We demonstrate the preclinical potential of the proposed WMTI technique in in vivo rat brain (300 μm isotropic resolution with whole brain coverage in a 1 h acquisition). WMTI parameter estimates are subject to a duality leading to two solution branches dependent on a sign choice, which is currently debated. Results from both of these branches are presented and discussed throughout our analysis. The proposed fast WMTI approach may be useful for preclinical research and e.g. clinical evaluation of patients with traumatic white matter injuries or symptoms of neurovascular or neuroinflammatory disorders.
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Affiliation(s)
- Brian Hansen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Ahmad R. Khan
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Noam Shemesh
- Champalimaud Neuroscience Programme, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Torben E. Lund
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Ryan Sangill
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Simon F. Eskildsen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Leif Østergaard
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Sune N. Jespersen
- Center of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
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7
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Flint JJ, Hansen B, Blackband SJ. Diffusion tensor microscopy data (15.6 μm in-plane) of white matter tracts in the human, pig, and rat spinal cord with corresponding tissue histology. Data Brief 2016; 9:271-4. [PMID: 27668273 PMCID: PMC5024313 DOI: 10.1016/j.dib.2016.08.020] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2016] [Revised: 07/26/2016] [Accepted: 08/09/2016] [Indexed: 11/21/2022] Open
Abstract
The following article contains nine diffusion tensor imaging (DTI) datasets acquired with magnetic resonance microscopy (MRM, 15.6 μm in-plane). All data was collected in the region bordering the ventral horn and white matter of cross sections from the spinal cord enlargements along with each sample׳s corresponding tissue histology. These data are collected in fixed spinal cord sections of varying thicknesses taken from rat (2×21 direction DTI datasets), pig (1×21 direction DTI dataset), and human (5×21 direction DTI datasets + 1×6 direction DTI dataset) tissue sources. Following MRM acquisition, the sections were histologically processed using Nissl or Black-Gold II (Histo-Chem Inc., 1BGII) myelin stain and imaged again using light microscopy techniques. Methodological procedures are an amalgamation of protocol components described previously (doi:10.1016/j.neuroimage.2010.04.031 [1], doi:10.1016/j.neuroimage.2011.04.052 [2]).
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Affiliation(s)
- Jeremy J Flint
- Department of Neuroscience, University of Florida, Gainesville, FL, USA; McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Brian Hansen
- Center for Functionally Integrative Neuroscience, Aarhus University, Denmark
| | - Stephen J Blackband
- Department of Neuroscience, University of Florida, Gainesville, FL, USA; McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Structural Biology, University of Florida, Gainesville, FL, USA; National High Magnetic Field Laboratory, Tallahassee, FL, USA
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