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Fastenau C, Bunce M, Keating M, Wickline J, Hopp SC, Bieniek KF. Distinct patterns of plaque and microglia glycosylation in Alzheimer's disease. Brain Pathol 2024; 34:e13267. [PMID: 38724175 PMCID: PMC11189777 DOI: 10.1111/bpa.13267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 04/22/2024] [Indexed: 06/23/2024] Open
Abstract
Glycosylation is the most common form of post-translational modification in the brain. Aberrant glycosylation has been observed in cerebrospinal fluid and brain tissue of Alzheimer's disease (AD) cases, including dysregulation of terminal sialic acid (SA) modifications. While alterations in sialylation have been identified in AD, the localization of SA modifications on cellular or aggregate-associated glycans is largely unknown because of limited spatial resolution of commonly utilized methods. The present study aims to overcome these limitations with novel combinations of histologic techniques to characterize the sialylation landscape of O- and N-linked glycans in autopsy-confirmed AD post-mortem brain tissue. Sialylated glycans facilitate important cellular functions including cell-to-cell interaction, cell migration, cell adhesion, immune regulation, and membrane excitability. Previous studies have not investigated both N- and O-linked sialylated glycans in neurodegeneration. In this study, the location and distribution of sialylated glycans were evaluated in three brain regions (frontal cortex, hippocampus, and cerebellum) from 10 AD cases using quantitative digital pathology techniques. Notably, we found significantly greater N-sialylation of the Aβ plaque microenvironment compared with O-sialylation. Plaque-associated microglia displayed the most intense N-sialylation proximal to plaque pathology. Further analyses revealed distinct differences in the levels of N- and O-sialylation between cored and diffuse Aβ plaque morphologies. Interestingly, phosphorylated tau pathology led to a slight increase in N-sialylation and no influence of O-sialylation in these AD brains. Confirming our previous observations in mice with novel histologic approach, these findings support microglia sialylation appears to have a relationship with AD protein aggregates while providing potential targets for therapeutic strategies.
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Affiliation(s)
- Caitlyn Fastenau
- Department of PharmacologyUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
| | - Madison Bunce
- Department of PharmacologyUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
| | - Mallory Keating
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
| | - Jessica Wickline
- Department of PharmacologyUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
| | - Sarah C. Hopp
- Department of PharmacologyUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
| | - Kevin F. Bieniek
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
- Department of Pathology and Laboratory MedicineUniversity of Texas Health Science Center San AntonioSan AntonioTexasUSA
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2
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Zejlon C, Sennfält S, Finnsson J, Connolly B, Petersson S, Granberg T, Ingre C. Motor band sign is specific for amyotrophic lateral sclerosis and corresponds to motor symptoms. Ann Clin Transl Neurol 2024; 11:1280-1289. [PMID: 38647181 DOI: 10.1002/acn3.52066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 03/15/2024] [Accepted: 04/02/2024] [Indexed: 04/25/2024] Open
Abstract
OBJECTIVE Magnetic resonance imaging can detect neurodegenerative iron accumulation in the motor cortex, called the motor band sign. This study aims to evaluate its sensitivity/specificity and correlations to symptomatology, biomarkers, and clinical outcome in amyotrophic lateral sclerosis. METHODS This prospective study consecutively enrolled 114 persons with amyotrophic lateral sclerosis and 79 mimics referred to Karolinska University Hospital, and also 31 healthy controls. All underwent 3-Tesla brain susceptibility-weighted imaging. Three raters independently assessed motor cortex susceptibility with total and regional motor band scores. Survival was evaluated at a median of 34.2 months after the imaging. RESULTS The motor band sign identified amyotrophic lateral sclerosis with a sensitivity of 59.6% and a specificity of 91.1% versus mimics and 96.8% versus controls. Higher motor band scores were more common with genetic risk factors (p = 0.032), especially with C9orf72 mutation, and were associated with higher neurofilament light levels (std. β 0.22, p = 0.019). Regional scores correlated strongly with focal symptoms (medial region vs. gross motor dysfunction, std. β -0.64, p = 0.001; intermediate region vs. fine motor dysfunction, std. β -0.51, p = 0.031; lateral region vs. bulbar symptoms std. β -0.71, p < 0.001). There were no associations with cognition, progression rate, or survival. INTERPRETATION In a real-life clinical setting, the motor band sign has high specificity but relatively low sensitivity for identifying amyotrophic lateral sclerosis. Associations with genetic risk factors, neurofilament levels and somatotopic correspondence to focal motor weakness suggest that the motor band sign could be a suitable biomarker for diagnostics and clinical trials in amyotrophic lateral sclerosis.
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Affiliation(s)
- Charlotte Zejlon
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Stefan Sennfält
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Johannes Finnsson
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Bryan Connolly
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Sven Petersson
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Tobias Granberg
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Caroline Ingre
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
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3
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Northall A, Doehler J, Weber M, Tellez I, Petri S, Prudlo J, Vielhaber S, Schreiber S, Kuehn E. Multimodal layer modelling reveals in vivo pathology in amyotrophic lateral sclerosis. Brain 2024; 147:1087-1099. [PMID: 37815224 PMCID: PMC10907094 DOI: 10.1093/brain/awad351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 09/01/2023] [Accepted: 09/24/2023] [Indexed: 10/11/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a rapidly progressing neurodegenerative disease characterized by the loss of motor control. Current understanding of ALS pathology is largely based on post-mortem investigations at advanced disease stages. A systematic in vivo description of the microstructural changes that characterize early stage ALS, and their subsequent development, is so far lacking. Recent advances in ultra-high field (7 T) MRI data modelling allow us to investigate cortical layers in vivo. Given the layer-specific and topographic signature of ALS pathology, we combined submillimetre structural 7 T MRI data (qT1, QSM), functional localizers of body parts (upper limb, lower limb, face) and layer modelling to systematically describe pathology in the primary motor cortex (M1), in 12 living ALS patients with reference to 12 matched controls. Longitudinal sampling was performed for a subset of patients. We calculated multimodal pathology maps for each layer (superficial layer, layer 5a, layer 5b, layer 6) of M1 to identify hot spots of demyelination, iron and calcium accumulation in different cortical fields. We show preserved mean cortical thickness and layer architecture of M1, despite significantly increased iron in layer 6 and significantly increased calcium in layer 5a and superficial layer, in patients compared to controls. The behaviourally first-affected cortical field shows significantly increased iron in L6 compared to other fields, while calcium accumulation is atopographic and significantly increased in the low myelin borders between cortical fields compared to the fields themselves. A subset of patients with longitudinal data shows that the low myelin borders are particularly disrupted and that calcium hot spots, but to a lesser extent iron hot spots, precede demyelination. Finally, we highlight that a very slow progressing patient (Patient P4) shows a distinct pathology profile compared to the other patients. Our data show that layer-specific markers of in vivo pathology can be identified in ALS patients with a single 7 T MRI measurement after first diagnosis, and that such data provide critical insights into the individual disease state. Our data highlight the non-topographic architecture of ALS disease spread and the role of calcium, rather than iron accumulation, in predicting future demyelination. We also highlight a potentially important role of low myelin borders, that are known to connect to multiple areas within the M1 architecture, in disease spread. Finally, the distinct pathology profile of a very-slow progressing patient (Patient P4) highlights a distinction between disease duration and progression. Our findings demonstrate the importance of in vivo histology imaging for the diagnosis and prognosis of neurodegenerative diseases such as ALS.
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Affiliation(s)
- Alicia Northall
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
| | - Juliane Doehler
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
| | - Miriam Weber
- Department of Neurology, Otto-von-Guericke University Magdeburg (OVGU), Magdeburg 39120, Germany
| | - Igor Tellez
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
| | - Susanne Petri
- Department of Neurology, Hannover Medical School (MHH), Hanover 30625, Germany
| | - Johannes Prudlo
- Department of Neurology, Rostock University Medical Centre, Rostock 18147, Germany
- German Center for Neurodegenerative Diseases (DZNE), Rostock 18147, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto-von-Guericke University Magdeburg (OVGU), Magdeburg 39120, Germany
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
- Department of Neurology, Otto-von-Guericke University Magdeburg (OVGU), Magdeburg 39120, Germany
- Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg 39120, Germany
| | - Esther Kuehn
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg 39120, Germany
- Center for Behavioral Brain Sciences (CBBS) Magdeburg, Magdeburg 39120, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen 72076, Germany
- Hertie Institute for Clinical Brain Research (HIH), Tübingen 72076, Germany
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McMackin R, Bede P, Ingre C, Malaspina A, Hardiman O. Biomarkers in amyotrophic lateral sclerosis: current status and future prospects. Nat Rev Neurol 2023; 19:754-768. [PMID: 37949994 DOI: 10.1038/s41582-023-00891-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/09/2023] [Indexed: 11/12/2023]
Abstract
Disease heterogeneity in amyotrophic lateral sclerosis poses a substantial challenge in drug development. Categorization based on clinical features alone can help us predict the disease course and survival, but quantitative measures are also needed that can enhance the sensitivity of the clinical categorization. In this Review, we describe the emerging landscape of diagnostic, categorical and pharmacodynamic biomarkers in amyotrophic lateral sclerosis and their place in the rapidly evolving landscape of new therapeutics. Fluid-based markers from cerebrospinal fluid, blood and urine are emerging as useful diagnostic, pharmacodynamic and predictive biomarkers. Combinations of imaging measures have the potential to provide important diagnostic and prognostic information, and neurophysiological methods, including various electromyography-based measures and quantitative EEG-magnetoencephalography-evoked responses and corticomuscular coherence, are generating useful diagnostic, categorical and prognostic markers. Although none of these biomarker technologies has been fully incorporated into clinical practice or clinical trials as a primary outcome measure, strong evidence is accumulating to support their clinical utility.
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Affiliation(s)
- Roisin McMackin
- Discipline of Physiology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland
| | - Peter Bede
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- Computational Neuroimaging Group, School of Medicine, Trinity College Dublin, The University of Dublin, Dublin, Ireland
- Department of Neurology, St James's Hospital, Dublin, Ireland
| | - Caroline Ingre
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Andrea Malaspina
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Orla Hardiman
- Academic Unit of Neurology, School of Medicine, Trinity Biomedical Sciences Institute, Trinity College Dublin, The University of Dublin, Dublin, Ireland.
- Department of Neurology, Beaumont Hospital, Dublin, Ireland.
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Grossman M, Seeley WW, Boxer AL, Hillis AE, Knopman DS, Ljubenov PA, Miller B, Piguet O, Rademakers R, Whitwell JL, Zetterberg H, van Swieten JC. Frontotemporal lobar degeneration. Nat Rev Dis Primers 2023; 9:40. [PMID: 37563165 DOI: 10.1038/s41572-023-00447-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/12/2023] [Indexed: 08/12/2023]
Abstract
Frontotemporal lobar degeneration (FTLD) is one of the most common causes of early-onset dementia and presents with early social-emotional-behavioural and/or language changes that can be accompanied by a pyramidal or extrapyramidal motor disorder. About 20-25% of individuals with FTLD are estimated to carry a mutation associated with a specific FTLD pathology. The discovery of these mutations has led to important advances in potentially disease-modifying treatments that aim to slow progression or delay disease onset and has improved understanding of brain functioning. In both mutation carriers and those with sporadic disease, the most common underlying diagnoses are linked to neuronal and glial inclusions containing tau (FTLD-tau) or TDP-43 (FTLD-TDP), although 5-10% of patients may have inclusions containing proteins from the FUS-Ewing sarcoma-TAF15 family (FTLD-FET). Biomarkers definitively identifying specific pathological entities in sporadic disease have been elusive, which has impeded development of disease-modifying treatments. Nevertheless, disease-monitoring biofluid and imaging biomarkers are becoming increasingly sophisticated and are likely to serve as useful measures of treatment response during trials of disease-modifying treatments. Symptomatic trials using novel approaches such as transcranial direct current stimulation are also beginning to show promise.
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Affiliation(s)
- Murray Grossman
- Department of Neurology and Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA, USA
| | - William W Seeley
- Departments of Neurology and Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA.
- Department of Pathology, University of California, San Francisco, San Francisco, CA, USA.
| | - Adam L Boxer
- Departments of Neurology and Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Argye E Hillis
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | | | - Peter A Ljubenov
- Departments of Neurology and Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Bruce Miller
- Departments of Neurology and Memory and Aging Center, University of California, San Francisco, San Francisco, CA, USA
| | - Olivier Piguet
- School of Psychology and Brain and Mind Center, University of Sydney, Sydney, New South Wales, Australia
| | - Rosa Rademakers
- VIB Center for Molecular Neurology, University of Antwerp, Antwerp, Belgium
| | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The University of Gothenburg, Mölndal, Sweden
- Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
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Howard AFD, Huszar IN, Smart A, Cottaar M, Daubney G, Hanayik T, Khrapitchev AA, Mars RB, Mollink J, Scott C, Sibson NR, Sallet J, Jbabdi S, Miller KL. An open resource combining multi-contrast MRI and microscopy in the macaque brain. Nat Commun 2023; 14:4320. [PMID: 37468455 PMCID: PMC10356772 DOI: 10.1038/s41467-023-39916-1] [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: 09/16/2022] [Accepted: 07/03/2023] [Indexed: 07/21/2023] Open
Abstract
Understanding brain structure and function often requires combining data across different modalities and scales to link microscale cellular structures to macroscale features of whole brain organisation. Here we introduce the BigMac dataset, a resource combining in vivo MRI, extensive postmortem MRI and multi-contrast microscopy for multimodal characterisation of a single whole macaque brain. The data spans modalities (MRI and microscopy), tissue states (in vivo and postmortem), and four orders of spatial magnitude, from microscopy images with micrometre or sub-micrometre resolution, to MRI signals on the order of millimetres. Crucially, the MRI and microscopy images are carefully co-registered together to facilitate quantitative multimodal analyses. Here we detail the acquisition, curation, and first release of the data, that together make BigMac a unique, openly-disseminated resource available to researchers worldwide. Further, we demonstrate example analyses and opportunities afforded by the data, including improvement of connectivity estimates from ultra-high angular resolution diffusion MRI, neuroanatomical insight provided by polarised light imaging and myelin-stained histology, and the joint analysis of MRI and microscopy data for reconstruction of the microscopy-inspired connectome. All data and code are made openly available.
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Affiliation(s)
- Amy F D Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Michiel Cottaar
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Greg Daubney
- Wellcome Centre for Integrative Neuroimaging, Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Taylor Hanayik
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Connor Scott
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | | | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Experimental Psychology, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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Cannon AE, Zürrer WE, Zejlon C, Kulcsar Z, Lewandowski S, Piehl F, Granberg T, Ineichen BV. Neuroimaging findings in preclinical amyotrophic lateral sclerosis models-How well do they mimic the clinical phenotype? A systematic review. Front Vet Sci 2023; 10:1135282. [PMID: 37205225 PMCID: PMC10185801 DOI: 10.3389/fvets.2023.1135282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 04/10/2023] [Indexed: 05/21/2023] Open
Abstract
Background and objectives Animal models for motor neuron diseases (MND) such as amyotrophic lateral sclerosis (ALS) are commonly used in preclinical research. However, it is insufficiently understood how much findings from these model systems can be translated to humans. Thus, we aimed at systematically assessing the translational value of MND animal models to probe their external validity with regards to magnetic resonance imaging (MRI) features. Methods In a comprehensive literature search in PubMed and Embase, we retrieved 201 unique publications of which 34 were deemed eligible for qualitative synthesis including risk of bias assessment. Results ALS animal models can indeed present with human ALS neuroimaging features: Similar to the human paradigm, (regional) brain and spinal cord atrophy as well as signal changes in motor systems are commonly observed in ALS animal models. Blood-brain barrier breakdown seems to be more specific to ALS models, at least in the imaging domain. It is noteworthy that the G93A-SOD1 model, mimicking a rare clinical genotype, was the most frequently used ALS proxy. Conclusions Our systematic review provides high-grade evidence that preclinical ALS models indeed show imaging features highly reminiscent of human ALS assigning them a high external validity in this domain. This opposes the high attrition of drugs during bench-to-bedside translation and thus raises concerns that phenotypic reproducibility does not necessarily render an animal model appropriate for drug development. These findings emphasize a careful application of these model systems for ALS therapy development thereby benefiting refinement of animal experiments. Systematic review registration https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022373146.
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Affiliation(s)
| | | | - Charlotte Zejlon
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | | | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Tobias Granberg
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Benjamin Victor Ineichen
- Center for Reproducible Science, University of Zurich, Zurich, Switzerland
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- *Correspondence: Benjamin Victor Ineichen
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8
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Huszar IN, Pallebage-Gamarallage M, Bangerter-Christensen S, Brooks H, Fitzgibbon S, Foxley S, Hiemstra M, Howard AFD, Jbabdi S, Kor DZL, Leonte A, Mollink J, Smart A, Tendler BC, Turner MR, Ansorge O, Miller KL, Jenkinson M. Tensor image registration library: Deformable registration of stand-alone histology images to whole-brain post-mortem MRI data. Neuroimage 2023; 265:119792. [PMID: 36509214 PMCID: PMC10933796 DOI: 10.1016/j.neuroimage.2022.119792] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 10/26/2022] [Accepted: 12/04/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Accurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to assist the registration of stand-alone histology sections to whole-brain MRI data. METHODS Our pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slab photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline. RESULTS All 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks. CONCLUSIONS Our open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies.
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Affiliation(s)
- Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | | | - Sarah Bangerter-Christensen
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Brigham Young University, Provo, UT, USA
| | - Hannah Brooks
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Sean Fitzgibbon
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Sean Foxley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Radiology, University of Chicago, Chicago, IL, USA
| | - Marlies Hiemstra
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Anatomy, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Amy F D Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Daniel Z L Kor
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Anna Leonte
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Neuroscience, University of Groningen, Groningen, the Netherlands
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Anatomy, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Martin R Turner
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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9
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Lahna D, Roese N, Woltjer R, Boespflug EL, Schwartz D, Grinstead J, Dodge HH, Wall R, Kaye JA, Rooney WD, Silbert LC. Postmortem 7T MRI for guided histopathology and evaluation of cerebrovascular disease. J Neuropathol Exp Neurol 2022; 82:57-70. [PMID: 36343095 PMCID: PMC9764082 DOI: 10.1093/jnen/nlac103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Postmortem (PM) magnetic resonance imaging (MRI) can serve as a bridge between in vivo imaging and histology by connecting MRI observed macrostructural findings to histological staining and microstructural changes. Data were acquired from 20 formalin-fixed brains including T2, T1, PD, and T2*-weighted images of left hemispheres and 6-mm-thick coronal slices. Tissue slices were bisected, aligned to MR images and used to guide histological sampling. Markers of myelin and oligodendroglia alterations were semiquantitatively rated and compared within white matter hyperintensities (WMHs) and normal-appearing white matter. Tissue priors were created from 3T in vivo data and used to guide segmentation of WMH. PM WMH and hemisphere volumes were compared to volumes derived from in vivo data. PM T2 WMH and T1 hemisphere volumes were correlated with in vivo 3T FLAIR WMH and T1 hemisphere volumes. WMH showed significant myelin loss, decreased GFAP expression and increased vimentin expression. MR-visible perivascular spaces and cortical microvascular lesions were successfully captured on histopathological sections. PM MRI can quantify cerebrovascular disease burden and guide tissue sampling, allowing for more comprehensive characterization of cerebrovascular disease that may be used to study etiologies of age-related cognitive change.
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Affiliation(s)
- David Lahna
- NIA-Layton Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Natalie Roese
- NIA-Layton Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Randy Woltjer
- NIA-Layton Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, Oregon, USA
- Department of Pathology, Oregon Health & Science University, Portland, Oregon, USA
| | - Erin L Boespflug
- NIA-Layton Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Daniel Schwartz
- NIA-Layton Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, Oregon, USA
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | | | - Hiroko H Dodge
- NIA-Layton Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, Oregon, USA
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Rachel Wall
- NIA-Layton Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, Oregon, USA
- Veterans Affairs Portland Health Care System, Portland, Oregon, USA
| | - Jeffrey A Kaye
- NIA-Layton Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - William D Rooney
- Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA
| | - Lisa C Silbert
- NIA-Layton Alzheimer’s Disease Research Center, Oregon Health & Science University, Portland, Oregon, USA
- Veterans Affairs Portland Health Care System, Portland, Oregon, USA
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10
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Kor DZL, Jbabdi S, Huszar IN, Mollink J, Tendler BC, Foxley S, Wang C, Scott C, Smart A, Ansorge O, Pallebage-Gamarallage M, Miller KL, Howard AFD. An automated pipeline for extracting histological stain area fraction for voxelwise quantitative MRI-histology comparisons. Neuroimage 2022; 264:119726. [PMID: 36368503 PMCID: PMC10933753 DOI: 10.1016/j.neuroimage.2022.119726] [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: 07/06/2022] [Revised: 10/27/2022] [Accepted: 10/31/2022] [Indexed: 11/11/2022] Open
Abstract
The acquisition of MRI and histology in the same post-mortem tissue sample enables direct correlation between MRI and histologically-derived parameters. However, there still lacks a standardised automated pipeline to process histology data, with most studies relying on manual intervention. Here, we introduce an automated pipeline to extract a quantitative histological measure for staining density (stain area fraction, SAF) from multiple immunohistochemical (IHC) stains. The pipeline is designed to directly address key IHC artefacts related to tissue staining and slide digitisation. Here, the pipeline was applied to post-mortem human brain data from multiple subjects, relating MRI parameters (FA, MD, RD, AD, R2*, R1) to IHC slides stained for myelin, neurofilaments, microglia and activated microglia. Utilising high-quality MRI-histology co-registrations, we then performed whole-slide voxelwise comparisons (simple correlations, partial correlations and multiple regression analyses) between multimodal MRI- and IHC-derived parameters. The pipeline was found to be reproducible, robust to artefacts and generalisable across multiple IHC stains. Our partial correlation results suggest that some simple MRI-SAF correlations should be interpreted with caution, due to the co-localisation of other tissue features (e.g., myelin and neurofilaments). Further, we find activated microglia-a generic biomarker of inflammation-to consistently be the strongest predictor of high DTI FA and low RD, which may suggest sensitivity of diffusion MRI to aspects of neuroinflammation related to microglial activation, even after accounting for other microstructural changes (demyelination, axonal loss and general microglia infiltration). Together, these results show the utility of this approach in carefully curating IHC data and performing multimodal analyses to better understand microstructural relationships with MRI.
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Affiliation(s)
- Daniel Z L Kor
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom.
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Sean Foxley
- Department of Radiology, University of Chicago, Chicago, IL, United States of America
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Connor Scott
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom; Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Olaf Ansorge
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Menuka Pallebage-Gamarallage
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Amy F D Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
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11
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Zejlon C, Nakhostin D, Winklhofer S, Pangalu A, Kulcsar Z, Lewandowski S, Finnsson J, Piehl F, Ingre C, Granberg T, Ineichen BV. Structural magnetic resonance imaging findings and histopathological correlations in motor neuron diseases—A systematic review and meta-analysis. Front Neurol 2022; 13:947347. [PMID: 36110394 PMCID: PMC9468579 DOI: 10.3389/fneur.2022.947347] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 07/08/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectivesThe lack of systematic evidence on neuroimaging findings in motor neuron diseases (MND) hampers the diagnostic utility of magnetic resonance imaging (MRI). Thus, we aimed at performing a systematic review and meta-analysis of MRI features in MND including their histopathological correlation.MethodsIn a comprehensive literature search, out of 5941 unique publications, 223 records assessing brain and spinal cord MRI findings in MND were eligible for a qualitative synthesis. 21 records were included in a random effect model meta-analysis.ResultsOur meta-analysis shows that both T2-hyperintensities along the corticospinal tracts (CST) and motor cortex T2*-hypointensitites, also called “motor band sign”, are more prevalent in ALS patients compared to controls [OR 2.21 (95%-CI: 1.40–3.49) and 10.85 (95%-CI: 3.74–31.44), respectively]. These two imaging findings correlate to focal axonal degeneration/myelin pallor or glial iron deposition on histopathology, respectively. Additionally, certain clinical MND phenotypes such as amyotrophic lateral sclerosis (ALS) seem to present with distinct CNS atrophy patterns.ConclusionsAlthough CST T2-hyperintensities and the “motor band sign” are non-specific imaging features, they can be leveraged for diagnostic workup of suspected MND cases, together with certain brain atrophy patterns. Collectively, this study provides high-grade evidence for the usefulness of MRI in the diagnostic workup of suspected MND cases.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42020182682.
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Affiliation(s)
- Charlotte Zejlon
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Dominik Nakhostin
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Sebastian Winklhofer
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Athina Pangalu
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | - Zsolt Kulcsar
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
| | | | - Johannes Finnsson
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Fredrik Piehl
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Center of Neurology, Academic Specialist Center, Stockholm Health Services, Stockholm, Sweden
| | - Caroline Ingre
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
| | - Tobias Granberg
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Benjamin Victor Ineichen
- Department of Neuroradiology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neuroradiology, Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zürich, Switzerland
- *Correspondence: Benjamin Victor Ineichen
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12
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Yendiki A, Aggarwal M, Axer M, Howard AF, van Cappellen van Walsum AM, Haber SN. Post mortem mapping of connectional anatomy for the validation of diffusion MRI. Neuroimage 2022; 256:119146. [PMID: 35346838 PMCID: PMC9832921 DOI: 10.1016/j.neuroimage.2022.119146] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 01/13/2023] Open
Abstract
Diffusion MRI (dMRI) is a unique tool for the study of brain circuitry, as it allows us to image both the macroscopic trajectories and the microstructural properties of axon bundles in vivo. The Human Connectome Project ushered in an era of impressive advances in dMRI acquisition and analysis. As a result of these efforts, the quality of dMRI data that could be acquired in vivo improved substantially, and large collections of such data became widely available. Despite this progress, the main limitation of dMRI remains: it does not image axons directly, but only provides indirect measurements based on the diffusion of water molecules. Thus, it must be validated by methods that allow direct visualization of axons but that can only be performed in post mortem brain tissue. In this review, we discuss methods for validating the various features of connectional anatomy that are extracted from dMRI, both at the macro-scale (trajectories of axon bundles), and at micro-scale (axonal orientations and other microstructural properties). We present a range of validation tools, including anatomic tracer studies, Klingler's dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.
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Affiliation(s)
- Anastasia Yendiki
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States,Corresponding author (A. Yendiki)
| | - Manisha Aggarwal
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Markus Axer
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich, Germany,Department of Physics, University of Wuppertal Germany
| | - Amy F.D. Howard
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Anne-Marie van Cappellen van Walsum
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Nijmegen, the Netherland,Cognition and Behaviour, Donders Institute for Brain, Nijmegen, the Netherland
| | - Suzanne N. Haber
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, United States,McLean Hospital, Belmont, MA, United States
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13
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Distribution Indices of Magnetic Susceptibility Values in the Primary Motor Cortex Enable to Classify Patients with Amyotrophic Lateral Sclerosis. Brain Sci 2022; 12:brainsci12070942. [PMID: 35884748 PMCID: PMC9313208 DOI: 10.3390/brainsci12070942] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/14/2022] [Accepted: 07/15/2022] [Indexed: 12/10/2022] Open
Abstract
Quantitative Susceptibility Mapping (QSM) can measure iron concentration increase in the primary motor cortex (M1) of patients with Amyotrophic Lateral Sclerosis (ALS). However, such alteration is confined to only specific regions interested by upper motor neuron pathology; therefore, mean QSM values in the entire M1 have limited diagnostic accuracy in discriminating between ALS patients and control subjects. This study investigates the diagnostic accuracy of a broader set of M1 QSM distribution indices in classifying ALS patients and controls. Mean, standard deviation, skewness and kurtosis of M1 QSM values were used either individually or as combined predictors in support vector machines. The classification performance was compared to that obtained by the radiological assessment of T2* signal hypo-intensity of M1 in susceptibility-weighted MRI. The least informative index for the classification of ALS patients and controls was the subject’s mean QSM value in M1. The highest diagnostic performance was obtained when all the distribution indices of positive QSM values in M1 were considered, which yielded a diagnostic accuracy of 0.90, with sensitivity = 0.89 and specificity = 1. The radiological assessment of M1 yielded a diagnostic accuracy of 0.79, with sensitivity = 0.76 and specificity = 0.90. The joint evaluation of QSM distribution indices could support the clinical examination in ALS diagnosis and patient monitoring.
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14
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Stram MN, Seifert AC, Cortes E, Akyatan A, Woodoff-Leith E, Borukhov V, Tetlow A, Alyemni D, Greenberg M, Gupta A, Krausert A, Mecca L, Rodriguez S, Stahl-Herz J, Guzman MA, Delman B, Crary JF, Dams-O'Connor K, Folkerth RD. Neuropathology of Pediatric SARS-CoV-2 Infection in the Forensic Setting: Novel Application of Ex Vivo Imaging in Analysis of Brain Microvasculature. Front Neurol 2022; 13:894565. [PMID: 35685741 PMCID: PMC9170881 DOI: 10.3389/fneur.2022.894565] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 04/25/2022] [Indexed: 11/13/2022] Open
Abstract
Two years into the COVID-19 pandemic, there are few published accounts of postmortem SARS-CoV-2 pathology in children. We report 8 such cases (4 infants aged 7–36 weeks, 4 children aged 5–15 years). Four underwent ex vivo magnetic resonance neuroimaging, to assist in identification of subtle lesions related to vascular compromise. All infants were found unresponsive (3 in unsafe sleeping conditions); all but 1 had recent rhinitis and/or influenza-like illness (ILI) in the family; 1 had history of sickle cell disease. Ex vivo neuroimaging in 1 case revealed white matter (WM) signal hyperintensity and diffuse exaggeration of perivascular spaces, corresponding microscopically to WM mineralization. Neurohistology in the remaining 3 infants variably encompassed WM gliosis and mineralization; brainstem gliosis; perivascular vacuolization; perivascular lymphocytes and brainstem microglia. One had ectopic hippocampal neurons (with pathogenic variant in DEPDC5). Among the children, 3 had underlying conditions (e.g., obesity, metabolic disease, autism) and all presented with ILI. Three had laboratory testing suggesting multisystem inflammatory syndrome (MIS-C). Two were hospitalized for critical care including mechanical ventilation and extracorporeal membrane oxygenation (ECMO); one (co-infected with adenovirus) developed right carotid stroke ipsilateral to the ECMO cannula and the other required surgery for an ingested foreign body. Autopsy findings included: acute lung injury in 3 (1 with microthrombi); and one each with diabetic ketoacidosis and cardiac hypertrophy; coronary and cerebral arteritis and aortitis, resembling Kawasaki disease; and neuronal storage and enlarged fatty liver. All 4 children had subtle meningoencephalitis, focally involving the brainstem. On ex vivo neuroimaging, 1 had focal pontine susceptibility with corresponding perivascular inflammation/expanded perivascular spaces on histopathology. Results suggest SARS-CoV-2 in infants may present as sudden unexpected infant death, while in older children, signs and symptoms point to severe disease. Underlying conditions may predispose to fatal outcomes. As in adults, the neuropathologic changes may be subtle, with vascular changes such as perivascular vacuolization and gliosis alongside sparse perivascular lymphocytes. Detection of subtle vascular pathology is enhanced by ex vivo neuroimaging. Additional analysis of the peripheral/autonomic nervous system and investigation of co-infection in children with COVID-19 is necessary to understand risk for cardiovascular collapse/sudden death.
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Affiliation(s)
- Michelle N. Stram
- Office of Chief Medical Examiner, New York, NY, United States
- Department of Forensic Medicine, New York University Grossman School of Medicine, New York, NY, United States
| | - Alan C. Seifert
- Department of Diagnostic, Molecular and Interventional Radiology, Biomedical Engineering and Imaging Institute, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Etty Cortes
- Department of Pathology, Molecular and Cell Based Medicine, Mount Sinai Hospital, New York, NY, United States
- Neuropathology Brain Bank & Research Center of Research Excellence (CoRE), Mount Sinai Hospital, New York, NY, United States
| | - Alara Akyatan
- University of New England College of Medicine, Biddeford, ME, United States
| | - Emma Woodoff-Leith
- Department of Pathology, Molecular and Cell Based Medicine, Mount Sinai Hospital, New York, NY, United States
- Neuropathology Brain Bank & Research Center of Research Excellence (CoRE), Mount Sinai Hospital, New York, NY, United States
| | - Valeriy Borukhov
- Department of Pathology, Molecular and Cell Based Medicine, Mount Sinai Hospital, New York, NY, United States
- Neuropathology Brain Bank & Research Center of Research Excellence (CoRE), Mount Sinai Hospital, New York, NY, United States
| | - Amber Tetlow
- Department of Pathology, Molecular and Cell Based Medicine, Mount Sinai Hospital, New York, NY, United States
- Neuropathology Brain Bank & Research Center of Research Excellence (CoRE), Mount Sinai Hospital, New York, NY, United States
| | - Dimath Alyemni
- Office of Chief Medical Examiner, New York, NY, United States
- Department of Forensic Medicine, New York University Grossman School of Medicine, New York, NY, United States
| | - Michael Greenberg
- Office of Chief Medical Examiner, New York, NY, United States
- Department of Forensic Medicine, New York University Grossman School of Medicine, New York, NY, United States
| | - Avneesh Gupta
- Office of Chief Medical Examiner, New York, NY, United States
- Department of Forensic Medicine, New York University Grossman School of Medicine, New York, NY, United States
| | - Amanda Krausert
- Department of Pathology, Molecular and Cell Based Medicine, Mount Sinai Hospital, New York, NY, United States
| | - Lauren Mecca
- Office of Chief Medical Examiner, New York, NY, United States
- Department of Forensic Medicine, New York University Grossman School of Medicine, New York, NY, United States
| | - Sophia Rodriguez
- Office of the Medical Investigator, Albuquerque, NM, United States
| | - Jay Stahl-Herz
- Office of Chief Medical Examiner, New York, NY, United States
- Department of Forensic Medicine, New York University Grossman School of Medicine, New York, NY, United States
| | - Miguel A. Guzman
- Department of Pathology at Saint Louis University School of Medicine, SSM Cardinal Glennon Hospital, St. Louis, MO, United States
| | - Bradley Delman
- Department of Diagnostic, Molecular and Interventional Radiology, Biomedical Engineering and Imaging Institute, Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - John F. Crary
- Department of Pathology, Molecular and Cell Based Medicine, Mount Sinai Hospital, New York, NY, United States
- Neuropathology Brain Bank & Research Center of Research Excellence (CoRE), Mount Sinai Hospital, New York, NY, United States
| | - Kristen Dams-O'Connor
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY, United States
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Rebecca D. Folkerth
- Office of Chief Medical Examiner, New York, NY, United States
- Department of Forensic Medicine, New York University Grossman School of Medicine, New York, NY, United States
- *Correspondence: Rebecca D. Folkerth
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15
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Tendler BC, Hanayik T, Ansorge O, Bangerter-Christensen S, Berns GS, Bertelsen MF, Bryant KL, Foxley S, van den Heuvel MP, Howard AFD, Huszar IN, Khrapitchev AA, Leonte A, Manger PR, Menke RAL, Mollink J, Mortimer D, Pallebage-Gamarallage M, Roumazeilles L, Sallet J, Scholtens LH, Scott C, Smart A, Turner MR, Wang C, Jbabdi S, Mars RB, Miller KL. The Digital Brain Bank, an open access platform for post-mortem imaging datasets. eLife 2022; 11:e73153. [PMID: 35297760 PMCID: PMC9042233 DOI: 10.7554/elife.73153] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
Abstract
Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes-Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.
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Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Taylor Hanayik
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Olaf Ansorge
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sarah Bangerter-Christensen
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | | | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen ZooFrederiksbergDenmark
| | - Katherine L Bryant
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sean Foxley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Department of Radiology, University of ChicagoChicagoUnited States
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
- Department of Child Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Amy FD Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Alexandre A Khrapitchev
- Medical Research Council Oxford Institute for Radiation Oncology, University of OxfordOxfordUnited Kingdom
| | - Anna Leonte
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Paul R Manger
- School of Anatomical Sciences, Faculty of Health Sciences, University of the WitwatersrandJohannesburgSouth Africa
| | - Ricarda AL Menke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Duncan Mortimer
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Menuka Pallebage-Gamarallage
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- Stem Cell and Brain Research Institute, Université Lyon 1, INSERMBronFrance
| | - Lianne H Scholtens
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Connor Scott
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Martin R Turner
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
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16
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Tisdall MD, Ohm DT, Lobrovich R, Das SR, Mizsei G, Prabhakaran K, Ittyerah R, Lim S, McMillan CT, Wolk DA, Gee J, Trojanowski JQ, Lee EB, Detre JA, Yushkevich P, Grossman M, Irwin DJ. Ex vivo MRI and histopathology detect novel iron-rich cortical inflammation in frontotemporal lobar degeneration with tau versus TDP-43 pathology. Neuroimage Clin 2022; 33:102913. [PMID: 34952351 PMCID: PMC8715243 DOI: 10.1016/j.nicl.2021.102913] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 10/28/2021] [Accepted: 12/08/2021] [Indexed: 02/08/2023]
Abstract
Comparative study of whole-hemisphere ex vivo T2*-weighted MRI and histopathology. Sample of FTLD-Tau and FTLD-TDP subtypes with reference to healthy and AD brain. Novel focal upper cortical-layer iron-rich pathology distinguishes FTLD-TDP from clinically-similar FTLD-Tau and AD. Distinct novel iron-rich FTLD-Tau pathology in mid-to-deep cortical-layers and WM. T2*-weighted MRI signatures offer in vivo biomarker targets for FTLD proteinopathy.
Frontotemporal lobar degeneration (FTLD) is a heterogeneous spectrum of age-associated neurodegenerative diseases that include two main pathologic categories of tau (FTLD-Tau) and TDP-43 (FTLD-TDP) proteinopathies. These distinct proteinopathies are often clinically indistinguishable during life, posing a major obstacle for diagnosis and emerging therapeutic trials tailored to disease-specific mechanisms. Moreover, MRI-derived measures have had limited success to date discriminating between FTLD-Tau or FTLD-TDP. T2*-weighted (T2*w) ex vivo MRI has previously been shown to be sensitive to non-heme iron in healthy intracortical lamination and myelin, and to pathological iron deposits in amyloid-beta plaques and activated microglia in Alzheimer’s disease neuropathologic change (ADNC). However, an integrated, ex vivo MRI and histopathology approach is understudied in FTLD. We apply joint, whole-hemisphere ex vivo MRI at 7 T and histopathology to the study autopsy-confirmed FTLD-Tau (n = 4) and FTLD-TDP (n = 3), relative to ADNC disease-control brains with antemortem clinical symptoms of frontotemporal dementia (n = 2), and an age-matched healthy control. We detect distinct laminar patterns of novel iron-laden glial pathology in both FTLD-Tau and FTLD-TDP brains. We find iron-positive ameboid and hypertrophic microglia and astrocytes largely in deeper GM and adjacent WM in FTLD-Tau. In contrast, FTLD-TDP presents prominent superficial cortical layer iron reactivity in astrocytic processes enveloping small blood vessels with limited involvement of adjacent WM, as well as more diffuse distribution of punctate iron-rich dystrophic microglial processes across all GM lamina. This integrated MRI/histopathology approach reveals ex vivo MRI features that are consistent with these pathological observations distinguishing FTLD-Tau and FTLD-TDP subtypes, including prominent irregular hypointense signal in deeper cortex in FTLD-Tau whereas FTLD-TDP showed upper cortical layer hypointense bands and diffuse cortical speckling. Moreover, differences in adjacent WM degeneration and iron-rich gliosis on histology between FTLD-Tau and FTLD-TDP were also readily apparent on MRI as hyperintense signal and irregular areas of hypointensity, respectively that were more prominent in FTLD-Tau compared to FTLD-TDP. These unique histopathological and radiographic features were distinct from healthy control and ADNC brains, suggesting that iron-sensitive T2*w MRI, adapted to in vivo application at sufficient resolution, may eventually offer an opportunity to improve antemortem diagnosis of FTLD proteinopathies using tissue-validated methods.
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Affiliation(s)
- M Dylan Tisdall
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States.
| | - Daniel T Ohm
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Rebecca Lobrovich
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Sandhitsu R Das
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Gabor Mizsei
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Karthik Prabhakaran
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Ranjit Ittyerah
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Sydney Lim
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Corey T McMillan
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - David A Wolk
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - James Gee
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - John Q Trojanowski
- Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States
| | - Edward B Lee
- Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States
| | - John A Detre
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States; Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Paul Yushkevich
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Murray Grossman
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - David J Irwin
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States; Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States.
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17
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Donatelli G, Costagli M, Cecchi P, Migaleddu G, Bianchi F, Frumento P, Siciliano G, Cosottini M. Motor cortical patterns of upper motor neuron pathology in amyotrophic lateral sclerosis: A 3 T MRI study with iron-sensitive sequences. NEUROIMAGE: CLINICAL 2022; 35:103138. [PMID: 36002961 PMCID: PMC9421531 DOI: 10.1016/j.nicl.2022.103138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 07/05/2022] [Accepted: 07/27/2022] [Indexed: 11/11/2022] Open
Abstract
M1 regions associated with the body site of onset are frequently affected at MRI. The simultaneous involvement of both homologous M1 regions is frequent. The T2* hypointensity in non-contiguous M1 regions seems rare.
Background Patterns of initiation and propagation of disease in Amyotrophic Lateral Sclerosis (ALS) are still partly unknown. Single or multiple foci of neurodegeneration followed by disease diffusion to contiguous or connected regions have been proposed as mechanisms underlying symptom occurrence. Here, we investigated cortical patterns of upper motor neuron (UMN) pathology in ALS using iron-sensitive MR imaging. Methods Signal intensity and magnetic susceptibility of the primary motor cortex (M1), which are associated with clinical UMN burden and neuroinflammation, were assessed in 78 ALS patients using respectively T2*-weighted images and Quantitative Susceptibility Maps. The signal intensity of the whole M1 and each of its functional regions was rated as normal or reduced, and the magnetic susceptibility of each M1 region was measured. Results The highest frequencies of T2* hypointensity were found in M1 regions associated with the body sites of symptom onset. Homologous M1 regions were both hypointense in 80–93 % of patients with cortical abnormalities, and magnetic susceptibility values measured in homologous M1 regions were strongly correlated with each other (ρ = 0.88; p < 0.0001). In some cases, the T2* hypointensity was detectable in two non-contiguous M1 regions but spared the cortex in between. Conclusions M1 regions associated with the body site of onset are frequently affected at imaging. The simultaneous involvement of both homologous M1 regions is frequent, followed by that of adjacent regions; the affection of non-contiguous regions, instead, seems rare. This type of cortical involvement suggests the interhemispheric connections as one of the preferential paths for the UMN pathology diffusion in ALS.
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18
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McKenzie AT, Woodoff-Leith E, Dangoor D, Cervera A, Ressler HW, Whitney K, Dams-O'Connor K, Wu Z, Hillman EMC, Seifert AC, Crary JF. Ex situ perfusion fixation for brain banking: a technical report. FREE NEUROPATHOLOGY 2022; 3:3-22. [PMID: 37284166 PMCID: PMC10209847 DOI: 10.17879/freeneuropathology-2022-4368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 09/20/2022] [Indexed: 06/08/2023]
Abstract
Perfusion fixation is a well-established technique in animal research to improve preservation quality in the study of many tissues, including the brain. There is a growing interest in using perfusion to fix postmortem human brain tissue to achieve the highest fidelity preservation for downstream high-resolution morphomolecular brain mapping studies. Numerous practical barriers arise when applying perfusion fixation in brain banking settings, including the large mass of the organ, degradation of vascular integrity and patency prior to the start of the procedure, and differing investigator goals sometimes necessitating part of the brain to be frozen. As a result, there is a critical need to establish a perfusion fixation procedure in brain banking that is flexible and scalable. This technical report describes our approach to developing an ex situ perfusion fixation protocol. We discuss the challenges encountered and lessons learned while implementing this procedure. Routine morphological staining and RNA in situ hybridization data show that the perfused brains have well-preserved tissue cytoarchitecture and intact biomolecular signal. However, it remains uncertain whether this procedure leads to improved histology quality compared to immersion fixation. Additionally, ex vivo magnetic resonance imaging (MRI) data suggest that the perfusion fixation protocol may introduce imaging artifacts in the form of air bubbles in the vasculature. We conclude with further research directions to investigate the use of perfusion fixation as a rigorous and reproducible alternative to immersion fixation for the preparation of postmortem human brains.
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Affiliation(s)
- Andrew T. McKenzie
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Emma Woodoff-Leith
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Diana Dangoor
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Alessandra Cervera
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Hadley Walsh Ressler
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Kristen Whitney
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Kristen Dams-O'Connor
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Zhuhao Wu
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Cell, Developmental, and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Elizabeth M. C. Hillman
- Laboratory for Functional Optical Imaging, Departments of Biomedical Engineering and Radiology and the Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, New York, USA
| | - Alan C. Seifert
- Biomedical Engineering and Imaging Institute, Department of Diagnostic, Molecular and Interventional Radiology, and Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - John F. Crary
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Friedman Brain Institute, Departments of Pathology, Neuroscience, and Artificial Intelligence & Human Health, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Neuropathology Brain Bank & Research Core and Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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19
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Tendler BC, Qi F, Foxley S, Pallebage-Gamarallage M, Menke RAL, Ansorge O, Hurley SA, Miller KL. A method to remove the influence of fixative concentration on postmortem T 2 maps using a kinetic tensor model. Hum Brain Mapp 2021; 42:5956-5972. [PMID: 34541735 PMCID: PMC8596944 DOI: 10.1002/hbm.25661] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 08/06/2021] [Accepted: 08/30/2021] [Indexed: 12/20/2022] Open
Abstract
Formalin fixation has been shown to substantially reduce T2 estimates, primarily driven by the presence of fixative in tissue. Prior to scanning, post‐mortem samples are often placed into a fluid that has more favourable imaging properties. This study investigates whether there is evidence for a change in T2 in regions close to the tissue surface due to fixative outflux into this surrounding fluid. Furthermore, we investigate whether a simulated spatial map of fixative concentration can be used as a confound regressor to reduce T2 inhomogeneity. To achieve this, T2 maps and diffusion tensor estimates were obtained in 14 whole, formalin‐fixed post‐mortem brains placed in Fluorinert approximately 48 hr prior to scanning. Seven brains were fixed with 10% formalin and seven brains were fixed with 10% neutral buffered formalin (NBF). Fixative outflux was modelled using a proposed kinetic tensor (KT) model, which incorporates voxelwise diffusion tensor estimates to account for diffusion anisotropy and tissue‐specific diffusion coefficients. Brains fixed with 10% NBF revealed a spatial T2 pattern consistent with modelled fixative outflux. Confound regression of fixative concentration reduced T2 inhomogeneity across both white and grey matter, with the greatest reduction attributed to the KT model versus simpler models of fixative outflux. No such effect was observed in brains fixed with 10% formalin. Correlations between the transverse relaxation rate R2 and ferritin/myelin proteolipid protein (PLP) histology lead to an increased similarity for the relationship between R2 and PLP for the two fixative types after KT correction.
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Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford
| | - Feng Qi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford
| | - Sean Foxley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford.,Department of Radiology, University of Chicago, Chicago, Illinois, USA
| | | | - Ricarda A L Menke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Samuel A Hurley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford.,Department of Radiology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford
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20
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Barton SK, Gregory JM, Selvaraj BT, McDade K, Henstridge CM, Spires-Jones TL, James OG, Mehta AR, Story D, Burr K, Magnani D, Isaacs AM, Smith C, Chandran S. Dysregulation in Subcellular Localization of Myelin Basic Protein mRNA Does Not Result in Altered Myelination in Amyotrophic Lateral Sclerosis. Front Neurosci 2021; 15:705306. [PMID: 34539336 PMCID: PMC8440970 DOI: 10.3389/fnins.2021.705306] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 07/23/2021] [Indexed: 11/13/2022] Open
Abstract
Pathological hallmarks of amyotrophic lateral sclerosis (ALS), including protein misfolding, are well established in oligodendrocytes. More recently, an RNA trafficking deficit of key myelin proteins has been suggested in oligodendrocytes in ALS but the extent to which this affects myelination and the relative contribution of this to disease pathogenesis is unclear. ALS autopsy research findings showing demyelination contrasts with the routine clinical-pathological workup of ALS cases where it is rare to see white matter abnormalities other than simple Wallerian degeneration secondary to widespread neuronal loss. To begin to address this apparent variance, we undertook a comprehensive evaluation of myelination at an RNA, protein and structural level using human pathological material from sporadic ALS patients, genetic ALS patients (harboring C9orf72 mutation) and age- and sex-matched non-neurological controls. We performed (i) quantitative spatial profiling of the mRNA transcript encoding myelin basic protein (MBP), (ii) quantification of MBP protein and (iii) the first quantitative structural assessment of myelination in ALS post-mortem specimens by electron microscopy. We show no differences in MBP protein levels or ultrastructural myelination, despite a significant dysregulation in the subcellular trafficking of MBP mRNA in ALS patients compared to controls. We therefore confirm that whilst there are cell autonomous mRNA trafficking deficits affecting oligodendrocytes in ALS, this has no effect on myelin structure.
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Affiliation(s)
- Samantha K. Barton
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Jenna M. Gregory
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Bhuvaneish T. Selvaraj
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Karina McDade
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Christopher M. Henstridge
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Discovery Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Tara L. Spires-Jones
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Discovery Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Owen G. James
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Arpan R. Mehta
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - David Story
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Karen Burr
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Dario Magnani
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
| | - Adrian M. Isaacs
- UK Dementia Research Institute at UCL, Faculty of Brain Sciences, University College London, London, United Kingdom
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Colin Smith
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Siddharthan Chandran
- Euan MacDonald Centre for MND Research, The University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, The University of Edinburgh, Edinburgh, United Kingdom
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21
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Düzel E, Costagli M, Donatelli G, Speck O, Cosottini M. Studying Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis with 7-T magnetic resonance. Eur Radiol Exp 2021; 5:36. [PMID: 34435242 PMCID: PMC8387546 DOI: 10.1186/s41747-021-00221-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 04/07/2021] [Indexed: 12/18/2022] Open
Abstract
Ultra-high-field (UHF) magnetic resonance (MR) scanners, that is, equipment operating at static magnetic field of 7 tesla (7 T) and above, enable the acquisition of data with greatly improved signal-to-noise ratio with respect to conventional MR systems (e.g., scanners operating at 1.5 T and 3 T). The change in tissue relaxation times at UHF offers the opportunity to improve tissue contrast and depict features that were previously inaccessible. These potential advantages come, however, at a cost: in the majority of UHF-MR clinical protocols, potential drawbacks may include signal inhomogeneity, geometrical distortions, artifacts introduced by patient respiration, cardiac cycle, and motion. This article reviews the 7 T MR literature reporting the recent studies on the most widespread neurodegenerative diseases: Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis.
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Affiliation(s)
- Emrah Düzel
- Otto-von-Guericke University Magdeburg, Magdeburg, Germany. .,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany. .,University College London, London, UK.
| | - Mauro Costagli
- IRCCS Stella Maris, Pisa, Italy.,University of Genoa, Genova, Italy
| | - Graziella Donatelli
- Fondazione Imago 7, Pisa, Italy.,Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
| | - Oliver Speck
- Otto-von-Guericke University Magdeburg, Magdeburg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Mirco Cosottini
- Azienda Ospedaliero Universitaria Pisana, Pisa, Italy.,University of Pisa, Pisa, Italy
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22
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Scholz A, Etzel R, May MW, Mahmutovic M, Tian Q, Ramos-Llordén G, Maffei C, Bilgiç B, Witzel T, Stockmann JP, Mekkaoui C, Wald LL, Huang SY, Yendiki A, Keil B. A 48-channel receive array coil for mesoscopic diffusion-weighted MRI of ex vivo human brain on the 3 T connectome scanner. Neuroimage 2021; 238:118256. [PMID: 34118399 PMCID: PMC8439104 DOI: 10.1016/j.neuroimage.2021.118256] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 06/04/2021] [Accepted: 06/07/2021] [Indexed: 12/14/2022] Open
Abstract
In vivo diffusion-weighted magnetic resonance imaging is limited in signal-to-noise-ratio (SNR) and acquisition time, which constrains spatial resolution to the macroscale regime. Ex vivo imaging, which allows for arbitrarily long scan times, is critical for exploring human brain structure in the mesoscale regime without loss of SNR. Standard head array coils designed for patients are sub-optimal for imaging ex vivo whole brain specimens. The goal of this work was to design and construct a 48-channel ex vivo whole brain array coil for high-resolution and high b-value diffusion-weighted imaging on a 3T Connectome scanner. The coil was validated with bench measurements and characterized by imaging metrics on an agar brain phantom and an ex vivo human brain sample. The two-segment coil former was constructed for a close fit to a whole human brain, with small receive elements distributed over the entire brain. Imaging tests including SNR and G-factor maps were compared to a 64-channel head coil designed for in vivo use. There was a 2.9-fold increase in SNR in the peripheral cortex and a 1.3-fold gain in the center when compared to the 64-channel head coil. The 48-channel ex vivo whole brain coil also decreases noise amplification in highly parallel imaging, allowing acceleration factors of approximately one unit higher for a given noise amplification level. The acquired diffusion-weighted images in a whole ex vivo brain specimen demonstrate the applicability and advantage of the developed coil for high-resolution and high b-value diffusion-weighted ex vivo brain MRI studies.
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Affiliation(s)
- Alina Scholz
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany.
| | - Robin Etzel
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany
| | - Markus W May
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany
| | - Mirsad Mahmutovic
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany
| | - Qiyuan Tian
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Chiara Maffei
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Berkin Bilgiç
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Thomas Witzel
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Jason P Stockmann
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Choukri Mekkaoui
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Lawrence L Wald
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Susie Yi Huang
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Anastasia Yendiki
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany; Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
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23
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Li Hi Shing S, McKenna MC, Siah WF, Chipika RH, Hardiman O, Bede P. The imaging signature of C9orf72 hexanucleotide repeat expansions: implications for clinical trials and therapy development. Brain Imaging Behav 2021; 15:2693-2719. [PMID: 33398779 DOI: 10.1007/s11682-020-00429-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2020] [Indexed: 01/14/2023]
Abstract
While C9orf72-specific imaging signatures have been proposed by both ALS and FTD research groups and considerable presymptomatic alterations have also been confirmed in young mutation carriers, considerable inconsistencies exist in the literature. Accordingly, a systematic review of C9orf72-imaging studies has been performed to identify consensus findings, stereotyped shortcomings, and unique contributions to outline future directions. A formal literature review was conducted according to the STROBE guidelines. All identified papers were individually reviewed for sample size, choice of controls, study design, imaging modalities, statistical models, clinical profiling, and identified genotype-associated pathological patterns. A total of 74 imaging papers were systematically reviewed. ALS patients with GGGGCC repeat expansions exhibit relatively limited motor cortex involvement and widespread extra-motor pathology. C9orf72 positive FTD patients often show preferential posterior involvement. Reports of thalamic involvement are relatively consistent across the various phenotypes. Asymptomatic hexanucleotide repeat carriers often exhibit structural and functional changes decades prior to symptom onset. Common shortcomings included sample size limitations, lack of disease-controls, limited clinical profiling, lack of genetic testing in healthy controls, and absence of post mortem validation. There is a striking paucity of longitudinal studies and existing presymptomatic studies have not evaluated the predictive value of radiological changes with regard to age of onset and phenoconversion. With the advent of antisense oligonucleotide therapies, the meticulous characterisation of C9orf72-associated changes has gained practical relevance. Neuroimaging offers non-invasive biomarkers for future clinical trials, presymptomatic ascertainment, diagnostic and prognostic applications.
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Affiliation(s)
- Stacey Li Hi Shing
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Mary Clare McKenna
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - We Fong Siah
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Rangariroyashe H Chipika
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Orla Hardiman
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Peter Bede
- Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland.
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24
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Henmar S, Simonsen EB, Berg RW. What are the gray and white matter volumes of the human spinal cord? J Neurophysiol 2020; 124:1792-1797. [PMID: 33085549 DOI: 10.1152/jn.00413.2020] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
The gray matter of the spinal cord is the seat of somata of various types of neurons devoted to the sensory and motor activities of the limbs and trunk as well as a part of the autonomic nervous system. The volume of the spinal gray matter is an indicator of the local neuronal processing, and this can decrease due to atrophy associated with degenerative diseases and injury. Nevertheless, the absolute volume of the human spinal cord has rarely been reported, if ever. Here, we use high-resolution magnetic resonance imaging, with a cross-sectional resolution of 50 × 50 μm and a voxel size of 0.0005 mm3 to estimate the total gray and white matter volume of a post mortem human female spinal cord. Segregation of gray and white matter was accomplished using deep learning image segmentation. Furthermore, we include data from a male spinal cord of a previously published study. The gray and white matter volumes were found to be 2.87 and 11.33 mL, respectively, for the female and 3.55 and 19.33 mL, respectively, for the male. The gray and white matter profiles along the vertebral axis were found to be strikingly similar, and the volumes of the cervical, thoracic, and lumbosacral sections were almost equal.NEW & NOTEWORTHY Here, we combine high-field MRI (9.4 T) and deep learning for a post mortem reconstruction of the gray and white matter in human spinal cords. We report a minuscule total gray matter volume of 2.87 mL for a female and 3.55 mL for a male. For comparison, these volumes correspond approximately to the distal digit of the little finger.
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Affiliation(s)
- Simon Henmar
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Erik B Simonsen
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Rune W Berg
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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25
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Wang C, Foxley S, Ansorge O, Bangerter-Christensen S, Chiew M, Leonte A, Menke RA, Mollink J, Pallebage-Gamarallage M, Turner MR, Miller KL, Tendler BC. Methods for quantitative susceptibility and R2* mapping in whole post-mortem brains at 7T applied to amyotrophic lateral sclerosis. Neuroimage 2020; 222:117216. [PMID: 32745677 PMCID: PMC7775972 DOI: 10.1016/j.neuroimage.2020.117216] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Revised: 07/03/2020] [Accepted: 07/27/2020] [Indexed: 12/12/2022] Open
Abstract
Susceptibility weighted magnetic resonance imaging (MRI) is sensitive to the local concentration of iron and myelin. Here, we describe a robust image processing pipeline for quantitative susceptibility mapping (QSM) and R2* mapping of fixed post-mortem, whole-brain data. Using this pipeline, we compare the resulting quantitative maps in brains from patients with amyotrophic lateral sclerosis (ALS) and controls, with validation against iron and myelin histology. Twelve post-mortem brains were scanned with a multi-echo gradient echo sequence at 7T, from which susceptibility and R2* maps were generated. Semi-quantitative histological analysis for ferritin (the principal iron storage protein) and myelin proteolipid protein was performed in the primary motor, anterior cingulate and visual cortices. Magnetic susceptibility and R2* values in primary motor cortex were higher in ALS compared to control brains. Magnetic susceptibility and R2* showed positive correlations with both myelin and ferritin estimates from histology. Four out of nine ALS brains exhibited clearly visible hyperintense susceptibility and R2* values in the primary motor cortex. Our results demonstrate the potential for MRI-histology studies in whole, fixed post-mortem brains to investigate the biophysical source of susceptibility weighted MRI signals in neurodegenerative diseases like ALS.
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Affiliation(s)
- Chaoyue Wang
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, United Kingdom.
| | - Sean Foxley
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, United Kingdom; Department of Radiology, University of Chicago, United States
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom
| | - Sarah Bangerter-Christensen
- Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom; Brigham Young University, Provo, United States
| | - Mark Chiew
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, United Kingdom
| | - Anna Leonte
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, United Kingdom; University of Groningen,the Netherlands
| | - Ricarda Al Menke
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, United Kingdom
| | - Jeroen Mollink
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, United Kingdom; Department of Anatomy, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, the Netherlands
| | | | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom
| | - Karla L Miller
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, United Kingdom
| | - Benjamin C Tendler
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, United Kingdom
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26
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Tendler BC, Foxley S, Hernandez-Fernandez M, Cottaar M, Scott C, Ansorge O, Miller KL, Jbabdi S. Use of multi-flip angle measurements to account for transmit inhomogeneity and non-Gaussian diffusion in DW-SSFP. Neuroimage 2020; 220:117113. [PMID: 32621975 PMCID: PMC7573656 DOI: 10.1016/j.neuroimage.2020.117113] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 06/25/2020] [Accepted: 06/27/2020] [Indexed: 11/06/2022] Open
Abstract
Diffusion-weighted steady-state free precession (DW-SSFP) is an SNR-efficient diffusion imaging method. The improved SNR and resolution available at ultra-high field has motivated its use at 7T. However, these data tend to have severe B1 inhomogeneity, leading not only to spatially varying SNR, but also to spatially varying diffusivity estimates, confounding comparisons both between and within datasets. This study proposes the acquisition of DW-SSFP data at two-flip angles in combination with explicit modelling of non-Gaussian diffusion to address B1 inhomogeneity at 7T. Data were acquired from five fixed whole human post-mortem brains with a pair of flip angles that jointly optimize the diffusion contrast-to-noise (CNR) across the brain. We compared one- and two-flip angle DW-SSFP data using a tensor model that incorporates the full DW-SSFP Buxton signal, in addition to tractography performed over the cingulum bundle and pre-frontal cortex using a ball & sticks model. The two-flip angle DW-SSFP data produced angular uncertainty and tractography estimates close to the CNR optimal regions in the single-flip angle datasets. The two-flip angle tensor estimates were subsequently fitted using a modified DW-SSFP signal model that incorporates a gamma distribution of diffusivities. This allowed us to generate tensor maps at a single effective b-value yielding more consistent SNR across tissue, in addition to eliminating the B1 dependence on diffusion coefficients and orientation maps. Our proposed approach will allow the use of DW-SSFP at 7T to derive diffusivity estimates that have greater interpretability, both within a single dataset and between experiments.
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Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Sean Foxley
- Department of Radiology, University of Chicago, Chicago, IL, USA
| | | | - Michiel Cottaar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Connor Scott
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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27
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Mancini M, Casamitjana A, Peter L, Robinson E, Crampsie S, Thomas DL, Holton JL, Jaunmuktane Z, Iglesias JE. A multimodal computational pipeline for 3D histology of the human brain. Sci Rep 2020; 10:13839. [PMID: 32796937 PMCID: PMC7429828 DOI: 10.1038/s41598-020-69163-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 06/30/2020] [Indexed: 12/14/2022] Open
Abstract
Ex vivo imaging enables analysis of the human brain at a level of detail that is not possible in vivo with MRI. In particular, histology can be used to study brain tissue at the microscopic level, using a wide array of different stains that highlight different microanatomical features. Complementing MRI with histology has important applications in ex vivo atlas building and in modeling the link between microstructure and macroscopic MR signal. However, histology requires sectioning tissue, hence distorting its 3D structure, particularly in larger human samples. Here, we present an open-source computational pipeline to produce 3D consistent histology reconstructions of the human brain. The pipeline relies on a volumetric MRI scan that serves as undistorted reference, and on an intermediate imaging modality (blockface photography) that bridges the gap between MRI and histology. We present results on 3D histology reconstruction of whole human hemispheres from two donors.
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Affiliation(s)
- Matteo Mancini
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK.
- CUBRIC, Cardiff University, Cardiff, UK.
- NeuroPoly Lab, Polytechnique Montreal, Montreal, Canada.
| | - Adrià Casamitjana
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Loic Peter
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Eleanor Robinson
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Shauna Crampsie
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David L Thomas
- Neuroradiological Academic Unit, UCL Queen Square Institute of Neurology, University College London, London, UK
- Leonard Wolfson Experimental Neurology Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Janice L Holton
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Zane Jaunmuktane
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, MA, USA.
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28
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Barbone GE, Bravin A, Mittone A, Kraiger MJ, Hrabě de Angelis M, Bossi M, Ballarini E, Rodriguez-Menendez V, Ceresa C, Cavaletti G, Coan P. Establishing sample-preparation protocols for X-ray phase-contrast CT of rodent spinal cords: Aldehyde fixations and osmium impregnation. J Neurosci Methods 2020; 339:108744. [DOI: 10.1016/j.jneumeth.2020.108744] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 04/14/2020] [Accepted: 04/15/2020] [Indexed: 12/14/2022]
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29
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Müller HP, Del Tredici K, Lulé D, Müller K, Weishaupt JH, Ludolph AC, Kassubek J. In vivo histopathological staging in C9orf72-associated ALS: A tract of interest DTI study. Neuroimage Clin 2020; 27:102298. [PMID: 32505118 PMCID: PMC7270604 DOI: 10.1016/j.nicl.2020.102298] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 04/23/2020] [Accepted: 05/07/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Diffusion tensor imaging (DTI) can identify amyotrophic lateral sclerosis (ALS)-associated patterns of brain alterations at the group level according to a neuropathological staging system. OBJECTIVE The study was designed to investigate the in vivo staging in ALS patients with the C9orf72 expansion and potential differences to ALS patients with the SOD1 mutation. METHODS DTI-based white matter mapping was performed both by an unbiased voxel-wise statistical comparison and by a hypothesis-guided tract-wise analysis of fractional anisotropy (FA) maps according to the ALS-staging pattern for 27 ALS patients with C9orf72 expansion vs 15 ALS patients with SOD1 mutation vs 32 matched healthy controls. Clinical and neuropsychological data were acquired and correlated to DTI data. RESULTS The analysis of white matter integrity demonstrated regional FA reductions along the CST and also in frontal and prefrontal brain areas according to the proposed propagation pattern for the ALS patients with C9orf72 expansion and sporadic patients. This pattern could not be identified for the SOD1 mutation at the group level. In contrast, in the tract-specific analysis according to the neuropathological ALS-staging pattern, C9orf72 expansion ALS patients showed significant alterations of ALS-related tract systems similar to sporadic patients. CONCLUSIONS The DTI study including the tract-of-interest-based analysis showed a microstructural corticoefferent involvement pattern according to the staging scheme in C9orf72-associated ALS patients but not in the SOD1 mutation.
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Affiliation(s)
| | | | | | | | | | | | - Jan Kassubek
- Department of Neurology, University of Ulm, Germany.
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30
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Gabel MC, Broad RJ, Young AL, Abrahams S, Bastin ME, Menke RAL, Al‐Chalabi A, Goldstein LH, Tsermentseli S, Alexander DC, Turner MR, Leigh PN, Cercignani M. Evolution of white matter damage in amyotrophic lateral sclerosis. Ann Clin Transl Neurol 2020; 7:722-732. [PMID: 32367696 PMCID: PMC7261765 DOI: 10.1002/acn3.51035] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 03/16/2020] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE To characterize disease evolution in amyotrophic lateral sclerosis using an event-based model designed to extract temporal information from cross-sectional data. Conventional methods for understanding mechanisms of rapidly progressive neurodegenerative disorders are limited by the subjectivity inherent in the selection of a limited range of measurements, and the need to acquire longitudinal data. METHODS The event-based model characterizes a disease as a series of events, each comprising a significant change in subject state. The model was applied to data from 154 patients and 128 healthy controls selected from five independent diffusion MRI datasets acquired in four different imaging laboratories between 1999 and 2016. The biomarkers modeled were mean fractional anisotropy values of white matter tracts implicated in amyotrophic lateral sclerosis. The cerebral portion of the corticospinal tract was divided into three segments. RESULTS Application of the model to the pooled datasets revealed that the corticospinal tracts were involved before other white matter tracts. Distal corticospinal tract segments were involved earlier than more proximal (i.e., cephalad) segments. In addition, the model revealed early ordering of fractional anisotropy change in the corpus callosum and subsequently in long association fibers. INTERPRETATION These findings represent data-driven evidence for early involvement of the corticospinal tracts and body of the corpus callosum in keeping with conventional approaches to image analysis, while providing new evidence to inform directional degeneration of the corticospinal tracts. This data-driven model provides new insight into the dynamics of neuronal damage in amyotrophic lateral sclerosis.
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Affiliation(s)
- Matt C. Gabel
- Department of NeuroscienceClinical Imaging Sciences CentreBrighton and Sussex Medical SchoolUniversity of SussexBrightonEast SussexUnited Kingdom
| | - Rebecca J. Broad
- Department of NeuroscienceTrafford CentreBrighton and Sussex Medical SchoolUniversity of SussexBrightonEast SussexUnited Kingdom
| | - Alexandra L. Young
- Centre for Medical Image ComputingDepartment of Computer ScienceUniversity College LondonGower StreetLondonWC1E 6BTUnited Kingdom
| | - Sharon Abrahams
- Department of PsychologySchool of Philosophy, Psychology & Language SciencesEuan MacDonald Centre for Motor Neurone Disease ResearchUniversity of EdinburghEdinburghUnited Kingdom
| | - Mark E. Bastin
- Department of PsychologySchool of Philosophy, Psychology & Language SciencesEuan MacDonald Centre for Motor Neurone Disease ResearchUniversity of EdinburghEdinburghUnited Kingdom
| | - Ricarda A. L. Menke
- Wellcome Centre for Integrative NeuroimagingFMRIBNuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
| | - Ammar Al‐Chalabi
- Department of Basic and Clinical NeuroscienceKing's College LondonMaurice Wohl Clinical Neuroscience InstituteLondonUnited Kingdom
- Department of NeurologyKing’s College HospitalLondonUnited Kingdom
| | - Laura H. Goldstein
- Department of PsychologyInstitute of Psychiatry, Psychology, and NeuroscienceKing's College LondonLondonUnited Kingdom
| | | | - Daniel C. Alexander
- Centre for Medical Image ComputingDepartment of Computer ScienceUniversity College LondonGower StreetLondonWC1E 6BTUnited Kingdom
| | - Martin R. Turner
- Wellcome Centre for Integrative NeuroimagingFMRIBNuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
- Nuffield Department of Clinical NeurosciencesUniversity of OxfordOxfordUnited Kingdom
| | - P. Nigel Leigh
- Department of NeuroscienceTrafford CentreBrighton and Sussex Medical SchoolUniversity of SussexBrightonEast SussexUnited Kingdom
| | - Mara Cercignani
- Department of NeuroscienceClinical Imaging Sciences CentreBrighton and Sussex Medical SchoolUniversity of SussexBrightonEast SussexUnited Kingdom
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31
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Swash M, Burke D, Turner MR, Grosskreutz J, Leigh PN, deCarvalho M, Kiernan MC. Occasional essay: Upper motor neuron syndrome in amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry 2020; 91:227-234. [PMID: 32054724 DOI: 10.1136/jnnp-2019-321938] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 10/17/2019] [Accepted: 10/24/2019] [Indexed: 11/04/2022]
Affiliation(s)
- Michael Swash
- Barts and the London School of Medicine, QMUL, Instituto de Medicina Molecular, Faculdade de Medicina, Univeridade de Lisboa, London, UK
| | - David Burke
- University of Sydney and Department of Neurology, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Julian Grosskreutz
- Universitätsklinikum Jena, Friedrich-Schiller-University Jena, Jena, Germany
| | - P Nigel Leigh
- Trafford Centre for Biomedical Research, Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK
| | - Mamede deCarvalho
- Instituto de Fisiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Univeridade de Lisboa, and Department of Neurosciences and Mental Health, Hospital de Santa Maria, Centro Hospitalar Universitário de Lisboa Norte, Lisbon, Portugal
| | - Matthew C Kiernan
- University of Sydney and Department of Neurology, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia.,Neurology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
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32
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Donatelli G, Caldarazzo Ienco E, Costagli M, Migaleddu G, Cecchi P, Siciliano G, Cosottini M. MRI cortical feature of bulbar impairment in patients with amyotrophic lateral sclerosis. NEUROIMAGE-CLINICAL 2019; 24:101934. [PMID: 31377555 PMCID: PMC6698695 DOI: 10.1016/j.nicl.2019.101934] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 07/08/2019] [Accepted: 07/13/2019] [Indexed: 02/07/2023]
Abstract
The decline of voluntary bulbar functions such as speech and swallowing are among the clinical manifestations of amyotrophic lateral sclerosis (ALS) influencing a worst prognosis. Differential diagnosis between the contribution of upper motor neuron (UMN) and lower motor neuron degeneration to the bulbar impairment is often hard. Thinning and T2* hypointensity of the primary motor cortex have been recently suggested as possible MRI markers of UMN impairment in ALS patients, but little research has purposely targeted the orofacial region of the primary motor cortex (fM1). With the aim of finding an MRI marker of UMN impairment responsible for bulbar dysfunction, we investigated the T2* signal intensity of fM1 and the relationship with bulbar impairment in ALS patients. Fifty-five ALS patients were examined with 3 T MRI. Their fM1 was evaluated both qualitatively in terms of T2* signal intensity and quantitatively by measuring its magnetic susceptibility with Quantitative Susceptibility Mapping (QSM). Bulbar functions were assessed clinically, by neurological examination and using the items 1–3 of the ALSFRS-R, and with neurophysiological tests. The marked hypointensity of fM1 was detected in 25% of ALS patients, including all patients with bulbar onset, and was 74% sensitive, 100% specific and 91% accurate in diagnosing functional bulbar impairment. Such hypointensity involved the middle and ventral part of fM1 and was usually visible in both hemispheres. The magnetic susceptibility was significantly higher in patients with marked fM1 hypointensity than in the other patients (p ≤ .001). The relationship with clinical and neurophysiological data suggests that such feature could be a marker of UMN degeneration for voluntary bulbar functions. T2* hypointensity was assessed in the orofacial region of M1 (fM1) of ALS patients. All ALS patients with marked T2* hypointensity of fM1 had bulbar impairment (BI). The marked T2* hypointensity of fM1 was 91% accurate in diagnosing BI. fM1 hypointensity can be a marker of upper motor neuron degeneration causing BI.
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Affiliation(s)
- Graziella Donatelli
- Imago7 Research Foundation, Pisa, Italy; Neuroradiology Unit, Azienda Ospadaliero-Universitaria Pisana, Pisa, Italy
| | - Elena Caldarazzo Ienco
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Mauro Costagli
- Imago7 Research Foundation, Pisa, Italy; Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy.
| | - Gianmichele Migaleddu
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Paolo Cecchi
- Neuroradiology Unit, Azienda Ospadaliero-Universitaria Pisana, Pisa, Italy
| | - Gabriele Siciliano
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Mirco Cosottini
- Neuroradiology Unit, Azienda Ospadaliero-Universitaria Pisana, Pisa, Italy; Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
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33
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Bede P. The histological correlates of imaging metrics: postmortem validation of in vivo findings. Amyotroph Lateral Scler Frontotemporal Degener 2019; 20:457-460. [PMID: 31293187 DOI: 10.1080/21678421.2019.1639195] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Peter Bede
- Computational Neuroimaging Group, Trinity College Dublin , Dublin , Ireland
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34
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Querin G, Bede P, El Mendili MM, Li M, Pélégrini-Issac M, Rinaldi D, Catala M, Saracino D, Salachas F, Camuzat A, Marchand-Pauvert V, Cohen-Adad J, Colliot O, Le Ber I, Pradat PF. Presymptomatic spinal cord pathology in c9orf72 mutation carriers: A longitudinal neuroimaging study. Ann Neurol 2019; 86:158-167. [PMID: 31177556 DOI: 10.1002/ana.25520] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Revised: 06/03/2019] [Accepted: 06/06/2019] [Indexed: 12/11/2022]
Abstract
OBJECTIVE C9orf72 hexanucleotide repeats expansions account for almost half of familial amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) cases. Recent imaging studies in asymptomatic C9orf72 carriers have demonstrated cerebral white (WM) and gray matter (GM) degeneration before the age of 40 years. The objective of this study was to characterize cervical spinal cord (SC) changes in asymptomatic C9orf72 hexanucleotide carriers. METHODS Seventy-two asymptomatic individuals were enrolled in a prospective study of first-degree relatives of ALS and FTD patients carrying the c9orf72 hexanucleotide expansion. Forty of them carried the pathogenic mutation (C9+ ). Each subject underwent quantitative cervical cord imaging. Structural GM and WM metrics and diffusivity parameters were evaluated at baseline and 18 months later. Data were analyzed in C9+ and C9- subgroups, and C9+ subjects were further stratified by age. RESULTS At baseline, significant WM atrophy was detected at each cervical vertebral level in C9+ subjects older than 40 years without associated changes in GM and diffusion tensor imaging parameters. At 18-month follow-up, WM atrophy was accompanied by significant corticospinal tract (CST) fractional anisotropy (FA) reductions. Intriguingly, asymptomatic C9+ subjects older than 40 years with family history of ALS (as opposed to FTD) also exhibited significant CST FA reduction at baseline. INTERPRETATION Cervical SC imaging detects WM atrophy exclusively in C9+ subjects older than 40 years, and progressive CST FA reductions can be identified on 18-month follow-up. Cervical SC magnetic resonance imaging readily captures presymptomatic pathological changes and disease propagation in c9orf72-associated conditions. ANN NEUROL 2019;86:158-167.
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Affiliation(s)
- Giorgia Querin
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France.,Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Peter Bede
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France.,Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France.,Computational Neuroimaging Group, Academic Unit of Neurology, Trinity College Dublin, Dublin, Ireland
| | - Mohamed Mounir El Mendili
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France.,Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Menghan Li
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Mélanie Pélégrini-Issac
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Daisy Rinaldi
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France.,Reference Center for Rare or Early Dementia, Pitié-Salpêtrière Hospital, Paris, France
| | - Martin Catala
- Department of Neurology, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Sorbonne University, National Center for Scientific Research Mixed Unit of Research 7622, National Institute of Health and Medical Research Accademic Research Unit 1156, Biology Institute Paris-Seine, Paris, France
| | - Dario Saracino
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France
| | - François Salachas
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France
| | - Agnes Camuzat
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France
| | - Véronique Marchand-Pauvert
- Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France
| | - Julien Cohen-Adad
- NeuroPoly Laboratory, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Quebec, Canada.,Functional Neuroimaging Unit, Research Center of the University Institute of Geriatrics of Montreal, University of Montreal, Montreal, Quebec, Canada
| | - Olivier Colliot
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France.,Aramis Project Team, Inria Research Center of Paris, Paris, France.,Center for Image Acquisition and Processing, Brain and Spinal Cord Institute, Paris, France
| | - Isabelle Le Ber
- Brain and Spinal Cord Institute, Sorbonne University, National Institute of Health and Medical Research U1127, National Center for Scientific Research Mixed Unit of Research 7225, Pitié-Salpêtrière Hospital, Paris, France.,Reference Center for Rare or Early Dementia, Pitié-Salpêtrière Hospital, Paris, France.,Institute of Memory and Alzheimer's Disease, Center of Excellence of Neurodegenerative Disease, Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France
| | - Pierre-François Pradat
- Department of Neurology, SLA Reference Center, Pitié-Salpêtrière Hospital, Public Hospital Network of Paris, Paris, France.,Laboratory of Biomedical Imaging, National Center for Scientific Research, National Institute of Health and Medical Research, Sorbonne University, Paris, France.,Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute, Ulster University, Clinical-Translational Research and Innovation Center, Altnagelvin Hospital, Londonderry, United Kingdom
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Ndayisaba A, Kaindlstorfer C, Wenning GK. Iron in Neurodegeneration - Cause or Consequence? Front Neurosci 2019; 13:180. [PMID: 30881284 PMCID: PMC6405645 DOI: 10.3389/fnins.2019.00180] [Citation(s) in RCA: 173] [Impact Index Per Article: 34.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 02/14/2019] [Indexed: 12/12/2022] Open
Abstract
Iron dyshomeostasis can cause neuronal damage to iron-sensitive brain regions. Neurodegeneration with brain iron accumulation reflects a group of disorders caused by iron overload in the basal ganglia. High iron levels and iron related pathogenic triggers have also been implicated in sporadic neurodegenerative diseases including Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple system atrophy (MSA). Iron-induced dyshomeostasis within vulnerable brain regions is still insufficiently understood. Here, we summarize the modes of action by which iron might act as primary or secondary disease trigger in neurodegenerative disorders. In addition, available treatment options targeting brain iron dysregulation and the use of iron as biomarker in prodromal stages are critically discussed to address the question of cause or consequence.
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Affiliation(s)
- Alain Ndayisaba
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Gregor K Wenning
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
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Sébille SB, Rolland AS, Welter ML, Bardinet E, Santin MD. Post mortem high resolution diffusion MRI for large specimen imaging at 11.7 T with 3D segmented echo-planar imaging. J Neurosci Methods 2019; 311:222-234. [PMID: 30321565 DOI: 10.1016/j.jneumeth.2018.10.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Revised: 10/09/2018] [Accepted: 10/10/2018] [Indexed: 11/25/2022]
Abstract
BACKGROUND Diffusion weighted imaging (DWI) is the only in vivo technique allowing for the mapping of tissue fiber architecture. Post mortem DWI is an increasingly popular method, since longer acquisition times (compared to in vivo) allow higher spatial and angular resolutions to be achieved. However, DWI protocols must be adapted to post mortem tissue (e.g., tuning acquisition parameters to account for changes in T1/T2). New method: In this work, we developed a framework to obtain high quality diffusion weighted images on post mortem large samples by using a combination of fast imaging with 3D diffusion-weighted segmented EPI (3D-DW seg-EPI), Gadolinium soaking and data denoising. Analyses including tractography were used to check the quality of the acquired data, including a comparison with 3D-DW SE acquisitions. Comparison with existing method: Effects on diffusion data of each of the components of the framework were tested: 3D-DW seg-EPI versus 3D-DW SE EPI; with and without data denoising; with and without Gd-soaking. CONCLUSIONS Our study demonstrated the feasibility of analysing anatomical connectivity using diffusion imaging of a post mortem macaque brain with a 3D-DW seg-EPI sequence acquired at ultra-high field. The combination of high angular and spatial resolution DWI with Gd-soaking and denoising provided data allowing us to perform diffusion tractography with results very similar to those obtained with a 3D-DW SE acquisition (with shorter acquisition times: 222 h versus 37 h for 3D-DW seg-EPI).
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Affiliation(s)
- Sophie Bernadette Sébille
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, APHP GH Pitié-Salpêtrière, Institut du cerveau et de la moelle épinière (ICM), F-75013 Paris, France; Centre de Neuro-Imagerie de Recherche (CENIR), Paris, France
| | - Anne-Sophie Rolland
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, APHP GH Pitié-Salpêtrière, Institut du cerveau et de la moelle épinière (ICM), F-75013 Paris, France
| | - Marie-Laure Welter
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, APHP GH Pitié-Salpêtrière, Institut du cerveau et de la moelle épinière (ICM), F-75013 Paris, France
| | - Eric Bardinet
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, APHP GH Pitié-Salpêtrière, Institut du cerveau et de la moelle épinière (ICM), F-75013 Paris, France; Centre de Neuro-Imagerie de Recherche (CENIR), Paris, France
| | - Mathieu David Santin
- Sorbonne Universités, UPMC Univ Paris 06, CNRS, INSERM, APHP GH Pitié-Salpêtrière, Institut du cerveau et de la moelle épinière (ICM), F-75013 Paris, France; Centre de Neuro-Imagerie de Recherche (CENIR), Paris, France.
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Theme 6 Tissue biomarkers. Amyotroph Lateral Scler Frontotemporal Degener 2018; 19:198-216. [DOI: 10.1080/21678421.2018.1510573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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Gatto RG, Amin MY, Deyoung D, Hey M, Mareci TH, Magin RL. Ultra-High Field Diffusion MRI Reveals Early Axonal Pathology in Spinal Cord of ALS mice. Transl Neurodegener 2018; 7:20. [PMID: 30128146 PMCID: PMC6097419 DOI: 10.1186/s40035-018-0122-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 07/02/2018] [Indexed: 12/11/2022] Open
Abstract
Background Amyotrophic lateral sclerosis (ALS) is a disease characterized by a progressive degeneration of motor neurons leading to paralysis. Our previous MRI diffusion tensor imaging studies detected early white matter changes in the spinal cords of mice carrying the G93A-SOD1 mutation. Here, we extend those studies using ultra-high field MRI (17.6 T) and fluorescent microscopy to investigate the appearance of early structural and connectivity changes in the spinal cords of ALS mice. Methods The spinal cords from presymptomatic and symptomatic mice (80 to 120 days of age) were scanned (ex-vivo) using diffusion-weighted MRI. The fractional anisotropy (FA), axial (AD) and radial (RD) diffusivities were calculated for axial slices from the thoracic, cervical and lumbar regions of the spinal cords. The diffusion parameters were compared with fluorescence microscopy and membrane cellular markers from the same tissue regions. Results At early stages of the disease (day 80) in the lumbar region, we found, a 19% decrease in FA, a 9% decrease in AD and a 35% increase in RD. Similar changes were observed in cervical and thoracic spinal cord regions. Differences between control and ALS mice groups at the symptomatic stages (day 120) were larger. Quantitative fluorescence microscopy at 80 days, demonstrated a 22% reduction in axonal area and a 22% increase in axonal density. Tractography and quantitative connectome analyses measured by edge weights showed a 52% decrease in the lumbar regions of the spinal cords of this ALS mice group. A significant increase in ADC (23.3%) in the ALS mice group was related to an increase in aquaporin markers. Conclusions These findings suggest that the combination of ultra-high field diffusion MRI with fluorescent ALS mice reporters is a useful approach to detect and characterize presymptomatic white matter micro-ultrastructural changes and axonal connectivity anomalies in ALS.
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Affiliation(s)
- Rodolfo G Gatto
- 1Department of Anatomy and Cell Biology, University of Illinois at Chicago, 808 S. Wood St. Rm 578 M/C 512, Chicago, IL 60612 USA
| | - Manish Y Amin
- 2Department of Physics, University of Florida, Gainesville, FL USA
| | - Daniel Deyoung
- 2Department of Physics, University of Florida, Gainesville, FL USA
| | - Matthew Hey
- 3Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL USA
| | - Thomas H Mareci
- 4Department of Biochemistry and Molecular Biology, University of Florida, Gainesville, FL USA
| | - Richard L Magin
- 5Department of Bioengineering, University of Illinois at Chicago, Chicago, IL USA
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