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Nair G, Sun R, Merkle H, Xu Q, Hoskin K, Bree K, Dodd S, Koretsky AP. A method to image brain tissue frozen at autopsy. Neuroimage 2024; 296:120680. [PMID: 38857819 PMCID: PMC11220777 DOI: 10.1016/j.neuroimage.2024.120680] [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: 02/29/2024] [Revised: 06/04/2024] [Accepted: 06/07/2024] [Indexed: 06/12/2024] Open
Abstract
Magnetic Resonance Imaging (MRI) can provide the location and signal characteristics of pathological regions within a postmortem tissue block, thereby improving the efficiency of histopathological studies. However, such postmortem-MRI guided histopathological studies have so far only been performed on fixed samples as imaging tissue frozen at the time of extraction, while preserving its integrity, is significantly more challenging. Here we describe the development of cold-postmortem-MRI, which can preserve tissue integrity and help target techniques such as transcriptomics. As a first step, RNA integrity number (RIN) was used to determine the rate of tissue biomolecular degradation in mouse brains placed at various temperatures between -20 °C and +20 °C for up to 24 h. Then, human tissue frozen at the time of autopsy was immersed in 2-methylbutane, sealed in a bio-safe tissue chamber, and cooled in the MRI using a recirculating chiller to determine MRI signal characteristics. The optimal imaging temperature, which did not show significant RIN deterioration for over 12 h, at the same time giving robust MRI signal and contrast between brain tissue types was deemed to be -7 °C. Finally, MRI was performed on human tissue blocks at this optimal imaging temperatures using a magnetization-prepared rapid gradient echo (MPRAGE, isotropic resolution between 0.3-0.4 mm) revealing good gray-white matter contrast and revealing subpial, subcortical, and deep white matter lesions. RINs measured before and after imaging revealed no significant changes (n = 3, p = 0.18, paired t-test). In addition to improving efficiency of downstream processes, imaging tissue at sub-zero temperatures may also improve our understanding of compartment specificity of MRI signal.
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Affiliation(s)
- Govind Nair
- Quantitative MRI Core, National Institute of Neurological Disorders and Stroke, National Institutes of Health, 10 Center Dr, Bethesda, MD 20893, USA.
| | - Roy Sun
- Quantitative MRI Core, National Institute of Neurological Disorders and Stroke, National Institutes of Health, 10 Center Dr, Bethesda, MD 20893, USA
| | - Hellmut Merkle
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, USA
| | - Qing Xu
- Human Brain Collection Core, National Institute of Mental Health, National Institutes of Health, Bethesda, USA
| | - Kyra Hoskin
- Quantitative MRI Core, National Institute of Neurological Disorders and Stroke, National Institutes of Health, 10 Center Dr, Bethesda, MD 20893, USA
| | - Kendyl Bree
- Quantitative MRI Core, National Institute of Neurological Disorders and Stroke, National Institutes of Health, 10 Center Dr, Bethesda, MD 20893, USA
| | - Stephen Dodd
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, USA
| | - Alan P Koretsky
- Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, USA
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Sandgaard AD, Shemesh N, Østergaard L, Kiselev VG, Jespersen SN. The Larmor frequency shift of a white matter magnetic microstructure model with multiple sources. NMR IN BIOMEDICINE 2024; 37:e5150. [PMID: 38553824 DOI: 10.1002/nbm.5150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/15/2024] [Accepted: 02/28/2024] [Indexed: 07/11/2024]
Abstract
Magnetic susceptibility imaging may provide valuable information about chemical composition and microstructural organization of tissue. However, its estimation from the MRI signal phase is particularly difficult as it is sensitive to magnetic tissue properties ranging from the molecular to the macroscopic scale. The MRI Larmor frequency shift measured in white matter (WM) tissue depends on the myelinated axons and other magnetizable sources such as iron-filled ferritin. We have previously derived the Larmor frequency shift arising from a dense medium of cylinders with scalar susceptibility and arbitrary orientation dispersion. Here, we extend our model to include microscopic WM susceptibility anisotropy as well as spherical inclusions with scalar susceptibility to represent subcellular structures, biologically stored iron, and so forth. We validate our analytical results with computer simulations and investigate the feasibility of estimating susceptibility using simple iterative linear least squares without regularization or preconditioning. This is done in a digital brain phantom synthesized from diffusion MRI measurements of an ex vivo mouse brain at ultra-high field.
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Affiliation(s)
- Anders Dyhr Sandgaard
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Leif Østergaard
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Valerij G Kiselev
- Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | - Sune Nørhøj Jespersen
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
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3
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Shimozono T, Shiiba T, Takano K. Radiomics score derived from T1-w/T2-w ratio image can predict motor symptom progression in Parkinson's disease. Eur Radiol 2024:10.1007/s00330-024-10886-2. [PMID: 38958697 DOI: 10.1007/s00330-024-10886-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 04/08/2024] [Accepted: 04/26/2024] [Indexed: 07/04/2024]
Abstract
OBJECTIVES To clarify the association between a radiomics score (Rad-score) derived from T1-weighted signal intensity to T2-weighted signal intensity (T1-w/T2-w) ratio images and the progression of motor symptoms in Parkinson's disease (PD). MATERIALS AND METHODS This retrospective study included patients with PD enrolled in the Parkinson's Progression Markers Initiative. The Movement Disorders Society-Unified Parkinson's Disease Rating Scale Part III score ≥ 33 and/or Hoehn and Yahr stage ≥ 3 indicated motor function decline. The Rad-score was constructed using radiomics features extracted from T1-w/T2-w ratio images. The Kaplan-Meier analysis and Cox regression analyses were used to assess the time differences in motor function decline between the high and low Rad-score groups. RESULTS A total of 171 patients with PD were divided into training (n = 101, mean age at baseline, 61.6 ± 9.3 years) and testing (n = 70, mean age at baseline, 61.6 ± 10 years). The patients in the high Rad-score group had a shorter time to motor function decline than those in the low Rad-score group in the training dataset (log-rank test, p < 0.001) and testing dataset (log-rank test, p < 0.001). The multivariate Cox regression using the Rad-score and clinical factors revealed a significant association between the Rad-score and motor function decline in the training dataset (HR = 2.368, 95%CI:1.423-3.943, p < 0.001) and testing dataset (HR = 2.931, 95%CI:1.472-5.837, p = 0.002). CONCLUSION Rad-scores based on radiomics features derived from T1-w/T2-w ratio images were associated with the progression of motor symptoms in PD. CLINICAL RELEVANCE STATEMENT The radiomics score derived from the T1-weighted/T2-weighted ratio images offers a predictive tool for assessing the progression of motor symptom in patients with PD. KEY POINTS Radiomics score derived from T1-weighted/T2-weighted ratio images is correlated with the motor symptoms of Parkinson's disease. A high radiomics score correlated with faster motor function decline in patients with Parkinson's disease. The proposed radiomics score offers predictive insight into the progression of motor symptoms of Parkinson's disease.
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Affiliation(s)
- Takuya Shimozono
- Department of Neuroimaging and Brain Science, Major in Health Science, Graduate School of Health Sciences, Fujita Health University, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
| | - Takuro Shiiba
- Department of Molecular Imaging, Clinical Collaboration Unit, School of Medical Sciences, Fujita Health University, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan.
| | - Kazuki Takano
- Department of Molecular Imaging, Clinical Collaboration Unit, School of Medical Sciences, Fujita Health University, 1-98, Dengakugakubo, Kutsukake-cho, Toyoake, Aichi, 470-1192, Japan
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4
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Heij J, van der Zwaag W, Knapen T, Caan MWA, Forstman B, Veltman DJ, van Wingen G, Aghajani M. Quantitative MRI at 7-Tesla reveals novel frontocortical myeloarchitecture anomalies in major depressive disorder. Transl Psychiatry 2024; 14:262. [PMID: 38902245 PMCID: PMC11190139 DOI: 10.1038/s41398-024-02976-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 05/31/2024] [Accepted: 06/04/2024] [Indexed: 06/22/2024] Open
Abstract
Whereas meta-analytical data highlight abnormal frontocortical macrostructure (thickness/surface area/volume) in Major Depressive Disorder (MDD), the underlying microstructural processes remain uncharted, due to the use of conventional MRI scanners and acquisition techniques. We uniquely combined Ultra-High Field MRI at 7.0 Tesla with Quantitative Imaging to map intracortical myelin (proxied by longitudinal relaxation time T1) and iron concentration (proxied by transverse relaxation time T2*), microstructural processes deemed particularly germane to cortical macrostructure. Informed by meta-analytical evidence, we focused specifically on orbitofrontal and rostral anterior cingulate cortices among adult MDD patients (N = 48) and matched healthy controls (HC; N = 10). Analyses probed the association of MDD diagnosis and clinical profile (severity, medication use, comorbid anxiety disorders, childhood trauma) with aforementioned microstructural properties. MDD diagnosis (p's < 0.05, Cohen's D = 0.55-0.66) and symptom severity (p's < 0.01, r = 0.271-0.267) both related to decreased intracortical myelination (higher T1 values) within the lateral orbitofrontal cortex, a region tightly coupled to processing negative affect and feelings of sadness in MDD. No relations were found with local iron concentrations. These findings allow uniquely fine-grained insights on frontocortical microstructure in MDD, and cautiously point to intracortical demyelination as a possible driver of macroscale cortical disintegrity in MDD.
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Affiliation(s)
- Jurjen Heij
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Department of Computational Cognitive Neuroscience and Neuroimaging, NIN, Amsterdam, The Netherlands
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Wietske van der Zwaag
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Department of Computational Cognitive Neuroscience and Neuroimaging, NIN, Amsterdam, The Netherlands
| | - Tomas Knapen
- Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands
- Department of Computational Cognitive Neuroscience and Neuroimaging, NIN, Amsterdam, The Netherlands
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Matthan W A Caan
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Location University of Amsterdam, Amsterdam, The Netherlands
| | - Birte Forstman
- Department of Brain & Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Guido van Wingen
- Department of Psychiatry, Amsterdam UMC, Location University of Amsterdam, Amsterdam, The Netherlands
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
- Institute of Education and Child Studies, Section Forensic Family & Youth Care, Leiden University, Leiden, The Netherlands.
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Taleb S, Varela-Mattatall G, Allen A, Haast R, Khan AR, Kalia V, Howard JL, MacDonald SJ, Menon RS, Lanting BA, Teeter MG. Assessing brain integrity in patients with long-term and well-functioning metal-based hip implants. J Orthop Res 2024; 42:1292-1302. [PMID: 38235918 DOI: 10.1002/jor.25785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 12/08/2023] [Accepted: 01/03/2024] [Indexed: 01/19/2024]
Abstract
Production of metal debris from implant wear and corrosion processes is now a well understood occurrence following hip arthroplasty. Evidence has shown that metal ions can enter the bloodstream and travel to distant organs including the brain, and in extreme cases, can induce sensorial and neurological diseases. Our objective was tosimultaneously analyze brain anatomy and physiology in patients with long-term and well-functioning implants. Included were subjects who had received total hip or hip resurfacing arthroplastywith an implantation time of a minimum of 7 years (n = 28) and age- and sex-matched controls (n = 32). Blood samples were obtained to measure ion concentrations of cobalt and chromium, and the Montreal Cognitive Assessment was performed. 3T MRI brain scans were completed with an MPRAGE sequence for ROI segmentation and multiecho gradient echo sequences to generate QSM and R2* maps. Mean QSM and R2* values were recorded for five deep brain and four middle and cortical brain structures on both hemispheres: pallidum, putamen, caudate, amygdala, hippocampus, anterior cingulate, inferior temporal, and cerebellum. No differences in QSM or R2* or cognition scores were found between both groups (p > 0.6654). No correlation was found between susceptibility and blood ion levels for cobalt or chromium in any region of the brain. No correlation was found between blood ion levels and cognition scores. Clinical significance: Results suggest that metal ions released by long-term and well-functioning implants do not affect brain integrity.
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Affiliation(s)
- Shahnaz Taleb
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Gabriel Varela-Mattatall
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Abbigail Allen
- Department of Surgery, London Health Sciences Centre, Division of Orthopaedic Surgery, London, Ontario, Canada
| | - Roy Haast
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Ali R Khan
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Vishal Kalia
- Department of Medical Imaging, Schulich School of Medicine & Dentistry, Division of Musculoskeletal Imaging, Western University, London, Ontario, Canada
| | - James L Howard
- Department of Surgery, London Health Sciences Centre, Division of Orthopaedic Surgery, London, Ontario, Canada
| | - Steven J MacDonald
- Department of Surgery, London Health Sciences Centre, Division of Orthopaedic Surgery, London, Ontario, Canada
| | - Ravi S Menon
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
| | - Brent A Lanting
- Department of Surgery, London Health Sciences Centre, Division of Orthopaedic Surgery, London, Ontario, Canada
| | - Matthew G Teeter
- Schulich School of Medicine & Dentistry, Imaging Group, Robarts Research Institute, Western University, London, Ontario, Canada
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Kohli JS, Linke AC, Martindale IA, Wilkinson M, Kinnear MK, Lincoln AJ, Hau J, Shryock I, Omaleki V, Alemu K, Pedrahita S, Fishman I, Müller R, Carper RA. Associations between atypical intracortical myelin content and neuropsychological functions in middle to older aged adults with ASD. Brain Behav 2024; 14:e3594. [PMID: 38849980 PMCID: PMC11161394 DOI: 10.1002/brb3.3594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 05/06/2024] [Accepted: 05/23/2024] [Indexed: 06/09/2024] Open
Abstract
INTRODUCTION In vivo myeloarchitectonic mapping based on Magnetic Resonance Imaging (MRI) provides a unique view of gray matter myelin content and offers information complementary to other morphological indices commonly employed in studies of autism spectrum disorder (ASD). The current study sought to determine if intracortical myelin content (MC) and its age-related trajectories differ between middle aged to older adults with ASD and age-matched typical comparison participants. METHODS Data from 30 individuals with ASD and 36 age-matched typical comparison participants aged 40-70 years were analyzed. Given substantial heterogeneity in both etiology and outcomes in ASD, we utilized both group-level and subject-level analysis approaches to test for signs of atypical intracortical MC as estimated by T1w/T2w ratio. RESULTS Group-level analyses showed no significant differences in average T1w/T2w ratio or its associations with age between groups, but revealed significant positive main effects of age bilaterally, with T1w/T2w ratio increasing with age across much of the cortex. In subject-level analyses, participants were classified into subgroups based on presence or absence of clusters of aberrant T1w/T2w ratio, and lower neuropsychological function was observed in the ASD subgroup with atypically high T1w/T2w ratio in spatially heterogeneous cortical regions. These differences were observed across several neuropsychological domains, including overall intellectual functioning, processing speed, and aspects of executive function. CONCLUSIONS The group-level and subject-level approaches employed here demonstrate the value of examining inter-individual variability and provide important preliminary insights into relationships between brain structure and cognition in the second half of the lifespan in ASD, suggesting shared factors contributing to atypical intracortical myelin content and poorer cognitive outcomes for a subset of middle aged to older autistic adults. These atypicalities likely reflect diverse histories of neurodevelopmental deficits, and possible compensatory changes, compounded by processes of aging, and may serve as useful markers of vulnerability to further cognitive decline in older adults with ASD.
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Affiliation(s)
- Jiwandeep S. Kohli
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
- San Diego Joint Doctoral Program in Clinical PsychologySan Diego State University/University of CaliforniaSan DiegoCaliforniaUSA
| | - Annika C. Linke
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ian A. Martindale
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Molly Wilkinson
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
- San Diego Joint Doctoral Program in Clinical PsychologySan Diego State University/University of CaliforniaSan DiegoCaliforniaUSA
| | - Mikaela K. Kinnear
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Alan J. Lincoln
- California School of Professional PsychologyAlliant International UniversitySan DiegoCaliforniaUSA
| | - Janice Hau
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ian Shryock
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Vinton Omaleki
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Kalekirstos Alemu
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Stephanie Pedrahita
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Inna Fishman
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ralph‐Axel Müller
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
| | - Ruth A. Carper
- Brain Development Imaging Laboratories, Department of PsychologySan Diego State UniversitySan DiegoCaliforniaUSA
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Mueller SG. 7T MP2RAGE for cortical myelin segmentation: Impact of aging. PLoS One 2024; 19:e0299670. [PMID: 38626149 PMCID: PMC11020839 DOI: 10.1371/journal.pone.0299670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 02/14/2024] [Indexed: 04/18/2024] Open
Abstract
BACKGROUND Myelin and iron are major contributors to the cortical MR signal. The aim of this study was to investigate 1. Can MP2RAGE-derived contrasts at 7T in combination with k-means clustering be used to distinguish between heavily and sparsely myelinated layers in cortical gray matter (GM)? 2. Does this approach provide meaningful biological information? METHODS The following contrasts were generated from the 7T MP2RAGE images from 45 healthy controls (age: 19-75, f/m = 23/22) from the ATAG data repository: 1. T1 weighted image (UNI). 2. T1 relaxation image (T1map). 3. INVC/T1map ratio (RATIO). K-means clustering identified 6 clusters/tissue maps (csf, csf/gm-transition, wm, wm/gm transition, heavily myelinated cortical GM (dGM), sparsely myelinated cortical GM (sGM)). These tissue maps were then processed with SPM/DARTEL (volume-based analyses) and Freesurfer (surface-based analyses) and dGM and sGM volume/thickness of young adults (n = 27, 19-27 years) compared to those of older adults (n = 18, 42-75 years) at p<0.001 uncorrected. RESULTS The resulting maps showed good agreement with histological maps in the literature. Volume- and surface analyses found age-related dGM loss/thinning in the mid-posterior cingulate and parahippocampal/entorhinal gyrus and age-related sGM losses in lateral, mesial and orbitofrontal frontal, insular cortex and superior temporal gyrus. CONCLUSION The MP2RAGE derived UNI, T1map and RATIO contrasts can be used to identify dGM and sGM. Considering the close relationship between cortical myelo- and cytoarchitecture, the findings reported here indicate that this new technique might provide new insights into the nature of cortical GM loss in physiological and pathological conditions.
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Affiliation(s)
- Susanne G. Mueller
- Dept. of Radiology, University of California, San Francisco, San Francisco, CA, United States of America
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8
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Reiländer A, Engel M, Nöth U, Deichmann R, Shrestha M, Wagner M, Gracien RM, Seiler A. Cortical microstructural involvement in cerebral small vessel disease. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2024; 6:100218. [PMID: 38510580 PMCID: PMC10951897 DOI: 10.1016/j.cccb.2024.100218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/22/2024]
Abstract
Background In cerebral small vessel disease (CSVD), cortical atrophy occurs at a later stage compared to microstructural abnormalities and therefore cannot be used for monitoring short-term disease progression. We aimed to investigate whether cortical diffusion tensor imaging (DTI) and quantitative (q) magnetic resonance imaging (MRI) are able to detect early microstructural involvement of the cerebral cortex in CSVD. Materials and Methods 33 CSVD patients without significant cortical or whole-brain atrophy and 16 healthy control subjects were included and underwent structural MRI, DTI and high-resolution qMRI with T2, T2* and T2' mapping at 3 T as well as comprehensive cognitive assessment. After tissue segmentation and reconstruction of the cortical boundaries with the Freesurfer software, DTI and qMRI parameters were saved as surface datasets and averaged across all vertices. Results Cortical diffusivity and quantitative T2 values were significantly increased in patients compared to controls (p < 0.05). T2 values correlated significantly positively with white matter hyperintensity (WMH) volume (p < 0.01). Both cortical diffusivity and T2 showed significant negative associations with axonal damage to the white matter fiber tracts (p < 0.05). Conclusions Cortical diffusivity and quantitative T2 mapping are suitable to detect microstructural involvement of the cerebral cortex in CSVD and represent promising imaging biomarkers for monitoring disease progression and effects of therapeutical interventions in clinical studies.
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Affiliation(s)
- Annemarie Reiländer
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Marlene Engel
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Manoj Shrestha
- Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Marlies Wagner
- Brain Imaging Center, Goethe University, Frankfurt, Germany
- Institute of Neuroradiology, Goethe University Hospital, Frankfurt, Germany
| | - René-Maxime Gracien
- Department of Neurology, Goethe University Hospital, Frankfurt, Germany
- Brain Imaging Center, Goethe University, Frankfurt, Germany
| | - Alexander Seiler
- Brain Imaging Center, Goethe University, Frankfurt, Germany
- Department of Neurology, University Hospital Schleswig-Holstein, Kiel, Germany
- Neurovascular Center, University Hospital Schleswig-Holstein, Kiel, Germany
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9
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Sandgaard AD, Kiselev VG, Henriques RN, Shemesh N, Jespersen SN. Incorporating the effect of white matter microstructure in the estimation of magnetic susceptibility in ex vivo mouse brain. Magn Reson Med 2024; 91:699-715. [PMID: 37772624 DOI: 10.1002/mrm.29867] [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: 02/01/2023] [Revised: 08/07/2023] [Accepted: 08/25/2023] [Indexed: 09/30/2023]
Abstract
PURPOSE To extend quantitative susceptibility mapping to account for microstructure of white matter (WM) and demonstrate its effect on ex vivo mouse brain at 16.4T. THEORY AND METHODS Previous studies have shown that the MRI measured Larmor frequency also depends on local magnetic microstructure at the mesoscopic scale. Here, we include effects from WM microstructure using our previous results for the mesoscopic Larmor frequencyΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ of cylinders with arbitrary orientations. We scrutinize the validity of our model and QSM in a digital brain phantom includingΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ from a WM susceptibility tensor and biologically stored iron with scalar susceptibility. We also apply susceptibility tensor imaging to the phantom and investigate how the fitted tensors are biased fromΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ . Last, we demonstrate how to combine multi-gradient echo and diffusion MRI images of ex vivo mouse brains acquired at 16.4T to estimate an apparent scalar susceptibility without sample rotations. RESULTS Our new model improves susceptibility estimation compared to QSM for the brain phantom. Applying susceptibility tensor imaging to the phantom withΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ from WM axons with scalar susceptibility produces a highly anisotropic susceptibility tensor that mimics results from previous susceptibility tensor imaging studies. For the ex vivo mouse brain we find theΩ ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ due to WM microstructure to be substantial, changing susceptibility in WM up to 25% root-mean-squared-difference. CONCLUSION Ω ‾ Meso $$ {\overline{\Omega}}^{\mathrm{Meso}} $$ impacts susceptibility estimates and biases susceptibility tensor imaging fitting substantially. Hence, it should not be neglected when imaging structurally anisotropic tissue such as brain WM.
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Affiliation(s)
- Anders Dyhr Sandgaard
- Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Valerij G Kiselev
- Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | | | - Noam Shemesh
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Sune Nørhøj Jespersen
- Center for Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Physics and Astronomy, Aarhus University, Aarhus, Denmark
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10
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Merenstein JL, Zhao J, Overson DK, Truong TK, Johnson KG, Song AW, Madden DJ. Depth- and curvature-based quantitative susceptibility mapping analyses of cortical iron in Alzheimer's disease. Cereb Cortex 2024; 34:bhad525. [PMID: 38185996 PMCID: PMC10839848 DOI: 10.1093/cercor/bhad525] [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: 09/20/2023] [Revised: 11/21/2023] [Accepted: 12/15/2023] [Indexed: 01/09/2024] Open
Abstract
In addition to amyloid beta plaques and neurofibrillary tangles, Alzheimer's disease (AD) has been associated with elevated iron in deep gray matter nuclei using quantitative susceptibility mapping (QSM). However, only a few studies have examined cortical iron, using more macroscopic approaches that cannot assess layer-specific differences. Here, we conducted column-based QSM analyses to assess whether AD-related increases in cortical iron vary in relation to layer-specific differences in the type and density of neurons. We obtained global and regional measures of positive (iron) and negative (myelin, protein aggregation) susceptibility from 22 adults with AD and 22 demographically matched healthy controls. Depth-wise analyses indicated that global susceptibility increased from the pial surface to the gray/white matter boundary, with a larger slope for positive susceptibility in the left hemisphere for adults with AD than controls. Curvature-based analyses indicated larger global susceptibility for adults with AD versus controls; the right hemisphere versus left; and gyri versus sulci. Region-of-interest analyses identified similar depth- and curvature-specific group differences, especially for temporo-parietal regions. Finding that iron accumulates in a topographically heterogenous manner across the cortical mantle may help explain the profound cognitive deterioration that differentiates AD from the slowing of general motor processes in healthy aging.
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Affiliation(s)
- Jenna L Merenstein
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
| | - Jiayi Zhao
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
| | - Devon K Overson
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Medical Physics Graduate Program, Duke University, Durham, NC 27708, United States
| | - Trong-Kha Truong
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Medical Physics Graduate Program, Duke University, Durham, NC 27708, United States
| | - Kim G Johnson
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, United States
| | - Allen W Song
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Medical Physics Graduate Program, Duke University, Durham, NC 27708, United States
| | - David J Madden
- Brain Imaging and Analysis Center, Duke University Medical Center, Durham, NC 27710, United States
- Department of Psychiatry and Behavioral Sciences, Duke University Medical Center, Durham, NC 27710, United States
- Center for Cognitive Neuroscience, Duke University, Durham, NC 27708, United States
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11
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Nair G, Sun R, Merkle H, Hoskin K, Bree K, Dodd S, Koretsky A. Postmortem MRI of Tissue Frozen at Autopsy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.20.576456. [PMID: 38313300 PMCID: PMC10836069 DOI: 10.1101/2024.01.20.576456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2024]
Abstract
Introduction Postmortem MRI provides insight into location of pathology within tissue blocks, enabling efficient targeting of histopathological studies. While postmortem imaging of fixed tissue is gaining popularity, imaging tissue frozen at the time of extraction is significantly more challenging. Methods Tissue integrity was examined using RNA integrity number (RIN), in mouse brains placed between -20 °C and 20 °C for up to 24 hours, to determine the highest temperature that could potentially be used for imaging without tissue degeneration. Human tissue frozen at the time of autopsy was sealed in a tissue chamber filled with 2-methylbutane to prevent contamination of the MRI components. The tissue was cooled to a range of temperatures in a 9.4T MRI using a recirculating aqueous ethylene glycol solution. MRI was performed using a magnetization-prepared rapid gradient echo (MPRAGE) sequence with inversion time of 1400 ms to null the signal from 2-methylbutane bath, isotropic resolution between 0.3-0.4 mm, and scan time of about 4 hours was used to study the anatomical details of the tissue block. Results and Discussion A temperature of -7 °C was chosen for imaging as it was below the highest temperature that did not show significant RIN deterioration for over 12 hours, at the same time gave robust imaging signal and contrast between brain tissue types. Imaging performed on various human tissue blocks revealed good gray-white matter contrast and revealing subpial, subcortical, and deep white matter lesions typical of multiple sclerosis enabling further spatially targeted studies. Conclusion Here, we describe a new method to image cold tissue, while maintaining tissue integrity and biosafety during scanning. In addition to improving efficiency of downstream processes, imaging tissue at sub-zero temperatures may also improve our understanding of compartment specificity of MRI signal.
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Affiliation(s)
- Govind Nair
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Roy Sun
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Hellmut Merkle
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Kyra Hoskin
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Kendyl Bree
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Stephen Dodd
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
| | - Alan Koretsky
- National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda
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12
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Yee Y, Ellegood J, French L, Lerch JP. Organization of thalamocortical structural covariance and a corresponding 3D atlas of the mouse thalamus. Neuroimage 2024; 285:120453. [PMID: 37979895 DOI: 10.1016/j.neuroimage.2023.120453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 10/29/2023] [Accepted: 11/08/2023] [Indexed: 11/20/2023] Open
Abstract
For information from sensory organs to be processed by the brain, it is usually passed to appropriate areas of the cerebral cortex. Almost all of this information passes through the thalamus, a relay structure that reciprocally connects to the vast majority of the cortex. The thalamus facilitates this information transfer through a set of thalamocortical connections that vary in cellular structure, molecular profiles, innervation patterns, and firing rates. Additionally, corticothalamic connections allow for intracortical information transfer through the thalamus. These efferent and afferent connections between the thalamus and cortex have been the focus of many studies, and the importance of cortical connectivity in defining thalamus anatomy is demonstrated by multiple studies that parcellate the thalamus based on cortical connectivity profiles. Here, we examine correlated morphological variation between the thalamus and cortex, or thalamocortical structural covariance. For each voxel in the thalamus as a seed, we construct a cortical structural covariance map that represents correlated cortical volume variation, and examine whether high structural covariance is observed in cortical areas that are functionally relevant to the seed. Then, using these cortical structural covariance maps as features, we subdivide the thalamus into six non-overlapping regions (clusters of voxels), and assess whether cortical structural covariance is associated with cortical connectivity that specifically originates from these regions. We show that cortical structural covariance is high in areas of the cortex that are functionally related to the seed voxel, cortical structural covariance varies along cortical depth, and sharp transitions in cortical structural covariance profiles are observed when varying seed locations in the thalamus. Subdividing the thalamus based on structural covariance, we additionally demonstrate that the six thalamic clusters of voxels stratify cortical structural covariance along the dorsal-ventral, medial-lateral, and anterior-posterior axes. These cluster-associated structural covariance patterns are prominently detected in cortical regions innervated by fibers projecting out of their related thalamic subdivisions. Together, these results advance our understanding of how the thalamus and the cortex couple in their volumes. Our results indicate that these volume correlations reflect functional organization and structural connectivity, and further provides a novel segmentation of the mouse thalamus that can be used to examine thalamic structural variation and thalamocortical structural covariation in disease models.
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Affiliation(s)
- Yohan Yee
- Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada.
| | - Jacob Ellegood
- Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Canada
| | - Leon French
- Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Jason P Lerch
- Department of Medical Biophysics, University of Toronto, Toronto, Canada; Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
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13
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Raynaud Q, Di Domenicantonio G, Yerly J, Dardano T, van Heeswijk RB, Lutti A. A characterization of cardiac-induced noise in R 2 * maps of the brain. Magn Reson Med 2024; 91:237-251. [PMID: 37708206 DOI: 10.1002/mrm.29853] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 08/11/2023] [Accepted: 08/15/2023] [Indexed: 09/16/2023]
Abstract
PURPOSE Cardiac pulsation increases the noise level in brain maps of the transverse relaxation rate R2 *. Cardiac-induced noise is challenging to mitigate during the acquisition of R2 * mapping data because its characteristics are unknown. In this work, we aim to characterize cardiac-induced noise in brain maps of the MRI parameter R2 *. METHODS We designed a sampling strategy to acquire multi-echo 3D data in 12 intervals of the cardiac cycle, monitored with a fingertip pulse-oximeter. We measured the amplitude of cardiac-induced noise in this data and assessed the effect of cardiac pulsation on R2 * maps computed across echoes. The area of k-space that contains most of the cardiac-induced noise in R2 * maps was then identified. Based on these characteristics, we introduced a tentative sampling strategy that aims to mitigate cardiac-induced noise in R2 * maps of the brain. RESULTS In inferior brain regions, cardiac pulsation accounts for R2 * variations of up to 3 s-1 across the cardiac cycle (i.e., ∼35% of the overall variability). Cardiac-induced fluctuations occur throughout the cardiac cycle, with a reduced intensity during the first quarter of the cycle. A total of 50% to 60% of the overall cardiac-induced noise is localized near the k-space center (k < 0.074 mm-1 ). The tentative cardiac noise mitigation strategy reduced the variability of R2 * maps across repetitions by 11% in the brainstem and 6% across the whole brain. CONCLUSION We provide a characterization of cardiac-induced noise in brain R2 * maps that can be used as a basis for the design of mitigation strategies during data acquisition.
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Affiliation(s)
- Quentin Raynaud
- Laboratory for Research in Neuroimaging, Department for Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Giulia Di Domenicantonio
- Laboratory for Research in Neuroimaging, Department for Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Jérôme Yerly
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), Lausanne, Switzerland
| | - Thomas Dardano
- Laboratory for Research in Neuroimaging, Department for Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ruud B van Heeswijk
- Department of Diagnostic and Interventional Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department for Clinical Neuroscience, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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14
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Kruggel F, Solodkin A. Analyzing the cortical fine structure as revealed by ex-vivo anatomical MRI. J Comp Neurol 2023; 531:2146-2161. [PMID: 37522626 DOI: 10.1002/cne.25532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 04/15/2023] [Accepted: 06/21/2023] [Indexed: 08/01/2023]
Abstract
The human cortex has a rich fiber structure as revealed by myelin-staining of histological slices. Myelin also contributes to the image contrast in Magnetic Resonance Imaging (MRI). Recent advances in Magnetic Resonance (MR) scanner and imaging technology allowed the acquisition of an ex-vivo data set at an isotropic resolution of 100 µm. This study focused on a computational analysis of this data set with the aim of bridging between histological knowledge and MRI-based results. This work highlights: (1) the design and implementation of a processing chain that extracts intracortical features from a high-resolution MR image; (2) a demonstration of the correspondence between MRI-based cortical intensity profiles and the myelo-architectonic layering of the cortex; (3) the characterization and classification of four basic myelo-architectonic profile types; (4) the distinction of cortical regions based on myelo-architectonic features; and (5) the segmentation of cortical modules in the entorhinal cortex.
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Affiliation(s)
- Frithjof Kruggel
- Department of Biomedical Engineering, University of California, Irvine, Irvine, California, USA
| | - Ana Solodkin
- School of Behavioral and Brain Sciences, University of Texas, Richardson, Texas, USA
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15
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Ohm DT, Rhodes E, Bahena A, Capp N, Lowe M, Sabatini P, Trotman W, Olm CA, Phillips J, Prabhakaran K, Rascovsky K, Massimo L, McMillan C, Gee J, Tisdall MD, Yushkevich PA, Lee EB, Grossman M, Irwin DJ. Neuroanatomical and cellular degeneration associated with a social disorder characterized by new ritualistic belief systems in a TDP-C patient vs. a Pick patient. Front Neurol 2023; 14:1245886. [PMID: 37900607 PMCID: PMC10600461 DOI: 10.3389/fneur.2023.1245886] [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: 06/23/2023] [Accepted: 08/15/2023] [Indexed: 10/31/2023] Open
Abstract
Frontotemporal dementia (FTD) is a spectrum of clinically and pathologically heterogenous neurodegenerative dementias. Clinical and anatomical variants of FTD have been described and associated with underlying frontotemporal lobar degeneration (FTLD) pathology, including tauopathies (FTLD-tau) or TDP-43 proteinopathies (FTLD-TDP). FTD patients with predominant degeneration of anterior temporal cortices often develop a language disorder of semantic knowledge loss and/or a social disorder often characterized by compulsive rituals and belief systems corresponding to predominant left or right hemisphere involvement, respectively. The neural substrates of these complex social disorders remain unclear. Here, we present a comparative imaging and postmortem study of two patients, one with FTLD-TDP (subtype C) and one with FTLD-tau (subtype Pick disease), who both developed new rigid belief systems. The FTLD-TDP patient developed a complex set of values centered on positivity and associated with specific physical and behavioral features of pigs, while the FTLD-tau patient developed compulsive, goal-directed behaviors related to general themes of positivity and spirituality. Neuroimaging showed left-predominant temporal atrophy in the FTLD-TDP patient and right-predominant frontotemporal atrophy in the FTLD-tau patient. Consistent with antemortem cortical atrophy, histopathologic examinations revealed severe loss of neurons and myelin predominantly in the anterior temporal lobes of both patients, but the FTLD-tau patient showed more bilateral, dorsolateral involvement featuring greater pathology and loss of projection neurons and deep white matter. These findings highlight that the regions within and connected to anterior temporal lobes may have differential vulnerability to distinct FTLD proteinopathies and serve important roles in human belief systems.
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Affiliation(s)
- Daniel T. Ohm
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Emma Rhodes
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Alejandra Bahena
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Noah Capp
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - MaKayla Lowe
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Philip Sabatini
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Winifred Trotman
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Christopher A. Olm
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Jeffrey Phillips
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Karthik Prabhakaran
- Penn Image Computing and Science Lab, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Katya Rascovsky
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Lauren Massimo
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Corey McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - James Gee
- Penn Image Computing and Science Lab, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - M. Dylan Tisdall
- Center for Advanced Magnetic Resonance Imaging and Spectroscopy, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Paul A. Yushkevich
- Penn Image Computing and Science Lab, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Edward B. Lee
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - David J. Irwin
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
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16
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Kozel J, Školoudík D, Ressner P, Michalčová P, Dušek P, Hanzlíková P, Dvořáčková N, Heryán T, Bártová P. Echogenicity of Brain Structures in Huntington's Disease Patients Evaluated by Transcranial Sonography - Magnetic Resonance Fusion Imaging using Virtual Navigator and Digital Image Analysis. ULTRASCHALL IN DER MEDIZIN (STUTTGART, GERMANY : 1980) 2023; 44:495-502. [PMID: 37224875 DOI: 10.1055/a-2081-1635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
PURPOSE Transcranial sonography (TCS) magnetic resonance (MR) fusion imaging and digital image analysis are useful tools for the evaluation of various brain pathologies. This study aimed to compare the echogenicity of predefined brain structures in Huntington's disease (HD) patients and healthy controls by TCS-MR fusion imaging using Virtual Navigator and digitized image analysis. MATERIALS AND METHODS The echogenicity of the caudate nucleus (CN), substantia nigra (SN), lentiform nucleus (LN), insula, and brainstem raphe (BR) evaluated by TCS-MR fusion imaging using digitized image analysis was compared between 21 HD patients and 23 healthy controls. The cutoff values of echogenicity indices for the CN, LN, insula, and BR with optimal sensitivity and specificity were calculated using receiver operating characteristic analysis. RESULTS The mean echogenicity indices for the CN (67.0±22.6 vs. 37.9±7.6, p<0.0001), LN (110.7±23.6 vs. 59.7±11.1, p<0.0001), and insula (121.7±39.1 vs. 70.8±23.0, p<0.0001) were significantly higher in HD patients than in healthy controls. In contrast, BR echogenicity (24.8±5.3 vs. 30.1±5.3, p<0.001) was lower in HD patients than in healthy controls. The area under the curve was 90.9%, 95.5%, 84.1%, and 81.8% for the CN, LN, insula, and BR, respectively. The sensitivity and specificity were 86% and 96%, respectively, for the CN and 90% and 100%, respectively, for the LN. CONCLUSION Increased CN, LN, and insula echogenicity and decreased BR echogenicity are typical findings in HD patients. The high sensitivity and specificity of the CN and LN hyperechogenicity in TCS-MR fusion imaging make them promising diagnostic markers for HD.
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Affiliation(s)
- Jiří Kozel
- Center for Health Research, University of Ostrava Faculty of Medicine, Ostrava, Czech Republic
| | - David Školoudík
- Center for Health Research, University of Ostrava Faculty of Medicine, Ostrava, Czech Republic
| | - Pavel Ressner
- Neurology, Faculty of Medicine, Masaryk University and St. Anne's University Hospital, Brno, Czech Republic
| | - Patricie Michalčová
- Center for Health Research, University of Ostrava Faculty of Medicine, Ostrava, Czech Republic
| | - Petr Dušek
- Neurology, The First Faculty of Medicine, Charles University, Praha, Czech Republic
| | - Pavla Hanzlíková
- Radiodiagnostics, University Hospital Ostrava, Ostrava, Czech Republic
| | - Nina Dvořáčková
- Medical Genetics, University Hospital Ostrava, Ostrava, Czech Republic
| | - Tomáš Heryán
- Center for Health Research, University of Ostrava Faculty of Medicine, Ostrava, Czech Republic
| | - Petra Bártová
- Neurology, University Hospital Ostrava, Ostrava, Czech Republic
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17
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Corbin N, Oliveira R, Raynaud Q, Di Domenicantonio G, Draganski B, Kherif F, Callaghan MF, Lutti A. Statistical analyses of motion-corrupted MRI relaxometry data computed from multiple scans. J Neurosci Methods 2023; 398:109950. [PMID: 37598941 DOI: 10.1016/j.jneumeth.2023.109950] [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: 04/12/2023] [Revised: 05/30/2023] [Accepted: 08/12/2023] [Indexed: 08/22/2023]
Abstract
BACKGROUND Consistent noise variance across data points (i.e. homoscedasticity) is required to ensure the validity of statistical analyses of MRI data conducted using linear regression methods. However, head motion leads to degradation of image quality, introducing noise heteroscedasticity into ordinary-least square analyses. NEW METHOD The recently introduced QUIQI method restores noise homoscedasticity by means of weighted least square analyses in which the weights, specific for each dataset of an analysis, are computed from an index of motion-induced image quality degradation. QUIQI was first demonstrated in the context of brain maps of the MRI parameter R2 * , which were computed from a single set of images with variable echo time. Here, we extend this framework to quantitative maps of the MRI parameters R1, R2 * , and MTsat, computed from multiple sets of images. RESULTS QUIQI restores homoscedasticity in analyses of quantitative MRI data computed from multiple scans. QUIQI allows for optimization of the noise model by using metrics quantifying heteroscedasticity and free energy. COMPARISON WITH EXISTING METHODS QUIQI restores homoscedasticity more effectively than insertion of an image quality index in the analysis design and yields higher sensitivity than simply removing the datasets most corrupted by head motion from the analysis. CONCLUSION QUIQI provides an optimal approach to group-wise analyses of a range of quantitative MRI parameter maps that is robust to inherent homoscedasticity.
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Affiliation(s)
- Nadège Corbin
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/University Bordeaux, Bordeaux, France; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Rita Oliveira
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Quentin Raynaud
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Giulia Di Domenicantonio
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; Neurology Department, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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18
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Rocca MA, Margoni M, Battaglini M, Eshaghi A, Iliff J, Pagani E, Preziosa P, Storelli L, Taoka T, Valsasina P, Filippi M. Emerging Perspectives on MRI Application in Multiple Sclerosis: Moving from Pathophysiology to Clinical Practice. Radiology 2023; 307:e221512. [PMID: 37278626 PMCID: PMC10315528 DOI: 10.1148/radiol.221512] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 11/28/2022] [Accepted: 01/17/2023] [Indexed: 06/07/2023]
Abstract
MRI plays a central role in the diagnosis of multiple sclerosis (MS) and in the monitoring of disease course and treatment response. Advanced MRI techniques have shed light on MS biology and facilitated the search for neuroimaging markers that may be applicable in clinical practice. MRI has led to improvements in the accuracy of MS diagnosis and a deeper understanding of disease progression. This has also resulted in a plethora of potential MRI markers, the importance and validity of which remain to be proven. Here, five recent emerging perspectives arising from the use of MRI in MS, from pathophysiology to clinical application, will be discussed. These are the feasibility of noninvasive MRI-based approaches to measure glymphatic function and its impairment; T1-weighted to T2-weighted intensity ratio to quantify myelin content; classification of MS phenotypes based on their MRI features rather than on their clinical features; clinical relevance of gray matter atrophy versus white matter atrophy; and time-varying versus static resting-state functional connectivity in evaluating brain functional organization. These topics are critically discussed, which may guide future applications in the field.
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Affiliation(s)
- Maria Assunta Rocca
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Monica Margoni
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Marco Battaglini
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Arman Eshaghi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Jeffrey Iliff
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paolo Preziosa
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Loredana Storelli
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Toshiaki Taoka
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Paola Valsasina
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
| | - Massimo Filippi
- From the Neuroimaging Research Unit, Division of Neuroscience
(M.A.R., M.M., E.P., P.P., L.S., P.V., M.F.), Neurology Unit (M.A.R., M.M.,
P.P., M.F.), Neurorehabilitation Unit (M.F.), and Neurophysiology Service
(M.F.), IRCCS San Raffaele Scientific Institute, Via Olgettina 60, 20132 Milan,
Italy; Vita-Salute San Raffaele University, Milan, Italy (M.A.R., P.P., M.F.);
Department of Medicine, Surgery and Neuroscience, University of Siena, Siena,
Italy (M.B.); Queen Square Multiple Sclerosis Centre, Department of
Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain
Sciences, University College London, London, UK (A.E.); Centre for Medical Image
Computing, Department of Computer Science, University College London, London, UK
(A.E.); VISN20 NW Mental Illness Research, Education, and Clinical Center, VA
Puget Sound Healthcare System, Seattle, Wash (J.I.); Department of Psychiatry
and Behavioral Sciences and Department of Neurology, University of Washington
School of Medicine, Seattle, Wash (J.I.); and Department of Innovative
Biomedical Visualization (iBMV), Department of Radiology, Nagoya University
Graduate School of Medicine, Aichi, Japan (T.T.)
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19
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van Gelderen P, Li X, de Zwart JA, Beck ES, Okar SV, Huang Y, Lai K, Sulam J, van Zijl PCM, Reich DS, Duyn JH, Liu J. Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R 2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T. Neuroimage 2023; 270:119992. [PMID: 36858332 PMCID: PMC10278242 DOI: 10.1016/j.neuroimage.2023.119992] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 02/17/2023] [Accepted: 02/25/2023] [Indexed: 03/03/2023] Open
Abstract
MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.
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Affiliation(s)
- Peter van Gelderen
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Jacco A de Zwart
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Erin S Beck
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York City, NY, United States of America
| | - Serhat V Okar
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - KuoWei Lai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America; Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Daniel S Reich
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America.
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20
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Sandgaard AD, Shemesh N, Kiselev VG, Jespersen SN. Larmor frequency shift from magnetized cylinders with arbitrary orientation distribution. NMR IN BIOMEDICINE 2023; 36:e4859. [PMID: 36285793 PMCID: PMC10078263 DOI: 10.1002/nbm.4859] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 10/22/2022] [Accepted: 10/23/2022] [Indexed: 06/01/2023]
Abstract
The magnetic susceptibility of tissue can provide valuable information about its chemical composition and microstructural organization. However, the relation between the magnetic microstructure and the measurable Larmor frequency shift is understood only for a few idealized cases. Here we analyze the microstructure formed by magnetized, NMR-invisible infinite cylinders suspended in an NMR-reporting fluid. Through simulations, we scrutinize various geometries of mesoscopic Lorentz cavities and inclusions, and show that the cavity size should be approximately one order of magnitude larger than the width of the inclusions. We also analytically derive the Larmor frequency shift for a population of cylinders with arbitrary orientation dispersion and show that it is determined by the l = 2 Laplace expansion coefficients p 2 m of the cylinders' orientation distribution function. Our work underscores the need to account for microstructural organization when estimating magnetic tissue properties.
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Affiliation(s)
- Anders Dyhr Sandgaard
- Center for Functionally Integrative Neuroscience, Department of Clinical MedicineAarhus UniversityDenmark
| | - Noam Shemesh
- Champalimaud ResearchChampalimaud Centre for the UnknownLisbonPortugal
| | - Valerij G. Kiselev
- Division of Medical Physics, Department of RadiologyUniversity Medical Center FreiburgFreiburgGermany
| | - Sune Nørhøj Jespersen
- Center for Functionally Integrative Neuroscience, Department of Clinical MedicineAarhus UniversityDenmark
- Department of Physics and AstronomyAarhus UniversityDenmark
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21
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McKavanagh A, Ridzuan-Allen A, Kreilkamp BAK, Chen Y, Manjón JV, Coupé P, Bracewell M, Das K, Taylor PN, Marson AG, Keller SS. Midbrain structure volume, estimated myelin and functional connectivity in idiopathic generalised epilepsy. Epilepsy Behav 2023; 140:109084. [PMID: 36702054 DOI: 10.1016/j.yebeh.2023.109084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 01/01/2023] [Accepted: 01/01/2023] [Indexed: 01/26/2023]
Abstract
BACKGROUND Structural and functional neuroimaging studies often overlook lower basal ganglia structures located in and adjacent to the midbrain due to poor contrast on clinically acquired T1-weighted scans. Here, we acquired T1-weighted, T2-weighted, and resting-state fMRI scans to investigate differences in volume, estimated myelin content and functional connectivity of the substantia nigra (SN), subthalamic nuclei (SubTN) and red nuclei (RN) of the midbrain in IGE. METHODS Thirty-three patients with IGE (23 refractory, 10 non-refractory) and 39 age and sex-matched healthy controls underwent MR imaging. Midbrain structures were automatically segmented from T2-weighted images and structural volumes were calculated. The estimated myelin content for each structure was determined using a T1-weighted/T2-weighted ratio method. Resting-state functional connectivity analysis of midbrain structures (seed-based) was performed using the CONN toolbox. RESULTS An increased volume of the right RN was found in IGE and structural volumes of the right SubTN differed between patients with non-refractory and refractory IGE. However, no volume findings survived corrections for multiple comparisons. No myelin alterations of midbrain structures were found for any subject groups. We found functional connectivity alterations including significantly decreased connectivity between the left SN and the thalamus and significantly increased connectivity between the right SubTN and the superior frontal gyrus in IGE. CONCLUSIONS We report volumetric and functional connectivity alterations of the midbrain in patients with IGE. We postulate that potential increases in structural volumes are due to increased iron deposition that impacts T2-weighted contrast. These findings are consistent with previous studies demonstrating pathophysiological abnormalities of the lower basal ganglia in animal models of generalised epilepsy.
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Affiliation(s)
- Andrea McKavanagh
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; The Walton Centre NHS Foundation Trust, Liverpool, UK.
| | - Adam Ridzuan-Allen
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Barbara A K Kreilkamp
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; The Walton Centre NHS Foundation Trust, Liverpool, UK; Department of Neurology, University Medical Centre Göttingen, Göttingen, Germany
| | - Yachin Chen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital', United States
| | - José V Manjón
- Instituto de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas (ITACA), Universitat Politècnica de València, Valencia, Spain
| | - Pierrick Coupé
- Pictura Research Group, Unité Mixte de Recherche Centre National de la Recherche Scientifique (UMR 5800), Laboratoire Bordelais de Recherche en Informatique, Bordeaux, France
| | - Martyn Bracewell
- The Walton Centre NHS Foundation Trust, Liverpool, UK; Schools of Medical Sciences and Psychology, Bangor University, Bangor, UK
| | - Kumar Das
- The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Peter N Taylor
- Interdisciplinary Computing and Complex BioSystems Group, School of Computing Science, Newcastle University, UK
| | - Anthony G Marson
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; The Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Simon S Keller
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK; The Walton Centre NHS Foundation Trust, Liverpool, UK
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22
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Lee S, Shin HG, Kim M, Lee J. Depth-wise profiles of iron and myelin in the cortex and white matter using χ-separation: A preliminary study. Neuroimage 2023; 273:120058. [PMID: 36997135 DOI: 10.1016/j.neuroimage.2023.120058] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 03/26/2023] [Accepted: 03/27/2023] [Indexed: 03/30/2023] Open
Abstract
The in-vivo profiling of iron and myelin across cortical depths and underlying white matter has important implications for advancing knowledge about their roles in brain development and degeneration. Here, we utilize χ-separation, a recently-proposed advanced susceptibility mapping that creates positive (χpos) and negative (χneg) susceptibility maps, to generate the depth-wise profiles of χpos and χneg as surrogate biomarkers for iron and myelin, respectively. Two regional sulcal fundi of precentral and middle frontal areas are profiled and compared with findings from previous studies. The results show that the χpos profiles peak at superificial white matter (SWM), which is an area beneath cortical gray matter known to have the highest accumulation of iron within the cortex and white matter. On the other hand, the χneg profiles increase in SWM toward deeper white matter. These characteristics in the two profiles are in agreement with histological findings of iron and myelin. Furthermore, the χneg profiles report regional differences that agree with well-known distributions of myelin concentration. When the two profiles are compared with those of QSM and R2*, different shapes and peak locations are observed. This preliminary study offers an insight into one of the possible applications of χ-separation for exploring microstructural information of the human brain, as well as clinical applications in monitoring changes of iron and myelin in related diseases.
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23
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Paquola C, Hong SJ. The Potential of Myelin-Sensitive Imaging: Redefining Spatiotemporal Patterns of Myeloarchitecture. Biol Psychiatry 2023; 93:442-454. [PMID: 36481065 DOI: 10.1016/j.biopsych.2022.08.031] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/12/2022] [Accepted: 08/30/2022] [Indexed: 02/07/2023]
Abstract
Recent advances in magnetic resonance imaging (MRI) have paved the way for approximation of myelin content in vivo. In this review, our main goal was to determine how to best capitalize on myelin-sensitive imaging. First, we briefly overview the theoretical and empirical basis for the myelin sensitivity of different MRI markers and, in doing so, highlight how multimodal imaging approaches are important for enhancing specificity to myelin. Then, we discuss recent studies that have probed the nonuniform distribution of myelin across cortical layers and along white matter tracts. These approaches, collectively known as myelin profiling, have provided detailed depictions of myeloarchitecture in both the postmortem and living human brain. Notably, MRI-based profiling studies have recently focused on investigating whether it can capture interindividual variability in myelin characteristics as well as trajectories across the lifespan. Finally, another line of recent evidence emphasizes the contribution of region-specific myelination to large-scale organization, demonstrating the impact of myelination on global brain networks. In conclusion, we suggest that combining well-validated MRI markers with profiling techniques holds strong potential to elucidate individual differences in myeloarchitecture, which has important implications for understanding brain function and disease.
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Affiliation(s)
- Casey Paquola
- Institute of Neuroscience and Medicine, Forschungszentrum Jülich, Jülich, Germany.
| | - Seok-Jun Hong
- Center for Neuroscience Imaging Research, Institute for Basic Science, Sungkyunkwan University, Suwon, South Korea; Center for the Developing Brain, Child Mind Institute, New York, New York; Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
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24
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Balfourier A, Tsolaki E, Heeb L, Starsich FHL, Klose D, Boss A, Gupta A, Gogos A, Herrmann IK. Multiscale Multimodal Investigation of the Intratissural Biodistribution of Iron Nanotherapeutics with Single Cell Resolution Reveals Co-Localization with Endogenous Iron in Splenic Macrophages. SMALL METHODS 2023; 7:e2201061. [PMID: 36572638 DOI: 10.1002/smtd.202201061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 12/02/2022] [Indexed: 06/18/2023]
Abstract
Imaging of iron-based nanoparticles (NPs) remains challenging because of the presence of endogenous iron in tissues that is difficult to distinguish from exogenous iron originating from the NPs. Here, an analytical cascade for characterizing the biodistribution of biomedically relevant iron-based NPs from the organ scale to the cellular and subcellular scales is introduced. The biodistribution on an organ level is assessed by elemental analysis and quantification of magnetic iron by electron paramagnetic resonance, which allowed differentiation of exogenous and endogenous iron. Complementary to these bulk analysis techniques, correlative whole-slide optical and electron microscopy provided spatially resolved insight into the biodistribution of endo- and exogenous iron accumulation in macrophages, with single-cell and single-particle resolution, revealing coaccumulation of iron NPs with endogenous iron in splenic macrophages. Subsequent transmission electron microscopy revealed two types of morphologically distinct iron-containing structures (exogenous nanoparticles and endogenous ferritin) within membrane-bound vesicles in the cytoplasm, hinting at an attempt of splenic macrophages to extract and recycle iron from exogenous nanoparticles. Overall, this strategy enables the distinction of endo- and exogenous iron across scales (from cm to nm, based on the analysis of thousands of cells) and illustrates distribution on organ, cell, and organelle levels.
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Affiliation(s)
- Alice Balfourier
- Nanoparticle Systems Engineering Laboratory, Institute of Energy and Process Engineering (IEPE), Department of Mechanical and Process Engineering (D-MAVT), ETH Zurich, 8092, Zürich, Switzerland
- Particles-Biology Interactions Laboratory, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), 9014, St. Gallen, Switzerland
| | - Elena Tsolaki
- Nanoparticle Systems Engineering Laboratory, Institute of Energy and Process Engineering (IEPE), Department of Mechanical and Process Engineering (D-MAVT), ETH Zurich, 8092, Zürich, Switzerland
- Particles-Biology Interactions Laboratory, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), 9014, St. Gallen, Switzerland
| | - Laura Heeb
- Department of Visceral and Transplantation Surgery and Swiss HPB Center, University Hospital Zurich, 8091, Zürich, Switzerland
| | - Fabian H L Starsich
- Nanoparticle Systems Engineering Laboratory, Institute of Energy and Process Engineering (IEPE), Department of Mechanical and Process Engineering (D-MAVT), ETH Zurich, 8092, Zürich, Switzerland
- Particles-Biology Interactions Laboratory, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), 9014, St. Gallen, Switzerland
| | - Daniel Klose
- Department of Chemistry and Applied Biosciences, ETH Zurich, 8093, Zürich, Switzerland
| | - Andreas Boss
- Department of Radiology, University Hospital Zurich, 8091, Zürich, Switzerland
| | - Anurag Gupta
- Department of Visceral and Transplantation Surgery and Swiss HPB Center, University Hospital Zurich, 8091, Zürich, Switzerland
| | - Alexander Gogos
- Nanoparticle Systems Engineering Laboratory, Institute of Energy and Process Engineering (IEPE), Department of Mechanical and Process Engineering (D-MAVT), ETH Zurich, 8092, Zürich, Switzerland
- Particles-Biology Interactions Laboratory, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), 9014, St. Gallen, Switzerland
| | - Inge K Herrmann
- Nanoparticle Systems Engineering Laboratory, Institute of Energy and Process Engineering (IEPE), Department of Mechanical and Process Engineering (D-MAVT), ETH Zurich, 8092, Zürich, Switzerland
- Particles-Biology Interactions Laboratory, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), 9014, St. Gallen, Switzerland
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25
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Mapping myelin in white matter with T1-weighted/T2-weighted maps: discrepancy with histology and other myelin MRI measures. Brain Struct Funct 2023; 228:525-535. [PMID: 36692695 PMCID: PMC9944377 DOI: 10.1007/s00429-022-02600-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 11/18/2022] [Indexed: 01/25/2023]
Abstract
The ratio of T1-weighted/T2-weighted magnetic resonance images (T1w/T2w MRI) has been successfully applied at the cortical level since 2011 and is now one of the most used myelin mapping methods. However, no reports have explored the histological validity of T1w/T2w myelin mapping in white matter. Here we compare T1w/T2w with ex vivo postmortem histology and in vivo MRI methods, namely quantitative susceptibility mapping (QSM) and multi-echo T2 myelin water fraction (MWF) mapping techniques. We report a discrepancy between T1w/T2w myelin maps of the human corpus callosum and the histology and analyse the putative causes behind such discrepancy. T1w/T2w does not positively correlate with Luxol Fast Blue (LFB)-Optical Density but shows a weak to moderate, yet significant, negative correlation. On the contrary, MWF is strongly and positively correlated with LFB, whereas T1w/T2w and MWF maps are weakly negatively correlated. The discrepancy between T1w/T2w MRI maps, MWF and histological myelin maps suggests caution in using T1w/T2w as a white matter mapping method at the callosal level. While T1w/T2w imaging may correlate with myelin content at the cortical level, it is not a specific method to map myelin density in white matter.
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Bazala R, Zoppellaro G, Kletetschka G. Iron Level Changes in the Brain with Neurodegenerative Disease. BRAIN MULTIPHYSICS 2023. [DOI: 10.1016/j.brain.2023.100063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
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27
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Edwards LJ, McColgan P, Helbling S, Zarkali A, Vaculčiaková L, Pine KJ, Dick F, Weiskopf N. Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis. Cereb Cortex 2022; 33:5704-5716. [PMID: 36520483 PMCID: PMC10152104 DOI: 10.1093/cercor/bhac453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 10/20/2022] [Accepted: 10/21/2022] [Indexed: 12/23/2022] Open
Abstract
Abstract
Quantitative magnetic resonance imaging (qMRI) allows extraction of reproducible and robust parameter maps. However, the connection to underlying biological substrates remains murky, especially in the complex, densely packed cortex. We investigated associations in human neocortex between qMRI parameters and neocortical cell types by comparing the spatial distribution of the qMRI parameters longitudinal relaxation rate (${R_{1}}$), effective transverse relaxation rate (${R_{2}}^{\ast }$), and magnetization transfer saturation (MTsat) to gene expression from the Allen Human Brain Atlas, then combining this with lists of genes enriched in specific cell types found in the human brain. As qMRI parameters are magnetic field strength-dependent, the analysis was performed on MRI data at 3T and 7T. All qMRI parameters significantly covaried with genes enriched in GABA- and glutamatergic neurons, i.e. they were associated with cytoarchitecture. The qMRI parameters also significantly covaried with the distribution of genes enriched in astrocytes (${R_{2}}^{\ast }$ at 3T, ${R_{1}}$ at 7T), endothelial cells (${R_{1}}$ and MTsat at 3T), microglia (${R_{1}}$ and MTsat at 3T, ${R_{1}}$ at 7T), and oligodendrocytes and oligodendrocyte precursor cells (${R_{1}}$ at 7T). These results advance the potential use of qMRI parameters as biomarkers for specific cell types.
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Affiliation(s)
- Luke J Edwards
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Peter McColgan
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Huntington’s Disease Centre, University College London , London, UK
| | - Saskia Helbling
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Poeppel Lab, Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society , Frankfurt am Main, DE, Germany
| | - Angeliki Zarkali
- Dementia Research Centre, University College London , London, UK
| | - Lenka Vaculčiaková
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Kerrin J Pine
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
| | - Fred Dick
- Birkbeck/UCL Centre for Neuroimaging (BUCNI) , London, UK
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig, DE, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University , Leipzig, DE, Germany
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Decreased basal ganglia and thalamic iron in early psychotic spectrum disorders are associated with increased psychotic and schizotypal symptoms. Mol Psychiatry 2022; 27:5144-5153. [PMID: 36071113 PMCID: PMC9772130 DOI: 10.1038/s41380-022-01740-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 08/08/2022] [Accepted: 08/10/2022] [Indexed: 01/14/2023]
Abstract
Iron deficits have been reported as a risk factor for psychotic spectrum disorders (PSD). However, examinations of brain iron in PSD remain limited. The current study employed quantitative MRI to examine iron content in several iron-rich subcortical structures in 49 young adult individuals with PSD (15 schizophrenia, 17 schizoaffective disorder, and 17 bipolar disorder with psychotic features) compared with 35 age-matched healthy controls (HC). A parametric approach based on a two-pool magnetization transfer model was applied to estimate longitudinal relaxation rate (R1), which reflects both iron and myelin, and macromolecular proton fraction (MPF), which is specific to myelin. To describe iron content, a synthetic effective transverse relaxation rate (R2*) was modeled using a linear fitting of R1 and MPF. PSD patients compared to HC showed significantly reduced R1 and synthetic R2* across examined regions including the pallidum, ventral diencephalon, thalamus, and putamen areas. This finding was primarily driven by decreases in the subgroup with schizophrenia, followed by schizoaffective disorder. No significant group differences were noted for MPF between PSD and HC while for regional volume, significant reductions in patients were only observed in bilateral caudate, suggesting that R1 and synthetic R2* reductions in schizophrenia and schizoaffective patients likely reflect iron deficits that either occur independently or precede structural and myelin changes. Subcortical R1 and synthetic R2* were also found to be inversely related to positive symptoms within the PSD group and to schizotypal traits across the whole sample. These findings that decreased iron in subcortical regions are associated with PSD risk and symptomatology suggest that brain iron deficiencies may play a role in PSD pathology and warrant further study.
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Tranfa M, Pontillo G, Petracca M, Brunetti A, Tedeschi E, Palma G, Cocozza S. Quantitative MRI in Multiple Sclerosis: From Theory to Application. AJNR Am J Neuroradiol 2022; 43:1688-1695. [PMID: 35680161 DOI: 10.3174/ajnr.a7536] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 02/22/2022] [Indexed: 02/01/2023]
Abstract
Quantitative MR imaging techniques allow evaluating different aspects of brain microstructure, providing meaningful information about the pathophysiology of damage in CNS disorders. In the study of patients with MS, quantitative MR imaging techniques represent an invaluable tool for studying changes in myelin and iron content occurring in the context of inflammatory and neurodegenerative processes. In the first section of this review, we summarize the physics behind quantitative MR imaging, here defined as relaxometry and quantitative susceptibility mapping, and describe the neurobiological correlates of quantitative MR imaging findings. In the second section, we focus on quantitative MR imaging application in MS, reporting the main findings in both the gray and white matter compartments, separately addressing macroscopically damaged and normal-appearing parenchyma.
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Affiliation(s)
- M Tranfa
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.)
| | - G Pontillo
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.) .,Electrical Engineering and Information Technology (G. Pontillo), University of Naples "Federico II," Naples, Italy
| | - M Petracca
- Department of Human Neurosciences (M.P.), Sapienza University of Rome, Rome, Italy
| | - A Brunetti
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.)
| | - E Tedeschi
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.)
| | - G Palma
- Institute of Nanotechnology (G. Palma), National Research Council, Lecce, Italy
| | - S Cocozza
- From the Departments of Advanced Biomedical Sciences (M.T., G. Pontillo, A.B., E.T., S.C.)
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30
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Ali TS, Lv J, Calamante F. Gradual changes in microarchitectural properties of cortex and juxtacortical white matter: Observed by anatomical and diffusion MRI. Magn Reson Med 2022; 88:2485-2503. [PMID: 36045582 DOI: 10.1002/mrm.29413] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/18/2022] [Accepted: 07/22/2022] [Indexed: 01/07/2023]
Abstract
PURPOSE Characterization of cerebral cortex is challenged by the complexity and heterogeneity of its cyto- and myeloarchitecture. This study evaluates quantitative MRI metrics, measured across two cortical depths and in subcortical white matter (WM) adjacent to cortex (juxtacortical WM), indicative of myelin content, neurite density, and diffusion microenvironment, for a comprehensive characterization of cortical microarchitecture. METHODS High-quality structural and diffusion MRI data (N = 30) from the Human Connectome Project were processed to compute myelin index, neurite density index, fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity from superficial cortex, deep cortex, and juxtacortical WM. The distributional patterns of these metrics were analyzed individually, correlated to one another, and were compared to established parcellations. RESULTS Our results supported that myeloarchitectonic and the coexisting cytoarchitectonic structures influence the diffusion properties of water molecules residing in cortex. Full cortical thickness showed myelination patterns similar to those previously observed in humans. Higher myelin indices with similar distributional patterns were observed in deep cortex whereas lower myelin indices were observed in superficial cortex. Neurite density index and other diffusion MRI derived parameters provided complementary information to myelination. Reliable and reproducible correlations were identified among the cortical microarchitectural properties and fiber distributional patterns in proximal WM structures. CONCLUSION We demonstrated gradual changes across the cortical sheath by assessing depth-specific cortical micro-architecture using anatomical and diffusion MRI. Mutually independent but coexisting features of cortical layers and juxtacortical WM provided new insights towards structural organizational units and variabilities across cortical regions and through depth.
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Affiliation(s)
- Tonima S Ali
- School of Biomedical Engineering, The University of Sydney, Sydney, Australia.,Brain and Mind Centre, The University of Sydney, Sydney, Australia
| | - Jinglei Lv
- School of Biomedical Engineering, The University of Sydney, Sydney, Australia.,Brain and Mind Centre, The University of Sydney, Sydney, Australia.,Sydney Imaging, The University of Sydney, Sydney, Australia
| | - Fernando Calamante
- School of Biomedical Engineering, The University of Sydney, Sydney, Australia.,Brain and Mind Centre, The University of Sydney, Sydney, Australia.,Sydney Imaging, The University of Sydney, Sydney, Australia
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Mesoscopic in vivo human T 2* dataset acquired using quantitative MRI at 7 Tesla. Neuroimage 2022; 264:119733. [PMID: 36375782 DOI: 10.1016/j.neuroimage.2022.119733] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 10/15/2022] [Accepted: 11/03/2022] [Indexed: 11/13/2022] Open
Abstract
Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models. Despite the variety of MRI contrasts measured in recent years at the mesoscopic scale, in vivo quantitative imaging of T2* has not been performed. Here we provide a dataset containing empirical T2* measurements acquired at 0.35 × 0.35 × 0.35 mm3 voxel resolution using 7 Tesla MRI. To demonstrate unique features and high quality of this dataset, we generate flat map visualizations that reveal fine-scale cortical substructures such as layers and vessels, and we report quantitative depth-dependent T2* (as well as R2*) values in primary visual cortex and auditory cortex that are highly consistent across subjects. This dataset is freely available at https://doi.org/10.17605/OSF.IO/N5BJ7, and may prove useful for anatomical investigations of the human brain, as well as for improving our understanding of the basis of the T2*-weighted (f)MRI signal.
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32
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Sui YV, Masurkar AV, Rusinek H, Reisberg B, Lazar M. Cortical myelin profile variations in healthy aging brain: A T1w/T2w ratio study. Neuroimage 2022; 264:119743. [PMID: 36368498 PMCID: PMC9904172 DOI: 10.1016/j.neuroimage.2022.119743] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 10/31/2022] [Accepted: 11/07/2022] [Indexed: 11/09/2022] Open
Abstract
Demyelination is observed in both healthy aging and age-related neurodegenerative disorders. While the significance of myelin within the cortex is well acknowledged, studies focused on intracortical demyelination and depth-specific structural alterations in normal aging are lacking. Using the recently available Human Connectome Project Aging dataset, we investigated intracortical myelin in a normal aging population using the T1w/T2w ratio. To capture the fine changes across cortical depths, we employed a surface-based approach by constructing cortical profiles traveling perpendicularly through the cortical ribbon and sampling T1w/T2w values. The curvatures of T1w/T2w cortical profiles may be influenced by differences in local myeloarchitecture and other tissue properties, which are known to vary across cortical regions. To quantify the shape of these profiles, we parametrized the level of curvature using a nonlinearity index (NLI) that measures the deviation of the profile from a straight line. We showed that NLI exhibited a steep decline in aging that was independent of local cortical thinning. Further examination of the profiles revealed that lower T1w/T2w near the gray-white matter boundary and superficial cortical depths were major contributors to the apparent NLI variations with age. These findings suggest that demyelination and changes in other T1w/T2w related tissue properties in normal aging may be depth-specific and highlight the potential of NLI as a unique marker of microstructural alterations within the cerebral cortex.
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Affiliation(s)
- Yu Veronica Sui
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Corresponding author. (Y.V. Sui)
| | - Arjun V. Masurkar
- Department of Neurology, Center for Cognitive Neurology, NYU Grossman School of Medicine, New York, NY, USA,Department of Neuroscience and Physiology, NYU Grossman School of Medicine, New York, NY, USA,Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, USA
| | - Henry Rusinek
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA,Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Barry Reisberg
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Mariana Lazar
- Department of Radiology, NYU Grossman School of Medicine, 660 1st Ave, rm440, New York, NY 10016, USA
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33
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Wawrzyniak A, Balawender K, Lalak R, Staszkiewicz R, Boroń D, Grabarek BO. Oligodendrocytes in the periaqueductal gray matter and the corpus callosum in adult male and female domestic sheep. Brain Res 2022; 1792:148036. [DOI: 10.1016/j.brainres.2022.148036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 07/22/2022] [Accepted: 07/27/2022] [Indexed: 11/02/2022]
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34
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Wang Y, Zhan M, Roebroeck A, De Weerd P, Kashyap S, Roberts MJ. Inconsistencies in atlas-based volumetric measures of the human nucleus basalis of Meynert: A need for high-resolution alternatives. Neuroimage 2022; 259:119421. [PMID: 35779763 DOI: 10.1016/j.neuroimage.2022.119421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 06/10/2022] [Accepted: 06/28/2022] [Indexed: 10/17/2022] Open
Abstract
The nucleus basalis of Meynert (nbM) is the major source of cortical acetylcholine (ACh) and has been related to cognitive processes and to neurological disorders. However, spatially delineating the human nbM in MRI studies remains challenging. Due to the absence of a functional localiser for the human nbM, studies to date have localised it using nearby neuroanatomical landmarks or using probabilistic atlases. To understand the feasibility of MRI of the nbM we set our four goals; our first goal was to review current human nbM region-of-interest (ROI) selection protocols used in MRI studies, which we found have reported highly variable nbM volume estimates. Our next goal was to quantify and discuss the limitations of existing atlas-based volumetry of nbM. We found that the identified ROI volume depends heavily on the atlas used and on the probabilistic threshold set. In addition, we found large disparities even for data/studies using the same atlas and threshold. To test whether spatial resolution contributes to volume variability, as our third goal, we developed a novel nbM mask based on the normalized BigBrain dataset. We found that as long as the spatial resolution of the target data was 1.3 mm isotropic or above, our novel nbM mask offered realistic and stable volume estimates. Finally, as our last goal we tried to discern nbM using publicly available and novel high resolution structural MRI ex vivo MRI datasets. We find that, using an optimised 9.4T quantitative T2⁎ ex vivo dataset, the nbM can be visualised using MRI. We conclude caution is needed when applying the current methods of mapping nbM, especially for high resolution MRI data. Direct imaging of the nbM appears feasible and would eliminate the problems we identify, although further development is required to allow such imaging using standard (f)MRI scanning.
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Affiliation(s)
- Yawen Wang
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
| | - Minye Zhan
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; U992 (Cognitive neuroimaging unit), NeuroSpin, INSERM-CEA, Gif sur Yvette, France
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Peter De Weerd
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Sriranga Kashyap
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands; Techna Institute, University Health Network, Toronto, ON, Canada
| | - Mark J Roberts
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
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35
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Glasser MF, Coalson TS, Harms MP, Xu J, Baum GL, Autio JA, Auerbach EJ, Greve DN, Yacoub E, Van Essen DC, Bock NA, Hayashi T. Empirical transmit field bias correction of T1w/T2w myelin maps. Neuroimage 2022; 258:119360. [PMID: 35697132 PMCID: PMC9483036 DOI: 10.1016/j.neuroimage.2022.119360] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 06/01/2022] [Accepted: 06/04/2022] [Indexed: 12/30/2022] Open
Abstract
T1-weighted divided by T2-weighted (T1w/T2w) myelin maps were initially developed for neuroanatomical analyses such as identifying cortical areas, but they are increasingly used in statistical comparisons across individuals and groups with other variables of interest. Existing T1w/T2w myelin maps contain radiofrequency transmit field (B1+) biases, which may be correlated with these variables of interest, leading to potentially spurious results. Here we propose two empirical methods for correcting these transmit field biases using either explicit measures of the transmit field or alternatively a 'pseudo-transmit' approach that is highly correlated with the transmit field at 3T. We find that the resulting corrected T1w/T2w myelin maps are both better neuroanatomical measures (e.g., for use in cross-species comparisons), and more appropriate for statistical comparisons of relative T1w/T2w differences across individuals and groups (e.g., sex, age, or body-mass-index) within a consistently acquired study at 3T. We recommend that investigators who use the T1w/T2w approach for mapping cortical myelin use these B1+ transmit field corrected myelin maps going forward.
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Affiliation(s)
| | | | - Michael P Harms
- Psychiatry, Washington University Medical School, St. Louis, MO, United States
| | - Junqian Xu
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States; Departments of Radiology and Psychiatry, Baylor College of Medicine, Houston, TX, United States
| | - Graham L Baum
- Department of Psychology, Harvard University, Cambridge, MA, United States
| | - Joonas A Autio
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
| | - Edward J Auerbach
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Douglas N Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | | | - Nicholas A Bock
- Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, ON, Canada
| | - Takuya Hayashi
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan
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36
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Tang Y, Blümcke I, Su TY, Choi JY, Krishnan B, Murakami H, Alexopoulos AV, Najm IM, Jones SE, Wang ZI. Black Line Sign in Focal Cortical Dysplasia IIB: A 7T MRI and Electroclinicopathologic Study. Neurology 2022; 99:e616-e626. [PMID: 35940890 PMCID: PMC9442623 DOI: 10.1212/wnl.0000000000200702] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 03/23/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES We aim to provide detailed imaging-electroclinicopathologic characterization of the black line sign, a novel MRI marker for focal cortical dysplasia (FCD) IIB. METHODS 7T T2*-weighted gradient-echo (T2*w-GRE) images were retrospectively reviewed in a consecutive cohort of patients with medically intractable epilepsy with pathology-proven FCD II, for the occurrence of the black line sign. We examined the overlap between the black line region and the seizure-onset zone (SOZ) defined by intracranial EEG (ICEEG) and additionally assessed whether complete inclusion of the black line region in the surgical resection was associated with postoperative seizure freedom. The histopathologic specimen was aligned with the MRI to investigate the pathologic underpinning of the black line sign. Region-of-interest-based quantitative MRI (qMRI) analysis on the 7T T1 map was performed in the black line region, entire lesional gray matter (GM), and contralateral/ipsilateral normal gray and white matter (WM). RESULTS We included 20 patients with FCD II (14 IIB and 6 IIA). The black line sign was identified in 12/14 (85.7%) of FCD IIB and 0/6 of FCD IIA on 7T T2*w-GRE. The black line region was highly concordant with the ICEEG-defined SOZ (5/7 complete and 2/7 partial overlap). Seizure freedom was seen in 8/8 patients whose black line region was completely included in the surgical resection; in the 2 patients whose resection did not completely include the black line region, both had recurring seizures. Inclusion of the black line region in the surgical resection was significantly associated with seizure freedom (p = 0.02). QMRI analyses showed that the T1 mean value of the black line region was significantly different from the WM (p < 0.001), but similar to the GM. Well-matched histopathologic slices in one case revealed accumulated dysmorphic neurons and balloon cells in the black line region. DISCUSSION The black line sign may serve as a noninvasive marker for FCD IIB. Both MRI-pathology and qMRI analyses suggest that the black line region was an abnormal GM component within the FCD. Being highly concordant with ICEEG-defined SOZ and significantly associated with seizure freedom when included in resection, the black line sign may contribute to the planning of ICEEG/surgery of patients with medically intractable epilepsy with FCD IIB. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in individuals with intractable focal epilepsy undergoing resection who have a 7T MRI with adequate image quality, the presence of the black line sign may suggest FCD IIB, be concordant with SOZ from ICEEG, and be associated with more seizure freedom if fully included in resection.
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Affiliation(s)
- Yingying Tang
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Ingmar Blümcke
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Ting-Yu Su
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Joon Yul Choi
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Balu Krishnan
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Hiroatsu Murakami
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Andreas V Alexopoulos
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Imad M Najm
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Stephen E Jones
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH
| | - Zhong Irene Wang
- From the Department of Neurology (Y.T.), West China Hospital of Sichuan University, Chengdu, Sichuan, China; Charles Shor Epilepsy Center (Y.T., I.B., T.-Y.S., J.Y.C., B.K., H.M., A.V.A., I.M.N., Z.I.W.), Cleveland Clinic; Department of Neuropathology (I.B.), University of Erlangen, Germany; Department of Biomedical Engineering (T.-Y.S.), Case Western Reserve University; and Imaging Institute (S.E.J.), Cleveland Clinic, OH.
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Hofer E, Pirpamer L, Langkammer C, Tinauer C, Seshadri S, Schmidt H, Schmidt R. Heritability of R2* iron in the basal ganglia and cortex. Aging (Albany NY) 2022; 14:6415-6426. [PMID: 35951362 PMCID: PMC9467397 DOI: 10.18632/aging.204212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 07/12/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND While iron is essential for normal brain functioning, elevated concentrations are commonly found in neurodegenerative diseases and are associated with impaired cognition and neurological deficits. Currently, only little is known about genetic and environmental factors that influence brain iron concentrations. METHODS Heritability and bivariate heritability of regional brain iron concentrations, assessed by R2* relaxometry at 3 Tesla MRI, were estimated with variance components models in 130 middle-aged to elderly participants of the Austrian Stroke Prevention Family Study. RESULTS Heritability of R2* iron ranged from 0.46 to 0.82 in basal ganglia and from 0.65 to 0.76 in cortical lobes. Age and BMI explained up to 12% and 9% of the variance of R2* iron, while APOE ε4 carrier status, hypertension, diabetes, hypercholesterolemia, sex and smoking explained 5% or less. The genetic correlation of R2* iron among basal ganglionic nuclei and among cortical lobes ranged from 0.78 to 0.87 and from 0.65 to 0.97, respectively. R2* rates in basal ganglia and cortex were not genetically correlated. CONCLUSIONS Regional brain iron concentrations are mainly driven by genetic factors while environmental factors contribute to a certain extent. Brain iron levels in the basal ganglia and cortex are controlled by distinct sets of genes.
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Affiliation(s)
- Edith Hofer
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Styria, Austria.,Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Styria, Austria
| | - Lukas Pirpamer
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Styria, Austria
| | | | - Christian Tinauer
- Department of Neurology, Medical University of Graz, Styria, Austria
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX 78229, USA.,Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| | - Helena Schmidt
- Research Unit-Genetic Epidemiology, Gottfried Schatz Research Centre for Cell Signalling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Graz, Styria, Austria
| | - Reinhold Schmidt
- Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Styria, Austria
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Wawrzyniak A, Balawender K, Lalak R, Golan MP, Wróbel K, Boroń D, Staszkiewicz R, Grabarek BO. Distribution and Morphological Characteristics of Oligodendrocytes in Selected Areas of the Brain of Male and Female Red Kangaroos (Macropus rufus). Brain Sci 2022; 12:brainsci12081035. [PMID: 36009098 PMCID: PMC9405871 DOI: 10.3390/brainsci12081035] [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: 07/11/2022] [Revised: 07/27/2022] [Accepted: 08/03/2022] [Indexed: 02/04/2023] Open
Abstract
This study was carried out on six adult red kangaroos of both sexes. To determine the location of the oligodendrocytes (OLGs) of the hippocampus (Hip) and corpus callosum (CC), the method of impregnation of the neuroglia with silver salts was applied. The iron distribution in the OLGs was determined by the histochemical method. The Nissl method was used to determine the location of the brain structure and to analyze the number of OLGs. In the Hip, these cells are located one beside another, mainly in blood vessels and neurons; in the neocortex (NC), they are located in layers I–VI; and in the CC, they are arranged in characteristic rows and accompany both nerve fibers and blood vessels. The analysis of the results obtained by the chosen methods in the Hip, NC, and CC in males and females did not show statistically significant differences in the distribution and location of the red kangaroo OLGs. The involvement of these cells is a physiological process that proceeds in a similar manner throughout the life of individuals and actively influences the metabolism of neurons and myelin.
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Affiliation(s)
- Agata Wawrzyniak
- Department of Morphological Sciences, College of Medical Sciences, Institute of Medical Sciences, University of Rzeszow, 35-315 Rzeszow, Poland
| | - Krzysztof Balawender
- Department of Morphological Sciences, College of Medical Sciences, Institute of Medical Sciences, University of Rzeszow, 35-315 Rzeszow, Poland
- Correspondence:
| | - Roman Lalak
- Department of Animal Anatomy and Histology, University of Life Sciences in Lublin, 20-400 Lublin, Poland
| | - Maciej Przemysław Golan
- Laboratory of Molecular Oncology and Innovative Therapies, Military Institute of Medicine in Warsaw, 04-141 Warsaw, Poland
| | - Konrad Wróbel
- Department of Morphological Sciences, College of Medical Sciences, Institute of Medical Sciences, University of Rzeszow, 35-315 Rzeszow, Poland
| | - Dariusz Boroń
- Department of Histology, Cytophysiology and Embryology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, 41-800 Zabrze, Poland
- Department of Gynaecology and Obstetrics, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, 41-800 Zabrze, Poland
| | - Rafał Staszkiewicz
- Department of Histology, Cytophysiology and Embryology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, 41-800 Zabrze, Poland
- Department of Neurosurgery, 5th Military Clinical Hospital with the SP ZOZ Polyclinic in Krakow, 30-901 Krakow, Poland
| | - Beniamin Oskar Grabarek
- Department of Histology, Cytophysiology and Embryology, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, 41-800 Zabrze, Poland
- Department of Gynaecology and Obstetrics, Faculty of Medicine in Zabrze, Academy of Silesia in Katowice, 41-800 Zabrze, Poland
- GynCentrum, Laboratory of Molecular Biology and Virology, 40-851 Katowice, Poland
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Baum GL, Flournoy JC, Glasser MF, Harms MP, Mair P, Sanders AFP, Barch DM, Buckner RL, Bookheimer S, Dapretto M, Smith S, Thomas KM, Yacoub E, Van Essen DC, Somerville LH. Graded Variation in T1w/T2w Ratio during Adolescence: Measurement, Caveats, and Implications for Development of Cortical Myelin. J Neurosci 2022; 42:5681-5694. [PMID: 35705486 PMCID: PMC9302463 DOI: 10.1523/jneurosci.2380-21.2022] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 04/07/2022] [Accepted: 06/04/2022] [Indexed: 01/22/2023] Open
Abstract
Adolescence is characterized by the maturation of cortical microstructure and connectivity supporting complex cognition and behavior. Axonal myelination influences brain connectivity during development by enhancing neural signaling speed and inhibiting plasticity. However, the maturational timing of cortical myelination during human adolescence remains poorly understood. Here, we take advantage of recent advances in high-resolution cortical T1w/T2w mapping methods, including principled correction of B1+ transmit field effects, using data from the Human Connectome Project in Development (HCP-D; N = 628, ages 8-21). We characterize microstructural changes relevant to myelination by estimating age-related differences in T1w/T2w throughout the cerebral neocortex from childhood to early adulthood. We apply Bayesian spline models and clustering analysis to demonstrate graded variation in age-dependent cortical T1w/T2w differences that are correlated with the sensorimotor-association (S-A) axis of cortical organization reported by others. In sensorimotor areas, T1w/T2w ratio measures start at high levels at early ages, increase at a fast pace, and decelerate at later ages (18-21). In intermediate multimodal areas along the S-A axis, T1w/T2w starts at intermediate levels and increases linearly at an intermediate pace. In transmodal/paralimbic association areas, T1w/T2w starts at low levels and increases linearly at the slowest pace. These data provide evidence for graded variation of the T1w/T2w ratio along the S-A axis that may reflect cortical myelination changes during adolescence underlying the development of complex information processing and psychological functioning. We discuss the implications of these results as well as caveats in interpreting magnetic resonance imaging (MRI)-based estimates of myelination.SIGNIFICANCE STATEMENT Myelin is a lipid membrane that is essential to healthy brain function. Myelin wraps axons to increase neural signaling speed, enabling complex neuronal functioning underlying learning and cognition. Here, we characterize the developmental timing of myelination across the cerebral cortex during adolescence using a noninvasive proxy measure, T1w/T2w mapping. Our results provide new evidence demonstrating graded variation across the cortex in the timing of T1w/T2w changes during adolescence, with rapid T1w/T2w increases in lower-order sensory areas and gradual T1w/T2w increases in higher-order association areas. This spatial pattern of microstructural brain development closely parallels the sensorimotor-to-association axis of cortical organization and plasticity during ontogeny.
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Affiliation(s)
- Graham L Baum
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, USA, 02138
| | - John C Flournoy
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, USA, 02138
| | - Matthew F Glasser
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA, 63110
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA, 63110
| | - Michael P Harms
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA, 63110
| | - Patrick Mair
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, USA, 02138
| | - Ashley F P Sanders
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA, 63110
| | - Deanna M Barch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA, 63110
- Department of Psychological and Brain Sciences, Washington University, St. Louis, MO, USA, MO 63130
| | - Randy L Buckner
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, USA, 02138
| | - Susan Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA, 90095
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, University of California, Los Angeles, CA, USA, 90095
| | - Stephen Smith
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom, OX3 9DU
| | - Kathleen M Thomas
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA, 55455
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA, 55455
| | - David C Van Essen
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO, USA, 63110
| | - Leah H Somerville
- Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA, USA, 02138
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Drori E, Berman S, Mezer AA. Mapping microstructural gradients of the human striatum in normal aging and Parkinson's disease. SCIENCE ADVANCES 2022; 8:eabm1971. [PMID: 35857492 PMCID: PMC9286505 DOI: 10.1126/sciadv.abm1971] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Mapping structural spatial change (i.e., gradients) in the striatum is essential for understanding the function of the basal ganglia in both health and disease. We developed a method to identify and quantify gradients of microstructure in the single human brain in vivo. We found spatial gradients in the putamen and caudate nucleus of the striatum that were robust across individuals, clinical conditions, and datasets. By exploiting multiparametric quantitative MRI, we found distinct, spatially dependent, aging-related alterations in water content and iron concentration. Furthermore, we found cortico-striatal microstructural covariation, showing relations between striatal structural gradients and cortical hierarchy. In Parkinson's disease (PD) patients, we found abnormal gradients in the putamen, revealing changes in the posterior putamen that explain patients' dopaminergic loss and motor dysfunction. Our work provides a noninvasive approach for studying the spatially varying, structure-function relationship in the striatum in vivo, in normal aging and PD.
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Affiliation(s)
- Elior Drori
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Shai Berman
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Aviv A Mezer
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
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Harada T, Kudo K, Fujima N, Yoshikawa M, Ikebe Y, Sato R, Shirai T, Bito Y, Uwano I, Miyata M. Quantitative Susceptibility Mapping: Basic Methods and Clinical Applications. Radiographics 2022; 42:1161-1176. [PMID: 35522577 DOI: 10.1148/rg.210054] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Quantitative susceptibility mapping (QSM), one of the advanced MRI techniques for evaluating magnetic susceptibility, offers precise quantitative measurements of spatial distributions of magnetic susceptibility. Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and is a substance-specific value. Recently, QSM has been widely used to estimate various levels of substances in the brain, including iron, hemosiderin, and deoxyhemoglobin (paramagnetism), as well as calcification (diamagnetism). By visualizing iron distribution in the brain, it is possible to identify anatomic structures that are not evident on conventional images and to evaluate various neurodegenerative diseases. It has been challenging to apply QSM in areas outside the brain because of motion artifacts from respiration and heartbeats, as well as the presence of fat, which has a different frequency to the proton. In this review, the authors provide a brief overview of the theoretical background and analyze methods of converting MRI phase images to QSM. Moreover, we provide an overview of the current clinical applications of QSM. Online supplemental material is available for this article. ©RSNA, 2022.
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Affiliation(s)
- Taisuke Harada
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Kohsuke Kudo
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Noriyuki Fujima
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Masato Yoshikawa
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Yohei Ikebe
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Ryota Sato
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Toru Shirai
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Yoshitaka Bito
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Ikuko Uwano
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
| | - Mari Miyata
- From the Department of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, N15 W7, Kita-ku, Sapporo, Japan (T.H., K.K., M.Y.); Center for Cause of Death Investigation (T.H.) and Global Center for Biomedical Science and Engineering (K.K.), Faculty of Medicine, Hokkaido University, Sapporo, Japan; Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan (T.H., K.K., N.F., M.Y., Y.I.); Innovative Technology Laboratory, Fujifilm Healthcare Corporation, Tokyo, Japan (R.S., T.S.); Fujifilm Healthcare Corporation, Chiba, Japan (Y.B.); Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Yahaba, Japan (I.U.); and Department of Functional Brain Imaging, Institute for Quantum Medical Science, Quantum Life and Medical Science Directorate, National Institutes for Quantum Science and Technology, Chiba, Japan (M.M.)
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Balasubramanian M, Mulkern RV, Polimeni JR. In vivo irreversible and reversible transverse relaxation rates in human cerebral cortex via line scans at 7 T with 250 micron resolution perpendicular to the cortical surface. Magn Reson Imaging 2022; 90:44-52. [PMID: 35398027 PMCID: PMC9930184 DOI: 10.1016/j.mri.2022.04.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 03/10/2022] [Accepted: 04/02/2022] [Indexed: 01/15/2023]
Abstract
Understanding how and why MR signals and their associated relaxation rates vary with cortical depth could ultimately enable the noninvasive investigation of the laminar architecture of cerebral cortex in the living human brain. However, cortical gray matter is typically only a few millimeters thick, making it challenging to sample many cortical depths with the voxel sizes commonly used in MRI studies. Line-scan techniques provide a way to overcome this challenge and here we implemented a novel line-scan GESSE pulse sequence that allowed us to measure irreversible and reversible transverse relaxation rates-R2 and R2´, respectively-with extremely high resolution (250 μm) in the radial direction, perpendicular to the cortical surface. Eight healthy human subjects were scanned at 7 T using this sequence, with primary visual cortex (V1) targeted in three subjects and primary motor (M1) and somatosensory cortex (S1) targeted in the other five. In all three cortical areas, a peak in R2 values near the central depths was seen consistently across subjects-an observation that has not been made before, to our knowledge. On the other hand, no consistent pattern was apparent for R2´ values as a function of cortical depth. The intracortical R2 peak reported here is unlikely to be explained by myelin content or by deoxyhemoglobin in the microvasculature; however, this peak is in accord with the laminar distribution of non-heme iron in these cortical areas, known from prior histology studies. Obtaining information about tissue microstructure via measurements of transverse relaxation (and other quantitative MR contrast mechanisms) at the extremely high radial resolutions achievable through the use of line-scan techniques could therefore bring us closer to being able to perform "in vivo histology" of the cerebral cortex.
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Affiliation(s)
- Mukund Balasubramanian
- Harvard Medical School, Boston, MA, USA; Department of Radiology, Boston Children's Hospital, Boston, MA, USA.
| | - Robert V. Mulkern
- Harvard Medical School, Boston, MA, USA,Department of Radiology, Boston Children’s Hospital, Boston, MA, USA
| | - Jonathan R. Polimeni
- Harvard Medical School, Boston, MA, USA,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
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Margoni M, Pagani E, Meani A, Storelli L, Mesaros S, Drulovic J, Barkhof F, Vrenken H, Strijbis E, Gallo A, Bisecco A, Pareto D, Sastre-Garriga J, Ciccarelli O, Yiannakas M, Palace J, Preziosa P, Rocca MA, Filippi M. Exploring in vivo multiple sclerosis brain microstructural damage through T1w/T2w ratio: a multicentre study. J Neurol Neurosurg Psychiatry 2022; 93:741-752. [PMID: 35580993 DOI: 10.1136/jnnp-2022-328908] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 03/29/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To evaluate white matter and grey matter T1-weighted (w)/T2w ratio (T1w/T2w ratio) in healthy controls and patients with multiple sclerosis, and its association with clinical disability. METHODS In this cross-sectional study, 270 healthy controls and 434 patients with multiple sclerosis were retrospectively selected from 7 European sites. T1w/T2w ratio was obtained from brain T2w and T1w scans after intensity calibration using eyes and temporal muscle. RESULTS In healthy controls, T1w/T2w ratio increased until 50-60 years both in white and grey matter. Compared with healthy controls, T1w/T2w ratio was significantly lower in white matter lesions of all multiple sclerosis phenotypes, and in normal-appearing white matter and cortex of patients with relapsing-remitting and secondary progressive multiple sclerosis (p≤0.026), but it was significantly higher in the striatum and pallidum of patients with relapsing-remitting, secondary progressive and primary progressive multiple sclerosis (p≤0.042). In relapse-onset multiple sclerosis, T1w/T2w ratio was significantly lower in white matter lesions and normal-appearing white matter already at Expanded Disability Status Scale (EDSS) <3.0 and in the cortex only for EDSS ≥3.0 (p≤0.023). Conversely, T1w/T2w ratio was significantly higher in the striatum and pallidum for EDSS ≥4.0 (p≤0.005). In primary progressive multiple sclerosis, striatum and pallidum showed significantly higher T1w/T2w ratio beyond EDSS=6.0 (p≤0.001). In multiple sclerosis, longer disease duration, higher EDSS, higher brain lesional volume and lower normalised brain volume were associated with lower lesional and cortical T1w/T2w ratio and a higher T1w/T2w ratio in the striatum and pallidum (β from -1.168 to 0.286, p≤0.040). CONCLUSIONS T1w/T2w ratio may represent a clinically relevant marker sensitive to demyelination, neurodegeneration and iron accumulation occurring at the different multiple sclerosis phases.
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Affiliation(s)
- Monica Margoni
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Meani
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Loredana Storelli
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Sarlota Mesaros
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Beograd, Serbia
| | - Jelena Drulovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Beograd, Serbia
| | - Frederik Barkhof
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,MS Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, UK
| | - Hugo Vrenken
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,MS Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eva Strijbis
- MS Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Antonio Gallo
- Department of Advanced Medical and Surgical Sciences, and 3T MRI-Center, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Alvino Bisecco
- Department of Advanced Medical and Surgical Sciences, and 3T MRI-Center, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Deborah Pareto
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Jaume Sastre-Garriga
- Department of Neurology/Neuroimmunology, Multiple Sclerosis Centre of Catalonia, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Olga Ciccarelli
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, UK
| | - Marios Yiannakas
- NMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, UK
| | - Jacqueline Palace
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Maria A Rocca
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy .,Neurology Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy.,Vita-Salute San Raffaele University, Milano, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
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Fernandez-Alvarez M, Atienza M, Zallo F, Matute C, Capetillo-Zarate E, Cantero JL. Linking Plasma Amyloid Beta and Neurofilament Light Chain to Intracortical Myelin Content in Cognitively Normal Older Adults. Front Aging Neurosci 2022; 14:896848. [PMID: 35783126 PMCID: PMC9247578 DOI: 10.3389/fnagi.2022.896848] [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: 03/15/2022] [Accepted: 05/23/2022] [Indexed: 11/29/2022] Open
Abstract
Evidence suggests that lightly myelinated cortical regions are vulnerable to aging and Alzheimer’s disease (AD). However, it remains unknown whether plasma markers of amyloid and neurodegeneration are related to deficits in intracortical myelin content, and whether this relationship, in turn, is associated with altered patterns of resting-state functional connectivity (rs-FC). To shed light into these questions, plasma levels of amyloid-β fragment 1–42 (Aβ1–42) and neurofilament light chain (NfL) were measured using ultra-sensitive single-molecule array (Simoa) assays, and the intracortical myelin content was estimated with the ratio T1-weigthed/T2-weighted (T1w/T2w) in 133 cognitively normal older adults. We assessed: (i) whether plasma Aβ1–42 and/or NfL levels were associated with intracortical myelin content at different cortical depths and (ii) whether cortical regions showing myelin reductions also exhibited altered rs-FC patterns. Surface-based multiple regression analyses revealed that lower plasma Aβ1–42 and higher plasma NfL were associated with lower myelin content in temporo-parietal-occipital regions and the insular cortex, respectively. Whereas the association with Aβ1–42 decreased with depth, the NfL-myelin relationship was most evident in the innermost layer. Older individuals with higher plasma NfL levels also exhibited altered rs-FC between the insula and medial orbitofrontal cortex. Together, these findings establish a link between plasma markers of amyloid/neurodegeneration and intracortical myelin content in cognitively normal older adults, and support the role of plasma NfL in boosting aberrant FC patterns of the insular cortex, a central brain hub highly vulnerable to aging and neurodegeneration.
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Affiliation(s)
- Marina Fernandez-Alvarez
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Mercedes Atienza
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Fatima Zallo
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Carlos Matute
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Estibaliz Capetillo-Zarate
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Jose L. Cantero
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- *Correspondence: Jose L. Cantero,
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45
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Okada T, Fujimoto K, Fushimi Y, Akasaka T, Thuy DHD, Shima A, Sawamoto N, Oishi N, Zhang Z, Funaki T, Nakamoto Y, Murai T, Miyamoto S, Takahashi R, Isa T. Neuroimaging at 7 Tesla: a pictorial narrative review. Quant Imaging Med Surg 2022; 12:3406-3435. [PMID: 35655840 PMCID: PMC9131333 DOI: 10.21037/qims-21-969] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/05/2022] [Indexed: 01/26/2024]
Abstract
Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.
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Affiliation(s)
- Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Thai Akasaka
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Dinh H. D. Thuy
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsushi Shima
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Medial Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Funaki
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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46
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Oliveira R, Pelentritou A, Di Domenicantonio G, De Lucia M, Lutti A. In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data. Front Neurosci 2022; 16:874023. [PMID: 35527816 PMCID: PMC9070985 DOI: 10.3389/fnins.2022.874023] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 03/24/2022] [Indexed: 11/13/2022] Open
Abstract
Purpose We present a novel approach that allows the estimation of morphological features of axonal fibers from data acquired in vivo in humans. This approach allows the assessment of white matter microscopic properties non-invasively with improved specificity. Theory The proposed approach is based on a biophysical model of Magnetic Resonance Imaging (MRI) data and of axonal conduction velocity estimates obtained with Electroencephalography (EEG). In a white matter tract of interest, these data depend on (1) the distribution of axonal radius [P(r)] and (2) the g-ratio of the individual axons that compose this tract [g(r)]. P(r) is assumed to follow a Gamma distribution with mode and scale parameters, M and θ, and g(r) is described by a power law with parameters α and β. Methods MRI and EEG data were recorded from 14 healthy volunteers. MRI data were collected with a 3T scanner. MRI-measured g-ratio maps were computed and sampled along the visual transcallosal tract. EEG data were recorded using a 128-lead system with a visual Poffenberg paradigm. The interhemispheric transfer time and axonal conduction velocity were computed from the EEG current density at the group level. Using the MRI and EEG measures and the proposed model, we estimated morphological properties of axons in the visual transcallosal tract. Results The estimated interhemispheric transfer time was 11.72 ± 2.87 ms, leading to an average conduction velocity across subjects of 13.22 ± 1.18 m/s. Out of the 4 free parameters of the proposed model, we estimated θ – the width of the right tail of the axonal radius distribution – and β – the scaling factor of the axonal g-ratio, a measure of fiber myelination. Across subjects, the parameter θ was 0.40 ± 0.07 μm and the parameter β was 0.67 ± 0.02 μm−α. Conclusion The estimates of axonal radius and myelination are consistent with histological findings, illustrating the feasibility of this approach. The proposed method allows the measurement of the distribution of axonal radius and myelination within a white matter tract, opening new avenues for the combined study of brain structure and function, and for in vivo histological studies of the human brain.
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47
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Chen B, Linke A, Olson L, Kohli J, Kinnear M, Sereno M, Müller RA, Carper R, Fishman I. Cortical Myelination in Toddlers and Preschoolers with Autism Spectrum Disorder. Dev Neurobiol 2022; 82:261-274. [PMID: 35348301 PMCID: PMC9325547 DOI: 10.1002/dneu.22874] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 02/22/2022] [Accepted: 03/17/2022] [Indexed: 11/07/2022]
Abstract
Intracortical myelin is thought to play a significant role in the development of neural circuits and functional networks, with consistent evidence of atypical network connectivity in children with autism spectrum disorders (ASD). However, little is known about the development of intracortical myelin in the first years of life in ASD, during the critical neurodevelopmental period when autism symptoms first emerge. Using T1-weighted (T1w) and T2-weighted (T2w) structural magnetic resonance imaging (MRI) in 21 young children with ASD and 16 typically developing (TD) children, ages 1.5 to 5.5 years, we demonstrate the feasibility of estimating intracortical myelin in vivo using the T1w/T2w ratio as a proxy. The resultant T1w/T2w maps were largely comparable with those reported in prior T1w/T2w studies in typically developing children and adults, and revealed no group differences between TD children and those with ASD. However, differential associations between T1w/T2w and age were identified in several early myelinated regions (e.g., visual, posterior cingulate, precuneus cortices) in the ASD and TD groups, with age-related increase in estimated myelin content across the toddler and preschool years detected in TD children, but not in children with ASD. The atypical age-related effects in intracortical myelin, suggesting a disrupted myelination in the first years of life in ASD, may be related to the aberrant brain network connectivity reported in young children with ASD in some of the same cortical regions and circuits. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Bosi Chen
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California, San Diego, USA
| | - Annika Linke
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University
| | - Lindsay Olson
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California, San Diego, USA
| | - Jiwandeep Kohli
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California, San Diego, USA
| | - Mikaela Kinnear
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University
| | - Martin Sereno
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California, San Diego, USA
| | - Ralph-Axel Müller
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California, San Diego, USA.,Center for Autism and Developmental Disorders, San Diego State University
| | - Ruth Carper
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California, San Diego, USA.,Center for Autism and Developmental Disorders, San Diego State University
| | - Inna Fishman
- Brain Development Imaging Laboratories, Department of Psychology, San Diego State University.,Joint Doctoral Program in Clinical Psychology, San Diego State University and University of California, San Diego, USA.,Center for Autism and Developmental Disorders, San Diego State University
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48
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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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49
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Lutti A, Corbin N, Ashburner J, Ziegler G, Draganski B, Phillips C, Kherif F, Callaghan MF, Di Domenicantonio G. Restoring statistical validity in group analyses of motion-corrupted MRI data. Hum Brain Mapp 2022; 43:1973-1983. [PMID: 35112434 PMCID: PMC8933245 DOI: 10.1002/hbm.25767] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 12/09/2021] [Accepted: 12/14/2021] [Indexed: 01/07/2023] Open
Abstract
Motion during the acquisition of magnetic resonance imaging (MRI) data degrades image quality, hindering our capacity to characterise disease in patient populations. Quality control procedures allow the exclusion of the most affected images from analysis. However, the criterion for exclusion is difficult to determine objectively and exclusion can lead to a suboptimal compromise between image quality and sample size. We provide an alternative, data‐driven solution that assigns weights to each image, computed from an index of image quality using restricted maximum likelihood. We illustrate this method through the analysis of quantitative MRI data. The proposed method restores the validity of statistical tests, and performs near optimally in all brain regions, despite local effects of head motion. This method is amenable to the analysis of a broad type of MRI data and can accommodate any measure of image quality.
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Affiliation(s)
- Antoine Lutti
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Nadège Corbin
- Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/University Bordeaux, Bordeaux, France.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - John Ashburner
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Gabriel Ziegler
- Institute for Cognitive Neurology and Dementia Research, University of Magdeburg, Germany
| | - Bogdan Draganski
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Neurology Department, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Christophe Phillips
- GIGA Cyclotron Research Centre - in vivo imaging, GIGA Institute, University of Liège, Liège, Belgium
| | - Ferath Kherif
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Giulia Di Domenicantonio
- Laboratory for Research in Neuroimaging, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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50
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Yamada K, Yoshimura J, Watanabe M, Suzuki K. Application of 7 tesla magnetic resonance imaging for pediatric neurological disorders: Early clinical experience. J Clin Imaging Sci 2022; 11:65. [PMID: 34992941 PMCID: PMC8720429 DOI: 10.25259/jcis_185_2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 11/07/2021] [Indexed: 11/04/2022] Open
Abstract
Ultra-high field magnetic resonance imaging (MRI) has been introduced for use in pediatric developmental neurology. While higher magnetic fields have certain advantages, optimized techniques with specific considerations are required to ensure rational and safe use in children and those with pediatric neurological disorders (PNDs). Here, we summarize our initial experience with clinical translational studies that utilized 7 tesla (T)-MRI in the fields of developmental neurology. T2-reversed images and three-dimensional anisotropy contrast imaging enabled the depiction of targeted pathological brain structures with better spatial resolution. Diffusion imaging and susceptibility-weighted imaging enabled visualization of intracortical, subcortical, and intratumoral microstructures in vivo within highly limited scan times appropriate for patients with PNDs. 7T-MRI appears to have significant potential to enhance the depiction of the structural and functional properties of the brain, particularly those associated with atypical brain development.
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Affiliation(s)
- Kenichi Yamada
- Center for Integrated Human Brain Science, Brain Research Institute, Niigata University, Niigata, Japan
| | - Junichi Yoshimura
- Department of Neurosurgery, Brain Research Institute, Niigata University, Niigata, Japan
| | - Masaki Watanabe
- Center for Integrated Human Brain Science, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kiyotaka Suzuki
- Center for Integrated Human Brain Science, Brain Research Institute, Niigata University, Niigata, Japan
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