1
|
Alzaidi AA, Panek R, Blockley NP. Quantitative BOLD (qBOLD) imaging of oxygen metabolism and blood oxygenation in the human body: A scoping review. Magn Reson Med 2024; 92:1822-1837. [PMID: 39072791 DOI: 10.1002/mrm.30165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 05/06/2024] [Accepted: 05/08/2024] [Indexed: 07/30/2024]
Abstract
PURPOSE There are many approaches to the quantitative BOLD (qBOLD) technique described in the literature, differing in pulse sequences, MRI parameters and data processing. Thus, in this review, we summarized the acquisition methods, approaches used for oxygenation quantification and clinical populations investigated. METHODS Three databases were systematically searched (Medline, Embase, and Web of Science) for published research that used qBOLD methods for quantification of oxygen metabolism. Data extraction and synthesis were performed by one author and reviewed by a second author. RESULTS A total of 93 relevant papers were identified. Acquisition strategies were summarized, and oxygenation parameters were found to have been investigated in many pathologies such as steno-occlusive diseases, stroke, glioma, and multiple sclerosis disease. CONCLUSION A summary of qBOLD approaches for oxygenation measurements and applications could help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.
Collapse
Affiliation(s)
- Ahlam A Alzaidi
- David Greenfield Human Physiology Unit, School of Life Sciences, University of Nottingham, Nottingham, UK
- Radiology Department, College of Applied Medical Sciences, Taif University, Taif, Saudi Arabia
| | - Rafal Panek
- Medical Physics and Clinical Engineering, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Nicholas P Blockley
- David Greenfield Human Physiology Unit, School of Life Sciences, University of Nottingham, Nottingham, UK
| |
Collapse
|
2
|
Tomaszewski MR, Sukstanskii AL, Haley H, Meng X, Miller CO, Yablonskiy DA. Quantitative gradient recalled echo (qGRE) MRI enables in vivo measurement of pre-atrophic neurodegeneration in a mouse model of Alzheimer's disease. Neuroimage 2024; 298:120794. [PMID: 39173693 DOI: 10.1016/j.neuroimage.2024.120794] [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: 04/05/2024] [Revised: 08/09/2024] [Accepted: 08/14/2024] [Indexed: 08/24/2024] Open
Abstract
Robust methods are needed for preclinical evaluation of novel Alzheimer Disease (AD) therapies to accelerate drug discovery. Quantitative Gradient Recalled Echo (qGRE) MRI has shown promise to provide insight into neurodegeneration in AD prior to atrophy development in humans, highlighting areas of low neuronal density. In this study a novel qGRE method (20 echoes, TE=2-40ms) is shown to non-invasively measure the longitudinal neuronal loss in the hippocampus of a mouse model of AD tauopathy Tg4510. Tg4510 (n=10) and wild type (WT, n=6) mice underwent MRI (7T field strength) at 3-7 months old. 3D qGRE approach was used to generate brain-specific R2* maps free of magnetic field inhomogeneity artifacts. Light-sheet microscopy of the brains stained with NeuN and MBP served to visualize neuronal nuclei and myelin content respectively. Significant decrease in NeuN staining between 3mo and 5mo was observed in the hippocampus of Tg4510, validating the mouse AD model. Longitudinal analysis showed clear decreases in R2* metric of qGRE signal in the Tg4510 mice hippocampus undergoing neurodegeneration between 3 and 5 months old. Histogram analysis revealed an upward trend in patterns of low R2* value (Dark Matter, DM), and broadening of R2* distribution. These were quantified as significant increase in both DM Volume Fraction (DMVF) and R2* Standard Deviation (SD) in Tg4510 mice (p=0.004/p=0.016 DMVF/SD) but not in WT controls (p>0.25). Further monotonical increase was also observed in both metrics in time. A significant negative correlation was observed between the DMVF and myelin content (p=0.01, r=-0.76), suggesting sensitivity of the technique to the loss of myelinated axons. The presented qGRE technique, validated by histological measurements, can be readily applied as in vivo tool in preclinical models of neurodegeneration for pharmacodynamics and mechanism of action assessment.
Collapse
Affiliation(s)
| | - Alexander L Sukstanskii
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| | - Hyking Haley
- Translational Imaging Department, Merck & Co., Inc., Rahway, NJ, USA
| | - Xiangjun Meng
- Translational Imaging Department, Merck & Co., Inc., Rahway, NJ, USA
| | - Corin O Miller
- Translational Imaging Department, Merck & Co., Inc., Rahway, NJ, USA
| | - Dmitriy A Yablonskiy
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States
| |
Collapse
|
3
|
Biondetti E, Cho J, Lee H. Cerebral oxygen metabolism from MRI susceptibility. Neuroimage 2023; 276:120189. [PMID: 37230206 PMCID: PMC10335841 DOI: 10.1016/j.neuroimage.2023.120189] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 04/26/2023] [Accepted: 05/23/2023] [Indexed: 05/27/2023] Open
Abstract
This article provides an overview of MRI methods exploiting magnetic susceptibility properties of blood to assess cerebral oxygen metabolism, including the tissue oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2). The first section is devoted to describing blood magnetic susceptibility and its effect on the MRI signal. Blood circulating in the vasculature can have diamagnetic (oxyhemoglobin) or paramagnetic properties (deoxyhemoglobin). The overall balance between oxygenated and deoxygenated hemoglobin determines the induced magnetic field which, in turn, modulates the transverse relaxation decay of the MRI signal via additional phase accumulation. The following sections of this review then illustrate the principles underpinning susceptibility-based techniques for quantifying OEF and CMRO2. Here, it is detailed whether these techniques provide global (OxFlow) or local (Quantitative Susceptibility Mapping - QSM, calibrated BOLD - cBOLD, quantitative BOLD - qBOLD, QSM+qBOLD) measurements of OEF or CMRO2, and what signal components (magnitude or phase) and tissue pools they consider (intravascular or extravascular). Validations studies and potential limitations of each method are also described. The latter include (but are not limited to) challenges in the experimental setup, the accuracy of signal modeling, and assumptions on the measured signal. The last section outlines the clinical uses of these techniques in healthy aging and neurodegenerative diseases and contextualizes these reports relative to results from gold-standard PET.
Collapse
Affiliation(s)
- Emma Biondetti
- Department of Neuroscience, Imaging and Clinical Sciences, "D'Annunzio University" of Chieti-Pescara, Chieti, Italy; Institute for Advanced Biomedical Technologies, "D'Annunzio University" of Chieti-Pescara, Chieti, Italy
| | - Junghun Cho
- Department of Biomedical Engineering, University at Buffalo, The State University of New York, New York, USA
| | - Hyunyeol Lee
- School of Electronic and Electrical Engineering, Kyungpook National University, Daegu, Republic of Korea; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
| |
Collapse
|
4
|
Kahali S, Kothapalli SVVN, Xu X, Kamilov US, Yablonskiy DA. Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient-Recalled Echo (qGRE) magnetic resonance imaging metrics associated with human brain neuronal structure and hemodynamic properties. NMR IN BIOMEDICINE 2023; 36:e4883. [PMID: 36442839 DOI: 10.1002/nbm.4883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/23/2022] [Accepted: 11/24/2022] [Indexed: 06/16/2023]
Abstract
The purpose of the current study was to introduce a Deep learning-based Accelerated and Noise-Suppressed Estimation (DANSE) method for reconstructing quantitative maps of biological tissue cellular-specific, R2t*, and hemodynamic-specific, R2', metrics of quantitative gradient-recalled echo (qGRE) MRI. The DANSE method adapts a supervised learning paradigm to train a convolutional neural network for robust estimation of R2t* and R2' maps with significantly reduced sensitivity to noise and the adverse effects of macroscopic (B0 ) magnetic field inhomogeneities directly from the gradient-recalled echo (GRE) magnitude images. The R2t* and R2' maps for training were generated by means of a voxel-by-voxel fitting of a previously developed biophysical quantitative qGRE model accounting for tissue, hemodynamic, and B0 -inhomogeneities contributions to multigradient-echo GRE signal using a nonlinear least squares (NLLS) algorithm. We show that the DANSE model efficiently estimates the aforementioned qGRE maps and preserves all the features of the NLLS approach with significant improvements including noise suppression and computation speed (from many hours to seconds). The noise-suppression feature of DANSE is especially prominent for data with low signal-to-noise ratio (SNR ~ 50-100), where DANSE-generated R2t* and R2' maps had up to three times smaller errors than that of the NLLS method. The DANSE method enables fast reconstruction of qGRE maps with significantly reduced sensitivity to noise and magnetic field inhomogeneities. The DANSE method does not require any information about field inhomogeneities during application. It exploits spatial and gradient echo time-dependent patterns in the GRE data and previously gained knowledge from the biophysical model, thus producing high quality qGRE maps, even in environments with high noise levels. These features along with fast computational speed can lead to broad qGRE clinical and research applications.
Collapse
Affiliation(s)
- Sayan Kahali
- Department of Radiology, Washington University in Saint Louis, St. Louis, Missouri, USA
| | | | - Xiaojian Xu
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Ulugbek S Kamilov
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University in Saint Louis, St. Louis, Missouri, USA
| |
Collapse
|
5
|
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.
Collapse
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
| |
Collapse
|
6
|
Using quantitative MRI to study the association of isocitrate dehydrogenase (IDH) status with oxygen metabolism and cellular structure changes in glioma. Eur J Radiol 2022; 155:110502. [PMID: 36049408 DOI: 10.1016/j.ejrad.2022.110502] [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: 06/14/2022] [Revised: 08/14/2022] [Accepted: 08/23/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE To investigate the characteristics of oxygen metabolism and the cellular structure of glioma using quantitative MRI to predict the isocitrate dehydrogenase 1 (IDH1) status and to further understand the biological characteristics of gliomas. METHODS In this retrospective study, 94 patients with gliomas eventually received quantitative MRI measures to study oxygen metabolism. The oxygen metabolism biomarker maps (oxygen extraction fraction [OEF] and cerebral metabolic rate of oxygen [CMRO2]) and the tissue-cellular-specific (R2t*) MRI relaxation parameter were evaluated in different regions of glioma. RESULTS MRI results showed differences in oxygen metabolism measures in all patients with gliomas of different IDH1 statuses. Compared to patients with IDH1 mutant gliomas, patients with IDH1 wild type gliomas showed increased (P < 0.01) CMRO2, OEF, cerebral blood volume [CBF], and R2t* measures in tumor regions, while only OEF, CBF and R2t* were found to be increased (P < 0.05) in the peritumoral area. OEF achieved the best performance for distinguishing IDH1 wild type and mutant gliomas in the tumor area (AUC = 0.732, P < 0.001). R2t* values correlated with Ki-67(R = 0.35, P < 0.001) in the tumor area, while no significant correlations between Ki-67 and R2t* were found in the peritumoral area (R = 0.19, P = 0.072). CONCLUSION Quantitative MRI has potential applications in studying the tumor and peritumoral areas of glioma, and it has the ability to predict and reveal the characteristics of oxygen metabolism and cellular structure in different regions of gliomas.
Collapse
|
7
|
Xu X, Kothapalli SVVN, Liu J, Kahali S, Gan W, Yablonskiy DA, Kamilov US. Learning-based motion artifact removal networks for quantitative R 2 ∗ mapping. Magn Reson Med 2022; 88:106-119. [PMID: 35257400 DOI: 10.1002/mrm.29188] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 01/11/2022] [Accepted: 01/18/2022] [Indexed: 11/12/2022]
Abstract
PURPOSE To introduce two novel learning-based motion artifact removal networks (LEARN) for the estimation of quantitative motion- and B 0 -inhomogeneity-corrected R 2 ∗ maps from motion-corrupted multi-Gradient-Recalled Echo (mGRE) MRI data. METHODS We train two convolutional neural networks (CNNs) to correct motion artifacts for high-quality estimation of quantitative B 0 -inhomogeneity-corrected R 2 ∗ maps from mGRE sequences. The first CNN, LEARN-IMG, performs motion correction on complex mGRE images, to enable the subsequent computation of high-quality motion-free quantitative R 2 ∗ (and any other mGRE-enabled) maps using the standard voxel-wise analysis or machine learning-based analysis. The second CNN, LEARN-BIO, is trained to directly generate motion- and B 0 -inhomogeneity-corrected quantitative R 2 ∗ maps from motion-corrupted magnitude-only mGRE images by taking advantage of the biophysical model describing the mGRE signal decay. RESULTS We show that both CNNs trained on synthetic MR images are capable of suppressing motion artifacts while preserving details in the predicted quantitative R 2 ∗ maps. Significant reduction of motion artifacts on experimental in vivo motion-corrupted data has also been achieved by using our trained models. CONCLUSION Both LEARN-IMG and LEARN-BIO can enable the computation of high-quality motion- and B 0 -inhomogeneity-corrected R 2 ∗ maps. LEARN-IMG performs motion correction on mGRE images and relies on the subsequent analysis for the estimation of R 2 ∗ maps, while LEARN-BIO directly performs motion- and B 0 -inhomogeneity-corrected R 2 ∗ estimation. Both LEARN-IMG and LEARN-BIO jointly process all the available gradient echoes, which enables them to exploit spatial patterns available in the data. The high computational speed of LEARN-BIO is an advantage that can lead to a broader clinical application.
Collapse
Affiliation(s)
- Xiaojian Xu
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Jiaming Liu
- Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Sayan Kahali
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Weijie Gan
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Ulugbek S Kamilov
- Department of Computer Science and Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| |
Collapse
|
8
|
Kothapalli SV, Benzinger TL, Aschenbrenner AJ, Perrin RJ, Hildebolt CF, Goyal MS, Fagan AM, Raichle ME, Morris JC, Yablonskiy DA. Quantitative Gradient Echo MRI Identifies Dark Matter as a New Imaging Biomarker of Neurodegeneration that Precedes Tisssue Atrophy in Early Alzheimer's Disease. J Alzheimers Dis 2022; 85:905-924. [PMID: 34897083 PMCID: PMC8842777 DOI: 10.3233/jad-210503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/27/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Currently, brain tissue atrophy serves as an in vivo MRI biomarker of neurodegeneration in Alzheimer's disease (AD). However, postmortem histopathological studies show that neuronal loss in AD exceeds volumetric loss of tissue and that loss of memory in AD begins when neurons and synapses are lost. Therefore, in vivo detection of neuronal loss prior to detectable atrophy in MRI is essential for early AD diagnosis. OBJECTIVE To apply a recently developed quantitative Gradient Recalled Echo (qGRE) MRI technique for in vivo evaluation of neuronal loss in human hippocampus. METHODS Seventy participants were recruited from the Knight Alzheimer Disease Research Center, representing three groups: Healthy controls [Clinical Dementia Rating® (CDR®) = 0, amyloid β (Aβ)-negative, n = 34]; Preclinical AD (CDR = 0, Aβ-positive, n = 19); and mild AD (CDR = 0.5 or 1, Aβ-positive, n = 17). RESULTS In hippocampal tissue, qGRE identified two types of regions: one, practically devoid of neurons, we designate as "Dark Matter", and the other, with relatively preserved neurons, "Viable Tissue". Data showed a greater loss of neurons than defined by atrophy in the mild AD group compared with the healthy control group; neuronal loss ranged between 31% and 43%, while volume loss ranged only between 10% and 19%. The concept of Dark Matter was confirmed with histopathological study of one participant who underwent in vivo qGRE 14 months prior to expiration. CONCLUSION In vivo qGRE method identifies neuronal loss that is associated with impaired AD-related cognition but is not recognized by MRI measurements of tissue atrophy, therefore providing new biomarkers for early AD detection.
Collapse
Affiliation(s)
| | - Tammie L. Benzinger
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Andrew J. Aschenbrenner
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Richard J. Perrin
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Manu S. Goyal
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Anne M. Fagan
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Marcus E. Raichle
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - John C. Morris
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Dmitriy A. Yablonskiy
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
- The Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| |
Collapse
|
9
|
Kahali S, Raichle ME, Yablonskiy DA. The Role of the Human Brain Neuron-Glia-Synapse Composition in Forming Resting-State Functional Connectivity Networks. Brain Sci 2021; 11:1565. [PMID: 34942867 PMCID: PMC8699258 DOI: 10.3390/brainsci11121565] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 11/17/2022] Open
Abstract
While significant progress has been achieved in studying resting-state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brain's cellular constituents remain. Here, we use quantitative Gradient-Recalled Echo (qGRE) MRI for mapping the human brain cellular composition and BOLD (blood-oxygen level-dependent) MRI to explore how the brain cellular constituents relate to resting-state functional networks. Results show that the BOLD signal-defined synchrony of connections between cellular circuits in network-defined individual functional units is mainly associated with the regional neuronal density, while the between-functional units' connectivity strength is also influenced by the glia and synaptic components of brain tissue cellular constituents. These mechanisms lead to a rather broad distribution of resting-state functional network properties. Visual networks with the highest neuronal density (but lowest density of glial cells and synapses) exhibit the strongest coherence of the BOLD signal as well as the strongest intra-network connectivity. The Default Mode Network (DMN) is positioned near the opposite part of the spectrum with relatively low coherence of the BOLD signal but with a remarkably balanced cellular contents, enabling DMN to have a prominent role in the overall organization of the brain and hierarchy of functional networks.
Collapse
Affiliation(s)
- Sayan Kahali
- Department of Radiology, Washington University in Saint Louis, Saint Louis, MO 63110, USA; (S.K.); (M.E.R.)
| | - Marcus E. Raichle
- Department of Radiology, Washington University in Saint Louis, Saint Louis, MO 63110, USA; (S.K.); (M.E.R.)
- Department of Neurology, Washington University in Saint Louis, Saint Louis, MO 63110, USA
| | - Dmitriy A. Yablonskiy
- Department of Radiology, Washington University in Saint Louis, Saint Louis, MO 63110, USA; (S.K.); (M.E.R.)
| |
Collapse
|
10
|
Lema Dopico A, Choi S, Hua J, Li X, Harrison DM. Multi-layer analysis of quantitative 7 T magnetic resonance imaging in the cortex of multiple sclerosis patients reveals pathology associated with disability. Mult Scler 2021; 27:2040-2051. [PMID: 33596719 PMCID: PMC8371108 DOI: 10.1177/1352458521994556] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Cortical demyelination is a relevant aspect of tissue damage in multiple sclerosis (MS). Microstructural changes may affect each layer in the cortex differently. OBJECTIVES To evaluate the sensitivity of quantitative magnetic resonance imaging (qMRI) measurements on cortical layers as clinically accessible biomarkers of grey matter (GM) pathology. METHODS Forty-five participants with MS underwent 7 T magnetic resonance imaging (MRI) of the brain. Magnetization prepared two rapid acquisition gradient echoes (MP2RAGE) was processed for T1-weighted images and a T1 map. Multi-echo gradient echo images were processed for quantitative susceptibility and R2* maps. Cortical GM volumes were segmented into four cortical layers, and relaxometry metrics were calculated within and between these layers. RESULTS Significant correlations were found for disability scales and multi-layer metrics, for example, Expanded Disability Status Scale (EDSS) and peak height (PH) in the subpial (T1: ρ = -0.372, p < 0.050) and inner (R2*: ρ = -0.359, p < 0.050) cortical layers. Multivariate regression showed interdependency between atrophy and cortical metrics in some instances, but an independent relationship between cortical metrics and disability in others. CONCLUSION Cortical layer 7 T qMRI analyses reveal layer-specific relationships with disability in MS and allow emergence of clinically relevant associations that are hidden when analysing the full cortex.
Collapse
Affiliation(s)
- Alfonso Lema Dopico
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Seongjin Choi
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jun Hua
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA/Neurosection, Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA/Neurosection, Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel M Harrison
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA/F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| |
Collapse
|
11
|
Yablonskiy DA, Wen J, Kothapalli SVVN, Sukstanskii AL. In vivo evaluation of heme and non-heme iron content and neuronal density in human basal ganglia. Neuroimage 2021; 235:118012. [PMID: 33838265 PMCID: PMC10468262 DOI: 10.1016/j.neuroimage.2021.118012] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 03/24/2021] [Accepted: 03/25/2021] [Indexed: 12/16/2022] Open
Abstract
Non-heme iron is an important element supporting the structure and functioning of biological tissues. Imbalance in non-heme iron can lead to different neurological disorders. Several MRI approaches have been developed for iron quantification relying either on the relaxation properties of MRI signal or measuring tissue magnetic susceptibility. Specific quantification of the non-heme iron can, however, be constrained by the presence of the heme iron in the deoxygenated blood and contribution of cellular composition. The goal of this paper is to introduce theoretical background and experimental MRI method allowing disentangling contributions of heme and non-heme irons simultaneously with evaluation of tissue neuronal density in the iron-rich basal ganglia. Our approach is based on the quantitative Gradient Recalled Echo (qGRE) MRI technique that allows separation of the total R2* metric characterizing decay of GRE signal into tissue-specific (R2t*) and the baseline blood oxygen level-dependent (BOLD) contributions. A combination with the QSM data (also available from the qGRE signal phase) allowed further separation of the tissue-specific R2t* metric in a cell-specific and non-heme-iron-specific contributions. It is shown that the non-heme iron contribution to R2t* relaxation can be described with the previously developed Gaussian Phase Approximation (GPA) approach. qGRE data were obtained from 22 healthy control participants (ages 26-63 years). Results suggest that the ferritin complexes are aggregated in clusters with an average radius about 100nm comprising approximately 2600 individual ferritin units. It is also demonstrated that the concentrations of heme and non-heme iron tend to increase with age. The strongest age effect was seen in the pallidum region, where the highest age-related non-heme iron accumulation was observed.
Collapse
Affiliation(s)
- Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis, MO 63110, United States.
| | - Jie Wen
- Department of Radiology, The First Affiliated Hospital of USTC, Hefei, Anhui 230001, China
| | - Satya V V N Kothapalli
- Department of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis, MO 63110, United States
| | - Alexander L Sukstanskii
- Department of Radiology, Washington University in St. Louis, 4525 Scott Ave. Room 3216, St. Louis, MO 63110, United States
| |
Collapse
|
12
|
Liu Y, Ye Q, Zeng F, Jiang X, Cai B, Lv W, Wen J. Library-driven approach for fast implementation of the voxel spread function to correct magnetic field inhomogeneity artifacts for gradient-echo sequences. Med Phys 2021; 48:3714-3720. [PMID: 33914914 DOI: 10.1002/mp.14904] [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: 12/08/2020] [Revised: 03/15/2021] [Accepted: 04/12/2021] [Indexed: 11/10/2022] Open
Abstract
PURPOSE Previously developed Voxel Spread Function (VSF) method (Yablonskiy, et al, MRM, 2013;70:1283) provides solution to correct artifacts induced by macroscopic magnetic field inhomogeneity in the images obtained by multi-Gradient-Recalled-Echo (mGRE) techniques. The goal of this study was to develop a library-driven approach for fast VSF implementation. METHODS The VSF approach describes the contribution of the magnetic field inhomogeneity effects on the mGRE signal decay in terms of the F-function calculated from mGRE phase and magnitude images. A pre-calculated library accounting for a variety of background field gradients caused by magnetic field inhomogeneity was used herein to speed up the calculation of F-function. Quantitative R2* maps from the mGRE data collected from two healthy volunteers were generated using the library as validation. RESULTS As compared with direct calculation of the F-function based on a voxel-wise approach, the new library-driven method substantially reduces computational time from several hours to few minutes, while, at the same time, providing similar accuracy of R2* mapping. CONCLUSION The new procedure proposed in this study provides a fast post-processing algorithm that can be incorporated in the quantitative analysis of mGRE data to account for background field inhomogeneity artifacts, thus can facilitate the applications of mGRE-based quantitative techniques in clinical practices.
Collapse
Affiliation(s)
- Ying Liu
- Department of Radiology, The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Qiong Ye
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui, China
| | - Feiyan Zeng
- Department of Radiology, The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Xiaohua Jiang
- The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Bin Cai
- Department of Radiation Oncology, Washington University in St. Louis, St. Louis, MO, USA
| | - Weifu Lv
- Department of Radiology, The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Jie Wen
- Department of Radiology, The First Affiliated Hospital of USTC (Anhui Provincial Hospital), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| |
Collapse
|
13
|
Astafiev SV, Wen J, Brody DL, Cross AH, Anokhin AP, Zinn KL, Corbetta M, Yablonskiy DA. A Novel Gradient Echo Plural Contrast Imaging Method Detects Brain Tissue Abnormalities in Patients With TBI Without Evident Anatomical Changes on Clinical MRI: A Pilot Study. Mil Med 2019; 184:218-227. [PMID: 30901451 DOI: 10.1093/milmed/usy394] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 10/10/2018] [Accepted: 11/21/2018] [Indexed: 01/06/2023] Open
Abstract
RESEARCH OBJECTIVES It is widely accepted that mild traumatic brain injury (mTBI) causes injury to the white matter, but the extent of gray matter (GM) damage in mTBI is less clear. METHODS We tested 26 civilian healthy controls and 14 civilian adult subacute-chronic mTBI patients using quantitative features of MRI-based Gradient Echo Plural Contrast Imaging (GEPCI) technique. GEPCI data were reconstructed using previously developed algorithms allowing the separation of R2t*, a cellular-specific part of gradient echo MRI relaxation rate constant, from global R2* affected by BOLD effect and background gradients. RESULTS Single-subject voxel-wise analysis (comparing each mTBI patient to the sample of 26 control subjects) revealed GM abnormalities that were not visible on standard MRI images (T1w and T2w). Analysis of spatial overlap for voxels with low R2t* revealed tissue abnormalities in multiple GM regions, especially in the frontal and temporal regions, that are frequently damaged after mTBI. The left posterior insula was the region with abnormalities found in the highest proportion (50%) of mTBI patients. CONCLUSIONS Our data suggest that GEPCI quantitative R2t* metric has potential to detect abnormalities in GM cellular integrity in individual TBI patients, including abnormalities that are not detectable by a standard clinical MRI.
Collapse
Affiliation(s)
- Serguei V Astafiev
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO.,Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8134, St. Louis, MO
| | - Jie Wen
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO
| | - David L Brody
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8111, St. Louis, MO.,Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD
| | - Anne H Cross
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8111, St. Louis, MO
| | - Andrey P Anokhin
- Department of Psychiatry, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8134, St. Louis, MO
| | - Kristina L Zinn
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8111, St. Louis, MO
| | - Maurizio Corbetta
- Department of Neurology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8111, St. Louis, MO.,Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Palazzina Neuroscienze, Via Giustiniani, 2, Padova, Italy
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, 660 S. Euclid Ave, Campus Box 8225, St. Louis, MO
| |
Collapse
|
14
|
Pur DR, Eagleson RA, de Ribaupierre A, Mella N, de Ribaupierre S. Moderating Effect of Cortical Thickness on BOLD Signal Variability Age-Related Changes. Front Aging Neurosci 2019; 11:46. [PMID: 30914944 PMCID: PMC6422923 DOI: 10.3389/fnagi.2019.00046] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2018] [Accepted: 02/18/2019] [Indexed: 11/13/2022] Open
Abstract
The time course of neuroanatomical structural and functional measures across the lifespan is commonly reported in association with aging. Blood oxygen-level dependent signal variability, estimated using the standard deviation of the signal, or "BOLDSD," is an emerging metric of variability in neural processing, and has been shown to be positively correlated with cognitive flexibility. Generally, BOLDSD is reported to decrease with aging, and is thought to reflect age-related cognitive decline. Additionally, it is well established that normative aging is associated with structural changes in brain regions, and that these predict functional decline in various cognitive domains. Nevertheless, the interaction between alterations in cortical morphology and BOLDSD changes has not been modeled quantitatively. The objective of the current study was to investigate the influence of cortical morphology metrics [i.e., cortical thickness (CT), gray matter (GM) volume, and cortical area (CA)] on age-related BOLDSD changes by treating these cortical morphology metrics as possible physiological confounds using linear mixed models. We studied these metrics in 28 healthy older subjects scanned twice at approximately 2.5 years interval. Results show that BOLDSD is confounded by cortical morphology metrics. Respectively, changes in CT but not GM volume nor CA, show a significant interaction with BOLDSD alterations. Our study highlights that CT changes should be considered when evaluating BOLDSD alternations in the lifespan.
Collapse
Affiliation(s)
- Daiana R. Pur
- School of Biomedical Engineering, Western University, London, ON, Canada
| | - Roy A. Eagleson
- School of Biomedical Engineering, Western University, London, ON, Canada
- Department of Electrical and Computer Engineering, Western University, London, ON, Canada
| | | | - Nathalie Mella
- Department of Psychology, University of Geneva, Geneva, Switzerland
| | - Sandrine de Ribaupierre
- School of Biomedical Engineering, Western University, London, ON, Canada
- Department of Clinical Neurological Sciences, Schulich School of Medicine, Western University, London, ON, Canada
| |
Collapse
|
15
|
Ruuth R, Kuusela L, Mäkelä T, Melkas S, Korvenoja A. Comparison of reconstruction and acquisition choices for quantitative T2* maps and synthetic contrasts. Eur J Radiol Open 2019; 6:42-48. [PMID: 30619919 PMCID: PMC6314103 DOI: 10.1016/j.ejro.2018.12.006] [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: 08/10/2018] [Revised: 12/19/2018] [Accepted: 12/19/2018] [Indexed: 11/23/2022] Open
Abstract
Phase images have artifacts if reconstructed with a vendor’s sum of squares mode. Quantitative T2* values can be obtained from DICOM data instead of k-space data. Reconstruction from DICOM data does not reduce white matter/gray matter contrast.
Aim and scope A Gradient Echo Plural Contrast Imaging technique (GEPCI) is a post-processing method, which can be used to obtain quantitative T2* values and generate multiple synthetic contrasts from a single acquisition. However, scan duration and image reconstruction from k-space data present challenges in a clinical workflow. This study aimed at optimizing image reconstruction and acquisition duration to facilitate a post-processing method for synthetic image contrast creation in clinical settings. Materials and methods This study consists of tests using the American College of Radiology (ACR) image quality phantom, two healthy volunteers, four mild traumatic brain injury patients and four small vessel disease patients. The measurements were carried out on a 3.0 T scanner with multiple echo times. Reconstruction from k-space data and DICOM data with two different coil-channel combination modes were investigated. Partial Fourier techniques were tested to optimize the scanning time. Conclusions Sum of squares coil-channel combination produced artifacts in phase images, but images created with adaptive combination were artifact-free. The voxel-wise median signed difference of T2* between the vendor’s adaptive channel combination and k-space reconstruction modes was 2.9 ± 0.7 ms for white matter and 4.5 ± 0.6 ms for gray matter. Relative white matter/gray matter contrast of all synthetic images and contrast-to-noise ratio of synthetic T1-weighted images were almost equal between reconstruction modes. Our results indicate that synthetic contrasts can be generated from the vendor’s DICOM data with the adaptive combination mode without affecting the quantitative T2* values or white matter/gray matter contrast.
Collapse
Affiliation(s)
- Riikka Ruuth
- HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland
- Department of Physics, Faculty of Science, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland
- Corresponding author at: HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland.
| | - Linda Kuusela
- HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland
- Department of Physics, Faculty of Science, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland
| | - Teemu Mäkelä
- HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland
- Department of Physics, Faculty of Science, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland
| | - Susanna Melkas
- Clinical Neurosciences, Neurology, University of Helsinki and Helsinki University Hospital, P.O. Box 302, FI-00029, HUS, Finland
| | - Antti Korvenoja
- HUS Medical Imaging Center, Radiology, University of Helsinki and Helsinki University Hospital, P.O. Box 340, FI-00029, HUS, Finland
| |
Collapse
|
16
|
Microstructural imaging of human neocortex in vivo. Neuroimage 2018; 182:184-206. [DOI: 10.1016/j.neuroimage.2018.02.055] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Revised: 02/13/2018] [Accepted: 02/26/2018] [Indexed: 12/12/2022] Open
|
17
|
Abstract
fMRI revolutionized neuroscience by allowing in vivo real-time detection of human brain activity. While the nature of the fMRI signal is understood as resulting from variations in the MRI signal due to brain-activity-induced changes in the blood oxygenation level (BOLD effect), these variations constitute a very minor part of a baseline MRI signal. Hence, the fundamental (and not addressed) questions are how underlying brain cellular composition defines this baseline MRI signal and how a baseline MRI signal relates to fMRI. Herein we investigate these questions by using a multimodality approach that includes quantitative gradient recalled echo (qGRE), volumetric and functional connectivity MRI, and gene expression data from the Allen Human Brain Atlas. We demonstrate that in vivo measurement of the major baseline component of a GRE signal decay rate parameter (R2t*) provides a unique genetic perspective into the cellular constituents of the human cortex and serves as a previously unidentified link between cortical tissue composition and fMRI signal. Data show that areas of the brain cortex characterized by higher R2t* have high neuronal density and have stronger functional connections to other brain areas. Interestingly, these areas have a relatively smaller concentration of synapses and glial cells, suggesting that myelinated cortical axons are likely key cortical structures that contribute to functional connectivity. Given these associations, R2t* is expected to be a useful signal in assessing microstructural changes in the human brain during development and aging in health and disease.
Collapse
|
18
|
Xiang B, Wen J, Cross AH, Yablonskiy DA. Single scan quantitative gradient recalled echo MRI for evaluation of tissue damage in lesions and normal appearing gray and white matter in multiple sclerosis. J Magn Reson Imaging 2018; 49:487-498. [PMID: 30155934 DOI: 10.1002/jmri.26218] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Accepted: 05/22/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Multiple sclerosis (MS) is a chronic disease affecting the human central nervous system (CNS) and leading to neurologic disability. Although conventional MRI techniques can readily detect focal white matter (WM) lesions, it remains challenging to quantify tissue damage in normal-appearing gray matter (GM) and WM. PURPOSE To demonstrate that a new MRI biomarker, R2t*, can provide quantitative analysis of tissue damage across the brain in MS patients in a single scan. STUDY TYPE Prospective. SUBJECTS Forty-four MS patients and 19 healthy controls (HC). FIELD STRENGTH/SEQUENCE 3T, quantitative gradient-recalled-echo (qGRE), Magnetization-prepared rapid gradient-echo, fluid-attenuated inversion recovery. ASSESSMENT Severity of tissue damage was assessed by reduced R2t*. Tissue atrophy was assessed by cortical thickness and cervical spinal cord cross-sectional area (CSA). Multiple Sclerosis Functional Composite was used for clinical assessment. RESULTS R2t* in cortical GM was more sensitive to MS damage than cortical atrophy. Using more than two standard deviations (SD) reduction versus age-matched HC as the cutoff, 48% of MS patients showed lower R2t*, versus only 9% with lower cortical thickness. Significant correlations between severities of tissue injury were identified among 1) upper cervical cord and several cortical regions, including motor cortex (P < 0.001), and 2) adjacent regions of GM and subcortical WM (P < 0.001). R2t*-defined tissue cellular damage in cortical GM was greater relative to adjacent WM. Reductions in cortical R2t* correlated with cognitive impairment (P < 0.01). Motor-related clinical signs correlated most with cervical cord CSA (P < 0.001). DATA CONCLUSION Reductions in R2t* within cortical GM was more sensitive to tissue damage than atrophy, potentially allowing a reduced sample size in clinical trials. R2t* together with structural morphometry suggested topographic patterns of regions showing correlated tissue damage throughout the brain and the cervical spinal cord of MS patients. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:487-498.
Collapse
Affiliation(s)
- Biao Xiang
- Department of Chemistry, Washington University, St. Louis, Missouri, USA
| | - Jie Wen
- Department of Radiology, Washington University, St. Louis, Missouri, USA
| | - Anne H Cross
- Department of Neurology, Washington University, St. Louis, Missouri, USA
| | | |
Collapse
|
19
|
Wen J, Yablonskiy DA, Salter A, Cross AH. Limbic system damage in MS: MRI assessment and correlations with clinical testing. PLoS One 2017; 12:e0187915. [PMID: 29121642 PMCID: PMC5679614 DOI: 10.1371/journal.pone.0187915] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Accepted: 10/27/2017] [Indexed: 12/21/2022] Open
Abstract
Volume loss in some limbic region structures has been observed in multiple sclerosis (MS) patients. However, in vivo evaluation of existing tissue cellular microstructure integrity has received less attention. The goal of studies reported here was to quantitatively assess loss of limbic system volumes and tissue integrity, and to evaluate associations of these measures with cognitive and physical dysfunction in MS patients. Thirty-one healthy controls (HC) and 80 MS patients, including 32 relapsing remitting (RRMS), 32 secondary progressive (SPMS) and 16 primary progressive (PPMS), participated in this study. Tissue cellular integrity was evaluated by means of recently introduced tissue-specific parameter R2t* that was calculated from multi-gradient-echo MRI signals using a recently developed method that separates R2t* from BOLD (blood oxygen level dependent) contributions to GRE signal decay rate constant (R2*), and accounting for physiological fluctuations and artifacts from background gradients. Volumes in limbic system regions, normalized to skull size (NV), were measured from standard MPRAGE images. MS patients had lower R2t* and smaller normalized volumes in the hippocampus, amygdala, and several other limbic system regions, compared to HC. Alterations in R2t* of several limbic system regions correlated with clinical and neurocognitive test scores in MS patients. In contrast, smaller normalized volumes in MS were only correlated with neurocognitive test scores in the hippocampus and amygdala. This study reports the novel finding that R2t*, a measure that estimates tissue integrity, is more sensitive to tissue damage in limbic system structures than is atrophy. R2t* measurements can serve as a biomarker that is distinct from and complementary to volume measurements.
Collapse
Affiliation(s)
- Jie Wen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Dmitriy A. Yablonskiy
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Amber Salter
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, United States of America
| | - Anne H. Cross
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States of America
- * E-mail:
| |
Collapse
|
20
|
Giacalone G, Zanoletti M, Contini D, Re R, Spinelli L, Roveri L, Torricelli A. Cerebral time domain-NIRS: reproducibility analysis, optical properties, hemoglobin species and tissue oxygen saturation in a cohort of adult subjects. BIOMEDICAL OPTICS EXPRESS 2017; 8:4987-5000. [PMID: 29188096 PMCID: PMC5695946 DOI: 10.1364/boe.8.004987] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Revised: 09/14/2017] [Accepted: 09/22/2017] [Indexed: 05/20/2023]
Abstract
The reproducibility of cerebral time-domain near-infrared spectroscopy (TD-NIRS) has not been investigated so far. Besides, reference intervals of cerebral optical properties, of absolute concentrations of deoxygenated-hemoglobin (HbR), oxygenated-hemoglobin (HbO), total hemoglobin (HbT) and tissue oxygen saturation (StO2) and their variability have not been reported. We have addressed these issues on a sample of 88 adult healthy subjects. TD-NIRS measurements at 690, 785, 830 nm were fitted with the diffusion model for semi-infinite homogenous media. Reproducibility, performed on 3 measurements at 5 minutes intervals, ranges from 1.8 to 6.9% for each of the hemoglobin species. The mean ± SD global values of HbR, HbO, HbT, StO2 are respectively 24 ± 7 μM, 33.3 ± 9.5 μM, 57.4 ± 15.8 μM, 58 ± 4.2%. StO2 displays the narrowest range of variability across brain regions.
Collapse
Affiliation(s)
- Giacomo Giacalone
- San Raffaele Scientific Institute, Neurology Department, Via Olgettina 60, 20132, Milan, Italy
- University “Vita-Salute” San Raffaele, Via Olgettina 60, 20132, Milan, Italy
| | - Marta Zanoletti
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
| | - Davide Contini
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
| | - Rebecca Re
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
| | - Lorenzo Spinelli
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
| | - Luisa Roveri
- San Raffaele Scientific Institute, Neurology Department, Via Olgettina 60, 20132, Milan, Italy
- University “Vita-Salute” San Raffaele, Via Olgettina 60, 20132, Milan, Italy
- These authors contributed equally to this paper
| | - Alessandro Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
- Istituto di Fotonica e Nanotecnologie, Consiglio Nazionale delle Ricerche, Piazza Leonardo da Vinci 32, 20133 Milan, Italy
- These authors contributed equally to this paper
| |
Collapse
|
21
|
O'Callaghan J, Holmes H, Powell N, Wells JA, Ismail O, Harrison IF, Siow B, Johnson R, Ahmed Z, Fisher A, Meftah S, O'Neill MJ, Murray TK, Collins EC, Shmueli K, Lythgoe MF. Tissue magnetic susceptibility mapping as a marker of tau pathology in Alzheimer's disease. Neuroimage 2017; 159:334-345. [PMID: 28797738 PMCID: PMC5678288 DOI: 10.1016/j.neuroimage.2017.08.003] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 07/27/2017] [Accepted: 08/01/2017] [Indexed: 01/15/2023] Open
Abstract
Alzheimer's disease is connected to a number of other neurodegenerative conditions, known collectively as 'tauopathies', by the presence of aggregated tau protein in the brain. Neuroinflammation and oxidative stress in AD are associated with tau pathology and both the breakdown of axonal sheaths in white matter tracts and excess iron accumulation grey matter brain regions. Despite the identification of myelin and iron concentration as major sources of contrast in quantitative susceptibility maps of the brain, the sensitivity of this technique to tau pathology has yet to be explored. In this study, we perform Quantitative Susceptibility Mapping (QSM) and T2* mapping in the rTg4510, a mouse model of tauopathy, both in vivo and ex vivo. Significant correlations were observed between histological measures of myelin content and both mean regional magnetic susceptibility and T2* values. These results suggest that magnetic susceptibility is sensitive to tissue myelin concentrations across different regions of the brain. Differences in magnetic susceptibility were detected in the corpus callosum, striatum, hippocampus and thalamus of the rTg4510 mice relative to wild type controls. The concentration of neurofibrillary tangles was found to be low to intermediate in these brain regions indicating that QSM may be a useful biomarker for early stage detection of tau pathology in neurodegenerative diseases.
Collapse
Affiliation(s)
- J O'Callaghan
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, UCL, UK.
| | - H Holmes
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, UCL, UK
| | - N Powell
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, UCL, UK
| | - J A Wells
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, UCL, UK
| | - O Ismail
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, UCL, UK
| | - I F Harrison
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, UCL, UK
| | - B Siow
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, UCL, UK
| | - R Johnson
- Eli Lilly and Company, 355 E Merrill Street, Dock 48, Indianapolis, IN, 46225, USA
| | - Z Ahmed
- Eli Lilly & Co. Ltd, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - A Fisher
- Eli Lilly & Co. Ltd, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - S Meftah
- Eli Lilly & Co. Ltd, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - M J O'Neill
- Eli Lilly & Co. Ltd, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - T K Murray
- Eli Lilly & Co. Ltd, Erl Wood Manor, Windlesham, Surrey, GU20 6PH, UK
| | - E C Collins
- Eli Lilly and Company, 355 E Merrill Street, Dock 48, Indianapolis, IN, 46225, USA
| | - K Shmueli
- Department of Medical Physics and Biomedical Engineering, UCL, UK
| | - M F Lythgoe
- UCL Centre for Advanced Biomedical Imaging, Division of Medicine, UCL, UK
| |
Collapse
|
22
|
Ayton S, Fazlollahi A, Bourgeat P, Raniga P, Ng A, Lim YY, Diouf I, Farquharson S, Fripp J, Ames D, Doecke J, Desmond P, Ordidge R, Masters CL, Rowe CC, Maruff P, Villemagne VL, Salvado O, Bush AI. Cerebral quantitative susceptibility mapping predicts amyloid-β-related cognitive decline. Brain 2017; 140:2112-2119. [PMID: 28899019 DOI: 10.1093/brain/awx137] [Citation(s) in RCA: 188] [Impact Index Per Article: 26.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Accepted: 05/07/2017] [Indexed: 11/14/2022] Open
Abstract
See Derry and Kent (doi:10.1093/awx167) for a scientific commentary on this article.The large variance in cognitive deterioration in subjects who test positive for amyloid-β by positron emission tomography indicates that convergent pathologies, such as iron accumulation, might combine with amyloid-β to accelerate Alzheimer's disease progression. Here, we applied quantitative susceptibility mapping, a relatively new magnetic resonance imaging method sensitive to tissue iron, to assess the relationship between iron, amyloid-β load, and cognitive decline in 117 subjects who underwent baseline magnetic resonance imaging and amyloid-β positron emission tomography from the Australian Imaging, Biomarkers and Lifestyle study (AIBL). Cognitive function data were collected every 18 months for up to 6 years from 100 volunteers who were either cognitively normal (n = 64) or diagnosed with mild cognitive impairment (n = 17) or Alzheimer's disease (n = 19). Among participants with amyloid pathology (n = 45), higher hippocampal quantitative susceptibility mapping levels predicted accelerated deterioration in composite cognition tests for episodic memory [β(standard error) = -0.169 (0.034), P = 9.2 × 10-7], executive function [β(standard error) = -0.139 (0.048), P = 0.004), and attention [β(standard error) = -0.074 (0.029), P = 0.012]. Deteriorating performance in a composite of language tests was predicted by higher quantitative susceptibility mapping levels in temporal lobe [β(standard error) = -0.104 (0.05), P = 0.036] and frontal lobe [β(standard error) = -0.154 (0.055), P = 0.006]. These findings indicate that brain iron might combine with amyloid-β to accelerate clinical progression and that quantitative susceptibility mapping could be used in combination with amyloid-β positron emission tomography to stratify individuals at risk of decline.
Collapse
Affiliation(s)
- Scott Ayton
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia
| | - Amir Fazlollahi
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Pierrick Bourgeat
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Parnesh Raniga
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Amanda Ng
- Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, Australia
| | - Yen Ying Lim
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia
| | - Ibrahima Diouf
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia
| | - Shawna Farquharson
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, Australia
| | - Jurgen Fripp
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - David Ames
- National Ageing Research Institute, Parkville, Victoria, Australia.,University of Melbourne Academic Unit for the Psychiatry of Old Age, Parkville, Australia
| | - James Doecke
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Patricia Desmond
- Department of Medicine and Radiology, Royal Melbourne Hospital, University of Melbourne, Parkville, Australia
| | - Roger Ordidge
- Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, Australia
| | - Colin L Masters
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Christopher C Rowe
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Austin Health, Heidelberg, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Cogstate Ltd, Melbourne, Australia
| | - Victor L Villemagne
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Austin Health, Heidelberg, Australia
| | | | - Olivier Salvado
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Brisbane, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| | - Ashley I Bush
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia.,Cooperative Research Centre for Mental Health, Parkville, Australia
| |
Collapse
|
23
|
Zhao Y, Raichle ME, Wen J, Benzinger TL, Fagan AM, Hassenstab J, Vlassenko AG, Luo J, Cairns NJ, Christensen JJ, Morris JC, Yablonskiy DA. In vivo detection of microstructural correlates of brain pathology in preclinical and early Alzheimer Disease with magnetic resonance imaging. Neuroimage 2016; 148:296-304. [PMID: 27989773 DOI: 10.1016/j.neuroimage.2016.12.026] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Revised: 12/08/2016] [Accepted: 12/10/2016] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Alzheimer disease (AD) affects at least 5 million individuals in the USA alone stimulating an intense search for disease prevention and treatment therapies as well as for diagnostic techniques allowing early identification of AD during a long pre-symptomatic period that can be used for the initiation of prevention trials of disease-modifying therapies in asymptomatic individuals. METHODS Our approach to developing such techniques is based on the Gradient Echo Plural Contrast Imaging (GEPCI) technique that provides quantitative in vivo measurements of several brain-tissue-specific characteristics of the gradient echo MRI signal (GEPCI metrics) that depend on the integrity of brain tissue cellular structure. Preliminary data were obtained from 34 participants selected from the studies of aging and dementia at the Knight Alzheimer's Disease Research Center at Washington University in St. Louis. Cognitive status was operationalized with the Clinical Dementia Rating (CDR) scale. The participants, assessed as cognitively normal (CDR=0; n=23) or with mild AD dementia (CDR=0.5 or 1; n=11) underwent GEPCI MRI, a collection of cognitive performance tests and CSF amyloid (Aβ) biomarker Aβ42. A subset of 19 participants also underwent PET PiB studies to assess their brain Aβ burden. According to the Aβ status, cognitively normal participants were divided into normal (Aβ negative; n=13) and preclinical (Aβ positive; n=10) groups. RESULTS GEPCI quantitative measurements demonstrated significant differences between all the groups: normal and preclinical, normal and mild AD, and preclinical and mild AD. GEPCI quantitative metrics characterizing tissue cellular integrity in the hippocampus demonstrated much stronger correlations with psychometric tests than the hippocampal atrophy. Importantly, GEPCI-determined changes in the hippocampal tissue cellular integrity were detected even in the hippocampal areas not affected by the atrophy. Our studies also uncovered strong correlations between GEPCI brain tissue metrics and beta-amyloid (Aβ) burden defined by positron emission tomography (PET) - the current in vivo gold standard for detection of cortical Aβ, thus supporting GEPCI as a potential surrogate marker for Aβ imaging - a known biomarker of early AD. Remarkably, the data show significant correlations not only in the areas of high Aβ accumulation (e.g. precuneus) but also in some areas of medial temporal lobe (e.g. parahippocampal cortex), where Aβ accumulation is relatively low. CONCLUSION We have demonstrated that GEPCI provides a new approach for the in vivo evaluation of AD-related tissue pathology in the preclinical and early symptomatic stages of AD. Since MRI is a widely available technology, the GEPCI surrogate markers of AD pathology have a potential for improving the quality of AD diagnostic, and the evaluation of new disease-modifying therapies.
Collapse
Affiliation(s)
- Yue Zhao
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Marcus E Raichle
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jie Wen
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Tammie L Benzinger
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Andrei G Vlassenko
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jie Luo
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Nigel J Cairns
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jon J Christensen
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - John C Morris
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA; Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Dmitriy A Yablonskiy
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA.
| |
Collapse
|