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Yao M, Wei Z, Nielsen JOS, Kakazu A, Ouyang Y, Li R, Chu T, Scafidi S, Lu H, Aggarwal M, Duan W. Senolytic therapy preserves blood-brain barrier integrity and promotes microglia homeostasis in a tauopathy model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.25.586662. [PMID: 38585805 PMCID: PMC10996647 DOI: 10.1101/2024.03.25.586662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Cellular senescence, characterized by expressing the cell cycle inhibitory proteins, is evident in driving age-related diseases. Senescent cells play a crucial role in the initiation and progression of tau-mediated pathology, suggesting that targeting cell senescence offers a therapeutic potential for treating tauopathy associated diseases. This study focuses on identifying non-invasive biomarkers and validating their responses to a well-characterized senolytic therapy combining dasatinib and quercetin (D+Q), in a widely used tauopathy mouse model, PS19. We employed human-translatable MRI measures, including water extraction with phase-contrast arterial spin tagging (WEPCAST) MRI, T2 relaxation under spin tagging (TRUST), longitudinally assessed brain physiology and high-resolution structural MRI evaluated the brain regional volumes in PS19 mice. Our data reveal increased BBB permeability, decreased oxygen extraction fraction, and brain atrophy in 9-month-old PS19 mice compared to their littermate controls. (D+Q) treatment effectively preserves BBB integrity, rescues cerebral oxygen hypometabolism, attenuates brain atrophy, and alleviates tau hyperphosphorylation in PS19 mice. Mechanistically, D+Q treatment induces a shift of microglia from a disease-associated to a homeostatic state, reducing a senescence-like microglial phenotype marked by increased p16/INK4a. D+Q-treated PS19 mice exhibit enhanced cue-associated cognitive performance in the tracing fear conditioning test compared to the vehicle-treated littermates, implying improved cognitive function by D+Q treatment. Our results pave the way for application of senolytic treatment as well as these noninvasive MRI biomarkers in clinical trials in tauopathy associated neurological disorders.
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Wei Z, Li Y, Bibic A, Duan W, Xu J, Lu H. Toward accurate cerebral blood flow estimation in mice after accounting for anesthesia. Front Physiol 2023; 14:1169622. [PMID: 37123257 PMCID: PMC10130671 DOI: 10.3389/fphys.2023.1169622] [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: 02/19/2023] [Accepted: 04/03/2023] [Indexed: 05/02/2023] Open
Abstract
Purpose: To improve the accuracy of cerebral blood flow (CBF) measurement in mice by accounting for the anesthesia effects. Methods: The dependence of CBF on anesthesia dose and time was investigated by simultaneously measuring respiration rate (RR) and heart rate (HR) under four different anesthetic regimens. Quantitative CBF was measured by a phase-contrast (PC) MRI technique. RR was evaluated with a mouse monitoring system (MouseOX) while HR was determined using an ultrashort-TE MRI sequence. CBF, RR, and HR were recorded dynamically with a temporal resolution of 1 min in a total of 19 mice. Linear regression models were used to investigate the relationships among CBF, anesthesia dose, RR, and HR. Results: CBF, RR, and HR all showed a significant dependence on anesthesia dose (p < 0.0001). However, the dose in itself was insufficient to account for the variations in physiological parameters, in that they showed a time-dependent change even for a constant dose. RR and HR together can explain 52.6% of the variations in CBF measurements, which is greater than the amount of variance explained by anesthesia dose (32.4%). Based on the multi-parametric regression results, a model was proposed to correct the anesthesia effects in mouse CBF measurements, specificallyC B F c o r r e c t e d = C B F + 0.58 R R - 0.41 H R - 32.66 D o s e . We also reported awake-state CBF in mice to be 142.0 ± 8.8 mL/100 g/min, which is consistent with the model-predicted value. Conclusion: The accuracy of CBF measurement in mice can be improved by using a correction model that accounts for respiration rate, heart rate, and anesthesia dose.
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Affiliation(s)
- Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, United States
| | - Yuguo Li
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, United States
| | - Adnan Bibic
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, United States
| | - Wenzhen Duan
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, United States
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, United States
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States
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Wei Z, Liu H, Lin Z, Yao M, Li R, Liu C, Li Y, Xu J, Duan W, Lu H. Non-contrast assessment of blood-brain barrier permeability to water in mice: An arterial spin labeling study at cerebral veins. Neuroimage 2023; 268:119870. [PMID: 36640948 PMCID: PMC9908858 DOI: 10.1016/j.neuroimage.2023.119870] [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: 08/23/2022] [Revised: 11/15/2022] [Accepted: 01/10/2023] [Indexed: 01/13/2023] Open
Abstract
Blood-brain barrier (BBB) plays a critical role in protecting the brain from toxins and pathogens. However, in vivo tools to assess BBB permeability are scarce and often require the use of exogenous contrast agents. In this study, we aimed to develop a non-contrast arterial-spin-labeling (ASL) based MRI technique to estimate BBB permeability to water in mice. By determining the relative fraction of labeled water spins that were exchanged into the brain tissue as opposed to those that remained in the cerebral veins, we estimated indices of global BBB permeability to water including water extraction fraction (E) and permeability surface-area product (PS). First, using multiple post-labeling delay ASL experiments, we estimated the bolus arrival time (BAT) of the labeled spins to reach the great vein of Galen (VG) to be 691.2 ± 14.5 ms (N = 5). Next, we investigated the dependence of the VG ASL signal on labeling duration and identified an optimal imaging protocol with a labeling duration of 1200 ms and a PLD of 100 ms. Quantitative E and PS values in wild-type mice were found to be 59.9 ± 3.2% and 260.9 ± 18.9 ml/100 g/min, respectively. In contrast, mice with Huntington's disease (HD) revealed a significantly higher E (69.7 ± 2.4%, P = 0.026) and PS (318.1 ± 17.1 ml/100 g/min, P = 0.040), suggesting BBB breakdown in this mouse model. Reproducibility studies revealed a coefficient-of-variation (CoV) of 4.9 ± 1.7% and 6.1 ± 1.2% for E and PS, respectively. The proposed method may open new avenues for preclinical research on pathophysiological mechanisms of brain diseases and therapeutic trials in animal models.
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Affiliation(s)
- Zhiliang Wei
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600N. Wolfe Street, Park 326, Baltimore, MD 21287, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA.
| | - Hongshuai Liu
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 North Wolfe Street, CMSC 8-121, Baltimore, MD 21287, USA
| | - Zixuan Lin
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600N. Wolfe Street, Park 326, Baltimore, MD 21287, USA
| | - Minmin Yao
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 North Wolfe Street, CMSC 8-121, Baltimore, MD 21287, USA
| | - Ruoxuan Li
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 North Wolfe Street, CMSC 8-121, Baltimore, MD 21287, USA
| | - Chang Liu
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 North Wolfe Street, CMSC 8-121, Baltimore, MD 21287, USA
| | - Yuguo Li
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600N. Wolfe Street, Park 326, Baltimore, MD 21287, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Jiadi Xu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600N. Wolfe Street, Park 326, Baltimore, MD 21287, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Wenzhen Duan
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, 600 North Wolfe Street, CMSC 8-121, Baltimore, MD 21287, USA; The Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 600N. Wolfe Street, Park 326, Baltimore, MD 21287, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Jiang D, Lu H. Cerebral oxygen extraction fraction MRI: Techniques and applications. Magn Reson Med 2022; 88:575-600. [PMID: 35510696 PMCID: PMC9233013 DOI: 10.1002/mrm.29272] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 03/20/2022] [Accepted: 03/29/2022] [Indexed: 12/20/2022]
Abstract
The human brain constitutes 2% of the body's total mass but uses 20% of the oxygen. The rate of the brain's oxygen utilization can be derived from a knowledge of cerebral blood flow and the oxygen extraction fraction (OEF). Therefore, OEF is a key physiological parameter of the brain's function and metabolism. OEF has been suggested to be a useful biomarker in a number of brain diseases. With recent advances in MRI techniques, several MRI-based methods have been developed to measure OEF in the human brain. These MRI OEF techniques are based on the T2 of blood, the blood signal phase, the magnetic susceptibility of blood-containing voxels, the effect of deoxyhemoglobin on signal behavior in extravascular tissue, and the calibration of the BOLD signal using gas inhalation. Compared to 15 O PET, which is considered the "gold standard" for OEF measurement, MRI-based techniques are non-invasive, radiation-free, and are more widely available. This article provides a review of these emerging MRI-based OEF techniques. We first briefly introduce the role of OEF in brain oxygen homeostasis. We then review the methodological aspects of different categories of MRI OEF techniques, including their signal mechanisms, acquisition methods, and data analyses. The strengths and limitations of the techniques are discussed. Finally, we review key applications of these techniques in physiological and pathological conditions.
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Affiliation(s)
- Dengrong Jiang
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hanzhang Lu
- The Russell H. Morgan Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
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Xu M, Bo B, Pei M, Chen Y, Shu CY, Qin Q, Hirschler L, Warnking JM, Barbier EL, Wei Z, Lu H, Herman P, Hyder F, Liu ZJ, Liang Z, Thompson GJ. High-resolution relaxometry-based calibrated fMRI in murine brain: Metabolic differences between awake and anesthetized states. J Cereb Blood Flow Metab 2022; 42:811-825. [PMID: 34910894 PMCID: PMC9014688 DOI: 10.1177/0271678x211062279] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Functional magnetic resonance imaging (fMRI) techniques using the blood-oxygen level-dependent (BOLD) signal have shown great potential as clinical biomarkers of disease. Thus, using these techniques in preclinical rodent models is an urgent need. Calibrated fMRI is a promising technique that can provide high-resolution mapping of cerebral oxygen metabolism (CMRO2). However, calibrated fMRI is difficult to use in rodent models for several reasons: rodents are anesthetized, stimulation-induced changes are small, and gas challenges induce noisy CMRO2 predictions. We used, in mice, a relaxometry-based calibrated fMRI method which uses cerebral blood flow (CBF) and the BOLD-sensitive magnetic relaxation component, R2', the same parameter derived in the deoxyhemoglobin-dilution model of calibrated fMRI. This method does not use any gas challenges, which we tested on mice in both awake and anesthetized states. As anesthesia induces a whole-brain change, our protocol allowed us to overcome the former limitations of rodent studies using calibrated fMRI. We revealed 1.5-2 times higher CMRO2, dependent upon brain region, in the awake state versus the anesthetized state. Our results agree with alternative measurements of whole-brain CMRO2 in the same mice and previous human anesthesia studies. The use of calibrated fMRI in rodents has much potential for preclinical fMRI.
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Affiliation(s)
- Mengyang Xu
- iHuman Institute, ShanghaiTech University, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, China.,Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Binshi Bo
- CAS Center for Excellence in Brain Sciences and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Mengchao Pei
- CAS Center for Excellence in Brain Sciences and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Yuyan Chen
- CAS Center for Excellence in Brain Sciences and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Christina Y Shu
- Biomedical Engineering, Yale University, New Haven, CT, USA.,Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA
| | - Qikai Qin
- iHuman Institute, ShanghaiTech University, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, China.,Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China
| | - Lydiane Hirschler
- Grenoble Institut des Neurosciences, Inserm, Univ. Grenoble Alpes, Grenoble, France.,C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jan M Warnking
- Grenoble Institut des Neurosciences, Inserm, Univ. Grenoble Alpes, Grenoble, France
| | - Emmanuel L Barbier
- Grenoble Institut des Neurosciences, Inserm, Univ. Grenoble Alpes, Grenoble, France
| | - Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Peter Herman
- Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA.,Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA.,Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Fahmeed Hyder
- Biomedical Engineering, Yale University, New Haven, CT, USA.,Magnetic Resonance Research Center (MRRC), Yale University, New Haven, CT, USA.,Quantitative Neuroscience with Magnetic Resonance (QNMR) Core Center, Yale University, New Haven, CT, USA.,Radiology and Biomedical Imaging, Yale University, New Haven, CT, USA
| | - Zhi-Jie Liu
- iHuman Institute, ShanghaiTech University, Shanghai, China.,School of Life Science and Technology, ShanghaiTech University, Shanghai, China.,Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China
| | - Zhifeng Liang
- CAS Center for Excellence in Brain Sciences and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China
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Wei Z, Xu J, Chen L, Hirschler L, Barbier EL, Li T, Wong PC, Lu H. Brain metabolism in tau and amyloid mouse models of Alzheimer's disease: An MRI study. NMR IN BIOMEDICINE 2021; 34:e4568. [PMID: 34050996 PMCID: PMC9574887 DOI: 10.1002/nbm.4568] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 05/17/2021] [Accepted: 05/20/2021] [Indexed: 06/12/2023]
Abstract
Alzheimer's disease (AD) is the leading cause of cognitive impairment and dementia in elderly individuals. According to the current biomarker framework for "unbiased descriptive classification", biomarkers of neurodegeneration, "N", constitute a critical component in the tri-category "A/T/N" system. Current biomarkers of neurodegeneration suffer from potential drawbacks such as requiring invasive lumbar puncture, involving ionizing radiation, or representing a late, irreversible marker. Recent human studies have suggested that reduced brain oxygen metabolism may be a new functional marker of neurodegeneration in AD, but the heterogeneity and the presence of mixed pathology in human patients did not allow a full understanding of the role of oxygen extraction and metabolism in AD. In this report, global brain oxygen metabolism and related physiological parameters were studied in two AD mouse models with relatively pure pathology, using advanced MRI techniques including T2 -relaxation-under-spin-tagging (TRUST) and phase contrast (PC) MRI. Additionally, regional cerebral blood flow (CBF) was determined with pseudocontinuous arterial spin labeling. Reduced global oxygen extraction fraction (by -18.7%, p = 0.008), unit-mass cerebral metabolic rate of oxygen (CMRO2 ) (by -17.4%, p = 0.04) and total CMRO2 (by -30.8%, p < 0.001) were observed in Tau4RΔK mice-referred to as the tau AD model-which manifested pronounced neurodegeneration, as measured by diminished brain volume (by -15.2%, p < 0.001). Global and regional CBF in these mice were not different from those of wild-type mice (p > 0.05), suggesting normal vascular function. By contrast, in B6;SJL-Tg [APPSWE]2576Kha (APP) mice-referred to as the amyloid AD model-no brain volume reduction, as well as relatively intact brain oxygen extraction and metabolism, were found (p > 0.05). Consistent with the imaging data, behavioral measures of walking distance were impaired in Tau4RΔK mice (p = 0.004), but not in APP mice (p = 0.88). Collectively, these findings support the hypothesis that noninvasive MRI measurement of brain oxygen metabolism may be a promising biomarker of neurodegeneration in AD.
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Affiliation(s)
- Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
| | - Lin Chen
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian, China
| | - Lydiane Hirschler
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Emmanuel L. Barbier
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, Grenoble, France
| | - Tong Li
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Philip C. Wong
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Automatic knee cartilage and bone segmentation using multi-stage convolutional neural networks: data from the osteoarthritis initiative. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:859-875. [PMID: 34101071 DOI: 10.1007/s10334-021-00934-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 05/25/2021] [Accepted: 05/26/2021] [Indexed: 10/21/2022]
Abstract
OBJECTIVES Accurate and efficient knee cartilage and bone segmentation are necessary for basic science, clinical trial, and clinical applications. This work tested a multi-stage convolutional neural network framework for MRI image segmentation. MATERIALS AND METHODS Stage 1 of the framework coarsely segments images outputting probabilities of each voxel belonging to the classes of interest: 4 cartilage tissues, 3 bones, 1 background. Stage 2 segments overlapping sub-volumes that include Stage 1 probability maps concatenated to raw image data. Using six fold cross-validation, this framework was tested on two datasets comprising 176 images [88 individuals in the Osteoarthritis Initiative (OAI)] and 60 images (15 healthy young men), respectively. RESULTS On the OAI segmentation dataset, the framework produces cartilage segmentation accuracies (Dice similarity coefficient) of 0.907 (femoral), 0.876 (medial tibial), 0.913 (lateral tibial), and 0.840 (patellar). Healthy cartilage accuracies are excellent (femoral = 0.938, medial tibial = 0.911, lateral tibial = 0.930, patellar = 0.955). Average surface distances are less than in-plane resolution. Segmentations take 91 ± 11 s per knee. DISCUSSION The framework learns to automatically segment knee cartilage tissues and bones from MR images acquired with two sequences, producing efficient, accurate quantifications at varying disease severities.
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Wei Z, Wang Q, Modi HR, Cho SM, Geocadin R, Thakor NV, Lu H. Acute-stage MRI cerebral oxygen consumption biomarkers predict 24-hour neurological outcome in a rat cardiac arrest model. NMR IN BIOMEDICINE 2020; 33:e4377. [PMID: 32662593 PMCID: PMC7541582 DOI: 10.1002/nbm.4377] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 06/15/2020] [Accepted: 06/19/2020] [Indexed: 05/13/2023]
Abstract
Brain injury following cardiac arrest (CA) is thought to be caused by a sudden loss of blood flow resulting in disruption in oxygen delivery, neural function and metabolism. However, temporal trajectories of the brain's physiology in the first few hours following CA have not been fully characterized. Furthermore, the extent to which these early measures can predict future neurological outcomes has not been determined. The present study sought to perform dynamic measurements of cerebral blood flow (CBF), oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO2 ) with MRI in the first 3 hours following the return of spontaneous circulation (ROSC) in a rat CA model. It was found that CBF, OEF and CMRO2 all revealed a time-dependent increase during the first 3 hours after the ROSC. Furthermore, the temporal trajectories of CBF and CMRO2 , but not OEF, were different across rats and related to neurologic outcomes at a later time (24 hours after the ROSC) (P < .001). Rats who manifested better outcomes revealed faster increases in CBF and CMRO2 during the acute stage. When investigating physiological parameters measured at a single time point, CBF (ρ = 0.82, P = .004) and CMRO2 (ρ = 0.80, P = .006) measured at ~ 3 hours post-ROSC were positively associated with neurologic outcome scores at 24 hours. These findings shed light on brain physiological changes following CA, and suggest that MRI measures of brain perfusion and metabolism may provide a potential biomarker to guide post-CA management.
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Affiliation(s)
- Zhiliang Wei
- Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Qihong Wang
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Center for Blood Oxygen Transport and Hemostasis, Department of Pediatrics, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Hiren R. Modi
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sung-Min Cho
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Romergryko Geocadin
- Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nitish V. Thakor
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Hanzhang Lu
- Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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Wei Z, Chen L, Hou X, van Zijl PCM, Xu J, Lu H. Age-Related Alterations in Brain Perfusion, Venous Oxygenation, and Oxygen Metabolic Rate of Mice: A 17-Month Longitudinal MRI Study. Front Neurol 2020; 11:559. [PMID: 32595596 PMCID: PMC7304368 DOI: 10.3389/fneur.2020.00559] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Accepted: 05/15/2020] [Indexed: 12/31/2022] Open
Abstract
Background: Characterization of physiological parameters of the aging brain, such as perfusion and brain metabolism, is important for understanding brain function and diseases. Aging studies on human brain have mostly been based on the cross-sectional design, while the few longitudinal studies used relatively short follow-up time compared to the lifespan. Objectives: To determine the longitudinal time courses of cerebral physiological parameters across the adult lifespan in mice. Methods: The present work examined longitudinal changes in cerebral blood flow (CBF), cerebral venous oxygenation (Yv), and cerebral metabolic rate of oxygen (CMRO2) using MRI in healthy C57BL/6 mice from 3 to 20 months of age. Each mouse received 16 imaging sessions at an ~1-month interval. Results: Significant increases with age were observed in CBF (p = 0.017) and CMRO2 (p < 0.001). Meanwhile, Yv revealed a significant decrease (p = 0.002) with a non-linear pattern (p = 0.013). The rate of change was 0.87, 2.26, and -0.24% per month for CBF, CMRO2, and Yv, respectively. On the other hand, systemic parameters such as heart rate did not show a significant age dependence (p = 0.47). No white-matter-hyperintensities (WMH) were observed on the T2-weighted image at any age of the mice. Conclusion: With age, the mouse brain revealed an increase in oxygen consumption. This observation is consistent with previous findings in humans using a cross-sectional design and suggests a degradation of the brain's energy production or utilization machinery. Cerebral perfusion remains relatively intact in aged mice, at least until 20 months of age, consistent with the absence of WMH in mice.
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Affiliation(s)
- Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Lin Chen
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Xirui Hou
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MA, United States
| | - Peter C. M. van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MA, United States
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MA, United States
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MA, United States
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Wei Z, Chen L, Lin Z, Jiang D, Xu J, Liu P, van Zijl PCM, Lu H. Optimization of phase-contrast MRI for the estimation of global cerebral blood flow of mice at 11.7T. Magn Reson Med 2018; 81:2566-2575. [PMID: 30393888 DOI: 10.1002/mrm.27592] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Revised: 10/08/2018] [Accepted: 10/13/2018] [Indexed: 01/02/2023]
Abstract
PURPOSE To optimize phase-contrast (PC) MRI for the measurement of global cerebral blood flow (CBF) in the mouse at 11.7T. METHODS We determined proper velocity encoding (VENC) for internal carotid arteries (ICAs) and vertebral arteries (VAs). Next, we optimized spatial resolution of the sequence. To shorten scan time without compromising data quality, we further optimized repetition time and developed a reduced field-of-view (FOV) scheme for ICA and VA PC MRI. Whole-brain volume was determined with T2 -weighted image to obtain unit-volume CBF. RESULTS Peak flow velocities were 13.8 ± 1.7, 14.4 ± 0.6, 6.5 ± 1.7, and 6.7 ± 1.3 cm/s for left ICA, right ICA, left VA, and right VA, respectively. Thus, VENC values of 20 and 10 cm/s were chosen for ICA and VA PC MRI, respectively. An in-plane spatial resolution of 50 × 50 μm2 was found to provide a reasonable trade-off between reducing partial-volume effects and maintaining signal-to-noise ratio. Because of the fact that saturated spins in the imaging slice are rapidly replaced by fresh spins, TR of the sequence can be decreased to as short as 15 ms without reducing signal intensity, thereby substantially lowering scan time. Moreover, reduced FOV along the phase-encoding direction was able to shorten scan time by 33.3% while maintaining measurement accuracy. With these optimizations, it took 96 seconds to evaluate CBF with a test-retest variability of approximately 5% and an inter-rater correlation of >0.95. Global unit-volume CBF was found to be 279.5 ± 11.1 mL of blood/100 ml of tissue/min. CONCLUSION We have optimized PC MRI for noninvasive quantification of blood flow in mice at 11.7T.
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Affiliation(s)
- Zhiliang Wei
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland
| | - Lin Chen
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland
| | - Zixuan Lin
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Dengrong Jiang
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Jiadi Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland
| | - Peiying Liu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland.,F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland.,Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland
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