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Xiong L, Zhang Y, He B, Zhang K, Zhu J, Lang X. Optimum Parameters in Ultrasound Coherent Plane Wave Compounding for High LPWV Estimation: Validation on Phantom and Feasibility in 10 Subjects. JOURNAL OF ULTRASOUND IN MEDICINE : OFFICIAL JOURNAL OF THE AMERICAN INSTITUTE OF ULTRASOUND IN MEDICINE 2024. [PMID: 38700113 DOI: 10.1002/jum.16469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Revised: 04/12/2024] [Accepted: 04/13/2024] [Indexed: 05/05/2024]
Abstract
OBJECTIVES The aim of this study is to determine the optimum and fine values of the number and transmission angles of tilted plane waves for coherent plane-wave compounding (CPWC)-based high local pulse wave velocity (LPWV) estimation. METHODS A Verasonics system incorporating a linear array probe L14-5/38 with 128 elements and a pulsatile pump, CompuFlow1000, were used to acquire radio frequency data of 3, 5, 7, and 9 tilted plane wave sequences with angle intervals from 0° to 12° with a coarse interval increment step of 1°, and the angle intervals from 0° to 2° with a fine interval increment step of 0.25° from a carotid vessel phantom with the LPWV of 13.42 ± 0.90 m/s. The mean value, standard deviation, and coefficients of variation (CV) of the estimated LPWVs were calculated to quantitatively assess the performance of different configurations for CPWC-based LPWV estimation. Ten healthy human subjects of two age groups were recruited to assess the in vivo feasibility of the optimum parameter values. RESULTS The CPWC technique with three plane waves (PRF of 12 kHz corresponding to a frame rate of 4000 Hz) with an interval of 0.75° had LPWVs of 13.52 ± 0.08 m/s with the lowest CV of 1.84% on the phantom, and 5.49 ± 1.46 m/s with the lowest CV of 12.35% on 10 subjects. CONCLUSIONS The optimum parameters determined in this study show the best repeatability of the LPWV measurements with a vessel phantom and 10 healthy subjects, which support further studies on larger datasets for potential applications.
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Affiliation(s)
- Li Xiong
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, China
| | - Yufeng Zhang
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, China
| | - Bingbing He
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, China
| | - Kexin Zhang
- The Second Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Jingying Zhu
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, China
| | - Xun Lang
- Department of Electronic Engineering, Information School, Yunnan University, Kunming, China
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2
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Zaidi M, Ma J, Thomas BP, Peña S, Harrison CE, Chen J, Lin SH, Derner KA, Baxter JD, Liticker J, Malloy CR, Bartnik-Olson B, Park JM. Functional activation of pyruvate dehydrogenase in human brain using hyperpolarized [1- 13 C]pyruvate. Magn Reson Med 2024; 91:1822-1833. [PMID: 38265104 PMCID: PMC10950523 DOI: 10.1002/mrm.30015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 12/28/2023] [Accepted: 12/29/2023] [Indexed: 01/25/2024]
Abstract
PURPOSE Pyruvate, produced from either glucose, glycogen, or lactate, is the dominant precursor of cerebral oxidative metabolism. Pyruvate dehydrogenase (PDH) flux is a direct measure of cerebral mitochondrial function and metabolism. Detection of [13 C]bicarbonate in the brain from hyperpolarized [1-13 C]pyruvate using carbon-13 (13 C) MRI provides a unique opportunity for assessing PDH flux in vivo. This study is to assess changes in cerebral PDH flux in response to visual stimuli using in vivo 13 C MRS with hyperpolarized [1-13 C]pyruvate. METHODS From seven sedentary adults in good general health, time-resolved [13 C]bicarbonate production was measured in the brain using 90° flip angles with minimal perturbation of its precursors, [1-13 C]pyruvate and [1-13 C]lactate, to test the hypothesis that the appearance of [13 C]bicarbonate signals in the brain reflects the metabolic changes associated with neuronal activation. With a separate group of healthy participants (n = 3), the likelihood of the bolus-injected [1-13 C]pyruvate being converted to [1-13 C]lactate prior to decarboxylation was investigated by measuring [13 C]bicarbonate production with and without [1-13 C]lactate saturation. RESULTS In the course of visual stimulation, the measured [13 C]bicarbonate signal normalized to the total 13 C signal in the visual cortex increased by 17.1% ± 15.9% (p = 0.017), whereas no significant change was detected in [1-13 C]lactate. Proton BOLD fMRI confirmed the regional activation in the visual cortex with the stimuli. Lactate saturation decreased bicarbonate-to-pyruvate ratio by 44.4% ± 9.3% (p < 0.01). CONCLUSION We demonstrated the utility of 13 C MRS with hyperpolarized [1-13 C]pyruvate for assessing the activation of cerebral PDH flux via the detection of [13 C]bicarbonate production.
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Affiliation(s)
- Maheen Zaidi
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Junjie Ma
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
- GE Precision Healthcare, Jersey City, New Jersey, USA 07302
| | - Binu P. Thomas
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Salvador Peña
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Crystal E. Harrison
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Jun Chen
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Sung-Han Lin
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Kelley A. Derner
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Jeannie D. Baxter
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Jeff Liticker
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Craig R. Malloy
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
| | - Brenda Bartnik-Olson
- Department of Radiology, Loma Linda University, Loma Linda, California, USA 92354
| | - Jae Mo Park
- Advanced Imaging Research Center, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
- Department of Radiology, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
- Department of Biomedical Engineering, The University of Texas Southwestern Medical Center, Dallas, Texas, USA 75390
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3
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Patel A, Chad JA, Chen JJ. Is adiposity associated with white matter microstructural health and intelligence differently in males and females? Obesity (Silver Spring) 2023; 31:1011-1023. [PMID: 36883598 DOI: 10.1002/oby.23686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 10/27/2022] [Accepted: 11/24/2022] [Indexed: 03/09/2023]
Abstract
OBJECTIVE The role of vascular risk factors in age-related brain degeneration has long been the subject of intense study, but the role of obesity remains understudied. Given known sex differences in fat storage and usage, this study investigates sex differences in the association between adiposity and white matter microstructural integrity, an important early marker of brain degeneration. METHODS This study assesses the associations between adiposity (abdominal fat ratio and liver proton density fat fraction) and brain health (measures of intelligence and white matter microstructure using diffusion-tensor imaging [DTI]) in a group of UK Biobank participants. RESULTS This study finds that intelligence and DTI metrics are indeed associated with adiposity differently in males and females. These sex differences are distinct from those in the associations of DTI metrics with age and blood pressure. CONCLUSIONS Taken together, these findings suggest that there are inherent sex-driven differences in how brain health is associated with obesity.
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Affiliation(s)
- Arjun Patel
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Department of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
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4
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Zhang Y, Zhang R, Wang S, Hong H, Jiaerken Y, Li K, Zeng Q, Luo X, Yu X, Zhang M, Huang P. Reduced coupling between the global blood-oxygen-level-dependent signal and cerebrospinal fluid inflow is associated with the severity of small vessel disease. Neuroimage Clin 2022; 36:103229. [PMID: 36252555 PMCID: PMC9668594 DOI: 10.1016/j.nicl.2022.103229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 10/10/2022] [Accepted: 10/10/2022] [Indexed: 11/11/2022]
Abstract
BACKGROUND Small vessel disease (SVD) is highly prevalent in the elderly and associated with an increased risk of dementia and stroke. SVD may have disturbed cerebrospinal fluid (CSF) flow, which can compromise waste clearance and accelerate disease progression. METHODS We retrospectively included 146 SVD patients from a prospectively collected dataset, with one- or two-year follow-up data in 61 patients. The coupling strength between the global blood-oxygen-level-dependent (gBOLD) signal and CSF inflow was used to reflect CSF dynamics. We performed regression analyses to investigate the association between the gBOLD-CSF coupling index and the severity of SVD and vascular risk factors. Longitudinal analysis was carried out to investigate causal relationships. RESULTS Patients with severe SVD had significantly decreased gBOLD-CSF coupling (β = -0.180, p = 0.032). Dilation of perivascular spaces in the basal ganglia area (β = -0.172, p = 0.033) and diabetes (β = -0.204, p = 0.014) were associated with reduced gBOLD-CSF coupling. In longitudinal analyses, diabetes was associated with faster decline in gBOLD-CSF coupling (β = 0.20, p = 0.039), while perivascular space (PVS) dilation in the centrum semiovale showed a opposite relationship (β = -0.20, p = 0.041). The gBOLD-CSF coupling could not predict SVD progression. CONCLUSION Altered CSF flow is associated with the severity of SVD.
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Affiliation(s)
- Yao Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Ruiting Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China,Department of Neurology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Shuyue Wang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Hui Hong
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Yeerfan Jiaerken
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Kaicheng Li
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Qingze Zeng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Xiao Luo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Xinfeng Yu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China
| | - Minming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China,Corresponding authors at: Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 310009, China.
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, 310000 Hangzhou, China,Corresponding authors at: Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 310009, China.
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Gibson BC, Claus ED, Sanguinetti J, Witkiewitz K, Clark VP. A review of functional brain differences predicting relapse in substance use disorder: Actionable targets for new methods of noninvasive brain stimulation. Neurosci Biobehav Rev 2022; 141:104821. [PMID: 35970417 DOI: 10.1016/j.neubiorev.2022.104821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 08/03/2022] [Accepted: 08/06/2022] [Indexed: 11/17/2022]
Abstract
Neuroimaging studies have identified a variety of brain regions whose activity predicts substance use (i.e., relapse) in patients with substance use disorder (SUD), suggesting that malfunctioning brain networks may exacerbate relapse. However, this knowledge has not yet led to a marked improvement in treatment outcomes. Noninvasive brain stimulation (NIBS) has shown some potential for treating SUDs, and a new generation of NIBS technologies offers the possibility of selectively altering activity in both superficial and deep brain structures implicated in SUDs. The goal of the current review was to identify deeper brain structures involved in relapse to SUD and give an account of innovative methods of NIBS that might be used to target them. Included studies measured fMRI in currently abstinent SUD patients and tracked treatment outcomes, and fMRI results were organized with the framework of the Addictions Neuroclinical Assessment (ANA). Four brain structures were consistently implicated: the anterior and posterior cingulate cortices, ventral striatum and insula. These four deeper brain structures may be appropriate future targets for the treatment of SUD using these innovative NIBS technologies.
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Affiliation(s)
- Benjamin C Gibson
- Psychology Clinical Neuroscience Center, Department of Psychology, University of New Mexico, Albuquerque, NM 87131, USA; Department of Psychology, University of New Mexico, Albuquerque, NM 87131, USA; The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA
| | - Eric D Claus
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA
| | - Jay Sanguinetti
- The Center for Consciousness Studies, University of Arizona, Tucson, AZ 85719, USA
| | - Katie Witkiewitz
- Department of Psychology, University of New Mexico, Albuquerque, NM 87131, USA
| | - Vincent P Clark
- Psychology Clinical Neuroscience Center, Department of Psychology, University of New Mexico, Albuquerque, NM 87131, USA; Department of Psychology, University of New Mexico, Albuquerque, NM 87131, USA; The Mind Research Network/Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA.
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6
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Coffin C, Suerken CK, Bateman JR, Whitlow CT, Williams BJ, Espeland MA, Sachs BC, Cleveland M, Yang M, Rogers S, Hayden KM, Baker LD, Williamson J, Craft S, Hughes TM, Lockhart SN. Vascular and microstructural markers of cognitive pathology. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12332. [PMID: 35814618 PMCID: PMC9257520 DOI: 10.1002/dad2.12332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 04/08/2022] [Accepted: 05/10/2022] [Indexed: 11/16/2022]
Abstract
Introduction Arterial stiffness may play a role in the development of dementia through poorly understood effects on brain microstructural integrity and perfusion. Methods We examined markers of arterial stiffness (carotid-femoral pulse wave velocity [cfPWV]) and elevated systolic blood pressure (SBP) in relation to cognitive function and brain magnetic resonance imaging macrostructure (gray matter [GM] and white matter [WM] volumes), microstructure (diffusion based free water [FW] and fractional anisotropy [FA]), and cerebral blood flow (CBF) in WM and GM in models adjusted for age, race, sex, education, and apolipoprotein E ε4 status. Results Among 460 participants (70 ± 8 years; 44 dementia, 158 mild cognitive impairment, 258 normal cognition), higher cfPWV and SBP were independently associated with higher FW, higher WM hyperintensity volume, and worse cognition (global and executive function). Higher SBP alone was significantly associated with lower WM and GM CBF. Discussion Arterial stiffness is associated with impaired WM microstructure and global and executive cognitive function.
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Affiliation(s)
- Claudia Coffin
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Cynthia K. Suerken
- Department of Biostatistics and Data ScienceDivision of Public Health SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - James R. Bateman
- Department of NeurologyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | | | - Benjamin J. Williams
- Department of NeurologyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Mark A. Espeland
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
- Department of Biostatistics and Data ScienceDivision of Public Health SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Bonnie C. Sachs
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
- Department of NeurologyWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Maryjo Cleveland
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Mia Yang
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Samantha Rogers
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Kathleen M. Hayden
- Department of Social Sciences and Health PolicyDivision of Public Health SciencesWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Laura D. Baker
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Jeff Williamson
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Suzanne Craft
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Timothy M. Hughes
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Samuel N. Lockhart
- Department of Internal MedicineSection on Gerontology and Geriatric MedicineWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
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7
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Poltojainen V, Kemppainen J, Keinänen N, Bode M, Isokangas JM, Kuitunen H, Nikkinen J, Sonkajärvi E, Korhonen V, Tuovinen T, Järvelä M, Huotari N, Raitamaa L, Kananen J, Korhonen T, Tetri S, Kuittinen O, Kiviniemi V. Physiological instability is linked to mortality in primary central nervous system lymphoma: A case-control fMRI study. Hum Brain Mapp 2022; 43:4030-4044. [PMID: 35543292 PMCID: PMC9374894 DOI: 10.1002/hbm.25901] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 04/07/2022] [Accepted: 04/26/2022] [Indexed: 11/07/2022] Open
Abstract
Primary central nervous system lymphoma (PCNSL) is an aggressive brain disease where lymphocytes invade along perivascular spaces of arteries and veins. The invasion markedly changes (peri)vascular structures but its effect on physiological brain pulsations has not been previously studied. Using physiological magnetic resonance encephalography (MREGBOLD ) scanning, this study aims to quantify the extent to which (peri)vascular PCNSL involvement alters the stability of physiological brain pulsations mediated by cerebral vasculature. Clinical implications and relevance were explored. In this study, 21 PCNSL patients (median 67y; 38% females) and 30 healthy age-matched controls (median 63y; 73% females) were scanned for MREGBOLD signal during 2018-2021. Motion effects were removed. Voxel-by-voxel Coefficient of Variation (CV) maps of MREGBOLD signal was calculated to examine the stability of physiological brain pulsations. Group-level differences in CV were examined using nonparametric covariate-adjusted tests. Subject-level CV alterations were examined against control population Z-score maps wherein clusters of increased CV values were detected. Spatial distributions of clusters and findings from routine clinical neuroimaging were compared [contrast-enhanced, diffusion-weighted, fluid-attenuated inversion recovery (FLAIR) data]. Whole-brain mean CV was linked to short-term mortality with 100% sensitivity and 100% specificity, as all deceased patients revealed higher values (n = 5, median 0.055) than surviving patients (n = 16, median 0.028) (p < .0001). After adjusting for medication, head motion, and age, patients revealed higher CV values (group median 0.035) than healthy controls (group median 0.024) around arterial territories (p ≤ .001). Abnormal clusters (median 1.10 × 105 mm3 ) extended spatially beyond FLAIR lesions (median 0.62 × 105 mm3 ) with differences in volumes (p = .0055).
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Affiliation(s)
- Valter Poltojainen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Janette Kemppainen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Cancer and Translational Medicine Research Unit, University of Oulu, Oulu, Finland
| | - Nina Keinänen
- Department of Anaesthesiology, Oulu University Hospital, Oulu, Finland
| | - Michaela Bode
- Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | | | - Hanne Kuitunen
- Department of Oncology and Haematology, Oulu University Hospital, Oulu, Finland
| | - Juha Nikkinen
- Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Oncology and Radiotherapy, Oulu University Hospital, Oulu, Finland
| | - Eila Sonkajärvi
- Department of Anaesthesiology, Oulu University Hospital, Oulu, Finland
| | - Vesa Korhonen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Matti Järvelä
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Niko Huotari
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Lauri Raitamaa
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Janne Kananen
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
| | - Tommi Korhonen
- Medical Research Center, University of Oulu/Oulu University Hospital, Oulu, Finland.,Department of Clinical Neuroscience, University of Oulu, Oulu, Finland
| | - Sami Tetri
- Medical Research Center, University of Oulu/Oulu University Hospital, Oulu, Finland.,Department of Clinical Neuroscience, University of Oulu, Oulu, Finland
| | - Outi Kuittinen
- Department of Oncology and Haematology, Oulu University Hospital, Oulu, Finland.,Cancer Center, Kuopio University Hospital, Kuopio, Finland.,Faculty of Health Medicine, Institute of Clinical Medicine, University of Eastern Finland, Oulu, Finland
| | - Vesa Kiviniemi
- Oulu Functional Neuroimaging, University of Oulu/Oulu University Hospital, Oulu, Finland.,Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland.,Department of Radiology, Oulu University Hospital, Oulu, Finland
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8
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Champagne AA, Coverdale NS, Allen MD, Tremblay JC, MacPherson REK, Pyke KE, Olver TD, Cook DJ. The physiological basis underlying functional connectivity differences in older adults: A multi-modal analysis of resting-state fMRI. Brain Imaging Behav 2022; 16:1575-1591. [PMID: 35092574 DOI: 10.1007/s11682-021-00570-0] [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: 04/11/2020] [Accepted: 09/27/2021] [Indexed: 11/02/2022]
Abstract
The purpose of this study was to determine if differences in functional connectivity strength (FCS) with age were confounded by vascular parameters including resting cerebral blood flow (CBF0), cerebrovascular reactivity (CVR), and BOLD-CBF coupling. Neuroimaging data were collected from 13 younger adults (24 ± 2 years) and 14 older adults (71 ± 4 years). A dual-echo resting state pseudo-continuous arterial spin labeling sequence was performed, as well as a BOLD breath-hold protocol. A group independent component analysis was used to identify networks, which were amalgamated into a region of interest (ROI). Within the ROI, FC strength (FCS) was computed for all voxels and compared across the groups. CBF0, CVR and BOLD-CBF coupling were examined within voxels where FCS was different between young and older adults. FCS was greater in old compared to young (P = 0.001). When the effect of CBF0, CVR and BOLD-CBF coupling on FCS was examined, BOLD-CBF coupling had a significant effect (P = 0.003) and group differences in FCS were not present once all vascular parameters were considered in the statistical model (P = 0.07). These findings indicate that future studies of FCS should consider vascular physiological markers in order to improve our understanding of aging processes on brain connectivity.
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Affiliation(s)
- Allen A Champagne
- Centre for Neuroscience Studies, Queen's University, Room 260, Kingston, ON, K7L 3N6, Canada
| | - Nicole S Coverdale
- Centre for Neuroscience Studies, Queen's University, Room 260, Kingston, ON, K7L 3N6, Canada
| | - Matti D Allen
- Department of Physical Medicine and Rehabilitation, Queen's University, Kingston, ON, Canada.,School of Kinesiology and Health Studies, Cardiovascular Stress Response Laboratory, Queen's University, Kingston, ON, K7L 3N6, Canada.,Department of Physical Medicine and Rehabilitation, Providence Care Hospital, 752 King St., Ontario, West Kingston, Canada
| | - Joshua C Tremblay
- School of Kinesiology and Health Studies, Cardiovascular Stress Response Laboratory, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - Rebecca E K MacPherson
- Department of Health Sciences, Faculty of Applied Health Sciences, Brock University, 1812 Sir Isaac Brock Way, St Catharines, ON, L2S 3A1, Canada
| | - Kyra E Pyke
- School of Kinesiology and Health Studies, Cardiovascular Stress Response Laboratory, Queen's University, Kingston, ON, K7L 3N6, Canada
| | - T Dylan Olver
- Biomedical Sciences, Western College of Veterinarian Medicine, University of Saskatchewan, 52 Campus Drive, Saskatoon, Saskatchewan, S7N 5B4, Canada
| | - Douglas J Cook
- Centre for Neuroscience Studies, Queen's University, Room 260, Kingston, ON, K7L 3N6, Canada. .,Department of Surgery, Queen's University, Room 232, 18 Stuart St, Kingston, ON, K7L 3N6, Canada.
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9
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Rolls ET, Wan Z, Cheng W, Feng J. Risk-taking in humans and the medial orbitofrontal cortex reward system. Neuroimage 2022; 249:118893. [PMID: 35007715 DOI: 10.1016/j.neuroimage.2022.118893] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/28/2021] [Accepted: 01/06/2022] [Indexed: 11/29/2022] Open
Abstract
Risk-taking differs between humans, and is associated with the personality measures of impulsivity and sensation-seeking. To analyse the brain systems involved, self-report risk-taking, resting state functional connectivity, and related behavioral measures were analyzed in 18,740 participants of both sexes from the UK Biobank. Functional connectivities of the medial orbitofrontal cortex, ventromedial prefrontal cortex (VMPFC), and the parahippocampal areas were significantly higher in the risk-taking group (p < 0.001, FDR corrected). The risk-taking measure was validated in that it was significantly associated with alcohol drinking amount (r = 0.08, p = 5.1×10-28), cannabis use (r = 0.12, p = 6.0×10-66), and anxious feelings (r = -0.12, p = 7.6×-98). The functional connectivity findings were cross-validated in two independent datasets. The higher functional connectivity of the medial orbitofrontal cortex and VMPFC included higher connectivity with the anterior cingulate cortex, which provides a route for these reward-related regions to have a greater influence on action in risk-taking individuals. In conclusion, the medial orbitofrontal cortex, which is involved in reward value and pleasure, was found to be related to risk-taking, which is associated with impulsivity. An implication is that risk-taking is driven by specific orbitofrontal cortex reward systems, and is different for different rewards which are represented differently in the brains of different individuals. This is an advance in understanding the bases and mechanisms of risk-taking in humans, given that the orbitofrontal cortex, VMPFC and anterior cingulate cortex are highly developed in humans, and that risk-taking can be reported in humans.
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Affiliation(s)
- Edmund T Rolls
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Oxford Centre for Computational Neuroscience, Oxford, UK.
| | - Zhuo Wan
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
| | - Wei Cheng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
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10
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Li X, Fischer H, Manzouri A, Månsson KNT, Li TQ. A Quantitative Data-Driven Analysis Framework for Resting-State Functional Magnetic Resonance Imaging: A Study of the Impact of Adult Age. Front Neurosci 2021; 15:768418. [PMID: 34744623 PMCID: PMC8565286 DOI: 10.3389/fnins.2021.768418] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 09/28/2021] [Indexed: 01/08/2023] Open
Abstract
The objective of this study is to introduce a new quantitative data-driven analysis (QDA) framework for the analysis of resting-state fMRI (R-fMRI) and use it to investigate the effect of adult age on resting-state functional connectivity (RFC). Whole-brain R-fMRI measurements were conducted on a 3T clinical MRI scanner in 227 healthy adult volunteers (N = 227, aged 18-76 years old, male/female = 99/128). With the proposed QDA framework we derived two types of voxel-wise RFC metrics: the connectivity strength index and connectivity density index utilizing the convolutions of the cross-correlation histogram with different kernels. Furthermore, we assessed the negative and positive portions of these metrics separately. With the QDA framework we found age-related declines of RFC metrics in the superior and middle frontal gyri, posterior cingulate cortex (PCC), right insula and inferior parietal lobule of the default mode network (DMN), which resembles previously reported results using other types of RFC data processing methods. Importantly, our new findings complement previously undocumented results in the following aspects: (1) the PCC and right insula are anti-correlated and tend to manifest simultaneously declines of both the negative and positive connectivity strength with subjects' age; (2) separate assessment of the negative and positive RFC metrics provides enhanced sensitivity to the aging effect; and (3) the sensorimotor network depicts enhanced negative connectivity strength with the adult age. The proposed QDA framework can produce threshold-free and voxel-wise RFC metrics from R-fMRI data. The detected adult age effect is largely consistent with previously reported studies using different R-fMRI analysis approaches. Moreover, the separate assessment of the negative and positive contributions to the RFC metrics can enhance the RFC sensitivity and clarify some of the mixed results in the literature regarding to the DMN and sensorimotor network involvement in adult aging.
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Affiliation(s)
- Xia Li
- Institute of Informatics Engineering, China Jiliang University, Hangzhou, China
| | - Håkan Fischer
- Department of Psychology, Stockholm University, Stockholm, Sweden.,Stockholm University Brain Imaging Centre, Stockholm, Sweden
| | | | - Kristoffer N T Månsson
- Department of Psychology, Stockholm University, Stockholm, Sweden.,Centre of Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Tie-Qiang Li
- Institute of Informatics Engineering, China Jiliang University, Hangzhou, China.,Department of Clinical Science, Intervention, and Technology, Karolinska Institute, Solna, Sweden.,Department of Medical Radiation and Nuclear Medicine, Karolinska University Hospital, Solna, Sweden
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11
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Schaeffer S, Iadecola C. Revisiting the neurovascular unit. Nat Neurosci 2021; 24:1198-1209. [PMID: 34354283 PMCID: PMC9462551 DOI: 10.1038/s41593-021-00904-7] [Citation(s) in RCA: 225] [Impact Index Per Article: 75.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Accepted: 06/30/2021] [Indexed: 02/06/2023]
Abstract
The brain is supplied by an elaborate vascular network that originates extracranially and reaches deep into the brain. The concept of the neurovascular unit provides a useful framework to investigate how neuronal signals regulate nearby microvessels to support the metabolic needs of the brain, but it does not consider the role of larger cerebral arteries and systemic vasoactive signals. Furthermore, the recently emerged molecular heterogeneity of cerebrovascular cells indicates that there is no prototypical neurovascular unit replicated at all levels of the vascular network. Here, we examine the cellular and molecular diversity of the cerebrovascular tree and the relative contribution of systemic and brain-intrinsic factors to neurovascular function. Evidence supports the concept of a 'neurovascular complex' composed of segmentally diverse functional modules that implement coordinated vascular responses to central and peripheral signals to maintain homeostasis of the brain. This concept has major implications for neurovascular regulation in health and disease and for brain imaging.
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12
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Raitamaa L, Huotari N, Korhonen V, Helakari H, Koivula A, Kananen J, Kiviniemi V. Spectral analysis of physiological brain pulsations affecting the BOLD signal. Hum Brain Mapp 2021; 42:4298-4313. [PMID: 34037278 PMCID: PMC8356994 DOI: 10.1002/hbm.25547] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 05/18/2021] [Accepted: 05/19/2021] [Indexed: 12/17/2022] Open
Abstract
Physiological pulsations have been shown to affect the global blood oxygen level dependent (BOLD) signal in human brain. While these pulsations have previously been regarded as noise, recent studies show their potential as biomarkers of brain pathology. We used the extended 5 Hz spectral range of magnetic resonance encephalography (MREG) data to investigate spatial and frequency distributions of physiological BOLD signal sources. Amplitude spectra of the global image signals revealed cardiorespiratory envelope modulation (CREM) peaks, in addition to the previously known very low frequency (VLF) and cardiorespiratory pulsations. We then proceeded to extend the amplitude of low frequency fluctuations (ALFF) method to each of these pulsations. The respiratory pulsations were spatially dominating over most brain structures. The VLF pulsations overcame the respiratory pulsations in frontal and parietal gray matter, whereas cardiac and CREM pulsations had this effect in central cerebrospinal fluid (CSF) spaces and major blood vessels. A quasi‐periodic pattern (QPP) analysis showed that the CREM pulsations propagated as waves, with a spatiotemporal pattern differing from that of respiratory pulsations, indicating them to be distinct intracranial physiological phenomenon. In conclusion, the respiration has a dominant effect on the global BOLD signal and directly modulates cardiovascular brain pulsations.
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Affiliation(s)
- Lauri Raitamaa
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Niko Huotari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Vesa Korhonen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Heta Helakari
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Anssi Koivula
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Janne Kananen
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
| | - Vesa Kiviniemi
- Oulu Functional Neuro Imaging Group, Research Unit of Medical Imaging Physics and Technology (MIPT), University of Oulu, Oulu.,Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, Oulu
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13
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Rajna Z, Mattila H, Huotari N, Tuovinen T, Krüger J, Holst SC, Korhonen V, Remes AM, Seppänen T, Hennig J, Nedergaard M, Kiviniemi V. Cardiovascular brain impulses in Alzheimer's disease. Brain 2021; 144:2214-2226. [PMID: 33787890 PMCID: PMC8422353 DOI: 10.1093/brain/awab144] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 03/13/2021] [Accepted: 03/23/2021] [Indexed: 11/30/2022] Open
Abstract
Accumulation of amyloid-β is a key neuropathological feature in brain of
Alzheimer’s disease patients. Alterations in cerebral haemodynamics,
such as arterial impulse propagation driving the (peri)vascular CSF flux,
predict future Alzheimer’s disease progression. We now present a
non-invasive method to quantify the three-dimensional propagation of
cardiovascular impulses in human brain using ultrafast 10 Hz magnetic
resonance encephalography. This technique revealed spatio-temporal abnormalities
in impulse propagation in Alzheimer’s disease. The arrival latency and
propagation speed both differed in patients with Alzheimer’s disease.
Our mapping of arterial territories revealed Alzheimer’s
disease-specific modifications, including reversed impulse propagation around
the hippocampi and in parietal cortical areas. The findings imply that pervasive
abnormality in (peri)vascular CSF impulse propagation compromises vascular
impulse propagation and subsequently glymphatic brain clearance of
amyloid-β in Alzheimer’s disease.
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Affiliation(s)
- Zalán Rajna
- Center for Machine Vision and Signal Analysis, University of Oulu, 90570 Oulu, Finland
| | - Heli Mattila
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
| | - Niko Huotari
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
| | - Timo Tuovinen
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
| | - Johanna Krüger
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, 90570 Oulu, Finland
| | - Sebastian C Holst
- Neurobiology Research Unit, Copenhagen University Hospital, 2100 Copenhagen, Denmark
| | - Vesa Korhonen
- Department of Diagnostic Radiology, Medical Research Center, Oulu University Hospital, 90220 Oulu, Finland
| | - Anne M Remes
- Research Unit of Clinical Neuroscience, Neurology, University of Oulu, 90570 Oulu, Finland
| | - Tapio Seppänen
- Center for Machine Vision and Signal Analysis, University of Oulu, 90570 Oulu, Finland
| | - Jürgen Hennig
- Department of Radiology, Medical Physics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Vesa Kiviniemi
- Oulu Functional Neuroimaging Group, Research Unit of Medical Imaging, Physics and Technology, University of Oulu, 90570 Oulu, Finland
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14
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Kim T, Kim SY, Agarwal V, Cohen A, Roush R, Chang YF, Cheng Y, Snitz B, Huppert TJ, Bagic A, Kamboh MI, Doman J, Becker JT. Cardiac-induced cerebral pulsatility, brain structure, and cognition in middle and older-aged adults. Neuroimage 2021; 233:117956. [PMID: 33716158 PMCID: PMC8145789 DOI: 10.1016/j.neuroimage.2021.117956] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 03/03/2021] [Accepted: 03/05/2021] [Indexed: 12/11/2022] Open
Abstract
Changes of cardiac-induced regional pulsatility can be associated with specific regions of brain volumetric changes, and these are related with cognitive alterations. Thus, mapping of cardiac pulsatility over the entire brain can be helpful to assess these relationships. A total of 108 subjects (age: 66.5 ± 8.4 years, 68 females, 52 healthy controls, 11 subjective cognitive decline, 17 impaired without complaints, 19 MCI and 9 AD) participated. The pulsatility map was obtained directly from resting-state functional MRI time-series data at 3T. Regional brain volumes were segmented from anatomical MRI. Multidomain neuropsychological battery was performed to test memory, language, attention and visuospatial construction. The Montreal Cognitive Assessment (MoCA) was also administered. The sparse partial least square (SPLS) method, which is desirable for better interpreting high-dimensional variables, was applied for the relationship between the entire brain voxels of pulsatility and 45 segmented brain volumes. A multiple holdout SPLS framework was used to optimize sparsity for assessing the pulsatility-volume relationship model and to test the reliability by fitting the models to 9 different splits of the data. We found statistically significant associations between subsets of pulsatility voxels and subsets of segmented brain volumes by rejecting the omnibus null hypothesis (any of 9 splits has p < 0.0056 (=0.05/9) with the Bonferroni correction). The pulsatility was positively associated with the lateral ventricle, choroid plexus, inferior lateral ventricle, and 3rd ventricle and negatively associated with hippocampus, ventral DC, and thalamus volumes for the first pulsatility-volume relationship. The pulsatility had an additional negative relationship with the amygdala and brain stem volumes for the second pulsatility-volume relationship. The spatial distribution of correlated pulsatility was observed in major feeding arteries to the brain regions, ventricles, and sagittal sinus. The indirect mediating pathways through the volumetric changes were statistically significant between the pulsatility and multiple cognitive measures (p < 0.01). Thus, the cerebral pulsatility, along with volumetric measurements, could be a potential marker for better understanding of pathophysiology and monitoring disease progression in age-related neurodegenerative disorders.
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Affiliation(s)
- Tae Kim
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, USA.
| | - Sang-Young Kim
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Vikas Agarwal
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Annie Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA
| | - Rebecca Roush
- Department of Neurology, University of Pittsburgh, Pittsburgh, USA
| | - Yue-Fang Chang
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, USA
| | - Yu Cheng
- Departments of Statistics and Biostatistics, University of Pittsburgh, Pittsburgh, USA
| | - Beth Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, USA
| | - Theodore J Huppert
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, USA; Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, USA
| | - Anto Bagic
- Department of Neurology, University of Pittsburgh, Pittsburgh, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, USA
| | - Jack Doman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA
| | - James T Becker
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA
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15
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Moore EE, Jefferson AL. Impact of Cardiovascular Hemodynamics on Cognitive Aging. Arterioscler Thromb Vasc Biol 2021; 41:1255-1264. [PMID: 33567862 DOI: 10.1161/atvbaha.120.311909] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Elizabeth E Moore
- Vanderbilt Memory & Alzheimer's Center (E.E.M., A.L.J.), Vanderbilt University Medical Center, Nashville, TN.,Medical Scientist Training Program, School of Medicine, Vanderbilt University, Nashville, TN (E.E.M.)
| | - Angela L Jefferson
- Vanderbilt Memory & Alzheimer's Center (E.E.M., A.L.J.), Vanderbilt University Medical Center, Nashville, TN.,Department of Neurology (A.L.J.), Vanderbilt University Medical Center, Nashville, TN
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16
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The variability of functional MRI brain signal increases in Alzheimer's disease at cardiorespiratory frequencies. Sci Rep 2020; 10:21559. [PMID: 33298996 PMCID: PMC7726142 DOI: 10.1038/s41598-020-77984-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 11/13/2020] [Indexed: 01/08/2023] Open
Abstract
Biomarkers sensitive to prodromal or early pathophysiological changes in Alzheimer's disease (AD) symptoms could improve disease detection and enable timely interventions. Changes in brain hemodynamics may be associated with the main clinical AD symptoms. To test this possibility, we measured the variability of blood oxygen level-dependent (BOLD) signal in individuals from three independent datasets (totaling 80 AD patients and 90 controls). We detected a replicable increase in brain BOLD signal variability in the AD populations, which constituted a robust biomarker for clearly differentiating AD cases from controls. Fast BOLD scans showed that the elevated BOLD signal variability in AD arises mainly from cardiovascular brain pulsations. Manifesting in abnormal cerebral perfusion and cerebrospinal fluid convection, present observation presents a mechanism explaining earlier observations of impaired glymphatic clearance associated with AD in humans.
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17
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Rivera-Rivera LA, Cody KA, Rutkowski D, Cary P, Eisenmenger L, Rowley HA, Carlsson CM, Johnson SC, Johnson KM. Intracranial vascular flow oscillations in Alzheimer's disease from 4D flow MRI. Neuroimage Clin 2020; 28:102379. [PMID: 32871386 PMCID: PMC7476069 DOI: 10.1016/j.nicl.2020.102379] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 07/10/2020] [Accepted: 08/07/2020] [Indexed: 11/26/2022]
Abstract
Recent modeling and experimental evidence suggests clearance of soluble metabolites from the brain can be driven by low frequency flow oscillations (LFOs) through the intramural periarterial drainage (IPAD) pathway. This study investigates the use of 4D flow MRI to derive LFOs from arterial and venous measures of blood flow. 3D radial 4D flow MRI data were acquired on a 3.0 T scanner and reconstructed using a low-rank constraint to produce time resolved measurements of blood flow. Physical phantom experiments were performed to validate the time resolved 4D flow against a standard 2D phase contrast (PC) approach. To evaluate the ability of 4D flow to distinguish physiologic flow changes from noise, healthy volunteers were scanned during a breath-hold (BH) maneuver and compared against 2D PC measures. Finally, flow measures were performed in intracranial arteries and veins of 112 participants including subjects diagnosed with Alzheimer's disease (AD) clinical syndrome (n = 23), and healthy controls (n = 89) on whom apolipoprotein ɛ4 positivity (APOE4+) and parental history of AD dementia (FH+) was known. To assess LFOs, flow range, standard deviation, demeaned temporal flow changes, and power spectral density were quantified from the time series. Group differences were assessed using ANOVA followed by Tukey-Kramer method for pairwise comparison for adjusted means (P < 0.05). Significantly lower LFOs as measured from flow variation range and standard deviations were observed in the arteries of AD subjects when compared to age-matched controls (P = 0.005, P = 0.011). Results suggest altered vascular function in AD subjects. 4D flow based spontaneous LFO measures might hold potential for longitudinal studies aimed at predicting cognitive trajectories in AD and study disease mechanisms.
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Affiliation(s)
- Leonardo A Rivera-Rivera
- Department of Medical Physics, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA
| | - Karly A Cody
- Alzheimer's Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA
| | - David Rutkowski
- Department of Radiology, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA
| | - Paul Cary
- Alzheimer's Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA
| | - Howard A Rowley
- Alzheimer's Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA; Department of Radiology, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA
| | - Cynthia M Carlsson
- Alzheimer's Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA; Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sterling C Johnson
- Alzheimer's Disease Research Center, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA; Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Kevin M Johnson
- Department of Medical Physics, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA; Department of Radiology, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA.
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18
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Hussein A, Matthews JL, Syme C, Macgowan C, MacIntosh BJ, Shirzadi Z, Pausova Z, Paus T, Chen JJ. The association between resting-state functional magnetic resonance imaging and aortic pulse-wave velocity in healthy adults. Hum Brain Mapp 2020; 41:2121-2135. [PMID: 32034832 PMCID: PMC7268071 DOI: 10.1002/hbm.24934] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Revised: 01/08/2020] [Accepted: 01/09/2020] [Indexed: 12/11/2022] Open
Abstract
Resting‐state functional magnetic resonance imaging (rs‐fMRI) is frequently used to study brain function; but, it is unclear whether BOLD‐signal fluctuation amplitude and functional connectivity are associated with vascular factors, and how vascular‐health factors are reflected in rs‐fMRI metrics in the healthy population. As arterial stiffening is a known age‐related cardiovascular risk factor, we investigated the associations between aortic stiffening (as measured using pulse‐wave velocity [PWV]) and rs‐fMRI metrics. We used cardiac MRI to measure aortic PWV (an established indicator of whole‐body vascular stiffness), as well as dual‐echo pseudo‐continuous arterial‐spin labeling to measure BOLD and CBF dynamics simultaneously in a group of generally healthy adults. We found that: (1) higher aortic PWV is associated with lower variance in the resting‐state BOLD signal; (2) higher PWV is also associated with lower BOLD‐based resting‐state functional connectivity; (3) regions showing lower connectivity do not fully overlap with those showing lower BOLD variance with higher PWV; (4) CBF signal variance is a significant mediator of the above findings, only when averaged across regions‐of‐interest. Furthermore, we found no significant association between BOLD signal variance and systolic blood pressure, which is also a known predictor of vascular stiffness. Age‐related vascular stiffness, as measured by PWV, provides a unique scenario to demonstrate the extent of vascular bias in rs‐fMRI signal fluctuations and functional connectivity. These findings suggest that a substantial portion of age‐related rs‐fMRI differences may be driven by vascular effects rather than directly by brain function.
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Affiliation(s)
- Ahmad Hussein
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Jacob L Matthews
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Catriona Syme
- SickKids Hospital, Toronto, Canada.,Department of Physiology, University of Toronto, Toronto, Canada
| | - Christopher Macgowan
- SickKids Hospital, Toronto, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Toronto, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada
| | - Zahra Shirzadi
- Department of Medical Biophysics, University of Toronto, Toronto, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada
| | - Zdenka Pausova
- SickKids Hospital, Toronto, Canada.,Department of Physiology, University of Toronto, Toronto, Canada
| | - Tomáš Paus
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada.,Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Canada
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